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David Shacochis, Lumen | AWS re:Invent 2022


 

(upbeat music) >> Hello, friends. Welcome back to The Cube's live coverage of AWS re:Invent 2022. We're in Vegas. Lovely Las Vegas. Beautiful outside, although I have only seen outside today once, but very excited to be at re:Invent. We're hearing between 50,000 and 70,000 attendees and it's insane, but people are ready to be back. This morning's keynote by CEO Adam Selipsky was full of great messages, big focus on data, customers, partners, the ecosystem. So excited. And I'm very pleased to welcome back one of our alumni to the program, David Shacochis, VP Enterprise Portfolio Strategy Product Management at Lumen. David, welcome back. >> Lisa, good to be here. The Five Timers Club. >> You are in the Five Timers Club. This is David's fifth appearance on the show. And we were talking before we went live- >> Do we do the jacket now and do we do the jacket later? >> Yeah, the jacket will come later. >> Okay. >> The Five Timers Club, like on SNL. We're going to have that for The Cube. We'll get you measured up and get that all fitted for you. >> That'd be better. >> So talk a little bit about Lumen. 'Cause last time you hear it wasn't Lumen. >> We weren't Lumen last time. So this is the first time... last time we were here on The Cube at re:Invent. This was probably 2019 or so. We were a different company. The company was called CenturyLink back then. We rebranded in 2020 to really represent our identity as a delivery of...as a solutions provider over our fiber network. So Lumen is the corporate brand, the company name. It represents basically a lot of the fiber that's been laid throughout the world and in North America and in enterprise metropolitan areas over the past 10 to 15 years. You know, companies like CenturyLink and Quest and Level 3, all those companies have really rolled up into building that core asset of the network. So Lumen is really the brand for the 21st century for the company, really focused on delivering services for the enterprise and then delivering a lot of value added services around that core network asset. >> So rebranding during the pandemic, what's been the customer feedback and sentiment? >> Yeah, I think customers have really actually appreciated it as certainly a more technology oriented brand, right? Sort of shifting away a little bit from some of the communications and telecom background of the company and the heritage. And while those assets that were built up during that period of time have been substantial, and we still build off of those assets going forward, really what a lot of the customer feedback has been is that it puts us in a posture to be a little bit more of a business solutions provider for customers, right? So there's a lot of things that we can do with that core network asset, the fiber networking a lot of the services that we launch on that in terms of public IP, you know, public internet capacity, private networking, private VPNs, VoIP and voice services. These are services that you'd expect from a company like that. But there's a lot of services inside the Lumen brand that you might surprise you, right? There's an edge computing capability that can deliver five milliseconds of latency within 95% of North American enterprise. >> Wow. >> There's a threat detection lab that goes and takes all of the traffic flowing over the public side of our network and analyzes it in a data lake and turns it into threat intelligence that we then offer off to our customers on a subscription basis. There's a production house that goes and, you know, does production networking for major sports arenas and sports events. There's a wide range of services inside of Lumen that really what the Lumen brand allows us to do is start talking about what those services can do and what networking can do for our customers in the enterprise in a more comprehensive way. >> So good changes, big brand changes for Lumen in the last couple of years. Also, I mean, during a time of such turmoil in the world, we've seen work change dramatically. You know, everybody...companies had to pivot massively quickly a couple years ago. >> Yep. >> Almost approaching three years ago, which is crazy amazing to be digital because they had to be able to survive. >> They did >> Now they're looking at being able to thrive, but now we're also in this hybrid work environment. The future of work has changed. >> Totally. >> Almost permanently. >> Yep. >> How is Lumen positioned to address some of the permanent changes to the work environments? Like the last time we were at re:Invented- >> Yeah. >> In person. This didn't exist. >> That's right. So really, it's one of the things we talk to our customers almost the most about is this idea of the future of work. And, you know, we really think about the future of work as about, you know, workers and workloads and the networks that connect them. You think about how much all of those demands are shifting and changing, right? What we were talking about, and it's very easy for all of us to conceptualize what the changing face of the worker looks like, whether those are knowledge workers or frontline workers the venues in which people are working the environments and that connectivity, predictability of those work desk environments changes so significantly. But workloads are changing and, you know we're sitting here at a trade show that does nothing but celebrate the transformation of workloads. Workloads running in ways in business logic and capturing of data and analysis of data. The changing methodologies and the changing formats of workloads, and then the changing venues for workloads. So workloads are running in places that never used to be data centers before. Workloads are running in interesting places and in different and challenging locations for what didn't used to be the data center. And so, you know, the workloads and the workloads are in a very dynamic situation. And the networks that connect them have to be dynamic, and they have to be flexible. And that's really why a lot of what Lumen invests in is working on the networks that connect workers and workloads both from a visibility and a managed services perspective to make sure that we're removing blind spots and then removing potential choke points and capacity issues, but then also being adaptable and dynamic enough to be able to go and reconfigure that network to reach all of the different places that, you know, workers and workloads are going to evolve into. What you'll find in a lot of cases, you know, the workers...a common scenario in the enterprise. A 500 person company with, you know, five offices and maybe one major facility. You know, that's now a 505 office company. >> Right. >> Right? The challenge of the network and the challenge of connecting workers and workloads is really one of the main conversations we have with our customers heading into this 21st century. >> What are some of the things that they're looking forward to in terms of embracing the future of work knowing this is probably how it's going to remain? >> Yeah, I think companies are really starting to experiment carefully and start to think about what they can do and certainly think about what they can do in the cloud with things like what the AWS platform allows them to do with some of the AWS abstractions and the AWS services allow them to start writing software for, and they're starting to really carefully, but very creatively and reach out into their you know, their base of enterprise data, their base of enterprise value to start running some experiments. We actually had a really interesting example of that in a session that Lumen shared here at re:Invent yesterday. You know, for the few hundred people that were there. You know, I think we got a lot of great feedback. It was really interesting session about the...really gets at this issue of the future of work and the changing ways that people are working. It actually was a really cool use case we worked on with Major League Baseball, Fox Sports, and AWS with the... using the Lumen network to essentially virtualize the production truck. Right? So you've all heard that, you know, the sports metaphor of, you know, the folks in the booth were sitting there started looking down and they're saying, oh great job by the guys or the gals in the truck. >> Yep. >> Right? That are, you know, that bring in that replay or great camera angle. They're always talking about the team and their production truck. Well, that production truck is literally a truck sitting outside the stadium. >> Yep. >> Full of electronics and software and gear. We were able to go and for a Major League Baseball game in...back in August, we were able to go and work with AWS, using the Lumen network, working with our partners and our customers at Fox Sports and virtualize all of that gear inside the truck. >> Wow. That's outstanding. >> Yep. So it was a live game. You know, they simulcast it, right? So, you know, we did our part of the broadcast and many hundreds of people, you know, saw that live broadcast was the first time they tried doing it. But, you know, to your point, what are enterprises doing? They're really starting to experiment, sort to push the envelope, right? They're kind of running things in new ways, you know, obviously hedging their bets, right? And sort of moving their way and sort of blue-green testing their way into the future by trying things out. But, you know, this is a massive revenue opportunity for a Major League Baseball game. You know, a premier, you know, Sunday night baseball contest between the Yankees and the Cardinals. We were able to go and take the entire truck, virtualize it down to a small rack of connectivity gear. Basically have that production network run over redundant fiber paths on the Lumen network up into AWS. And AWS is where all that software worked. The technical director of the show sitting in his office in North Carolina. >> Wow. >> The sound engineer is sitting in, you know, on his porch in Connecticut. Right? They were able to go and do the work of production anywhere while connected to AWS and then using the Lumen network, right? You know, the high powered capabilities of Lumens network underlay to be able to, you know, go and design a network topology and a worked topology that really wasn't possible before. >> Right. It's nice to hear, to your point, that customers are really embracing experimentation. >> Right. >> That's challenging to, obviously there was a big massive forcing function a couple of years ago where they didn't have a choice if they wanted to survive and eventually succeed and grow. >> Yeah. >> But the mindset of experimentation requires cultural change and that's a hard thing to do especially for I would think legacy organizations like Major League Baseball, but it sounds like they have the appetite. >> Yeah. They have the interest. >> They've been a fairly innovative organization for some time. But, you know, you're right. That idea of experimenting and that idea of trying out new things. Many people have observed, right? It's that forcing function of the pandemic that really drove a lot of organizations to go and make a lot of moves really quickly. And then they realized, oh, wait a minute. You know... I guess there's some sort of storytelling metaphor in there at some point of people realizing, oh wait, I can swim in these waters, right? I can do this. And so now they're starting to experiment and push the envelope even more using platforms like AWS, but then using a lot of the folks in the AWS partner network like Lumen, who are designing and sort of similarly inspired to deliver, you know, on demand and virtualized and dynamic capabilities within the core of our network and then within the services that our network can and the ways that our network connects to AWS. All of that experimentation now is possible because a lot of the things you need to do to try out the experiment are things you can get on demand and you can kind of pat, you can move back, you can learn. You can try new things and you can evolve. >> Right. >> Yep. >> Right. Absolutely. What are some of the things that you're excited about as, you know, here was this forcing function a couple years ago, we're coming out of that now, but the world has changed. The future of work as you are so brilliantly articulated has changed permanently. What are you excited about in terms of Lumen and AWS going forward? As we saw a lot of announcements this morning, big focus on data, vision of AWS is really that flywheel with Adams Selipsky is really, really going. What are you excited about going forward into 2023? >> Yeah, I mean we've been working with AWS for so long and have been critical partners for so long that, you know, I think a lot of it is continuation of a lot of the great work we've been doing. We've been investing in our own capabilities around the AWS partner network. You know, we're actually in a fairly unique position, you know, and we like to think that we're that unique position around the future of work where between workers, workloads and the networks that connect them. Our fingers are on a lot of those pulse points, right? Our fingers are on at really at the nexus of a lot of those dynamics. And our investment with AWS even puts us even more so in a position to go where a lot of the workloads are being transformed, right? So that's why, you know, we've invested in being one of the few network operators that is in the AWS partner network at the advanced tier that have the managed services competency, that have the migration competency and the network competency. You can count on one hand the number of network operators that have actually invested at that level with AWS. And there's an even smaller number that is, you know, based here in the United States. So, you know, I think that investment with AWS, investment in their partner programs and then investment co-innovation with AWS on things like that MLB use case really puts us in a position to keep on doing these kinds of things within the AWS partner network. And that's one of the biggest things we could possibly be excited about. >> So what does the go to market look like? Is it Lumen goes in, brings in AWS, vice versa? Both? >> Yeah, so a lot of being a member of the AWS partner network you have a lot of flexibility. You know, we have a lot of customers that are, you know, directly working with AWS. We have a lot of customers that would basically look to us to deliver the solution and, you know, and buy it all as a complete turnkey capability. So we have customers that do both. We have customers that, you know, just look to Lumen for the Lumen adjacent services and then pay, you know, pay a separate bill with AWS. So there's a lot of flexibility in the partner network in terms of what Lumen can deliver as a service, Lumen can deliver as a complete solution and then what parts of its with AWS and their platform factors into on an on-demand usage basis. >> And that would all be determined I imagine by what the customer really needs in their environment? >> Yeah, and sort of their own cloud strategy. There's a lot of customers who are all in on AWS and are really trying to driving and innovating and using some of the higher level services inside the AWS platform. And then there are customers who kind of looked at AWS as one of a few cloud platforms that they want to work with. The Lumen network is compatible and connected to all of them and our services teams are, you know, have the ability to go and let customers sort of take on whatever cloud posture they need. But if they are all in on AWS, there's, you know. Not many networks better to be on than Lumen in order to enable that. >> With that said, last question for you is if you had a bumper sticker or a billboard. Lumen's rebranded since we last saw you. What would that tagline or that phrase of impact be on that bumper sticker? >> Yeah, I'd get in a lot of trouble with our marketing team if I didn't give the actual bumper sticker for the company. But we really think of ourselves as the platform for amazing things. The fourth industrial revolution, everything going on in terms of the future of work, in terms of the future of industrial innovation, in terms of all the data that's being gathered. You know, Adam in the keynote this morning really went into a lot of detail on, you know, the depth of data and the mystery of data and how to harness it all and wrangle it all. It requires a lot of networking and a lot of connectivity. You know, for us to acquire, analyze and act on all that data and Lumen's platform for amazing things really helps forge that path forward to that fourth industrial revolution along with great partners like AWS. >> Outstanding. David, it's been such a pleasure having you back on The Cube. We'll get you fitted for that five timers club jacket. >> It sounds good. (Lisa laughs) >> I'll be back. >> Thanks so much for your insights and your time and well done with what you guys are doing at Lumen and AWS. >> Thanks Lisa. >> For David Shacochis, I'm Lisa Martin. You've been watching The Cube hopefully all day. This is our first full day of coverage at AWS re:Invent '22. Stick around. We'll be back tomorrow, and we know we're going to see you then. Have a great night. (upbeat music)

Published Date : Nov 30 2022

SUMMARY :

partners, the ecosystem. Lisa, good to be here. You are in the Five Timers Club. We're going to have that for The Cube. 'Cause last time you hear it wasn't Lumen. over the past 10 to 15 years. a lot of the services and takes all of the traffic for Lumen in the last couple of years. because they had to be able to survive. The future of work has changed. This didn't exist. of the different places that, you know, of the main conversations we have the sports metaphor of, you know, about the team and their production truck. gear inside the truck. Wow. of the broadcast and many to be able to, you know, It's nice to hear, to your point, a couple of years ago where But the mindset of experimentation They have the interest. because a lot of the things The future of work as you are and the networks that connect them. of the AWS partner network have the ability to go and be on that bumper sticker? into a lot of detail on, you know, We'll get you fitted for It sounds good. and well done with what you guys are doing and we know we're going to see you then.

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Jeff Sieracki, Lumen | VMware Explore 2022


 

foreign welcome back to thecube's coverage of VMware Explorer 2022 Lisa Martin and Dave Nicholson here at Moscone West we're with about seven to ten thousand folks here so really good attendance at this first event since 2019 and the First with the new name Dave and I are pleased to welcome Jeff seraki the senior director of product management at Lumen as our next guest Jeff great to have you thank you for having me welcome so looked at the website I always love to see what taglines are and and lumen's website says welcome to the platform for amazing things talk to the audience a little bit about Lumen it's Mission Vision value prop would love to so much like a lot of the Enterprises that are out there today in the market lumens in the process of transforming we're transforming to a technology company from our Network routes but we also have roots in the I.T infrastructure business so we're bringing those together and creating that platform for amazing things uh we believe that our purpose is if you further human progress through technology and how we do that is we're enabling the fourth Industrial Revolution so moving in to the digital age where everything is it's all about data it's about real-time use of that data you machine learning artificial intelligence autonomous Cars Smart cities so the key tenet that we have around the fourth Industrial Revolution is data you need to acquire it and once you acquire it you need to analyze it then you need to act upon it because when you think about it data is just growing and growing and growing from the phones in your pocket to the devices that are sitting in front of us it's not going to stop and information that data is critical to driving business value and outcomes for customers so um so with that the I totally lost my train of thought sorry um uh the ability to to leverage that is critical um you know driving driving the revenue from that so for example like machine learning you can't have machine learning without data to feed the machine so they can start learning so they can look at pictures like oh look this is a picture of a dog this is a picture of a kangaroo so that's what our platform enables and that's what we're building we're building it brand new sitting on top of the Lumen networking capabilities of Global Network one of the largest IP backbone providers so we're super excited about what we have so these days every company has to be a data company to be competitive to you know well even to survive talk a little bit about enabling lumens customers to become data companies while enabling the fourth Industrial Revolution those two seem to be hand in hand yes so with the services that we provide particularly with our partnership with VMware we provide private cloud services that we can deploy on the customer premises or so whether it's a corporate office manufacturing facility a you know logistical facility so we can provide compute there or we can provide it in one of our plus 60 Edge data centers that are located in plus 60 metros so you don't have to put equipment on premises that's all connected by the Lumen Network Dynamic networking capabilities that connect from a customer Prem to Edge data center third party data center all the way into the public Cloud so we can stitch all of that together so I know you mentioned that you know you're you're you know based on your history you're moving further up the value chain with your customers but I'm still fascinated by kind of the history of lumen and when you when you refer to this Lumen Network um tell us a little more about that because that that's kind of a secret sauce ingredient to what you're doing yes so roots and Telecom roots and fiber and we have one of the largest fiber networks in the world and with that comes not only breath but also capillarity going to the markets we have over a hundred and eighty thousand fiber fed Enterprise buildings so with that imagine if your compute's there or if it's in a one of our Edge data centers how quickly you can transmit information from that Prem to the compute all the way into the cloud to acquire analyze and act on that data so that's really kind of the secret sauce we have that as you mentioned is that is that fiber backbone so I'm going to use the word capillarity at least once a day for the next week that's one of my favorite words awesome awesome word in it because and it actually it's evocative of exactly what I know you're what you're referencing but so you you guys are experts in latency bandwidth throughput those underpinnings of making sure that you can get data where it needs to be you can communicate between between environments um you've got that you've got that down so that's a very very strong Foundation to build off of is I guess the point that I wanted to see if I was correct definitely understanding and um just with that capability it really it comes down to outside the data is the user experience and with application performance you know one of the levers you can pull to drive application performance is is network but also location so you can put more bandwidth at it you can take put it on a network with less hops that's one of the advantages of our large backbone or you move the compo compute closer to the point of digital interaction which is what we're doing with our Edge platform so whether it's an edge data center on-prem yeah one thing one thing at the cube that we like to do is we we dive into those things that sometimes people think are inane and banal because we know how important they are we have a whole series on the question of does Hardware matter and so so we understand that you're delivering higher value to your customers but we also want to acknowledge just how important it is for you to have that Foundation yes underneath yeah and we're I mean the customers that in the marketplace they're expecting more and more services up this stack they don't want to have to worry about speeds and feeds well the way we're looking at it is the network has compute endpoints on it and everything has compute customers want to run their applications they don't want to worry about everything underneath it so that's why we're moving up so we want to be able to create that platform you worry about your applications you worry about development and execution of your applications and we'll take care of everything else talk a little bit about the VMware partnership I see Lumen Edge private Cloud on VCF talk a little bit about that how you guys are working together and some of the value of what's in it for me as a customer okay we've been working with for VMware for decades they're one of our best partners and our Flagship private Cloud product is based upon the cloud Foundation and it's a tried and true platform that the market understands and they have confidence in so it's something that they can relate to and they already have experience in so they're not trying to learn something new like trying to go out and find resources that can manage kubernetes like that's probably one of the hottest jobs out there probably took the wrong career path but anyways it's it's new it's emerging whereas VMware people know it there's a lot of people that know it so why spend time as an Enterprise retooling and learning and going to a different platform so with that VMware brings that foundation and the security of that that cohesive ecosystem that comes with VCF so we can provide that dedicated solution to our customers that they know and they Trust trust is critical right I mean it's it's table Stakes for businesses and their vendors and suppliers you know here we are at the VMware explore event that called uh the center of the multi-cloud universe which just sounds like a Marvel movie to me haven't seen any superheroes yet but there's got to be somebody around here in a costume in any event talk about how Lumen and VMware are enabling customers to navigate the the multi-cloud world that they're in by default and really turn it into a strategic advantage uh sure it's tied to the network um as much as I'm trying to say we opsificate it but it's um network is the critical part to it because you do have to physically connect things and the cloud is their computer somewhere so there is a physical behind everything but with the connectivity that we have and the partnership with VMware and the ability to take that platform and either from on-prem Edge data center third party data center or we can also provide that service with uh vmc and AWS we can provide it in the cloud so you have a ubiquitous platform that looks and feels the same no matter where it is and then that's critical to our customers again that the switching costs of learning it's it's a great product VMware is a great partnership to help bring that all together so what is a delighted customer sound like you're interacting with a delighted customer they're not gonna they're not going to pick up the phone and tell you you know what I love your network what what are they going to be what are they going to tell you they're happy about a delighty customer wouldn't talk about our infrastructure at all our virtual machines work our applications work our software Engineers they can develop against it our costs are optimized that's what they're going to care about if they start talking about oh our virtual machines or servers and that means there's probably something wrong so we need to make sure that platform that we're providing as a service and managing works so it's really if your application if you want to talk to me about your application that's what's top of mind for you we're doing our job now you share that love with the folks in your organization responsible for making sure that that infrastructure works right yes you let them know it's like look no no one is no one is touting what you do but it really still is important it is very you want to make sure keep those folks happy yes very important talk a little bit Jeff about how your customer conversations have evolved over the last couple of years as we saw you know two and a half years ago businesses in every industry scrambling to go digital have you seen priorities shift up the c-suite stock over to the board in terms of the infrastructure and the network that powers these organizations yeah I mean over the past couple years with the proliferation of public cloud you know the edicts of got to go to the cloud we got to go Cloud go to the go to the cloud so everything goes to the cloud it's great it's good for a lot of applications but not for all applications and the customer conversations were having a lot of it are okay what what comes back because with Cloud cream and costs it just yeah if you're looking at a permanent VM basis you know public Cloud works but when you have an entire ecosystem of virtual machines and applications to support entire Enterprise that cost can get out of hand pretty quickly are you saying that we we yeah we hear the term repatriation yes used are you saying a fair fair amount of that yes we're seeing that then the other part that we're seeing is getting out of the data center business that's expensive especially if an Enterprise has their own like that's you're talking about 10 million dollars per megawatt just of capital cost there so and then if they're in a third party you still have physical space and power you have servers there you have to assume someone's optimizing those servers and even if you have a hypervisor sitting on top of it that's a lot of work that's a lot of resources and human capital that our private Cloud solution with VMware takes away so that they can again they can worry about their applications providing business value providing customer experience versus is there anything on this server or not does somebody need this virtual machine what are all these public Cloud spend items we have how's this out of control it allows them to focus so that's kind of how things have have evolved and changed over the years one of the things that VMware talked about this morning in terms of the journey the cloud journey is going from cloud chaos which is where a lot of businesses are now to Cloud smart how does Lumen facilitate that transition of a business from cloud chaos to Cloud smart what is a cloud smart strategy from lumen's lens look like first of all you have to have a strategy as an Enterprise you'd be surprised how many of those that are out there that they don't know what to do and part of not knowing what to do is do we even have the right people looking at this and so what Lumen what we bring is that consultative capability to start breaking down some of those issues so maybe they do have a hybrid Cloud strategy okay have you implemented it no why not we don't have enough people okay those are resources we can bring in because not only you provide network and infrastructure but we also have managed surface capabilities managed Services capabilities we can sit on top of that we have Cloud migration practices we have centers of excellence around sap and other services so let us help dissect your problem let's take a let's look at the landscape you have out there find out where everything's buried and dig it up and then we figure out okay how do we move from one place the other you don't just lift and shift and so that those are the other services that Lumen brings in and that's how we help them and our private Cloud product we have it sitting on our Edge right in those 60 metros they can spin up a private Cloud instance tomorrow and they can start moving virtual machines from their data center to that cloud as a staging point to either keep it there you know move it to another place or move it into the public Cloud if that's where the application needs to live I'm curious about lumen's go to market strategy customers have a finite number of strategic seats at the table when it comes time to planning things out like what you just were referencing you know what what do we do next uh what's lumen's path to a seat at that table are you are you generally seeking to directly engage separately with that end user customer or are you going in partnering with others what does that look like in the real world in the real world it's Partners working together no one single entity can provide everything we have to work together and with our infrastructure layer we want to find the right partners that can help provide vertical specific Solutions that then you know they can be Hardware Partners they can be software Partners but then we can collectively go talk to the market talk to our customers about what we can help them with and then with our managed Services capabilities that's how we can kind of glue it all together so that's the direction we're going in so be very focused we're focused on manufacturing you're focused on retail because we see the largest opportunities there that's where we have a strong customer base strong customer relationships and that's how we're doing it we don't want to have an infrastructure conversation we want to outcome and application conversation that's what every customer is talking about it's all about outcomes is there Jeff a favorite customer story in manufacturing or retail that you think really articulates the value of what Lumen and VMware are delivering together yeah it's a yeah we kind of use this one a lot but it's it's uh it's a really good one um and we've seen um uh clones of this and and other opportunities manufacturing smart manufacturing you need to have the equipment that takes that information again that data from all the iot devices analyze it operate your manufacturing facility because most of it's all automated now so you can run that facility at optimal production with that compute you don't necessarily want that compute you know a thousand miles away you want it as close as possible particularly if you look at what if there's a fiber cut your network goes down okay then your factory goes down that's millions of dollars so with that compute there we allow that smart manufacturing capabilities and that's running on Lumen private cloud based upon VMware on vcloud foundation and it's working great and it's it's an opportunity for us to continue to expand I've seen similar use cases in logistics it's yeah I mean it's phenomenal what we can do when you're in conversations with prospects what's the why what's the pitch that you give them about why they should be working with Lumen to help them really maximize the value of their Edge Solutions it's really the resources we bring to bear like you know we we keep talking a lot about Network and uh trying to get away from the sniper that's my cousin the network is is key to the value proposition but it's not what people look at first but it's those other resources the ability to to manage I.T infrastructure which have been doing for decades a lot of people don't know that but we've been doing this a very long time and then with those areas of expertise managed Services it's providing that all together and with lumen's history the Partnerships we have I mean we have a lot of Partnerships so we have the ability to bring all these resources to provide the best solution for the customer and we like to use the term best execution venue so each application has an optimal place to live and we'll help help customers find that out and it's really I mean it's that simple we just need to sit down and have a conversation we can figure out where we can help you and we can get started as soon as the customer is ready so obviously some some changes coming up for VMware in the next few months or so what are you excited about as you continue this long-standing partnership and evolving it forward I'm most excited about us working together even more because we have not only do we have our private Cloud products uh we're leveraging them for kubernetes but also our sassy product we're partnered with VMware on that so we're really tight at the hip with these Cutting Edge Products that we're taking to Market to help customers solve those problems that we were just talking about so I'm just looking forward us coming together more and just getting out there and helping people threatening of the partnership excellent Jeff thank you for joining Dave and me on the program talking about what's going on with Lumen how you're enabling the fourth Industrial Revolution enabling customers to really become data companies we appreciate your time on your insights thank you for Jeff saraki and Dave Nicholson I'm Lisa Martin you're watching thecube live from VMware Explorer 2022. you're watching thecube the leader in Live tech coverage [Music]

Published Date : Aug 30 2022

SUMMARY :

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MANUFACTURING Reduce Costs


 

>>Hey, we're here in the second manufacturing drill down session with Michael Gerber. He was the managing director for automotive and manufacturing solutions at Cloudera. And we're going to continue the discussion with a look at how to lower costs and drive quality in IOT analytics with better uptime and hook. When you do the math, it's really quite obvious when the system is down, productivity is lost and it hits revenue and the bottom line improve quality drives, better service levels and reduces lost opportunities. Michael. Great >>To see you take it away. >>All right, guys. Thank you so much. So I'd say we're going to talk a little bit about connected manufacturing, right? And how those IOT IOT around connected manufacturing can do as Dave talked about improved quality outcomes for manufacturing and flute and improve your plant uptime. So just a little bit quick, quick, little indulgent, quick history lesson. I promise to be quick. We've all heard about industry 4.0, right? That is the fourth industrial revolution. And that's really what we're here to talk about today. First industrial revolution, real simple, right? You had steam power, right? You would reduce backbreaking work. Second industrial revolution, mass assembly line. Right. So think about Henry Ford and motorized conveyor belts, mass automation, third industrial revolution, things got interesting, right? You started to see automation, but that automation was done essentially programmed your robot to do something and did the same thing over and over and over irrespective about of how your outside operations, your outside conditions change fourth industrial revolution, very different, right? >>Cause now we're connecting, um, equipment and processes and getting feedback from it. And through machine learning, we can make those, um, those processes adapted right through machine learning. That's really what we're talking about in the fourth industrial revolution. And it is intrinsically connected to data and a data life cycle. And by the way, it's important, not just for a little bit of a slight issue, there we'll issue that, but it's important. Not for technology's sake, right? It's important because it actually drives very important business outcomes. First of all, quality, right? If you look at the cost of quality, even despite decades of, of, of, uh, companies and manufacturers moving to improve while its quality prompts still accounts for 20% of sales, right? So every fifth of what you meant are manufactured from a revenue perspective, do back quality issues that are costing you a lot planned downtime, cost companies, $50 billion a year. >>So when we're talking about using data and these industry 4.0 types of use cases, connected data types of new spaces, we're not doing it just merely to implement technology. We're doing it to move these from members, improving quality, reducing downtime. So let's talk about how a connected manufacturing data life with what like, right, but this is actually the business. The cloud area is, is in. Let's talk a little bit about that. So we call this manufacturing edge to AI. This is analytics life cycle, and it starts with having your plants, right? Those plants are increasingly connected. As I say, sensor prices have come down two thirds over the last decade, right? And those sensors are connected over the internet. So suddenly we can collect all this data from your, um, manufacturing plants, and what do we want to be able to do? You know, we want to be able to collect it. >>We want to be able to analyze that data as it's coming across. Right? So, uh, in scream, right, we want to be able to analyze it and take intelligent time actions. Right? We might do some simple processing and filtering at the edge, but we really want to take real-time actions on that data. But, and this is the inference part of things are taking about time, but this, the ability to take these real-time actions or, um, is actually the result of a machine learning life cycle. I want to walk you through this, right? And it starts with, um, ingesting this data for the first time, putting it into an enterprise data lake, right in that data lake enterprise data lake can be either within your data center or it could be in the cloud. You're going to, you're going to ingest that data. You're going to store it. >>You're going to enrich it with enterprise data sources. So now you'll have say sensor data and you'll have maintenance repair orders from your maintenance management systems. Right now you could start to think about, you're getting really nice data sets. You can start to say, Hey, which sensor values correlate to the need for machine maintenance, right? You start to see the data sets. They're becoming very compatible with machine learning, but so you, you bring these data sets together. You process that you align your time series data from your sensors to your timestamp data from your, um, you know, from your enterprise systems that your maintenance management system, as I mentioned, you know, once you've done that, we can put a query layer on top. So now we can start to do advanced analytics query across all these different types of data sets. But as I mentioned to you, and what's really important here is the fact that once you've stored one history sets data, you can build out those machine learning models. >>I talked to you about earlier. So like I said, you can start to say, which sensor values drove the need of correlated to the need for equipment maintenance for my maintenance management systems, right? And you can build out those models and say, Hey, here are the sensor values of the conditions that predict the need for maintenance. Once you understand that you can actually then build out the smiles, you could deploy the models after the edge where they will then work in that inference mode, that photographer, I will continuously sniff that data as it's coming and say, Hey, which are the, are we experiencing those conditions that, that predicted the need for maintenance? If so, let's take real-time action, but schedule a work order and equipment maintenance work order in the past, let's in the future, let's order the parts ahead of time before that piece of equipment fails and allows us to be very, very proactive. >>So, >>You know, we have, this is a, one of the Mo the most popular use cases we're seeing in terms of connected, connected manufacturing. And we're working with many different manufacturers around the world. I want to just highlight. One of them is I thought it's really interesting. This company is for SIA for ECA is the, um, is the, was, is the, um, the, uh, a supplier associated with Pooja central line out of France. They are huge, right? This is a multinational automotive, um, parts and systems supplier. And as you can see, they operate in 300 sites in 35 countries. So very global, um, they connected 2000 machines, right. Um, and they once be able to take data from that. They started off with learning how to ingest the data. They started off very well with, um, you know, with, uh, manufacturing control towers, right? To be able to just monitor the data firms coming in, you know, monitor the process. >>That was the first step, right. Uh, and you know, 2000 machines, 300 different variables, things like, um, fibrations pressure temperature, right? So first let's do performance monitoring. Then they said, okay, let's start doing machine learning on some of these things to start to build out things like equipment, um, predictive maintenance models, or compute. What they really focused on is computer vision, wilding inspection. So let's take pictures of parts as they go through a process and then classify what that was this picture associated with the good or bad quality outcome. Then you teach the machine to make that decision on its own. So now, now the machine, the camera is doing the inspections beer. And so they both have those machine learning models. So they took that data. All this data was on-prem, but they pushed that data up to the cloud to do the machine learning models, develop those machine learning models. >>Then they push the machine learning models back into the plants where they, where they could take real-time actions through these computer vision, quality inspections. So great use case, a great example of how you can start with monitoring, move to machine learning, but at the end of the day, or improving quality and improving, um, uh, equipment uptime. And that is the goal of most manufacturers. So with that being said, um, I would like to say, if you want to learn some more, um, we've got a wealth of information on our website. You see the URL in front of you, please go there and you'll learn. There's a lot of information there in terms of the use cases that we're seeing in manufacturing and a lot more detail and a lot more talk about a lot more customers we'll work with. If you need that information, please do find it. Um, with that, I'm going to turn it over to Dave, to Steve. I think you had some questions you wanted to run by. >>I do, Michael, thank you very much for that. And before I get into the questions, I just wanted to sort of make some observations that was, you know, struck by what you're saying about the phases of industry. We talk about industry 4.0, and my observation is that, you know, traditionally, you know, machines have always replaced humans, but it's been around labor and, and the difference with 4.0, and what you talked about with connecting equipment is you're injecting machine intelligence. Now the camera inspection example, and then the machines are taking action, right? That's, that's different and, and is a really new kind of paradigm here. I think the, the second thing that struck me is, you know, the costs, you know, 20% of sales and plant downtime costing, you know, many tens of billions of dollars a year. Um, so that was huge. I mean, the business case for this is I'm going to reduce my expected loss quite dramatically. >>And then I think the third point, which we turn in the morning sessions and the main stage is really this, the world is hybrid. Everybody's trying to figure out hybrid, get hybrid, right. And it certainly applies here. Uh, this is, this is a hybrid world you've got to accommodate, you know, regardless of, of where the data is. You've gotta be able to get to it, blend it, enrich it, and then act on it. So anyway, those are my big, big takeaways. Um, so first question. So in thinking about implementing connected manufacturing initiatives, what are people going to run into? What are the big challenges that they're gonna, they're gonna hit? >>You know, there's, there's there, there's a few of the, but I think, you know, one of the, uh, one of the key ones is bridging what we'll call the it and OT data divide, right. And what we mean by the it, you know, your, it systems are the ones, your ERP systems, your MES systems, right? Those are your transactional systems that run on relational databases and your it departments are brilliant at running on that, right? The difficulty becomes an implementing these use cases that you also have to deal with operational technology, right? And those are, um, all of the, that's all the equipment in your manufacturing plant that runs on its proprietary network with proprietary pro protocols. That information can be very, very difficult to get to. Right. So, and it's unsafe, it's a much more unstructured than from your OT. So the key challenge is being able to bring these data sets together in a single place where you can start to do advanced analytics and leverage that diverse data to do machine learning. >>Right? So that is one of the, if I had to boil it down to the single hardest thing in this, uh, in this, in this type of environment, nectar manufacturing is that that operational technology has kind of run on its own in its own world for a long time, the silos, um, uh, you know, the silos, uh, bound, but at the end of the day, this is incredibly valuable data that now can be tapped, um, um, to, to, to, to move those, those metrics we talked about right around quality and uptime. So a huge opportunity. >>Well, and again, this is a hybrid theme and you've kind of got this world, that's going toward an equilibrium. You've got the OT side, you know, pretty hardcore engineers. And we know, we know it. Uh, a lot of that data historically has been analog data. Now it's getting, you know, instrumented and captured. Uh, so you've got that, that cultural challenge. And, you know, you got to blend those two worlds. That's critical. Okay. So Michael, let's talk about some of the use cases you touched on, on some, but let's peel the onion a bit when you're thinking about this world of connected manufacturing and analytics in that space. And when you talk to customers, you know, what are the most common use cases that you see? >>Yeah, that's a good, that's a great question. And you're right. I did allude to it earlier, but there really is. I want people to think about, there's a spectrum of use cases ranging from simple to complex, but you can get value even in the simple phases. And when I talk about the simple use cases, the simplest use cases really is really around monitoring, right? So in this, you monitor your equipment or monitor your processes, right? And you just make sure that you're staying within the bounds of your control plan, right? And this is much easier to do now. Right? Cause some of these sensors are a more sensors and those sensors are moving more and more towards internet types of technology. So, Hey, you've got the opportunity now to be able to do some monitoring. Okay. No machine learning, we're just talking about simple monitoring next level down. >>And we're seeing is something we would call quality event forensic announces. And now on this one, you say, imagine I've got warranty plans in the, in the field, right? So I'm starting to see warranty claims, kick kickoff. And what you simply want to be able to do is do the forensic analysis back to what was the root cause of within the manufacturing process that caused it. So this is about connecting the dots by about warranty issues. What were the manufacturing conditions of the day that caused it? Then you could also say which other tech, which other products were impacted by those same conditions. And we call those proactively rather than, and, and selectively rather than say, um, recalling an entire year's fleet of the car. So, and that, again, also not machine learning where simply connecting the dots from a warranty claims in the field to the manufacturing conditions of the day, so that you could take corrective actions, but then you get into a whole of machine learning use case, you know, and, and that ranges from things like quality or say yield optimization, where you start to collect sensor values and, um, manufacturing yield, uh, values from your ERP system. >>And you're certain start to say, which, um, you know, which map a sensor values or factors drove good or bad yield outcomes. And you can identify those factors that are the most important. So you, um, you, you measure those, you monitor those and you optimize those, right. That's how you optimize your, and then you go down to the more traditional machine learning use cases around predictive maintenance. So the key point here, Dave is, look, there's a huge, you know, depending on a customer's maturity around big data, you could start something with monitoring, get a lot of value, start, then bring together more diverse data sets to do things like connect the.analytics then and all the way then to, to, to the more advanced machine learning use cases there's value to be had throughout. I >>Remember when the, you know, the it industry really started to think about, or in the early days, you know, IOT and IOT. Um, it reminds me of when, you know, there was the, the old days of football field, we were grass and, and a new player would come in and he'd be perfectly white uniform and you had it. We had to get dirty as an industry, you know, it'll learn. And so, so my question relates to other technology partners that you might be working with that are maybe new in this space that, that to accelerate some of these solutions that we've been talking about. >>Yeah. That's a great question that it kind of, um, goes back to one of the things I alluded earlier, we've got some great partners, a partner, for example, litmus automation, whose whole world is the OT world. And what they've done is for example, they've built some adapters to be able to catch it practically every industrial protocol. And they've said, Hey, we can do that. And then give a single interface of that data to the Patera data platform. So now, you know, we're really good at ingesting it data and things like that. We can leverage say a company like litmus that can open the flood gates of that OT data, making it much easier to get that data into our platform. And suddenly you've got all the data you need to, to, to implement those types of industry 4.0, our analytics use cases. And it really boils down to, can I get to that? Can I break down that it OT, um, you know, uh, a barrier that we've always had and bring together those data sets that we can really move the needle in terms of improving manufacturing performance. >>Okay. Thank you for that last question. Speaking to moving the needle, I want to lead this discussion on the technology advances. I'd love to talk tech here, uh, are the key technology enablers, and advancers, if you will, that are going to move connected manufacturing and machine learning forward in this transportation space, sorry, manufacturing in >>A factory space. Yeah. I knew what you meant in know in the manufacturing space. There's a few things, first of all, I think the fact that obviously I know we touched upon this, the fact that sensor prices have come down and have become ubiquitous that number one, we can w we're finally being able to get to the OT data, right? That's that's number one, number, number two, I think, you know, um, we, we have the ability that now to be able to store that data a whole lot more efficiently, you know, we've got back way capabilities to be able to do that, to put it over into the cloud, to do the machine learning types of workloads. You've got things like if you're doing computer vision, while in analyst respect GPU's to make those machine learning models much more, uh, much more effective, if that 5g technology that starts to blur at least from a latency perspective where you do your computer, whether it be on the edge or in the cloud, you've, you've got more, you know, super business critical stuff. >>You probably don't want to rely on, uh, any type of network connection, but from a latency perspective, you're starting to see, uh, you know, the ability to do compute where it's the most effective now. And that's really important. And again, the machine learning capabilities, and they believed the book to build a GP, you know, GPU level machine learning, build out those models and then deployed by over the air updates to your equipment. All of those things are making this, um, there's, you know, there's the advanced analytics machine learning, uh, data life cycle just faster and better. And at the end of the day, to your point, Dave, that equipment and processor getting much smarter, very much more quickly. Yep. We got >>A lot of data and we have way lower cost, uh, processing platforms I'll throw in NP use as well. Watch that space neural processing units. Okay. Michael, we're going to leave it there. Thank you so much. Really appreciate your time, >>Dave. I really appreciate it. And thanks. Thanks for, for everybody who joined us. Thanks. Thanks for joining.

Published Date : Aug 5 2021

SUMMARY :

When you do the math, it's really quite obvious when the system is down, productivity is lost and it hits revenue and the bottom Thank you so much. So every fifth of what you meant are manufactured from a revenue perspective, So suddenly we can collect all this data from your, I want to walk you through this, You process that you align your time series data I talked to you about earlier. And as you can see, they operate in 300 sites Uh, and you know, 2000 machines, example of how you can start with monitoring, move to machine learning, but at the end of the day, I think the, the second thing that struck me is, you know, the costs, you know, 20% of sales And then I think the third point, which we turn in the morning sessions and the main stage is really this, And what we mean by the it, you know, your, it systems are the ones, for a long time, the silos, um, uh, you know, So Michael, let's talk about some of the use cases you touched on, on some, And you just make sure that you're staying within the bounds of your control plan, And now on this one, you say, imagine I've got warranty plans in the, in the field, And you can identify those factors that Remember when the, you know, the it industry really started to think about, or in the early days, So now, you know, we're really good at ingesting it if you will, that are going to move connected manufacturing and machine learning forward in that starts to blur at least from a latency perspective where you do your computer, and they believed the book to build a GP, you know, GPU level machine learning, Thank you so much. And thanks.

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>>Welcome to our industry. Drill-downs from manufacturing. I'm here with Michael Gerber, who is the managing director for automotive and manufacturing solutions at cloud era. And in this first session, we're going to discuss how to drive transportation efficiencies and improve sustainability with data connected trucks are fundamental to optimizing fleet performance costs and delivering new services to fleet operators. And what's going to happen here is Michael's going to present some data and information, and we're gonna come back and have a little conversation about what we just heard. Michael, great to see you over to you. >>Oh, thank you, Dave. And I appreciate having this conversation today. Hey, um, you know, this is actually an area connected trucks. You know, this is an area that we have seen a lot of action here at Cloudera. And I think the reason is kind of important, right? Because, you know, first of all, you can see that, you know, this change is happening very, very quickly, right? 150% growth is forecast by 2022. Um, and the reasons, and I think this is why we're seeing a lot of action and a lot of growth is that there are a lot of benefits, right? We're talking about a B2B type of situation here. So this is truck made truck makers providing benefits to fleet operators. And if you look at the F the top fleet operator, uh, the top benefits that fleet operators expect, you see this in the graph over here. >>Now almost 80% of them expect improved productivity, things like improved routing rates. So route efficiencies and improve customer service decrease in fuel consumption, but better technology. This isn't technology for technology sake, these connected trucks are coming onto the marketplace because Hey, it can provide for Mendez value to the business. And in this case, we're talking about fleet operators and fleet efficiencies. So, you know, one of the things that's really important to be able to enable this right, um, trucks are becoming connected because at the end of the day, um, we want to be able to provide fleet deficiencies through connected truck, um, analytics and machine learning. Let me explain to you a little bit about what we mean by that, because what, you know, how this happens is by creating a connected vehicle analytics machine learning life cycle, and to do that, you need to do a few different things, right? >>You start off of course, with connected trucks in the field. And, you know, you can have many of these trucks cause typically you're dealing at a truck level and at a fleet level, right? You want to be able to do analytics and machine learning to improve performance. So you start off with these trucks. And the first you need to be able to do is connect to those products, right? You have to have an intelligent edge where you can collect that information from the trucks. And by the way, once you conducted the, um, this information from the trucks, you want to be able to analyze that data in real-time and take real-time actions. Now what I'm going to show you the ability to take this real-time action is actually the result of your machine learning license. Let me explain to you what I mean by that. >>So we have this trucks, we start to collect data from it right at the end of the day. Well we'd like to be able to do is pull that data into either your data center or into the cloud where we can start to do more advanced analytics. And we start with being able to ingest that data into the cloud, into that enterprise data lake. We store that data. We want to enrich it with other data sources. So for example, if you're doing truck predictive maintenance, you want to take that sensor data that you've connected collected from those trucks. And you want to augment that with your dealership, say service information. Now you have, you know, you have sensor data and there was salting repair orders. You're now equipped to do things like predict one day maintenance will work correctly for all the data sets that you need to be able to do that. >>So what do you do here? Like I said, you adjusted your storage, you're enriching it with data, right? You're processing that data. You're aligning say the sensor data to that transactional system data from your, uh, from your, your pair maintenance systems, you know, you're bringing it together so that you can do two things you can do. First of all, you could do self-service BI on that date, right? You can do things like fleet analytics, but more importantly, what I was talking to you about before is you now have the data sets to be able to do create machine learning models. So if you have the sensor right values and the need, for example, for, for a dealership repair, or as you could start to correlate, which sensor values predicted the need for maintenance, and you could build out those machine learning models. And then as I mentioned to you, you could push those machine learning models back out to the edge, which is how you would then take those real-time action. >>I mentioned earlier as that data that then comes through in real-time, you're running it against that model, and you can take some real time actions. This is what we are, this, this, this, this analytics and machine learning model, um, machine learning life cycle is exactly what Cloudera enables this end-to-end ability to ingest, um, stroke, you know, store it, um, put a query, lay over it, um, machine learning models, and then run those machine learning models. Real-time now that's what we, that's what we do as a business. Now when such customer, and I just wanted to give you one example, um, a customer that we have worked with to provide these types of results is Navistar and Navistar was kind of an early, early adopter of connected truck analytics. And they provided these capabilities to their fleet operators, right? And they started off, uh, by, um, by, you know, connecting 475,000 trucks to up to well over a million now. >>And you know, the point here is with that, they were centralizing data from their telematics service providers, from their trucks, from telematics service providers. They're bringing in things like weather data and all those types of things. Um, and what they started to do was to build out machine learning models, aimed at predictive maintenance. And what's really interesting is that you see that Navistar, um, made tremendous strides in reducing the need or the expense associated with maintenance, right? So rather than waiting for a truck to break and then fixing it, they would predict when that truck needs service, condition-based monitoring and service it before it broke down so that you could do that in a much more cost-effective manner. And if you see the benefits, right, they, they reduced maintenance costs 3 cents a mile, um, from the, you know, down from the industry average of 15 cents a mile down to 12 cents cents a mile. >>So this was a tremendous success for Navistar. And we're seeing this across many of our, um, um, you know, um, uh, truck manufacturers. We were working with many of the truck OEMs and they are all working to achieve, um, you know, very, very similar types of, um, benefits to their customers. So just a little bit about Navistar. Um, now we're gonna turn to Q and a, Dave's got some questions for me in a second, but before we do that, if you want to learn more about our, how we work with connected vehicles and autonomous vehicles, please go to our lives or to our website, what you see up, uh, up on the screen, there's the URLs cloudera.com for slash solutions for slash manufacturing. And you'll see a whole slew of, um, um, lateral and information, uh, in much more detail in terms of how we connect, um, trucks to fleet operators who provide analytics, use cases that drive dramatically improved performance. So with that being said, I'm going to turn it over to Dave for questions. >>Thank you. Uh, Michael, that's a great example. You've got, I love the life cycle. You can visualize that very well. You've got an edge use case you do in both real time inference, really at the edge. And then you're blending that sensor data with other data sources to enrich your models. And you can push that back to the edge. That's that lifecycle. So really appreciate that, that info. Let me ask you, what are you seeing as the most common connected vehicle when you think about analytics and machine learning, the use cases that you see customers really leaning into. >>Yeah, that's really, that's a great question. They, you know, cause you know, everybody always thinks about machine learning. Like this is the first thing you go, well, actually it's not right for the first thing you really want to be able to go around. Many of our customers are doing slow. Let's simply connect our trucks or our vehicles or whatever our IOT asset is. And then you can do very simple things like just performance monitoring of the, of the piece of equipment in the truck industry, a lot of performance monitoring of the truck, but also performance monitoring of the driver. So how has the, how has the driver performing? Is there a lot of idle time spent, um, you know, what's, what's route efficiencies looking like, you know, by connecting the vehicles, right? You get insights, as I said into the truck and into the driver and that's not machine learning. >>Right. But that, that, that monitoring piece is really, really important. The first thing that we see is monitoring types of use cases. Then you start to see companies move towards more of the, uh, what I call the machine learning and AI models, where you're using inference on the edge. And then you start to see things like, uh, predictive maintenance happening, um, kind of route real-time, route optimization and things like that. And you start to see that evolution again, to those smarter, more intelligent dynamic types of decision-making, but let's not, let's not minimize the value of good old fashioned monitoring that site to give you that kind of visibility first, then moving to smarter use cases as you, as you go forward. >>You know, it's interesting. I'm, I'm envisioning when you talked about the monitoring, I'm envisioning a, you see the bumper sticker, you know, how am I driving this all the time? If somebody ever probably causes when they get cut off it's snow and you know, many people might think, oh, it's about big brother, but it's not. I mean, that's yeah. Okay, fine. But it's really about improvement and training and continuous improvement. And then of course the, the route optimization, I mean, that's, that's bottom line business value. So, so that's, I love those, uh, those examples. Um, I wonder, I mean, one of the big hurdles that people should think about when they want to jump into those use cases that you just talked about, what are they going to run into, uh, you know, the blind spots they're, they're going to, they're going to get hit with, >>There's a few different things, right? So first of all, a lot of times your it folks aren't familiar with the kind of the more operational IOT types of data. So just connecting to that type of data can be a new skill set, right? That's very specialized hardware in the car and things like that. And protocols that's number one, that that's the classic, it OT kind of conundrum that, um, you know, uh, many of our customers struggle with, but then more fundamentally is, you know, if you look at the way these types of connected truck or IOT solutions started, you know, oftentimes they were, the first generation were very custom built, right? So they were brittle, right? They were kind of hardwired. And as you move towards, um, more commercial solutions, you had what I call the silo, right? You had fragmentation in terms of this capability from this vendor, this capability from another vendor, you get the idea, you know, one of the things that we really think that we need with that, that needs to be brought to the table is first of all, having an end to end data management platform, that's kind of integrated, it's all tested together. >>You have the data lineage across the entire stack, but then also importantly, to be realistic, we have to be able to integrate to, um, industry kind of best practices as well in terms of, um, solution components in the car, how the hardware and all those types things. So I think there's, you know, it's just stepping back for a second. I think that there is, has been fragmentation and complexity in the past. We're moving towards more standards and more standard types of art, um, offerings. Um, our job as a software maker is to make that easier and connect those dots. So customers don't have to do it all on all on their own. >>And you mentioned specialized hardware. One of the things we heard earlier in the main stage was your partnership with Nvidia. We're talking about, you know, new types of hardware coming in, you guys are optimizing for that. We see the it and the OT worlds blending together, no question. And then that end to end management piece, you know, this is different from your right, from it, normally everything's controlled or the data center, and this is a metadata, you know, rethinking kind of how you manage metadata. Um, so in the spirit of, of what we talked about earlier today, uh, uh, other technology partners, are you working with other partners to sort of accelerate these solutions, move them forward faster? >>Yeah, I'm really glad you're asking that because we actually embarked on a product on a project called project fusion, which really was about integrating with, you know, when you look at that connected vehicle life cycle, there are some core vendors out there that are providing some very important capabilities. So what we did is we joined forces with them to build an end-to-end demonstration and reference architecture to enable the complete data management life cycle. Cloudera is Peter piece of this was ingesting data and all the things I talked about being storing and the machine learning, right? And so we provide that end to end. But what we wanted to do is we wanted to partner with some key partners and the partners that we did with, um, integrate with or NXP NXP provides the service oriented gateways in the car. So that's a hardware in the car when river provides an in-car operating system, that's Linux, right? >>That's hardened and tested. We then ran ours, our, uh, Apache magnify, which is part of flood era data flow in the vehicle, right on that operating system. On that hardware, we pump the data over into the cloud where we did them, all the data analytics and machine learning and, and builds out these very specialized models. And then we used a company called Arabic equity. Once we both those models to do, you know, they specialize in automotive over the air updates, right? So they can then take those models and update those models back to the vehicle very rapidly. So what we said is, look, there's, there's an established, um, you know, uh, ecosystem, if you will, of leaders in this space, what we wanted to do is make sure that our, there was part and parcel of this ecosystem. And by the way, you mentioned Nvidia as well. We're working closely with Nvidia now. So when we're doing the machine learning, we can leverage some of their hardware to get some further acceleration in the machine learning side of things. So, uh, yeah, you know, one of the things I always say about this types of use cases, it does take a village. And what we've really tried to do is build out that, that, uh, an ecosystem that provides that village so that we can speed that analytics and machine learning, um, lifecycle just as fast as it can be. This >>Is again another great example of, of data intensive workloads. It's not your, it's not your grandfather's ERP. That's running on, you know, traditional, you know, systems it's, these are really purpose-built, maybe they're customizable for certain edge use cases. They're low cost, low, low power. They can't be bloated, uh, ended you're right. It does take an ecosystem. You've got to have, you know, API APIs that connect and, and that's that, that takes a lot of work and a lot of thoughts. So that, that leads me to the technologies that are sort of underpinning this we've talked we've we talked a lot in the cube about semiconductor technology, and now that's changing and the advancements we're seeing there, what do you see as the, some of the key technical technology areas that are advancing this connected vehicle machine learning? >>You know, it's interesting, I'm seeing it in a few places, just a few notable ones. I think, first of all, you know, we see that the vehicle itself is getting smarter, right? So when you look at, we look at that NXP type of gateway that we talked about that used to be kind of a, a dumb gateway. That was really all it was doing was pushing data up and down and provided isolation, um, as a gateway down to the, uh, down from the lower level subsistence. So it was really security and just basic, um, you know, basic communication that gateway now is becoming what they call a service oriented gate. So it can run. It's not that it's bad desk. It's got memories that always, so now you could run serious compute in the car, right? So now all of these things like running machine learning, inference models, you have a lot more power in the corner at the same time. >>5g is making it so that you can push data fast enough, making low latency computing available, even on the cloud. So now you now you've got credible compute both at the edge in the vehicle and on the cloud. Right. And, um, you know, and then on the, you know, on the cloud, you've got partners like Nvidia who are accelerating, it's still further through better GPU based compute. So I mean the whole stack, if you look at it, that that machine learning life cycle we talked about, no, David seems like there's improvements and EV every step along the way, we're starting to see technology, um, optimum optimization, um, just pervasive throughout the cycle. >>And then real quick, it's not a quick topic, but you mentioned security. If it was seeing a whole new security model emerge, there is no perimeter anymore in this use case like this is there. >>No there isn't. And one of the things that we're, you know, remember where the data management platform platform and the thing we have to provide is provide end-to-end link, you know, end end-to-end lineage of where that data came from, who can see it, you know, how it changed, right? And that's something that we have integrated into from the beginning of when that data is ingested through, when it's stored through, when it's kind of processed and people are doing machine learning, we provide, we will provide that lineage so that, um, you know, that security and governance is a short throughout the, throughout the data learning life cycle, it >>Federated across in this example, across the fleet. So, all right, Michael, that's all the time we have right now. Thank you so much for that great information. Really appreciate it, >>Dave. Thank you. And thank you. Thanks for the audience for listening in today. Yes. Thank you for watching. >>Okay. We're here in the second manufacturing drill down session with Michael Gerber. He was the managing director for automotive and manufacturing solutions at Cloudera. And we're going to continue the discussion with a look at how to lower costs and drive quality in IOT analytics with better uptime. And look, when you do the math, that's really quite obvious when the system is down, productivity is lost and it hits revenue and the bottom line improve quality drives, better service levels and reduces loss opportunities. Michael. Great to see you >>Take it away. All right. Thank you so much. So I'd say we're going to talk a little bit about connected manufacturing, right. And how those IOT IOT around connected manufacturing can do as Dave talked about improved quality outcomes for manufacturing improve and improve your plant uptime. So just a little bit quick, quick, little indulgent, quick history lesson. I promise to be quick. We've all heard about industry 4.0, right? That is the fourth industrial revolution. And that's really what we're here to talk about today. First industrial revolution, real simple, right? You had steam power, right? You would reduce backbreaking work. Second industrial revolution, massive assembly line. Right. So think about Henry Ford and motorized conveyor belts, mass automation, third industrial revolution. Things got interesting, right? You started to see automation, but that automation was done, essentially programmed a robot to do something. It did the same thing over and over and over irrespective about it, of how your outside operations, your outside conditions change fourth industrial revolution, very different breakfast. >>Now we're connecting, um, equipment and processes and getting feedback from it. And through machine learning, we can make those, um, those processes adaptive right through machine learning. That's really what we're talking about in the fourth industrial revolution. And it is intrinsically connected to data and a data life cycle. And by the way, it's important, not just for a little bit of a slight issue. There we'll issue that, but it's important, not for technology sake, right? It's important because it actually drives and very important business outcomes. First of all, quality, right? If you look at the cost of quality, even despite decades of, of, of, of, uh, companies, um, and manufacturers moving to improve while its quality promise still accounted to 20% of sales, right? So every fifth of what you meant or manufactured from a revenue perspective, you've got quality issues that are costing you a lot. >>Plant downtime, cost companies, $50 billion a year. So when we're talking about using data and these industry 4.0 types of use cases, connected data types of use cases, we're not doing it just merely to implement technology. We're doing it to move these from drivers, improving quality, reducing downtime. So let's talk about how a connected manufacturing data life cycle, what like, right, because this is actually the business that cloud era is, is in. Let's talk a little bit about that. So we call this manufacturing edge to AI, this, this analytics life cycle, and it starts with having your plants, right? Those plants are increasingly connected. As I said, sensor prices have come down two thirds over the last decade, right? And those sensors have connected over the internet. So suddenly we can collect all this data from your, um, ma manufacturing plants. What do we want to be able to do? >>You know, we want to be able to collect it. We want to be able to analyze that data as it's coming across. Right? So, uh, in scream, right, we want to be able to analyze it and take intelligent real-time actions. Right? We might do some simple processing and filtering at the edge, but we really want to take real-time actions on that data. But, and this is the inference part of things, right? Taking the time. But this, the ability to take these real-time actions, um, is actually the result of a machine learning life cycle. I want to walk you through this, right? And it starts with, um, ingesting this data for the first time, putting it into our enterprise data lake, right in that data lake enterprise data lake can be either within your data center or it could be in the cloud. You've got, you're going to ingest that data. >>You're going to store it. You're going to enrich it with enterprise data sources. So now you'll have say sensor data and you'll have maintenance repair orders from your maintenance management systems. Right now you can start to think about do you're getting really nice data sets. You can start to say, Hey, which sensor values correlate to the need for machine maintenance, right? You start to see the data sets. They're becoming very compatible with machine learning, but so you, you bring these data sets together. You process that you align your time series data from your sensors to your timestamp data from your, um, you know, from your enterprise systems that your maintenance management system, as I mentioned, you know, once you've done that, we could put a query layer on top. So now we can start to do advanced analytics query across all these different types of data sets. >>But as I mentioned, you, and what's really important here is the fact that once you've stored long histories that say that you can build out those machine learning models I talked to you about earlier. So like I said, you can start to say, which sensor values drove the need, a correlated to the need for equipment maintenance for my maintenance management systems, right? And you can build out those models and say, Hey, here are the sensor values of the conditions that predict the need for Maples. Once you understand that you can actually then build out those models for deploy the models out the edge, where they will then work in that inference mode that we talked about, I will continuously sniff that data as it's coming and say, Hey, which are the, are we experiencing those conditions that PR that predicted the need for maintenance? If so, let's take real-time action, right? >>Let's schedule a work order or an equipment maintenance work order in the past, let's in the future, let's order the parts ahead of time before that piece of equipment fails and allows us to be very, very proactive. So, you know, we have, this is a, one of the Mo the most popular use cases we're seeing in terms of connecting connected manufacturing. And we're working with many different manufacturers around the world. I want to just highlight. One of them is I thought it's really interesting. This company is bought for Russia, for SIA, for ACA is the, um, is the, was, is the, um, the, uh, a supplier associated with Peugeot central line out of France. They are huge, right? This is a multi-national automotive parts and systems supplier. And as you can see, they operate in 300 sites in 35 countries. So very global, they connected 2000 machines, right. >>Um, and then once be able to take data from that. They started off with learning how to ingest the data. They started off very well with, um, you know, with, uh, manufacturing control towers, right? To be able to just monitor data firms coming in, you know, monitor the process. That was the first step, right. Uh, and, you know, 2000 machines, 300 different variables, things like, um, vibration pressure temperature, right? So first let's do performance monitoring. Then they said, okay, let's start doing machine learning on some of these things to start to build out things like equipment, um, predictive maintenance models or compute. And what they really focused on is computer vision while the inspection. So let's take pictures of, um, parts as they go through a process and then classify what that was this picture associated with the good or bad Bali outcome. Then you teach the machine to make that decision on its own. >>So now, now the machine, the camera is doing the inspections. And so they both had those machine learning models. They took that data, all this data was on-prem, but they pushed that data up to the cloud to do the machine learning models, develop those machine learning models. Then they push the machine learning models back into the plants where they, where they could take real-time actions through these computer vision, quality inspections. So great use case. Um, great example of how you can start with monitoring, moved to machine learning, but at the end of the day, or improving quality and improving, um, uh, equipment uptime. And that is the goal of most manufacturers. So with that being said, um, I would like to say, if you want to learn some more, um, we've got a wealth of information on our website. You see the URL in front of you, please go there and you'll learn. There's a lot of information there in terms of the use cases that we're seeing in manufacturing, a lot more detail, and a lot more talk about a lot more customers we'll work with. If you need that information, please do find it. Um, with that, I'm going to turn it over to Dave, to Steve. I think you had some questions you want to run by. >>I do, Michael, thank you very much for that. And before I get into the questions, I just wanted to sort of make some observations that was, you know, struck by what you're saying about the phases of industry. We talk about industry 4.0, and my observation is that, you know, traditionally, you know, machines have always replaced humans, but it's been around labor and, and the difference with 4.0, and what you talked about with connecting equipment is you're injecting machine intelligence. Now the camera inspection example, and then the machines are taking action, right? That's, that's different and, and is a really new kind of paradigm here. I think the, the second thing that struck me is, you know, the cost, you know, 20% of, of sales and plant downtime costing, you know, many tens of billions of dollars a year. Um, so that was huge. I mean, the business case for this is I'm going to reduce my expected loss quite dramatically. >>And then I think the third point, which we turned in the morning sessions, and the main stage is really this, the world is hybrid. Everybody's trying to figure out hybrid, get hybrid, right. And it certainly applies here. Uh, this is, this is a hybrid world you've got to accommodate, you know, regardless of, of where the data is. You've gotta be able to get to it, blend it, enrich it, and then act on it. So anyway, those are my big, big takeaways. Um, so first question. So in thinking about implementing connected manufacturing initiatives, what are people going to run into? What are the big challenges that they're going to, they're going to hit, >>You know, there's, there's, there, there's a few of the, but I think, you know, one of the ones, uh, w one of the key ones is bridging what we'll call the it and OT data divide, right. And what we mean by the it, you know, your, it systems are the ones, your ERP systems, your MES systems, right? Those are your transactional systems that run on relational databases and your it departments are brilliant, are running on that, right? The difficulty becomes an implementing these use cases that you also have to deal with operational technology, right? And those are, um, all of the, that's all the equipment in your manufacturing plant that runs on its proprietary network with proprietorial pro protocols. That information can be very, very difficult to get to. Right. So, and it's, it's a much more unstructured than from your OT. So th the key challenge is being able to bring these data sets together in a single place where you can start to do advanced analytics and leverage that diverse data to do machine learning. Right? So that is one of the, if I boil it down to the single hardest thing in this, uh, in this, in this type of environment, nectar manufacturing is that that operational technology has kind of run on its own in its own world. And for a long time, the silos, um, uh, the silos a, uh, bound, but at the end of the day, this is incredibly valuable data that now can be tapped, um, um, to, to, to, to move those, those metrics we talked about right around quality and uptime. So a huge, >>Well, and again, this is a hybrid team and you, you've kind of got this world, that's going toward an equilibrium. You've got the OT side and, you know, pretty hardcore engineers. And we know, we know it. A lot of that data historically has been analog data. Now it's getting, you know, instrumented and captured. Uh, so you've got that, that cultural challenge. And, you know, you got to blend those two worlds. That's critical. Okay. So, Michael, let's talk about some of the use cases you touched on, on some, but let's peel the onion a bit when you're thinking about this world of connected manufacturing and analytics in that space, when you talk to customers, you know, what are the most common use cases that you see? >>Yeah, that's a good, that's a great question. And you're right. I did allude to a little bit earlier, but there really is. I want people to think about, there's a spectrum of use cases ranging from simple to complex, but you can get value even in the simple phases. And when I talk about the simple use cases, the simplest use cases really is really around monitoring, right? So in this, you monitor your equipment or monitor your processes, right? And you just make sure that you're staying within the bounds of your control plan, right. And this is much easier to do now. Right? Cause some of these sensors are a more sensors and those sensors are moving more and more towards internet types of technology. So, Hey, you've got the opportunity now to be able to do some monitoring. Okay. No machine learning, but just talking about simple monitoring next level down, and we're seeing is something we would call quality event forensic analysis. >>And now on this one, you say, imagine I've got warranty plans in the, in the field, right? So I'm starting to see warranty claims kick up. And what you simply want to be able to do is do the forensic analysis back to what was the root cause of within the manufacturing process that caused it. So this is about connecting the dots. What about warranty issues? What were the manufacturing conditions of the day that caused it? Then you could also say which other tech, which other products were impacted by those same conditions. And we call those proactively rather than, and, and selectively rather than say, um, recalling an entire year's fleet of the car. So, and that, again, also not machine learning, we're simply connecting the dots from a warranty claims in the field to the manufacturing conditions of the day, so that you could take corrective actions, but then you get into a whole slew of machine learning, use dates, you know, and that ranges from things like Wally or say yield optimization. >>We start to collect sensor values and, um, manufacturing yield, uh, values from your ERP system. And you're certain start to say, which, um, you know, which on a sensor values or factors drove good or bad yield outcomes, and you can identify those factors that are the most important. So you, um, you, you measure those, you monitor those and you optimize those, right. That's how you optimize your, and then you go down to the more traditional machine learning use cases around predictive maintenance. So the key point here, Dave is, look, there's a huge, you know, depending on a customer's maturity around big data, you could start simply with, with monitoring, get a lot of value, start then bringing together more diverse data sets to do things like connect the.analytics then and all the way then to, to, to the more advanced machine learning use cases, there's this value to be had throughout. >>I remember when the, you know, the it industry really started to think about, or in the early days, you know, IOT and IOT. Um, it reminds me of when, you know, there was, uh, the, the old days of football field, we were grass and, and the new player would come in and he'd be perfectly white uniform, and you had it. We had to get dirty as an industry, you know, it'll learn. And so, so I question it relates to other technology partners that you might be working with that are maybe new in this space that, that to accelerate some of these solutions that we've been talking about. >>Yeah. That's a great question. And it kind of goes back to one of the things I alluded to alluded upon earlier. We've had some great partners, a partner, for example, litmus automation, whose whole world is the OT world. And what they've done is for example, they built some adapters to be able to catch it practically every industrial protocol. And they've said, Hey, we can do that. And then give a single interface of that data to the Idera data platform. So now, you know, we're really good at ingesting it data and things like that. We can leverage say a company like litmus that can open the flood gates of that OT data, making it much easier to get that data into our platform. And suddenly you've got all the data you need to, to, to implement those types of, um, industry for porno, our analytics use cases. And it really boils down to, can I get to that? Can I break down that it OT, um, you know, uh, a barrier that we've always had and, and bring together those data sets that we can really move the needle in terms of improving manufacturing performance. >>Okay. Thank you for that last question. Speaking to moving the needle, I want to li lead this discussion on the technology advances. I'd love to talk tech here. Uh, what are the key technology enablers and advancers, if you will, that are going to move connected manufacturing and machine learning forward in this transportation space. Sorry, manufacturing. Yeah. >>Yeah. I know in the manufacturing space, there's a few things, first of all, I think the fact that obviously I know we touched upon this, the fact that sensor prices have come down and have become ubiquitous that number one, we can, we've finally been able to get to the OT data, right? That's that's number one, you know, numb number two, I think, you know, um, we, we have the ability that now to be able to store that data a whole lot more efficiently, you know, we've got, we've got great capabilities to be able to do that, to put it over into the cloud, to do the machine learning types of workloads. You've got things like if you're doing computer vision, while in analyst respect GPU's to make those machine learning models much more, uh, much more effective, if that 5g technology that starts to blur at least from a latency perspective where you do your computer, whether it be on the edge or in the cloud, you've, you've got more, the super business critical stuff. >>You probably don't want to rely on, uh, any type of network connection, but from a latency perspective, you're starting to see, uh, you know, the ability to do compute where it's the most effective now. And that's really important. And again, the machine learning capabilities, and they believed a book to build a GP, you know, GPU level machine learning, build out those models and then deployed by over the air updates to, to your equipment. All of those things are making this, um, there's, you know, the advanced analytics and machine learning, uh, data life cycle just faster and better. And at the end of the day, to your point, Dave, that equipment and processor getting much smarter, uh, very much more quickly. Yeah, we got >>A lot of data and we have way lower cost, uh, processing platforms I'll throw in NP use as well. Watch that space neural processing units. Okay. Michael, we're going to leave it there. Thank you so much. Really appreciate your time, >>Dave. I really appreciate it. And thanks. Thanks for, uh, for everybody who joined us. Thanks. Thanks for joining today. Yes. Thank you for watching. Keep it right there.

Published Date : Aug 4 2021

SUMMARY :

Michael, great to see you over to you. And if you look at the F the top fleet operator, uh, the top benefits that So, you know, one of the things that's really important to be able to enable this right, And by the way, once you conducted the, um, this information from the trucks, you want to be able to analyze And you want to augment that with your dealership, say service information. So what do you do here? And they started off, uh, by, um, by, you know, connecting 475,000 And you know, the point here is with that, they were centralizing data from their telematics service providers, many of our, um, um, you know, um, uh, truck manufacturers. And you can push that back to the edge. And then you can do very simple things like just performance monitoring And then you start to see things like, uh, predictive maintenance happening, uh, you know, the blind spots they're, they're going to, they're going to get hit with, it OT kind of conundrum that, um, you know, So I think there's, you know, it's just stepping back for a second. the data center, and this is a metadata, you know, rethinking kind of how you manage metadata. with, you know, when you look at that connected vehicle life cycle, there are some core vendors And by the way, you mentioned Nvidia as well. and now that's changing and the advancements we're seeing there, what do you see as the, um, you know, basic communication that gateway now is becoming um, you know, and then on the, you know, on the cloud, you've got partners like Nvidia who are accelerating, And then real quick, it's not a quick topic, but you mentioned security. And one of the things that we're, you know, remember where the data management Thank you so much for that great information. Thank you for watching. And look, when you do the math, that's really quite obvious when the system is down, productivity is lost and it hits Thank you so much. So every fifth of what you meant or manufactured from a revenue So we call this manufacturing edge to AI, I want to walk you through this, um, you know, from your enterprise systems that your maintenance management system, And you can build out those models and say, Hey, here are the sensor values of the conditions And as you can see, they operate in 300 sites in They started off very well with, um, you know, great example of how you can start with monitoring, moved to machine learning, I think the, the second thing that struck me is, you know, the cost, you know, 20% of, And then I think the third point, which we turned in the morning sessions, and the main stage is really this, And what we mean by the it, you know, your, it systems are the ones, You've got the OT side and, you know, pretty hardcore engineers. And you just make sure that you're staying within the bounds of your control plan, And now on this one, you say, imagine I've got warranty plans in the, in the field, look, there's a huge, you know, depending on a customer's maturity around big data, I remember when the, you know, the it industry really started to think about, or in the early days, you know, uh, a barrier that we've always had and, if you will, that are going to move connected manufacturing and machine learning forward that starts to blur at least from a latency perspective where you do your computer, and they believed a book to build a GP, you know, GPU level machine learning, Thank you so much. Thank you for watching.

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Manufacturing Reduce Costs and Improve Quality with IoT Analytics


 

>>Okay. We're here in the second manufacturing drill down session with Michael Gerber. He was the managing director for automotive and manufacturing solutions at Cloudera. And we're going to continue the discussion with a look at how to lower costs and drive quality in IOT analytics with better uptime and hook. When you do the math, that's really quite obvious when the system is down, productivity is lost and it hits revenue and the bottom line improve quality drives, better service levels and reduces lost opportunities. Michael. Great to see you, >>Dave. All right, guys. Thank you so much. So I'll tell you, we're going to talk a little bit about connected manufacturing, right? And how those IOT IOT around connected manufacturing can do as Dave talked about improved quality outcomes for manufacturing improve and improve your plant uptime. So just a little bit quick, quick, little indulgent, quick history lesson. I promise to be quick. We've all heard about industry 4.0, right? That is the fourth industrial revolution. And that's really what we're here to talk about today. First industrial revolution, real simple, right? You had steam power, right? You would reduce backbreaking work. Second industrial revolution, mass assembly line. Right. So think about Henry Ford and motorized conveyor belts, mass automation, third industrial revolution. Things got interesting, right? You started to see automation, but that automation was done essentially programmed a robot to do something. It did the same thing over and over and over irrespective about of how your outside operations, your outside conditions change fourth industrial revolution, very different breakfasts. >>Now we're connecting, um, equipment and processes and getting feedback from it. And through machine learning, we can make those, um, those processes adapted right through machine learning. That's really what we're talking about in the fourth industrial revolution. And it is intrinsically connected to data and a data life cycle. And by the way, it's important, not just for a little bit of a slight issue. There we'll issue that, but it's important, not for technology sake, right? It's important because it actually drives very important business outcomes. First of all, falling, right? If you look at the cost of quality, even despite decades of, of, uh, companies and manufacturers moving to improve while its quality prompts still account to 20% of sales, right? So every fifth of what you meant or manufactured from a revenue perspective, you've got quality issues that are costing you a lot. Plant downtime, cost companies, $50 billion a year. >>So when we're talking about using data and these industry 4.0 types of use cases, connected data types of use cases, we're not doing it just narrowly to implement technology. We're doing it to move these from adverse, improving quality, reducing downtime. So let's talk about how a connected manufacturing data life cycle with what like, right. But so this is actually the business that cloud areas is in. Let's talk a little bit about that. So we call this manufacturing edge to AI. This is analytics, life something, and it starts with having your plants, right? Those plants are increasingly connected. As I said, sensor prices have come down two thirds over the last decade, right? And those sensors are connected over the internet. So suddenly we can collect all this data from your, um, manufacturing plants, and what do we want to be able to do? You know, we want to be able to collect it. >>We want to be able to analyze that data as it's coming across. Right? So, uh, in scream, right, we want to be able to analyze it and take intelligent real-time actions. Right? We might do some simple processing and filtering at the edge, but we really want to take real-time actions on that data. But, and this is the inference part of things, right? Taking that time. But this, the ability to take these real-time actions, um, is actually the result of a machine learning life cycle. I want to walk you through this, right? And it starts with, um, ingesting this data for the first time, putting it into our enterprise data lake, right? And that data lake enterprise data lake can be either within your data center or it could be in the cloud. You're going to, you're going to ingest that data. You're going to store it. >>You're going to enrich it with enterprise data sources. So now you'll have say sensor data and you'll have maintenance repair orders from your maintenance management systems. Right now you can start to think about do you're getting really nice data sets. You can start to say, Hey, which sensor values correlate to the need for machine maintenance, right? You start to see the data sets. They're becoming very compatible with machine learning, but so you bring these datasets together. You process that you align your time series data from your sensors to your timestamp data from your, um, you know, from your enterprise systems that your maintenance management system, as I mentioned, you know, once you've done that, we could put a query layer on top. So now we can start to do advanced analytics query across all these different types of data sets. But as I mentioned to you, and what's really important here is the fact that once you've stored one histories that say that you can build out those machine learning models I talked to you about earlier. >>So like I said, you can start to say, which sensor values drove the need of correlated to the need for equipment maintenance for my maintenance management systems, right? And then you can build out those models and say, Hey, here are the sensor values of the conditions that predict the need for maintenance. And once you understand that you can actually then build out those models, you deploy the models out to the edge where they will then work in that inference mode, that photographer, I will continuously sniff that data as it's coming and say, Hey, which are the, are we experiencing those conditions that, that predicted the need for maintenance? If so, let's take real-time action, right? Let's schedule a work order and equipment maintenance work order in the past, let's in the future, let's order the parts ahead of time before that a piece of equipment fails and allows us to be very, very proactive. >>So, you know, we have, this is a, one of the Mo the most popular use cases we're seeing in terms of connected, connected manufacturing. And we're working with many different, um, manufacturers around the world. I want to just highlight one of them. Cause I thought it's really interesting. This company is bought for Russia. And for SIA for ACA is the, um, is the, is the, um, the, uh, a supplier associated with out of France. They are huge, right? This is a multi-national automotive, um, parts and systems supplier. And as you can see, they operate in 300 sites in 35 countries. So very global, they connected 2000 machines, right. Um, I mean at once be able to take data from that. They started off with learning how to ingest the data. They started off very well with, um, you know, with, uh, manufacturing control towers, right? >>To be able to just monitor the data from coming in, you know, monitor the process. That was the first step, right. Uh, and you know, 2000 machines, 300 different variables, things like, um, vibration pressure temperature, right? So first let's do performance monitoring. Then they said, okay, let's start doing machine learning on some of these things, just start to build out things like equipment, um, predictive maintenance models, or compute. What they really focused on is computer vision while the inspection. So let's take pictures of, um, parts as they go through a process and then classify what that was this picture associated with the good or bad quality outcome. Then you teach the machine to make that decision on its own. So now, now the machine, the camera is doing the inspections for you. And so they both had those machine learning models. They took that data, all this data was on-prem, but they pushed that data up to the cloud to do the machine learning models, develop those machine learning models. >>Then they push the machine learning models back into the plants where they, where they could take real-time actions through these computer vision, quality inspections. So great use case. Um, great example of how you start with monitoring, move to machine learning, but at the end of the day, or improving quality and improving, um, uh, equipment uptime. And that is the goal of most manufacturers. So with that being said, um, I would like to say, if you want to learn some more, um, we've got a wealth of information on our website. You see the URL in front of you, please go, then you'll learn. There's a lot of information there in terms of the use cases that we're seeing in manufacturing and a lot more detail and a lot more talk about a lot more customers we'll work with. If you need that information, please do find it. Um, with that, I'm going to turn it over to Dave, to Steve. I think you had some questions you want to run by. >>I do, Michael, thank you very much for that. And before I get into the questions, I just wanted to sort of make some observations that was, you know, struck by what you're saying about the phases of industry. We talk about industry 4.0, and my observation is that, you know, traditionally, you know, machines have always replaced humans, but it's been around labor and, and the difference with 4.0, and what you talked about with connecting equipment is you're injecting machine intelligence. Now the camera inspection example, and then the machines are taking action, right? That's, that's different and, and is a really new kind of paradigm here. I think the, the second thing that struck me is, you know, the costs, you know, 20% of, of sales and plant downtime costing, you know, many tens of billions of dollars a year. Um, so that was huge. I mean, the business case for this is I'm going to reduce my expected loss quite dramatically. >>And then I think the third point, which we turned in the morning sessions, and the main stage is really this, the world is hybrid. Everybody's trying to figure out hybrid, get hybrid, right. And it certainly applies here. Uh, this is, this is a hybrid world you've got to accommodate, you know, regardless of where the data is, you've got to be able to get to it, blend it, enrich it, and then act on it. So anyway, those are my big, big takeaways. Um, so first question. So in thinking about implementing connected manufacturing initiatives, what are people going to run into? What are the big challenges that they're going to, they're going to hit? >>No, there's, there's there, there's a few of the, but I think, you know, one of the, uh, one of the key ones is bridging what we'll call the it and OT data divide, right. And what we mean by the it, you know, your, it systems are the ones, your ERP systems, your MES system, Freightos your transactional systems that run on relational databases and your it departments are brilliant at running on that, right? The difficulty becomes an implementing these use cases that you also have to deal with operational technology, right? And those are all of the, that's all the equipment in your manufacturing plant that runs on its proprietary network with proprietary pro protocols. That information can be very, very difficult to get to. Right? So, and it's uncertain, it's a much more unstructured than from your OT. So the key challenge is being able to bring these data sets together in a single place where you can start to do advanced analytics and leverage that diverse data to do machine learning. Right? So that is one of the, if I had to boil it down to the single hardest thing in this, uh, in this, in this type of environment, nectar manufacturing is that that operational technology has kind of run on its own in its own. And for a long time, the silos, the silos, a bound, but at the end of the day, this is incredibly valuable data that now can be tapped, um, um, to, to, to, to move those, those metrics we talked about right around quality and uptime. So a huge opportunity. >>Well, and again, this is a hybrid team and you, you've kind of got this world, that's going toward an equilibrium. You've got the OT side and, you know, pretty hardcore engineers. And we know, we know it. A lot of that data historically has been analog data. This is Chris now is getting, you know, instrumented and captured. Uh, and so you've got that, that cultural challenge and, you know, you got to blend those two worlds. That's critical. Okay. So Michael, let's talk about some of the use cases you touched on, on some, but let's peel the onion a bit when you're thinking about this world of connected manufacturing and analytics in that space, when you talk to customers, you know, what are the most common use cases that you see? >>Yeah, that's a great, that's a great question. And you're right. I did allude to a little bit earlier, but there really is. I want people to think about this, a spectrum of use cases ranging from simple to complex, but you can get value even in the simple phases. And when I talk about the simple use cases, the simplest use cases really is really around monitoring, right? So in this, you monitor your equipment or monitor your processes, right? And you just make sure that you're staying within the bounds of your control plan, right? And this is much easier to do now. Right? Cause some of these sensors are a more sensors and those sensors are moving more and more towards the internet types of technology. So, Hey, you've got the opportunity now to be able to do some monitoring. Okay. No machine learning, we're just talking about simple monitoring next level down. >>And we're seeing is something we would call quality event forensic announces. And now on this one, you say, imagine I'm got warranty plans in the, in the field, right? So I'm starting to see warranty claims kicked off on them. And what you simply want to be able to do is do the forensic analysis back to what was the root cause of within the manufacturing process that caused it. So this is about connecting the dots I've got, I've got warranty issues. What were the manufacturing conditions of the day that caused it? Then you could also say which other, which other products were impacted by those same conditions. And we call those proactively rather than, and, and selectively rather than say, um, recalling an entire year's fleet of a car. So, and that, again, also not machine learning is simply connecting the dots from a warranty claims in the field to the manufacturing conditions of the day so that you could take corrective actions, but then you get into a whole slew of machine learning use case, you know, and, and that ranges from things like quality or say yield optimization, where you start to collect sensor values and, um, manufacturing yield, uh, values from your ERP system. >>And you're certain start to say, which, um, you know, which map a sensor values or factors drove good or bad yield outcomes. And you can identify those factors that are the most important. So you, um, you, you measure those, you monitor those and you optimize those, right. That's how you optimize your, and then you go down to the more traditional machine learning use cases around predictive maintenance. So the key point here, Dave is, look, there's a huge, you know, depending on a customer's maturity around big data, you could start simply with monitoring, get a lot of value, start, then bring together more diverse datasets to do things like connect the.analytics then all and all the way then to, to, to the more advanced machine learning use cases this value to be had throughout. >>I remember when the, you know, the it industry really started to think about, or in the early days, you know, IOT and IOT. Um, it reminds me of when, you know, there was, uh, the, the old days of football field, we were grass and, and a new player would come in and he'd be perfectly white uniform and you had it. We had to get dirty as an industry, you know, it'll learn. And so, so my question relates to other technology partners that you might be working with that are maybe new in this space that, that to accelerate some of these solutions that we've been talking about. >>Yeah. That's a great question. I kind of, um, goes back to one of the things I alluded a little bit about earlier. We've got some great partners, a partner, for example, litmus automation, whose whole world is the OT world. And what they've done is for example, they built some adapters to be able to get to practically every industrial protocol. And they've said, Hey, we can do that. And then give a single interface of that data to the Idera data platform. So now, you know, we're really good at ingesting it data and things like that. We can leverage say a company like litmus that can open the flood gates of that OT data, making it much easier to get that data into our platform. And suddenly you've got all the data you need to, to implement those types of, um, industry 4.0, uh, analytics use cases. And it really boils down to, can I get to that? Can I break down that it OT, um, you know, uh, uh, barrier that we've always had and, and bring together those data sets that really move the needle in terms of improving manufacturing performance. >>Okay. Thank you for that last question. Speaking to moving the needle, I want to Lee lead this discussion on the technology advances. I'd love to talk tech here. Uh, what are the key technology enablers and advancers, if you will, that are going to move connected manufacturing and machine learning forward in this transportation space. Sorry. Manufacturing in >>Factor space. Yeah, I know in the manufacturing space, there's a few things, first of all, I think the fact that obviously I know we touched upon this, the fact that sensor prices have come down and it had become ubiquitous that number one, we can w we're finally been able to get to the OT data, right? That's that's number one, number, number two, I think, you know, um, we, we have the ability that now to be able to store that data a whole lot more efficiently, you know, we've got, we've got great capabilities to be able to do that, to put it over into the cloud, to do the machine learning types of workloads. You've got things like if you're doing computer vision, while in analyst respect GPU's to make those machine learning models much more, um, much more effective, if that 5g technology that starts to blur at least from a latency perspective where you do your computer, whether it be on the edge or in the cloud, you've, you've got more, you know, super business critical stuff. >>You probably don't want to rely on, uh, any type of network connection, but from a latency perspective, you're starting to see, uh, you know, the ability to do compute where it's the most effective now. And that's really important. And again, the machine learning capabilities, and they believed the book, bullet, uh, GP, you know, GPU level, machine learning, all that, those models, and then deployed by over the air updates to your equipment. All of those things are making this, um, there's, you know, there's the advanced analytics and machine learning, uh, data life cycle just faster and better. And at the end of the day, to your point, Dave, that equipment and processes are getting much smarter, uh, very much more quickly. >>Yep. We've got a lot of data and we have way lower costs, uh, processing platforms I'll throw in NP use as well. Watch that space neural processing units. Okay. Michael, we're going to leave it there. Thank you so much. Really appreciate your time, >>Dave. I really appreciate it. And thanks. Thanks for, uh, for everybody who joined. Uh, thanks. Thanks for joining today. Yes. Thank you for watching. Keep it right there.

Published Date : Aug 3 2021

SUMMARY :

When you do the math, that's really quite obvious when the system is down, productivity is lost and it hits revenue and the bottom Thank you so much. So every fifth of what you meant or manufactured from a revenue perspective, And those sensors are connected over the internet. I want to walk you through those machine learning models I talked to you about earlier. And then you can build out those models and say, Hey, here are the sensor values of the conditions And as you can see, they operate in 300 sites To be able to just monitor the data from coming in, you know, monitor the process. And that is the goal of most manufacturers. I think the, the second thing that struck me is, you know, the costs, you know, 20% of, And then I think the third point, which we turned in the morning sessions, and the main stage is really this, And what we mean by the it, you know, your, it systems are the ones, So Michael, let's talk about some of the use cases you touched on, on some, And you just make sure that you're staying within the bounds of your control plan, And now on this one, you say, imagine I'm got warranty plans in the, in the field, And you can identify those factors that I remember when the, you know, the it industry really started to think about, or in the early days, litmus that can open the flood gates of that OT data, making it much easier to if you will, that are going to move connected manufacturing and machine learning forward that data a whole lot more efficiently, you know, we've got, we've got great capabilities to be able to do that, And at the end of the day, to your point, Dave, that equipment and processes are getting much smarter, Thank you so much. Thank you for watching.

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Manish Chawla, IBM | IBM Think 2021


 

>> (soft music) >> Presenter: From around the globe. It's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Welcome back everyone to the CUBE's coverage of IBM Think 2021. I'm your host, John furry with theCUBE. Our next guest Manish Chawla who's the industry general manager of energy, resources and manufacturing, a great guest to break down this next generation of infrastructure modern applications and changing the business in the super important areas he's regulated verticals. Manish, it's great to see you. Thank you for coming back on theCUBE. >> Thank you John. Good to meet you. >> You know, this is the area where I've been saying for years the cloud brings great scale horizontally scalable data, but at the end of the day, AI and automation really has to be specialized in the verticals. In this we're going to see the action the ecosystems for connecting. This is a big deal here I think this year, transformation is the innovation, innovation at scale. This seems to be the underlying theme that we've been reporting on. So I'd love to get your thoughts on how you see this Fourth Industrial Revolution as you say, coming about. Can you define for us what that means? And when you say that, what does it mean for customers? >> Yeah, sure, sure. So, you know, in sort of simple terms all the technologies that we see around us, whether it's AI we talk about AI, we talk about 5G, we talk about Edge Cloud Robotics. So the application of those to the physical world in some sense in the industrial world is what we define as the Fourth Industrial Revolution. Essentially, it's the convergence between the humans, the physical aspect, like the machines and the cyber either digital aspects, bringing that together. So companies can unlock the value from the terabytes and petabytes of data that our connected world is now able to produce. >> How does the IOT world come in? We've been again, I did a panel I think two years ago called you know the industrial IOT Armageddon. And it was really kind of pointing. It was kind of provocative title, but the point was you know, the industrial connections are all devices now and they're connected to the network security super important. This industrial revolution includes this new edge. >> It's got to be smarter and intelligent. What's your take on that? >> Yeah, absolutely. It is about the edge. It's about devices. It's about delivering capturing the data from the umpteen devices. You know, we've recently heard about the chip shortage which gives you an idea that there is so much utilization of compute power everywhere in the world. And the world is becoming very software defined. So whether it's software defined machines software defined products, the washing machines that we use at home, the cars we use home, everything is gradually becoming, not gradually I'd say rapidly becoming intelligent. And so that edge or IOT is the foundation stone of everything we're talking about. >> Well, you mentioned software on a chip SOC that's a huge mega wave coming. That's going to bring so much more compute into smaller form factors which leads me to my next question, which kind of, I'm kind of answering for myself but I'm not a manufacturing company but why should they care about this trend from a business perspective besides the obvious new connection points? What's really in it for them? >> Yeah. So big topic right now is this topic of resilience, right? So that's one aspect. This, the pandemic has taught us that resilience is a core objective. The second objective, which is front and center of all CEOs or CEOs is out-performance. And so what we're seeing is out-performance are investing in technology for many goals, right? So it's either sustainability which is a big topic these days, and a huge priority. It's about efficiency. It's about productivity. It's also now more and more about delivering a much stronger customer experience, right? Making your products easier to use much easily consumable as well. So if you, when you pull it all together it's an end to end thinking about using data to drive those objectives of out-performance as well as resilience. >> What's the progress being made so far on the manufacturing industry on this front? I mean, is it moving faster or you mentioned accelerating but where is the progress bar right now? >> So I think as we came into 2020, I would have described it as we were starting to enter the chapter two where companies were moving from experimentation to really thinking of scaling this. And what we found is the pandemic really caused a big focus on these, as Winston Churchill has been attributed the quote "Never waste a good crisis." A lot of CEOs, a lot of executives and leadership really put their energy into accelerating digital transformation. I think we really, two thirds have been able to accelerate their digital transformation. So the good news is, you know companies don't have to be convinced about this anymore. They're really, their focus is on where should I start? Where should I focus? And what should I do next? Right, is really the focus. And they are investing in sort of two types of technologies is the way we see it. What I would call foundational technologies because there's a recognition that to apply the differentiating technologies like AI and capturing and taking value of the data you need a strong architectural foundation. So whether it's cybersecurity, it's what we call ITOT integration connecting the devices back to the mothership. And it's also applying cloud but cloud in this context is not about typically what we think as public cloud or a central spot. It's really bringing cloud-like technologies also to the edge or to the plant or to the device itself whether it's a mobile device or a physical device. And that foundation is that recognition that you've got to have the foundation that you can build your capabilities on top. Whether it's for customers or clients or colleagues. >> That's a great insight on the architecture. I think that's a successful playbook. It sounds so easy. I do agree with you. I think people have said this is a standard now hybrid cloud, the edge pretty clear visibility on the architecture of what to do or what needs to be done, how to do it, all other story. So I have to ask you, we hear of these barriers. There's always blockers. I think COVID's released some of those relieved some of those blockers because people have to force their way into the transformation but what are those barriers that are stopping the acceleration for customers to achieve the benefits that they need to see? >> Yeah. So I think one or one key barrier is a recognition that most of our plants or manufacturing facilities or supply chains really run in a brownfield manner. I, there's so many machines so many facilities that have been built over decades. So there's a proliferation of different ages of devices, machines, et cetera. So making sure that there is a focus on laying out a foundation, that's a key barrier. There is also a concern that, you know the companies have around cybersecurity. The more you connect the more you increase the attack surface. And we know that that hacks and so on are, are a dominant issue now whether it's for ransomware or for other malicious reasons. And so modernizing the foundation and making sure you're doing it in a secure way those are the key concerns that executives have. And then another key barrier I see is making sure that you have a key, key core objective and not making too many different varied experimentation beds. So keeping a focus on what's the core use case of benefit you're after and then what's the foundation to make sure that you're going after it. Like I said, whether it's quality or productivity or such like. >> So the keys to success, if I get this right is you have the right framework for this as you say, industry 4.0 you got to understand the collaborative dynamics and then have an ecosystem. >> Yeah. Can you unpack those three things? Because take me through that. You got to the framework, the collaboration and the ecosystem. What does that mean specifically? >> So the way I take the simplest way to think of it is the amount of work and effort that all companies have to put in, is so great in front of them. The opportunities are so great as well that nobody can hire all the smart people that are needed to achieve the goals. Everybody has their own specific I would say focus and capabilities they bring to bear. So the collaboration between manufacturers the collaboration between operational technology companies like the Siemens, ABB, Schlumberger, et cetera and IT technology companies like ourselves that three-part collaboration is sort of the heart of what I see as ecosystems coming together. The other dimensionality of ecosystems is also looking at it from a supply chain or a value chain perspective cause how something becomes more intelligent or smarter or more effective is also being able to work across the supply chain or value chain. So those are our key focus areas make sure we are collaborating across value chains and supply chains, as well as collaborating with manufacturers and OT, operational technology companies to be able to bring these digital capabilities with the right capabilities of operational technology companies into the manufacturers. >> If I asked you, how are you doing that? What specifically would you say? I mean, how are you collaborating? What's some examples give some examples of this enaction. >> Certainly. So we recently announced over the last say, nine months or so three strategic, very transformative partnerships. The first one I'll share with you is with Schlumberger. Schlumberger is the world's largest oil field services company. And now also the world's largest distill technology company for the oil and gas industry. So we've collaborated with them to bring hybrid cloud to the digital platform so they now can deploy their capabilities to any customer regardless of whether they want it in country or on a public cloud. Another example is we've established a data platform with Schlumberger for the oil and gas industry, to be able to bring again that data platform to any location around the world. The advantage of hybrid, the advantage of AI. With EVB, what we've done is we've taken our smart sync IT security connected with their products and capabilities for operational systems. And now are delivering an end to end solution that you can get cyber alerts or issues coming from manufacturing systems dry down to right up to an IT command center where you're seeing all the events and alerts so that they can be acted upon right away. So that's a great example of collaborating with IT from a security point of view. The third one is industrial IOT with Siemens and we've partnered with Siemens to deliver the MindSphere private cloud edition. Delivered on our red hat hybrid cloud. So this is an example where we are able to take our horizontal technologies, apply it with their verticals smarts and deep industry context put our services capabilities on top of it so they can deliver their innovations anywhere >> Manish is such an expert on this such a great leader on this area and I have to ask you you know, you've been in this mode of evangelizing and leading teams and building solutions around digital re platforming or whatever you want to call it, renovations. >> Manish: Right >> What's the big deal now, if you had to, I mean, it seems like it's all coming together with red hat under the covers, you get distributed networks with the Edge. It's all kind of coming together now for the verticals because you got the best of both worlds. Programmable scalable infrastructure with modern software applications on top. I mean, you've been even in the industry for many many waves, why is this wave so big and important? >> So I think there is no longer the big reason why it's important is I think there's no reason why companies have to be convinced now that the clarity is there that this needs to happen so that's one. The second is, I think there's a high degree of expectation among consumers, among employees and among customers as well, that everything that we touch will be intelligent. So these technologies really unlock the value unlock the value, and they can be deployed at scale that's really, I think what we're seeing as the focus now. And being able to deliver the innovation anywhere whether someone wants it at the Edge next to a machine that's operating, or be able to look at how a manufacturing facility or different product portfolio is doing in the boardroom. It's all available. And so that shop floor, the top floor connection is what everybody's aiming for but we also now call it Edge to enterprise. >> And everything works better, the employees are happy people are happy, stakeholders are happy. Manish great insight. Thank you for sharing here on theCUBE for Think 2021. Thanks for coming on theCUBE. >> Absolutely thanks John for having me. >> Okay. I'm John Furry host theCUBE for IBM Think 2021. Thanks for watching. (soft music)

Published Date : May 12 2021

SUMMARY :

of IBM Think 2021 brought to you by IBM. in the super important areas but at the end of the So the application of How does the IOT world come in? It's got to be smarter and intelligent. It is about the edge. besides the obvious new connection points? This, the pandemic has So the good news is, you know the benefits that they need to see? the more you increase the attack surface. So the keys to success, the collaboration and the ecosystem. So the way I take the I mean, how are you collaborating? Schlumberger is the world's and I have to ask you What's the big deal that the clarity is there better, the employees are happy Thanks for watching.

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IBM28 Manish Chawla VTT


 

>>from around the >>globe. It's the cube with digital >>coverage of IBM >>Think 2021 >>brought to you by IBM. Welcome back everyone to the cubes coverage of IBM Think 2021 I'm your host john ferry with the cube. Our next guest is Michelle well who's the industry General manager of Energy resources manufacturing. Great guest to break down this next generation of infrastructure, modern applications and changing the business and the super important areas is regulated verticals. Great to see you. Thank you for coming back on the queue. >>Thank you john good to meet you. >>You know this is the area where I've been saying for years the cloud brings great scale, horizontally scalable data but at the end of the day AI and automation really has to be specialized in in the verticals and this. We're going to see the action ecosystems for connecting. This is a big deal here think this year transformation is the innovation innovation at scale. It seems to be the underlying theme that we've been reporting on. So I'd love to get your thoughts on how you see this fourth industrial revolution as you say, coming about. Can you define for us what that means and when you say that, what does it mean for customers? >>Yeah, sure, sure. So you know, in in sort of simple terms, all the technologies that we see around us whether it's a I we talk about a I we talked about five G. We talk about edge cloud, robotics. So the application of those to the physical world in some sense, in the industrial world is what we define as uh as the fourth industrial revolution. Essentially it's the convergence between the humans, the physical aspect by the machines and the cyber at the digital aspects, bringing that together so companies can unlock the value from the terabytes and petabytes of data that's that are connected world is now able to produce, >>How does the IOT world come in? We've been again, I did a panel I think two years ago called you know the industrial IOT Armageddon. And it was really kind of point, it was kind of provocative title but the point was you know, the industrial connections are all devices now and they're connected to the network security. Super important, this industrial revolution includes this new edge, it's gotta be smarter and intelligent. What's your take on that? >>Absolutely, it is about the edge, it's about devices, it's about delivering capturing the data from the emptying devices. We've recently heard about the chip shortage which gives you an idea that there is so much utilization of compute power everywhere in the world and the world is becoming very software defined. So whether it's software defined machines, software defined products, the washing machines that he that we use at home, the cars we use at home, there everything is gradually becoming, not gradually, I'd say rapidly becoming intelligent and so that edge or IOT is the foundation stone also everything we're talking about. >>Well you mentioned software on a chip, S. O. C. Um, that's a huge mega wave coming. That's gonna bring so much more compute into smaller form factors. Which leads me to my next question, which kind of, I'm kind of answering for myself, but I'm not a manufacturing company, but why should they care about this trend from a business perspective? Besides the obvious new connection points? What's really in it for them? >>Yes, it's a big topic right now, is, is this topic of resilience? Right, So that's one aspect uh, this the pandemic has taught us that resilience is a core objective. The second objective which which is front and center of all CEOS, or CEOS, is out performance. And so what we're seeing is is out performance, are investing in technology for many goals, right? So it's either sustainability which is a big topic these days and huge priority. Uh it's about efficiency, it's about productivity, it's also now more and more about delivering a much stronger customer experience, right? Making your products easier to use much easily consumable as well. So, if you, when you pull it all together, it's it's an end to end thinking about using data to drive those objectives of out performance, as well as resilience. >>What's the progress being made so far in the manufacturing industry on this front? I mean, is it moving faster? Are you mentioned accelerating? But where is the progress bar? Right now? >>So, I think as we came into 2020, I would have described it as we were starting to enter the Chapter. Two companies were moving from experimentation to really thinking of scaling this and and what we found is the pandemic really caused a big focus on these. As Winston Churchill has been attributed the court never waste a good crisis. So a lot of ceos, a lot of executives and leadership really put their What their energy into accelerate industrial transformation. I think we relieve 2/3 southwell have been able to accelerate the industrial transformation. So the good news is, you know, companies don't have to be convinced about this anymore. They're really they're focuses on what's where should I start? Where should I focus on what should I do next? Right is really the focus and they're investing instead of two types of technologies is the way we see it, what I would call foundational technologies because there's a recognition that to apply the differentiating technologies like Ai and captured and taking value of the data, you need a strong architectural foundation. So whether it's it's cybersecurity, it's what we call it, the integration, connecting the devices back to to the mother ship and it's also applying cloud. But cloud in this context is not about typically what we think is public cloud or or or central spot. It's really bringing cloud like technology is also to the edge I. E. To the plant or to the device itself, whether it's a mobile device or a physical device. And that foundation is the recognition that you've got to have the foundation, that you can build your your capabilities on top, whether it's for customers or clients and colleagues >>as a great insight on the architecture, I think that's a successful playbook. Um It sounds so easy, I do agree with you. I think people have said this is a standard now, Hybrid cloud the edge, pretty clear visibility on the architecture of what to do or what needs to be done, how to do it almost story. So I have to ask you, we hear this barriers, there's always blockers. I think Covid released some of those, relieved some of those blockers because people have to force their way into into the transformation. But what are those barriers um that that are stopping the acceleration for customers to achieve the benefits that they need to see. >>Yes. So I think 11 key barrier is is a recognition that most of our plants or manufacturing facilities that supply chains really run run in a brownfield manner. I there's so many machines, so many facilities that have been built over decades. So there's a there's a proliferation of different ages of devices, machines, etcetera. So making sure that there is a focus on laying out the foundation. That's a key key barrier. Uh There is also a concern that uh you know, the companies have around cybersecurity, the more you connect, the more you increase the attack surface and we know that that acts and so on are the dominant issue. Now, whether it's for ransom, fair or for or for other malicious reasons, uh and so modernizing the foundation and making sure you're doing it in a secure way. Those are the key concerns that executives have. And then another key barrier I see is making sure that you have a key key core objective and not making sure making too many different varied experimentation bets. So keeping a focus on what's the call? Use case of benefit your after and then what's the foundation to make sure that you're going after it? Like I said, whether it's quality or productivity or such, like >>So the keys to success that I get this right is gonna have the right framework for this, as you say, industry 4.0, you got to understand the collaborative dynamics and then have an ecosystem. Yeah, can you unpack those three things? Because take me through that, you got to the framework, the collaboration and the ecosystem. What does that mean? Specifically? >>So uh the way, I think the simplest way to think of it as the amount of work and effort that all companies have been put in is so great in front of them, the opportunities are so great as well uh that nobody can hire all the smart people that are needed to achieve the goals. Everybody has their own specific I would say focus and capabilities they bring to bear. So the collaboration between manufacturers, the collaboration between operational technology companies like the Seaman's, A B B, Schlumberger's, etcetera. And and it technology companies like ourselves that three part collaboration is sort of the heart of what I see as ecosystems coming together. The other dimensionality of ecosystems is also looking at it from a supply chain or value chain perspective because how something becomes more intelligent or smarter or more effective is also being able to work across the supply chain or value chain. So those, those are our key focus areas, make sure we are collaborating across value chains and supply chains as well as collaborating with manufacturers and oT operational technology companies to be able to bring these digital capabilities with the right capabilities of operational technology companies into the manufacturers. >>If I asked you, how is you doing that? What specifically would you say? I mean, how are you collaborating? What's some examples, give some examples of of this in action? >>Certainly. So we recently announced uh over the last say nine months or so, three strategic very translated partnerships. The first one I'll share with you is uh is which number number two is the world's largest oil field services company and now also the world's largest distal technology company for the oil and gas industry. So we've collaborated with them to bring hybrid cloud to the digital platforms so they now can deploy the capabilities to any customer regardless of whether they want it in country or on a public cloud. Another example is we've we've established a data platform which number J for the oil and gas industry to be able to bring again that data platform to any location around the world. The advantage of hybrid, the advantage of A. I with the B. B. What we've done is we've taken our smarts in I. T. Security connected with their products and capabilities for operational systems and now are delivering an into institution that you can get cyber alerts or issues coming from from manufacturing systems right down to right up to an I. T. Command center where you're seeing all the events and alerts so that they can be acted upon right away. So that's a great example of collaborating with from a security point of view. The 3rd 1 is industrial iot with ceilings and we've partnered with Siemens to deliver their minds Fear Private cloud edition delivered on our red hat Hybrid cloud. So this is an example where we are able to take our horizontal technologies, apply it with their vertical smarts and deep industry cause of context put our services capabilities on top of it so they can deliver their innovations anymore. >>It is such an expert on this, such a great leader on this area. And I have to ask you, you know, you've been in this um mode of evangelizing and leading teams and building solutions around digital re platform or whatever you wanna call her innovation. Um what's the big deal now? If you had to? I mean, it seems like it's all coming together with red hat under the covers, get distributed networks with the edge, it's all kind of coming together now for the verticals because you get the best of both worlds programmable scalable infrastructure with modern software applications on top. I mean you've been even even in the industry for many, many waves, why is this wave so big and important? >>So I think there is no longer uh big reason why it's important. I think there's no no reason why companies have to be convinced now the clarity is there, that this needs to happen. So that's one. The second is I think there is a high degree of expectation among consumers, among employees and among among customers as well that everything that we touch will be intelligent. So these technologies really unlock the value, uh unlock the value and they can be deployed at scale. That's really, I think what we're seeing as the focus now and being able to deliver the innovation anywhere, whether someone wants it at the edge next to a machine that's operating or be able to look at how a manufacturing facility or different product portfolio is doing in the boardroom, it's all available and so that shop floor, the top floor connection is what everybody is aiming for. We also now called edge to enterprise >>And everything works better. The employees are happy, people are happy to, stakeholders are happy finish. Great insight. Thank you for sharing here on the Cube for think 2021. Thanks for coming on the Cube. >>Absolutely. Thanks for having me. >>Okay. I'm John Kerry hosted the queue for IBM think 2021. Thanks for watching. Yeah. Mm. Yeah.

Published Date : Apr 16 2021

SUMMARY :

It's the cube with digital brought to you by IBM. So I'd love to get your thoughts on how you see this fourth industrial revolution as you say, So the application of those they're connected to the network security. We've recently heard about the chip shortage which gives you an idea that there is so much utilization of Besides the obvious new connection points? So it's either sustainability which To the plant or to the device itself, whether it's a mobile device or a that are stopping the acceleration for customers to achieve the benefits that they need to see. modernizing the foundation and making sure you're doing it in a secure way. So the keys to success that I get this right is gonna have the right framework for this, as you say, industry 4.0, So the collaboration between manufacturers, the oil and gas industry to be able to bring again that data platform to any location it's all kind of coming together now for the verticals because you get the best of both worlds programmable scalable it's all available and so that shop floor, the top floor connection is what Thanks for coming on the Cube. Thanks for having me. Thanks for watching.

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AWS Executive Summit 2020


 

>>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to cube three 60 fives coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight. Today we are joined by a cube alum Karthik NurAin. He is Accenture senior managing director and lead Accenture cloud. First, welcome back to the show Karthik. >>Thank you. Thanks for having me here. >>Always a pleasure. So I want to talk to you. You are an industry veteran, you've been in Silicon Valley for decades. Um, I want to hear from your perspective what the impact of the COVID-19 pandemic has been, what are you hearing from clients? What are they struggling with? What are their challenges that they're facing day to day? >>I think, um, COVID-19 is being a eye-opener from, you know, various facets, you know, um, first and foremost, it's a, it's a head, um, situation that everybody's facing, which is not just, uh, highest economic bearings to it. It has enterprise, um, an organization with bedding to it. And most importantly, it's very personal to people, um, because they themselves and their friends, family near and dear ones are going to this challenge, uh, from various different dimension. But putting that aside, when you come to it from an organization enterprise standpoint, it has changed everything well, the behavior of organizations coming together, working in their campuses, working with each other as friends, family, and, uh, um, near and dear colleagues, all of them are operating differently. So that's what big change to get things done in a completely different way, from how they used to get things done. >>Number two, a lot of things that were planned for normal scenarios, like their global supply chain, how they interact with their client customers, how they coordinate with their partners on how that employees contribute to the success of an organization at all changed. And there are no data models that give them a hint of something like this for them to be prepared for this. So we are seeing organizations, um, that have adapted to this reasonably okay, and are, you know, launching to innovate faster in this. And there are organizations that have started with struggling, but are continuing to struggle. And the gap, uh, between the leaders and legs are widening. So this is creating opportunities in a different way for the leaders, um, with a lot of pivot their business, but it's also creating significant challenge for the lag guides, uh, as we defined in our future systems research that we did a year ago, uh, and those organizations are struggling further. So the gap is actually whitening. >>So you've just talked about the widening gap. I've talked about the tremendous uncertainty that so many companies, even the ones who have adapted reasonably well, uh, in this, in this time, talk a little bit about Accenture cloud first and why, why now? >>I think it's a great question. Um, we believe that for many of our clients COVID-19 has turned, uh, cloud from an experimentation aspiration to an origin mandate. What I mean by that is everybody has been doing something on the other end cloud. There's no company that says we don't believe in cloud. Uh, our, we don't want to do cloud. It was how much they did in cloud. And they were experimenting. They were doing the new things in cloud. Um, but they were operating a lot of their core business outside the cloud or not in the cloud. Those organizations have struggled to operate in this new normal, in a remote fashion as with us, uh, that ability to pivot to all the changes the pandemic has brought to them. But on the other hand, the organizations that had a solid foundation in cloud were able to collect faster and not actually gone into the stage of innovating faster and driving a new behavior in the market, new behavior within their organization. >>So we are seeing that spend to make is actually fast-forwarded something that we always believed was going to happen. This, uh, uh, moving to cloud over the next decade is fast, forwarded it to, uh, happen in the next three to five years. And it's created this moment where it's a once in an era, really replatforming of businesses in the cloud that we are going to see. And we see this moment as a cloud first moment where organizations will use cloud as the, the canvas and the foundation with which they're going to reimagine their business after they were born in the cloud. Uh, and this requires a whole new strategy. Uh, and as Accenture, we are getting a lot in cloud, but we thought that this is the moment where we bring all of that capabilities together because we need a strategy for addressing, moving to cloud are embracing cloud in a holistic fashion. And that's what Accenture cloud first brings together a holistic strategy, a team that's 70,000 plus people that's coming together with rich cloud skills, but investing to tie in all the various capabilities of cloud to Delaware, that holistic strategy to our clients. So I want you to >>Delve into a little bit more about what this strategy actually entails. I mean, it's clearly about embracing change and being willing to experiment and, and having capabilities to innovate. Can you tell us a little bit more about what this strategy entails? >>Yeah. The reason why we say that there's a need for the strategy is, like I said, COVID is not new. There's almost every customer client is doing something with the cloud, but all of them have taken different approaches to cloud and different boundaries to cloud. Some organizations say, I just need to consolidate my multiple data centers to a small data center footprint and move the nest to cloud. Certain other organizations say that well, I'm going to move certain workloads to cloud. Certain other organizations said, well, I'm going to build this Greenfield application or workload in cloud. Certain other said, um, I'm going to use the power of AI ML in the cloud to analyze my data and drive insights. But a cloud first strategy is all of this tied with the corporate strategy of the organization with an industry specific cloud journey to say, if in this current industry, if I were to be reborn in the cloud, would I do it in the exact same passion that I did in the past, which means that the products and services that they offer need to be the matching, how they interact with that customers and partners need to be revisited, how they bird and operate their IP systems need to be the, imagine how they unearthed the data from all the systems under which they attract need to be liberated so that you could drive insights of cloud. >>First strategy. Hans is a corporate wide strategy, and it's a C-suite responsibility. It doesn't take the ownership away from the CIO or CIO, but the CIO is, and CDI was felt that it was just their problem and they were to solve it. And everyone as being a customer, now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's agenda, where probably the CDI is the instrument to execute that that's a holistic cloud-first strategy >>And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, as you were saying, this idea of being reborn in the cloud. So now how do I think about things? How do I communicate? How do I collaborate? How do I get done? What I need to get done. Talk a little bit about how this has changed, the way you support your clients and how Accenture cloud first is changing your approach to cloud services. >>Wonderful. Um, you know, I did not color one very important aspect in my previous question, but that's exactly what you just asked me now, which is to do all of this. I talked about all of the vehicles, uh, an organization or an enterprise is going to go to, but the good part is they have one constant. And what is that? That is their employees, uh, because you do, the employees are able to embrace this change. If they are able to, uh, change them, says, pivot them says retool and train themselves to be able to operate in this new cloud. First one, the ability to reimagine every function of the business would be happening at speed. And cloud first approach is to do all of this at speed, because innovation is deadly proposed there, do the rate of probability on experimentation. You need to experiment a lot for any kind of experimentation. >>There's a probability of success. Organizations need to have an ability and a mechanism for them to be able to innovate faster for which they need to experiment a lot. The more the experiment and the lower cost at which they experiment is going to help them experiment a lot and experiment demic speed, fail fast, succeed more. And hence, they're going to be able to operate this at speed. So the cloud-first mindset is all about speed. I'm helping the clients fast track that innovation journey, and this is going to happen. Like I said, across the enterprise and every function across every department, I'm the agent of this change is going to be the employee's weapon, race, this change through new skills and new grueling and new mindset that they need to adapt to. >>So Karthik what you're describing it, it sounds so exciting. And yet for a pandemic wary workforce, that's been working remotely that may be dealing with uncertainty if for their kid's school and for so many other aspects of their life, it sounds hard. So how are you helping your clients, employees get onboard with this? And because the change management is, is often the hardest part. >>Yeah, I think it's, again, a great question. A bottle has only so much capacity. Something got to come off for something else to go in. That's what you're saying is absolutely right. And that is again, the power of cloud. The reason why cloud is such a fundamental breakthrough technology and capability for us to succeed in this era, because it helps in various forms. What we talked so far is the power of innovation that could create, but cloud can also simplify the life of the employees in an enterprise. There are several activities and tasks that people do in managing their complex infrastructure, complex ID landscape. They used to do certain jobs and activities in a very difficult, uh, underground about with cloud has simplified. And democratised a lot of these activities. So that things which had to be done in the past, like managing the complexity of the infrastructure, keeping them up all the time, managing the, um, the obsolescence of the capabilities and technologies and infrastructure, all of that could be offloaded to the cloud. >>So that the time that is available for all of these employees can be used to further innovate. Every organization is good to spend almost the same amount of money, but rather than spending activities, by looking at the rear view mirror on keeping the lights on, they're going to spend more money, more time, more energy, and spend their skills on things that are going to add value to their organization. Because you, every innovation that an enterprise can give to their end customer need not come from that enterprise. The word of platform economy is about democratising innovation. And the power of cloud is to get all of these capabilities from outside the four walls of the enterprise, >>It will add value to the organization, but I would imagine also add value to that employee's life because that employee, the employee will be more engaged in his or her job and therefore bring more excitement and energy into her, his or her day-to-day activities too. >>Absolutely. Absolutely. And this is, this is a normal evolution we would have seen everybody would have seen in their lives, that they keep moving up the value chain of what activities that, uh, gets performed buying by those individuals. And there's this, um, you know, no more true than how the United States, uh, as an economy has operated where, um, this is the power of a powerhouse of innovation, where the work that's done inside the country keeps moving up to that. You change. And, um, us leverages the global economy for a lot of things that is required to power the United States and that global economic, uh, phenomenon is very proof for an enterprise as well. There are things that an enterprise needs to do them soon. There are things an employee needs to do themselves. Um, but there are things that they could leverage from the external innovation and the power of innovation that is coming from technologies like cloud. >>So at Accenture, you have long, long, deep Stan, sorry, you have deep and long standing relationships with many cloud service providers, including AWS. How does the Accenture cloud first strategy, how does it affect your relationships with those providers? >>Yeah, we have great relationships with cloud providers like AWS. And in fact, in the cloud world, it was one of the first, um, capability that we started about years ago, uh, when we started developing these capabilities. But five years ago, we hit a very important milestone where the two organizations came together and said that we are forging a pharma partnership with joint investments to build this partnership. And we named that as a Accenture, AWS business group ABG, uh, where we co-invest and brought skills together and develop solutions. And we will continue to do that. And through that investment, we've also made several acquisitions that you would have seen in the recent times, like, uh, an invoice and gecko that we made acquisitions in in Europe. But now we're taking this to the next level. What we are saying is two cloud first and the $3 billion investment that we are bringing in, uh, through cloud first, we are going to make specific investment to create unique joint solution and landing zones foundation, um, cloud packs with which clients can accelerate their innovation or their journey to cloud first. >>And one great example is what we are doing with Takeda, uh, billable, pharmaceutical giant, um, between we've signed a five-year partnership. And it was out in the media just a month ago or so, where we are, the two organizations are coming together. We have created a partnership as a power of three partnership where the three organizations are jointly hoarding hats and taking responsibility for the innovation and the leadership position that Decatur wants to get to with this. We are going to simplify their operating model and organization by providing it flexibility. We're going to provide a lot more insights. Tequila has a 230 year old organization. Imagine the amount of trapped data and intelligence that is there. How about bringing all of that together with the power of AWS and Accenture and Takeda to drive more customer insights, um, come up with breakthrough, uh, R and D uh, accelerate clinical trials and improve the patient experience using AI ML and edge technologies. So all of these things that we will do through this partnership with joint investment from Accenture cloud first, as well as partner like AWS, so that Takeda can realize their gain. And, uh, they're seeing you actually made a statement that five years from now, every ticket an employee will have an AI assistant. That's going to make that beginner employee move up the value chain on how they contribute and add value to the future of tequila with the AI assistant, making them even more equipped and smarter than what they could be otherwise. >>So, one last question to close this out here. What is your future vision for, for Accenture cloud first? What are we going to be talking about at next year's Accenture executive summit? Yeah, the future >>Is going to be, um, evolving, but the part that is exciting to me, and this is, uh, uh, a fundamental belief that we are entering a new era of industrial revolution from industry first, second, and third industry. The third happened probably 20 years ago with the advent of Silicon and computers and all of that stuff that happened here in the Silicon Valley. I think the fourth industrial revolution is going to be in the cross section of, uh, physical, digital and biological boundaries. And there's a great article, um, in what economic forum that, that people, uh, your audience can Google and read about it. Uh, but the reason why this is very, very important is we are seeing a disturbing phenomenon that over the last 10 years, they are seeing a Blackwing of the, um, labor productivity and innovation, which has dropped to about 2.1%. When you see that kind of phenomenon over that longer period of time, there has to be breakthrough innovation that needs to happen to come out of this barrier and get to the next base camp, as I would call it to further this productivity, um, lack that we are seeing, and that is going to happen in the intersection of the physical, digital and biological boundaries. >>And I think cloud is going to be the connective tissue between all of these three, to be able to provide that where it's the edge, especially is going to come closer to the human lives. It's going to come from cloud pick totally in your mind, you can think about cloud as central, either in a private cloud, in a data center or in a public cloud, you know, everywhere. But when you think about edge, it's going to be far reaching and coming close to where we live and maybe work and very, um, get entertained and so on and so forth. And there's going to be, uh, intervention in a positive way in the field of medicine, in the field of entertainment, in the field of, um, manufacturing in the field of, um, uh, you know, mobility. When I say mobility, human mobility, people, transportation, and so on and so forth with all of this stuff, cloud is going to be the connective tissue and the vision of cloud first is going to be, uh, you know, blowing through this big change that is going to happen. And the evolution that is going to happen where, you know, the human grace of mankind, um, our person kind of being very gender neutral in today's world. Um, go first needs to be that beacon of, uh, creating the next generation vision for enterprises to take advantage of that kind of an exciting future. And that's why it, Accenture. We say, let there be change as our, as a purpose. >>I genuinely believe that cloud first is going to be in the forefront of that change agenda, both for Accenture as well as for the rest of the world. Excellent. Let there be change, indeed. Thank you so much for joining us Karthik. A pleasure I'm Rebecca night's stay tuned for more of Q3 60 fives coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS >>Welcome everyone to the Q virtual and our coverage of the Accenture executive summit, which is part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the green, the cloud and joining me is Kishor Dirk. He is Accenture senior managing director cloud first global services lead. Thank you so much for coming on the show. Kishor nice to meet you. So I want to start by asking you what it is that we mean when we say green cloud, we know that sustainability is a business imperative. So many organizations around the world are committing to responsible innovation, lowering carbon emissions, but what's this, what is it? What does it mean when they talk about cloud from a sustainability perspective? I think it's about responsible innovation being cloud is a cloud first approach that has profits and benefit the clients by helping reduce carbon emissions. >>Think about it this way. You have a large number of data centers. Each of these data centers are increasing by 14% every year. And this double digit growth. What you're seeing is these data centers and the consumption is nearly coolant to the kind of them should have a country like Spain. So the magnitude of the problem that is out there and how do we pursue a green approach. If you look at this, our Accenture analysis, in terms of the migration to public cloud, we've seen that we can reduce that by 59 million tons of CO2 per year with just the 5.9% reduction in total ID emissions and equates this to 22 million cars off the road. And the magnitude of reduction can go a long way in meeting climate change commitments, particularly for data sensitive. >>Wow, that's incredible. What the numbers that you're putting forward are, are absolutely mind blowing. So how does it work? Is it a simple cloud migration? So, you know, when companies begin their cloud journey and then they confront, uh, with them a lot of questions, the decision to make, uh, this particular, uh, element sustainable in the solution and benefits they drive and they have to make wise choices, and then they will be unprecedented level of innovation leading to both a greener planet, as well as, uh, a greener balance sheet, I would say, uh, so effectively it's all about ambition data, the ambition, greater the reduction in carbon emissions. So from a cloud migration perspective, we look at it as a, as a simple solution with approaches and sustainability benefits, uh, that vary based on things it's about selecting the right cloud provider, a very carbon thoughtful provider and the first step towards a sustainable cloud journey. >>And here we're looking at cloud operators, obviously they have different corporate commitments towards sustainability, and that determines how they plan, how they build, uh, their, uh, uh, the data centers, how they are consumed and assumptions that operate there and how they, or they retire their data centers. Then, uh, the next element that you want to do is how do you build it ambition, you know, for some of the companies, uh, and average on-prem, uh, drives about 65% energy reduction and the carbon emissions and reduction number was 84%, which is kind of good, I would say. But then if you could go up to 98% by configuring applications to the cloud, that is significant benefit for, uh, for the board. And obviously it's a, a greener cloud that we're talking about. And then the question is, how far can you go? And, uh, you know, the, obviously the companies have to unlock greater financial societal environmental benefits, and Accenture has this cloud based circular operations and sustainable products and services that we bring into play. So it's a, it's a very thoughtful, broader approach that w bringing in, in terms of, uh, just a simple concept of cloud migration, >>We know that in the COVID era, shifting to the cloud has really become a business imperative. How is Accenture working with its clients at a time when all of this movement has been accelerated? How do you partner and what is your approach in terms of helping them with their migration? >>Yeah, I mean, let, let me talk a little bit about the pandemic and the crisis that is there today. And if you really look at that in terms of how we partnered with a lot of our clients in terms of the cloud first approach, I'll give you a couple of examples. We worked with rolls Royce, McLaren, DHL, and others, as part of the ventilator challenge consortium, again, to, uh, coordinate production of medical ventilator surgically needed for the UK health service. Many of these farms I've taken similar initiatives in, in terms of, uh, you know, from a few manufacturers hand sanitizers and to hand sanitizers, and again, leading passionate labels, making PPE, and again, at the UN general assembly, we launched the end-to-end integration guide that helps company essentially to have a sustainable development goals. And that's how we have parking at a very large scale. >>Uh, and, and if you really look at how we work with our clients and what is Accenture's role there, uh, you know, from, in terms of our clients, you know, there are multiple steps that we look at. One is about, uh, planning, building, deploying, and managing an optimal green cloud solution. And Accenture has this concept of, uh, helping clients with a platform to kind of achieve that goal. And here we are having, we are having a platform or a mine app, which has a module called BGR advisor. And this is a capability that helps you provide optimal green cloud, uh, you know, a business case, and obviously a blueprint for each of our clients and right from the start in terms of how do we complete cloud migration recommendation to an improved solution, accurate accuracy to obviously bringing in the end to end perspective, uh, you know, with this green card advisor capability, we're helping our clients capture what we call as a carbon footprint for existing data centers and provide, uh, I would say the current cloud CO2 emission score that, you know, obviously helps them, uh, with carbon credits that can further that green agenda. >>So essentially this is about recommending a green index score, reducing carbon footprint for migration migrating for green cloud. And if we look at how Accenture itself is practicing what we preach, 95% of our applications are in the cloud. And this migration has helped us, uh, to lead to about $14.5 million in benefit. And in the third year and another 3 million analytics costs that are saved through right-sizing a service consumption. So it's a very broad umbrella and a footprint in terms of how we engage societaly with the UN or our clients. And what is it that we exactly bring to our clients in solving a specific problem? >>Accenture isn't is walking the walk, as you say yes. >>So that's that instead of it, we practice what we preach, and that is something that we take it to heart. We want to have a responsible business and we want to practice it. And we want to advise our clients around that >>You are your own use case. And so they can, they know they can take your advice. So talk a little bit about, um, the global, the cooperation that's needed. We know that conquering this pandemic is going to take a coordinated global effort and talk a little bit about the great reset initiative. First of all, what is that? Why don't we, why don't we start there and then we can delve into it a little bit more. >>Okay. So before we get to how we are cooperating, the great reset, uh, initiative is about improving the state of the world. And it's about a group of global stakeholders cooperating to simultaneously manage the direct consequences of their COVID-19 crisis. Uh, and in spirit of this cooperation that we're seeing during COVID-19, uh, which will obviously either to post pandemic, to tackle the world's pressing issues. As I say, uh, we are increasing companies to realize a combined potential of technology and sustainable impact to use enterprise solutions, to address with urgency and scale, and, um, obviously, uh, multiple challenges that are facing our world. One of the ways that you're increasing, uh, companies to reach their readiness cloud with Accenture's cloud core strategy is to build a solid foundation that is resilient and will be able to faster to the current, as well as future times. Now, when you think of cloud as the foundation, uh, that drives the digital transformation, it's about scale speed, streamlining your operations, and obviously reducing costs. >>And as these businesses seize the construct of cloud first, they must remain obviously responsible and trusted. Now think about this, right, as part of our analysis, uh, that profitability can co-exist with responsible and sustainable practices. Let's say that all the data centers, uh, migrated from on-prem to cloud based, we estimate that would reduce carbon emissions globally by 60 million tons per year. Uh, and think about it this way, right? Easier metric would be taking out 22 million cars off the road. Um, the other examples that you've seen, right, in terms of the NHS work that they're doing, uh, in, in UK to build, uh, uh, you know, uh, Microsoft teams in based integration. And, uh, the platform rolled out for 1.2 million in interest users, uh, and got 16,000 users that we were able to secure, uh, instant messages, obviously complete audio video calls and host virtual meetings across India. So, uh, this, this work that we did with NHS is something that we have are collaborating with a lot of tools and powering businesses. >>Well, you're vividly describing the business case for sustainability. What do you see as the future of cloud when thinking about it from this lens of sustainability, and also going back to what you were talking about in terms of how you are helping your, your fostering cooperation within these organizations. >>Yeah, that's a very good question. So if you look at today, right, businesses are obviously environmentally aware and they are expanding efforts to decrease power consumption, carbon emissions, and they want to run a sustainable operational efficiency across all elements of their business. And this is an increasing trend, and there is that option of energy efficient infrastructure in the global market. And this trend is the cloud first thinking. And with the right cloud migration that we've been discussing is about unlocking new opportunity, like clean energy foundations enable enabled by cloud based geographic analysis, material, waste reductions, and better data insights. And this is something that, uh, uh, we'll we'll drive, uh, with obviously faster analytics platform that is out there. Now, the sustainability is actually the future of business, which is companies that are historically different, the financial security or agility benefits to cloud. Now sustainability becomes an imperative for them. And I would on expedience Accenture's experience with cloud migrations, we have seen 30 to 40% total cost of ownership savings. And it's driving a greater workload, flexibility, better service, your obligation, and obviously more energy efficient, uh, public clouds that cost we'll see that, that drive a lot of these enterprise own data centers. So in our view, what we are seeing is that this, this, uh, sustainable cloud position helps, uh, helps companies to, uh, drive a lot of the goals in addition to their financial and other goods. >>So what should organizations who are, who are watching this interview and saying, Hey, I need to know more, what, what do you recommend to them? And what, where should they go to get more information on Greenplum? >>No, if you you're, if you are a business leader and you're thinking about which cloud provider is good, or how, how should applications be modernized to meet our day-to-day needs, which cloud driven innovations should be priorities. Uh, you know, that's why Accenture, uh, formed up the cloud first organization and essentially to provide the full stack of cloud services to help our clients become a cloud first business. Um, you know, it's all about excavation, uh, the digital transformation innovating faster, creating differentiated, uh, and sustainable value for our clients. And we're powering it up at 70,000 cloud professionals, $3 billion investment, and, uh, bringing together and services for our clients in terms of cloud solutions. And obviously the ecosystem partnership that we have that we are seeing today, uh, and the assets that help our clients realize their goals. Um, and again, to do reach out to us, uh, we can help them determine obviously, an optimal, sustainable cloud for solution that meets the business needs and being unprecedented levels of innovation. Our experience will be our advantage. And now more than ever, Rebecca, >>Just closing us out here. Do you have any advice for these companies who are navigating a great deal of uncertainty? We, what, what do you think the next 12 to 24 months? What do you think that should be on the minds of CEOs as they go through? >>So, as CEO's are thinking about rapidly leveraging cloud, migrating to cloud, uh, one of the elements that we want them to be thoughtful about is can they do that, uh, with unprecedent level of innovation, but also build a greener planet and a greener balance sheet, if we can achieve this balance and kind of, uh, have a, have a world which is greener, I think the world will win. And we all along with Accenture clients will win. That's what I would say, uh, >>Optimistic outlook. And I will take it. Thank you so much. Kishor for coming on the show >>That was >>Accenture's Kishor Dirk, I'm Rebecca Knight stay tuned for more of the cube virtuals coverage of the Accenture executive summit >>Around the globe. >>It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtual and our coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the power of three. And what happens when you bring together the scientific know-how of a global bias biopharmaceutical powerhouse in Takeda, a leading cloud services provider in AWS, and Accenture's ability to innovate, execute, and deliver innovation. Joining me to talk about these things. We have Aaron, sorry, Arjun, baby. He is the senior managing director and chairman of Accenture's diamond leadership council. Welcome Arjun Karl hick. He is the chief digital and information officer at Takeda. >>What is your bigger, thank you, Rebecca >>And Brian bowhead, global director, and head of the Accenture AWS business group at Amazon web services. Thanks so much for coming on. Thank you. So, as I said, we're talking today about this relationship between, uh, your three organizations. Carl, I want to talk with you. I know you're at the beginning of your cloud journey. What was the compelling reason? What, what, why, why move to the cloud and why now? >>Yeah, no, thank you for the question. So, you know, as a biopharmaceutical leader, we're committed to bringing better health and a brighter future to our patients. We're doing that by translating science into some really innovative and life transporting therapies, but throughout, you know, we believe that there's a responsible use of technology, of data and of innovation. And those three ingredients are really key to helping us deliver on that promise. And so, you know, while I think, uh, I'll call it, this cloud journey is already always been a part of our strategy. Um, and we've made some pretty steady progress over the last years with a number of I'll call it diverse approaches to the digital and AI. We just weren't seeing the impact at scale that we wanted to see. Um, and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and, uh, broaden that shift. >>And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. One of those has been certainly a number of the large acquisitions we've made Shire, uh, being the most pressing example, uh, but also the global pandemic, both of those highlight the need for us to move faster, um, at the speed of cloud, ultimately. Uh, and so we started thinking outside of the box because it was taking us too long and we decided to leverage this strategic partner model. Uh, and it's giving us a chance to think about our challenges very differently. We call this the power of three, uh, and ultimately our focus is singularly on our patients. I mean, they're waiting for us. We need to get there faster. It can take years. And so I think that there is a focus on innovation, um, at a rapid speed, so we can move ultimately from treating conditions to keeping people healthy. >>So as you are embarking on this journey, what are some of the insights you want to share about, about what you're seeing so far? >>Yeah, no, it's a great question. So, I mean, look, maybe right before I highlight some of the key insights, uh, I would say that, you know, with cloud now as the, as the launchpad for innovation, you know, our vision all along has been that in less than 10 years, we want every single to kid, uh, associate we're employed to be empowered by an AI assistant. And I think that, you know, that's going to help us make faster, better decisions. That'll help us, uh, fundamentally deliver transformative therapies and better experiences to, to that ecosystem, to our patients, to physicians, to payers, et cetera, much faster than we previously thought possible. Um, and I think that technologies like cloud and edge computing together with a very powerful I'll call it data fabric is going to help us to create this, this real-time, uh, I'll call it the digital ecosystem. >>The data has to flow ultimately seamlessly between our patients and providers or partners or researchers, et cetera. Uh, and so we've been thinking about this, uh, I'll call it legal, hold up, sort of this pyramid, um, that helps us describe our vision. Uh, and a lot of it has to do with ultimately modernizing the foundation, modernizing and rearchitecting, the platforms that drive the company, uh, heightening our focus on data, which means that there's an accelerated shift towards enterprise data platforms and digital products. And then ultimately, uh, uh, P you know, really an engine for innovation sitting at the very top. Um, and so I think with that, you know, there's a few different, uh, I'll call it insights that, you know, are quickly kind of come zooming into focus. I would say one is this need to collaborate very differently. Um, you know, not only internally, but you know, how do we define ultimately, and build a connected digital ecosystem with the right partners and technologies externally? >>I think the second, uh, component that maybe people don't think as much about, but, you know, I find critically important is for us to find ways of really transforming our culture. We have to unlock talent and shift the culture certainly as a large biopharmaceutical very differently. And then lastly, you've touched on it already, which is, you know, innovation at the speed of cloud. How do we re-imagine that, you know, how do ideas go from getting tested and months to kind of getting tested in days? You know, how do we collaborate very differently? Uh, and so I think those are three, uh, perhaps of the larger I'll call it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. >>So Arjun, I want to bring you into this conversation a little bit. Let's, let's delve into those a bit. Talk first about the collaboration, uh, that Carl was referencing there. How, how have you seen that it is enabling, uh, colleagues and teams to communicate differently and interact in new and different ways? Uh, both internally and externally, as Carl said, >>No, th thank you for that. And, um, I've got to give call a lot of credit, because as we started to think about this journey, it was clear, it was a bold ambition. It was, uh, something that, you know, we had all to do differently. And so the, the concept of the power of three that Carl has constructed has become a label for us as a way to think about what are we going to do to collectively drive this journey forward. And to me, the unique ways of collaboration means three things. The first one is that, um, what is expected is that the three parties are going to come together and it's more than just the sum of our resources. And by that, I mean that we have to bring all of ourselves, all of our collective capabilities, as an example, Amazon has amazing supply chain capabilities. >>They're one of the best at supply chain. So in addition to resources, when we have supply chain innovations, uh, that's something that they're bringing in addition to just, uh, talent and assets, similarly for Accenture, right? We do a lot, uh, in the talent space. So how do we bring our thinking as to how we apply best practices for talent to this partnership? So, um, as we think about this, so that's, that's the first one, the second one is about shared success very early on in this partnership, we started to build some foundations and actually develop seven principles that all of us would look at as the basis for this success shared success model. And we continue to hold that sort of in the forefront, as we think about this collaboration. And maybe the third thing I would say is this one team mindset. So whether it's the three of our CEOs that get together every couple of months to think about, uh, this partnership, or it is the governance model that Carl has put together, which has all three parties in the governance and every level of leadership, we always think about this as a collective group, so that we can keep that front and center. >>And what I think ultimately has enabled us to do is it allowed us to move at speed, be more flexible. And ultimately all we're looking at the target the same way, the North side, the same way. >>Brian, what about you? What have you observed and what are you thinking about in terms of how this is helping teams collaborate differently? >>Yeah, absolutely. And RJ made some, some great points there. And I think if you really think about what he's talking about, it's that, that diversity of talent, diversity of skill and viewpoint and even culture, right? And so we see that in the power of three. And then I think if we drill down into what we see at Takeda, and frankly, Takeda was, was really, I think, pretty visionary and on their way here, right. And taking this kind of cross-functional approach and applying it to how they operate day to day. So moving from a more functional view of the world to more of a product oriented view of the world, right? So when you think about we're going to be organized around a product or a service or a capability that we're going to provide to our customers or our patients or donors in this case, it implies a different structure, although altogether, and a different way of thinking, right? >>Because now you've got technical people and business experts and marketing experts, all working together in this is sort of cross collaboration. And what's great about that is it's really the only way to succeed with cloud, right? Because the old ways of thinking where you've got application people and infrastructure, people in business, people is suboptimal, right? Because we can all access this tool was, and these capabilities and the best way to do that, isn't across kind of a cross collaborative way. And so this is product oriented mindset. It's a keto was already on. I think it's allowed us to move faster in those areas. >>Carl, I want to go back to this idea of unlocking talent and culture. And this is something that both Brian and Arjun have talked about too. People are, are an essential part of their, at the heart of your organization. How will their experience of work change and how are you helping re-imagine and reinforce a strong organizational culture, particularly at this time when so many people are working remotely. >>Yeah. It's a great question. And it's something that, you know, I think we all have to think a lot about, I mean, I think, um, you know, driving this, this call it, this, this digital and data kind of capability building, uh, takes a lot of, a lot of thinking. So, I mean, there's a few different elements in terms of how we're tackling this one is we're recognizing, and it's not just for the technology organization or for those actors that, that we're innovating with, but it's really across all of the Cato where we're working through ways of raising what I'll call the overall digital leaders literacy of the organization, you know, what are the, you know, what are the skills that are needed almost at a baseline level, even for a global bio-pharmaceutical company and how do we deploy, I'll call it those learning resources very broadly. >>And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are very specialized skills that are needed. Uh, my organization is one of those. And so, you know, we're fostering ways in which, you know, we're very kind of quickly kind of creating, uh, avenues excitement for, for associates in that space. So one example specifically, as we use, you know, during these very much sort of remote, uh, sort of days, we, we use what we call global it days, and we set a day aside every single month and this last Friday, um, you know, we, we create during that time, it's time for personal development. Um, and we provide active seminars and training on things like, you know, robotic process automation, data analytics cloud, uh, in this last month we've been doing this for months and months now, but in his last month, more than 50% of my organization participated, and there's this huge positive shift, both in terms of access and excitement about really harnessing those new skills and being able to apply them. >>Uh, and so I think that that's, you know, one, one element that, uh, can be considered. And then thirdly, um, of course, every organization to work on, how do you prioritize talent, acquisition and management and competencies that you can't rescale? I mean, there are just some new capabilities that we don't have. And so there's a large focus that I have with our executive team and our CEO and thinking through those critical roles that we need to activate in order to kind of, to, to build on this, uh, this business led cloud transformation. And lastly, probably the hardest one, but the one that I'm most jazzed about is really this focus on changing the mindsets and behaviors. Um, and I think there, you know, this is where the power of three is, is really, uh, kind of coming together nicely. I mean, we're working on things like, you know, how do we create this patient obsessed curiosity, um, and really kind of unlock innovation with a real, kind of a growth mindset. >>Uh, and the level of curiosity that's needed, not to just continue to do the same things, but to really challenge the status quo. So that's one big area of focus we're having the agility to act just faster. I mean, to worry less, I guess I would say about kind of the standard chain of command, but how do you make more speedy, more courageous decisions? And this is places where we can emulate the way that a partner like AWS works, or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently to a number of partnerships that we can build. So we can break down some of these barriers and use these networks, um, whether it's within our own internal ecosystem or externally to help, to create value faster. So a lot of energy around ways of working and we'll have to check back in, but I mean, we're early in on this mindset and behavioral shift, um, but a lot of good early momentum. >>Carl you've given me a good segue to talk to Brian about innovation, because you said a lot of the things that I was the customer obsession and this idea of innovating much more quickly. Obviously now the world has its eyes on drug development, and we've all learned a lot about it, uh, in the past few months and accelerating drug development is all, uh, is of great interest to all of us. Brian, how does a transformation like this help a company's, uh, ability to become more agile and more innovative and at a quicker speed to, >>Yeah, no, absolutely. And I think some of the things that Carl talked about just now are critical to that, right? I think where sometimes folks fall short is they think, you know, we're going to roll out the technology and the technology is going to be the silver bullet where we're, in fact it is the culture. It is, is the talent. And it's the focus on that. That's going to be, you know, the determinant of success. And I will say, you know, in this power of three arrangement and Carl talked a little bit about the pyramid, um, talent and culture and that change, and the kind of thinking about that has been a first-class citizen since the very beginning, right. That absolutely is critical for, for being there. Um, and, and so that's been, that's been key. And so we think about innovation at Amazon and AWS, and Carl mentioned some of the things that, you know, partner like AWS can bring to the table is we talk a lot about builders, right? >>So kind of obsessive about builders. Um, and, and we meet what we mean by that is we at Amazon, we hire for builders, we cultivate builders and we like to talk to our customers about it as well. And it also implies a different mindset, right? When you're a builder, you have that, that curiosity, you have that ownership, you have that stake in whatever I'm creating, I'm going to be a co-owner of this product or this service, right. Getting back to that kind of product oriented mindset. And it's not just the technical people or the it people who are builders. It is also the business people as, as Carl talked about. Right. So when we start thinking about, um, innovation again, where we see folks kind of get into a little bit of a innovation pilot paralysis, is that you can focus on the technology, but if you're not focusing on the talent and the culture and the processes and the mechanisms, you're going to be putting out technology, but you're not going to have an organization that's ready to take it and scale it and accelerate it. >>Right. And so that's, that's been absolutely critical. So just a couple of things we've been doing with, with Takeda and Decatur has really been leading the way is, think about a mechanism and a process. And it's really been working backward from the customer, right? In this case, again, the patient and the donor. And that was an easy one because the key value of Decatur is to be a patient focused bio-pharmaceutical right. So that was embedded in their DNA. So that working back from that, that patient, that donor was a key part of that process. And that's really deep in our DNA as well. And Accenture's, and so we were able to bring that together. The other one is, is, is getting used to experimenting and even perhaps failing, right. And being able to iterate and fail fast and experiment and understanding that, you know, some decisions, what we call it at Amazon or two-way doors, meaning you can go through that door, not like what you see and turn around and go back. And cloud really helps there because the costs of experimenting and the cost of failure is so much lower than it's ever been. You can do it much faster and the implications are so much less. So just a couple of things that we've been really driving, uh, with the cadence around innovation, that's been really critical. Carl, where are you already seeing signs of success? >>Yeah, no, it's a great question. And so we chose, you know, uh, with our focus on innovation to try to unleash maybe the power of data digital in, uh, in focusing on what I call sort of a Maven. And so we chose our, our, our plasma derived therapy business, um, and you know, the plasma-derived therapy business unit, it develops critical life-saving therapies for patients with rare and complex diseases. Um, but what we're doing is by bringing kind of our energy together, we're focusing on creating, I'll call it state of the art digitally connected donation centers. And we're really modernizing, you know, the, the, the donor experience right now, we're trying to, uh, improve also I'll call it the overall plasma collection process. And so we've, uh, selected a number of alcohol at a very high speed pilots that we're working through right now, specifically in this, in this area. And we're seeing >>Really great results already. Um, and so that's, that's one specific area of focus are Jen, I want you to close this out here. Any ideas, any best practices advice you would have for other pharmaceutical companies that are, that are at the early stage of their cloud journey? Yes. Sorry. Arjun. >>Yeah, no, I was breaking up a bit. No, I think they, um, the key is what what's sort of been great for me to see is that when people think about cloud, you know, you always think about infrastructure technology. The reality is that the cloud is really the true enabler for innovation and innovating at scale. And, and if you think about that, right, in all the components that you need, uh, ultimately that's where the value is for the company, right? Because yes, you're going to get some cost synergies and that's great, but the true value is in how do we transform the organization in the case of the Qaeda and the life sciences clients, right. We're trying to take a 14 year process of research and development that takes billions of dollars and compress that right. Tremendous amounts of innovation opportunity. You think about the commercial aspect, lots of innovation can come there. The plasma derived therapy is a great example of how we're going to really innovate to change the trajectory of that business. So I think innovation is at the heart of what most organizations need to do. And the formula, the cocktail that Takeda has constructed with this Fuji program really has all the ingredients, um, that are required for that success. >>Great. Well, thank you so much. Arjun, Brian and Carl was really an enlightening conversation. >>Thank you. Yeah, it's been fun. Thanks Rebecca. >>And thank you for tuning into the cube. Virtual is coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of Accenture executive summit here at AWS reinvent. I'm your host Rebecca Knight for this segment? We have two guests. First. We have Helen Davis. She is the senior director of cloud platform services, assistant director for it and digital for the West Midlands police. Thanks so much for coming on the show, Helen, and we also have Matthew lb. He is Accenture health and public service associate director and West Midlands police account lead. Thanks so much for coming on the show. Matthew, thank you for joining us. So we are going to be talking about delivering data-driven insights to the West Midlands police force. Helen, I want to start with >>You. Can you tell us a little bit about the West Midlands police force? How big is the force and also what were some of the challenges that you were grappling with prior to this initiative? >>Yeah, certainly. So Westerners police is the second largest police force in the UK, outside of the metropolitan police in London. Um, we have an excessive, um, 11,000 people work at Westman ins police serving communities, um, through, across the Midlands region. So geographically, we're quite a big area as well, as well as, um, being population, um, density, having that as a, at a high level. Um, so the reason we sort of embarked on the data-driven insights platform and it, which was a huge change for us was for a number of reasons. Um, namely we had a lot of disparate data, um, which was spread across a range of legacy systems that were many, many years old, um, with some duplication of what was being captured and no single view for offices or, um, support staff. Um, some of the access was limited. You have to be in a, in an actual police building on a desktop computer to access it. Um, other information could only reach the offices on the front line, through a telephone call back to one of our enabling services where they would do a manual checkup, um, look at the information, then call the offices back, um, and tell them what they needed to know. So it was a very long laborious, um, process and not very efficient. Um, and we certainly weren't exploiting the data that we had in a very productive way. >>So it sounds like as you're describing, and I'm old clunky system that needed a technological, uh, reimagination. So what was the main motivation for, for doing, for making this shift? >>It was really, um, about making us more efficient and more effective in how we do how we do business. So, um, you know, certainly as a, as an it leader and some of my operational colleagues, we recognize the benefits, um, that data analytics could bring in, uh, in a policing environment, not something that was, um, really done in the UK at the time. You know, we have a lot of data, so we're very data rich and the information that we have, but we needed to turn it into information that was actionable. So that's where we started looking for, um, technology partners and suppliers to help us and sort of help us really with what's the art of the possible, you know, this hasn't been done before. So what could we do in this space? That's appropriate, >>Helen. I love that idea. What is the art of the possible, can you tell us a little bit about why you chose AWS? >>I think really, you know, as with all things and when we're procuring a partner in the public sector that, you know, there are many rules and regulations quite rightly as you would expect that to be because we're spending public money. So we have to be very, very careful and, um, it's, it's a long process and we have to be open to public scrutiny. So, um, we sort of look to everything, everything that was available as part of that process, but we recognize the benefits that Clyde would provide in this space because, you know, we're like moving to a cloud environment. We would literally be replacing something that was legacy with something that was a bit more modern. Um, that's not what we wanted to do. Our ambition was far greater than that. So I think, um, in terms of AWS, really, it was around scalability, interoperability, you know, just us things like the disaster recovery service, the fact that we can scale up and down quickly, we call it dialing up and dialing back. Um, you know, it's it's page go. So it just sort of ticked all the boxes for us. And then we went through the full procurement process, fortunately, um, it came out on top for us. So we were, we were able to move forward, but it just sort of had everything that we were looking for in that space. >>Matthew, I want to bring you into the conversation a little bit here. How are you working with a wet with the West Midlands police, sorry. And helping them implement this cloud-first >>Yeah, so I guess, um, by January the West Midlands police started, um, favorite five years ago now. So, um, we set up a partnership with the fools. I wanted to operate in a way that was very different to a traditional supplier relationship. Um, secretary that the data difference insights program is, is one of many that we've been working with last on, um, over the last five years, um, as having said already, um, cloud gave a number of, uh, advantages certainly from a big data perspective and things that, that enabled us today. Um, I'm from an Accenture perspective that allowed us to bring in a number of the different teams that we have say, cloud teams, security teams, um, and drafted from an insurance perspective, as well as the more traditional services that people would associate with the country. >>I mean, so much of this is about embracing comprehensive change to experiment and innovate and try different things. Matthew, how, how do you help, uh, an entity like West Midlands police think differently when they are, there are these ways of doing things that people are used to, how do you help them think about what is the art of the possible, as Helen said, >>There's a few things to that enable those being critical is trying to co-create solutions together. Yeah. There's no point just turning up with, um, what we think is the right answer, try and say, um, collectively work three, um, the issues that the fullest is seeing and the outcomes they're looking to achieve rather than simply focusing on a long list of requirements, I think was critical and then being really open to working together to create the right solution. Um, rather than just, you know, trying to pick something off the shelf that maybe doesn't fit the forces requirements in the way that it should too, >>Right. It's not always a one size fits all. >>Obviously, you know, today what we believe is critical is making sure that we're creating something that met the forces needs, um, in terms of the outcomes they're looking to achieve the financial envelopes that were available, um, and how we can deliver those in a, uh, iterative agile way, um, rather than spending years and years, um, working towards an outcome, um, that is gonna update before you even get that. >>So Helen, how, how are things different? What kinds of business functions and processes have been re-imagined in, in light of this change and this shift >>It's, it's actually unrecognizable now, um, in certain areas of the business as it was before. So to give you a little bit of, of context, when we, um, started working with essentially an AWS on the data driven insights program, it was very much around providing, um, what was called locally, a wizzy tool for our intelligence analyst to interrogate data, look at data, you know, decide whether they could do anything predictive with it. And it was very much sort of a back office function to sort of tidy things up for us and make us a bit better in that, in that area or a lot better in that area. And it was rolled out to a number of offices, a small number on the front line. Um, and really it was, um, in line with a mobility strategy that we, hardware officers were getting new smartphones for the first time, um, to do sort of a lot of things on, on, um, policing apps and things like that to again, to avoid them, having to keep driving back to police stations, et cetera. >>And the pilot was so successful. Every officer now has access to this data, um, on their mobile devices. So it literally went from a handful of people in an office somewhere using it to do sort of clever whizzbang things to, um, every officer in the force, being able to access that level of data at their fingertips. Literally. So what they were touched we've done before is if they needed to check and address or check details of an individual, um, just as one example, they would either have to, in many cases, go back to a police station to look it up themselves on a desktop computer. Well, they would have to make a call back to a centralized function and speak to an operator, relay the questions, either, wait for the answer or wait for a call back with the answer when those people are doing the data interrogation manually. >>So the biggest change for us is the self-service nature of the data we now have available. So officers can do it themselves on their phone, wherever they might be. So the efficiency savings from that point of view are immense. And I think just parallel to that is the quality of our, because we had a lot of data, but just because you've got a lot of data and a lot of information doesn't mean it's big data and it's valuable necessarily. Um, so again, it was having the single source of truth as we, as we call it. So you know that when you are completing those safe searches and getting the responses back, that it is the most accurate information we hold. And also you're getting it back within minutes, as opposed to, you know, half an hour, an hour or a drive back to a station. So it's making officers more efficient and it's also making them safer. The more efficient they are, the more time they have to spend out with the public doing what they, you know, we all should be doing, >>Seen that kind of return on investment, because what you were just describing with all the steps that we needed to be taken in prior to this, to verify an address say, and those are precious seconds when someone's life is on the line in, in sort of in the course of everyday police work. >>Absolutely. Yeah, absolutely. It's difficult to put a price on it. It's difficult to quantify. Um, but all the, you know, the minutes here and that certainly add up to a significant amount of efficiency savings, and we've certainly been able to demonstrate the officers are spending less time up police stations as a result or more time out on the front frontline also they're safer because they can get information about what may or may not be and address what may or may not have occurred in an area before very, very quickly without having to wait. >>Thank you. I want to hear your observations of working so closely with this West Midlands police. Have you noticed anything about changes in its culture and its operating model in how police officers interact with one another? Have you seen any changes since this technology change? >>What's unique about the Western new misplaces, the buy-in from the top down, the chief and his exact team and Helen as the leader from an IOT perspective, um, the entire force is bought in. So what is a significant change program? Uh, I'm not trickles three. Um, everyone in the organization, um, change is difficult. Um, and there's a lot of time effort. That's been put into both the technical delivery and the business change and adoption aspects around each of the projects. Um, but you can see the step change that is making in each aspect to the organization, uh, and where that's putting West Midlands police as a leader in, um, technology I'm policing in the UK. And I think globally, >>And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain intransigence in workplaces about this is just the way we've always done things and we're used to this and don't try us to get us. Don't try to get us to do anything new here. It works. How do you get the buy-in that you need to do this kind of digital transformation? >>I think it, it would be wrong to say it was easy. Um, um, we also have to bear in mind that this was one program in a five-year program. So there was a lot of change going on, um, both internally for some of our back office functions, as well as front Tai, uh, frontline offices. So with DDI in particular, I think the stat change occurred when people could see what it could do for them. You know, we had lots of workshops and seminars where we all talk about, you know, big data and it's going to be great and it's data analytics and it's transformational, you know, and quite rightly people that are very busy doing a day job that not necessarily technologists in the main and, you know, are particularly interested quite rightly so in what we are not dealing with the cloud, you know? >>And it was like, yeah, okay. It's one more thing. And then when they started to see on that, on their phones and what teams could do, that's when it started to sell itself. And I think that's when we started to see, you know, to see the stat change, you know, and, and if we, if we have any issues now it's literally, you know, our help desks in meltdown. Cause everyone's like, well, we call it manage without this anymore. And I think that speaks for itself. So it doesn't happen overnight. It's sort of incremental changes and then that's a step change in attitude. And when they see it working and they see the benefits, they want to use it more. And that's how it's become fundamental to all policing by itself, really, without much selling >>You, Helen just made a compelling case for how to get buy in. Have you discovered any other best practices when you are trying to get everyone on board for this kind of thing? >>We've um, we've used a lot of the traditional techniques, things around comms and engagement. We've also used things like, um, the 30 day challenge and nudge theory around how can we gradually encourage people to use things? Um, I think there's a point where all of this around, how do we just keep it simple and keep it user centric from an end user perspective? I think DDI is a great example of where the, the technology is incredibly complex. The solution itself is, um, you know, extremely large and, um, has been very difficult to, um, get delivered. But at the heart of it is a very simple front end for the user to encourage it and take that complexity away from them. Uh, I think that's been critical through the whole piece of DDR. >>One final word from Helen. I want to hear, where do you go from here? What is the longterm vision? I know that this has made productivity, um, productivity savings equivalent to 154 full-time officers. Uh, what's next, >>I think really it's around, um, exploiting what we've got. Um, I use the phrase quite a lot, dialing it up, which drives my technical architects crazy. But so, because it's apparently not that simple, but, um, you know, we've, we've been through significant change in the last five years and we are still continuing to batch all of those changes into everyday, um, operational policing. But what we need to see is we need to exploit and build on the investments that we've made in terms of data and claims specifically, the next step really is about expanding our pool of data and our functions. Um, so that, you know, we keep getting better and better at this. And the more we do, the more data we have, the more refined we can be, the more precise we are with all of our actions. Um, you know, we're always being expected to, again, look after the public purse and do more for less. >>And I think this is certainly an and our cloud journey and, and cloud first by design, which is where we are now, um, is helping us to be future-proofed. So for us, it's very much an investment. And I see now that we have good at embedded in operational policing for me, this is the start of our journey, not the end. So it's really exciting to see where we can go from here. Exciting times. Indeed. Thank you so much. Lily, Helen and Matthew for joining us. I really appreciate it. Thank you. And you are watching the cube stay tuned for more of the cubes coverage of the AWS reinvent Accenture executive summit. I'm Rebecca Knight from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to the cube virtual coverage of the executive summit at AWS reinvent 2020 virtual. This is the cube virtual. We can't be there in person like we are every year we have to be remote. This executive summit is with special programming supported by Accenture where the cube virtual I'm your host John for a year, we had a great panel here called uncloud first digital transformation from some experts, Stuart driver, the director of it and infrastructure and operates at lion Australia, Douglas Regan, managing director, client account lead at lion for Accenture as a deep Islam associate director application development lead for Centure gentlemen, thanks for coming on the cube virtual that's a mouthful, all that digital, but the bottom line it's cloud transformation. This is a journey that you guys have been on together for over 10 years to be really a digital company. Now, some things have happened in the past year that kind of brings all this together. This is about the next generation organization. So I want to ask Stuart you first, if you can talk about this transformation at lion has undertaken some of the challenges and opportunities and how this year in particular has brought it together because you know, COVID has been the accelerant of digital transformation. Well, if you're 10 years in, I'm sure you're there. You're in the, uh, on that wave right now. Take a minute to explain this transformation journey. >>Yeah, sure. So a number of years back, we, we looked at kind of our infrastructure in our landscape trying to figure out where we >>Wanted to go next. And we were very analog based and stuck in the old it groove of, you know, Capitol reef rash, um, struggling to transform, struggling to get to a digital platform and we needed to change it up so that we could become very different business to the one that we were back then obviously cloud is an accelerant to that. And we had a number of initiatives that needed a platform to build on. And a cloud infrastructure was the way that we started to do that. So we went through a number of transformation programs that we didn't want to do that in the old world. We wanted to do it in a new world. So for us, it was partnering up with a dried organizations that can take you on the journey and, uh, you know, start to deliver bit by bit incremental progress, uh, to get to the, uh, I guess the promise land. >>Um, we're not, not all the way there, but to where we're on the way along. And then when you get to some of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually change pretty quickly, um, provide capacity and, uh, and increase your environments and, you know, do the things that you need to do in a much more dynamic way than we would have been able to previously where we might've been waiting for the hardware vendors, et cetera, to deliver capacity. So for us this year, it's been a pretty strong year from an it perspective and delivering for the business needs >>Before I hit the Douglas. I want to just real quick, a redirect to you and say, you know, if all the people said, Oh yeah, you got to jump on cloud, get in early, you know, a lot of naysayers like, well, wait till to mature a little bit, really, if you got in early and you, you know, paying your dues, if you will taking that medicine with the cloud, you're really kind of peaking at the right time. Is that true? Is that one of the benefits that comes out of this getting in the cloud? Yeah, >>John, this has been an unprecedented year, right. And, um, you know, Australia, we had to live through Bush fires and then we had covert and, and then we actually had to deliver a, um, a project on very nice transformational project, completely remote. And then we also had had some, some cyber challenges, which is public as well. And I don't think if we weren't moved into and enabled through the cloud, we would have been able to achieve that this year. It would have been much different and would have been very difficult to do the backing. We're able to work and partner with Amazon through this year, which is unprecedented and actually come out the other end and we've delivered a brand new digital capability across the entire business. Um, in many, you know, wouldn't have been impossible if we could, I guess, stayed in the old world. The fact that we were moved into the new Naval by the new allowed us to work in this unprecedented year. >>Just quilt. What's your personal view on this? Because I've been saying on the Cuban reporting necessity is the mother of all invention and the word agility has been kicked around as kind of a cliche, Oh, it'd be agile. You know, we're going to get the city, you get a minute on specifically, but from your perspective, uh, Douglas, what does that mean to you? Because there is benefits there for being agile. And >>I mean, I think as Stuart mentioned, right, in a lot of these things we try to do and, you know, typically, you know, hardware and, uh, the last >>To be told and, and, and always on the critical path to be done, we really didn't have that in this case, what we were doing with our projects in our deployments, right. We were able to move quickly able to make decisions in line with the business and really get things going. Right. So you see a lot of times in a traditional world, you have these inhibitors, you have these critical path, it takes weeks and months to get things done as opposed to hours and days, and, and truly allowed us to, we had to, you know, VJ things, move things. And, you know, we were able to do that in this environment with AWS to support and the fact that they can kind of turn things off and on as quickly as we needed. >>Yeah. Cloud-scale is great for speed. So DECA, Gardez get your thoughts on this cloud first mission, you know, it, you know, the dev ops world, they saw this early, that jumping in there, they saw the, the, the agility. Now the theme this year is modern applications with the COVID pandemic pressure, there's real business pressure to make that happen. How did you guys learn to get there fast? And what specifically did you guys do at Accenture and how did it all come together? Can you take us inside kind of how it played out? >>Right. So, yeah, we started off with, as we do in most cases with a much more bigger group, and we worked with lions functional experts and, uh, the lost knowledge that allowed the infrastructure had. Um, we then applied our journey to cloud strategy, which basically revolves around the seminars and, and, uh, you know, the deep three steps from our perspective, uh, assessing the current and bottom and setting up the new cloud environment. And as we go modernizing and, and migrating these applications to the cloud now, you know, one of the key things that, uh, you know, we learned along this journey was that, you know, you can have the best plans, but bottom line that we were dealing with, we often than not have to make changes, uh, what a lot of agility and also work with a lot of collaboration with the, uh, lion team, as well as, uh, uh, AWS. I think the key thing for me was being able to really bring it all together. It's not just, uh, you know, we want to hear it's all of us working together to make this happen. >>What were some of the learnings real quick journey there? >>So I think perspective, the key learnings were that, you know, uh, you know, work, when you look back at, uh, the, the infrastructure that was that we were trying to migrate over to the cloud. A lot of the documentation, et cetera, was not, uh, available. We were having to, uh, figure out a lot of things on the fly. Now that really required us to have, uh, uh, people with deep expertise who could go into those environments and, and work out, uh, you know, the best ways to, to migrate the workloads to the cloud. Uh, I think, you know, the, the biggest thing for me was making sure all the had on that real SMEs across the board globally, that we could leverage across the various technologies, uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment with line. >>Let's do what I got to ask you. How did you address your approach to the cloud and what was your experience? >>Yeah, for me, it's around getting the foundations right. To start with and then building on them. Um, so, you know, you've got to have your, your, your process and you've got to have your, your kind of your infrastructure there and your blueprints ready. Um, AWS do a great job of that, right. Getting the foundations right. And then building upon it, and then, you know, partnering with Accenture allows you to do that very successfully. Um, I think, um, you know, the one thing that was probably surprising to us when we started down this journey and kind of after we got a long way down the track and looking backwards is actually how much you can just turn off. Right? So a lot of stuff that you, uh, you get electric with a legacy in your environment, and when you start to work through it with the types of people that civic just mentioned, you know, the technical expertise working with the business, um, you can really rationalize your environment and, uh, you know, cloud is a good opportunity to do that, to drive that legacy out. >>Um, so you know, a few things there, the other thing is, um, you've got to try and figure out the benefits that you're going to get out of moving here. So there's no point in just taking something that is not delivering a huge amount of value in the traditional world, moving it into the cloud, and guess what is going to deliver the same limited amount of value. So you've got to transform it, and you've got to make sure that you build it for the future and understand exactly what you're trying to gain out of it. So again, you need a strong collaboration. You need a good partners to work with, and you need good engagement from the business as well, because the kind of, uh, you know, digital transformation, cloud transformation, isn't really an it project, I guess, fundamentally it is at the core, but it's a business project that you've got to get the whole business aligned on. You've got to make sure that your investment streams are appropriate and that's, uh, you're able to understand the benefits and the value that say, you're going to drive back towards the business. >>Let's do it. If you don't mind me asking, what was some of the obstacles you encountered or learnings, um, that might different from the expectation we all been there, Hey, you know, we're going to change the world. Here's the sales pitch, here's the outcome. And then obviously things happen, you know, you learn legacy, okay. Let's put some containerization around that cloud native, um, all that rational. You're talking about what are, and you're going to have obstacles. That's how you learn. That's how perfection has developed. How, what obstacles did you come up with and how are they different from your expectations going in? >>Yeah, they're probably no different from other people that have gone down the same journey. If I'm totally honest, the, you know, 70 or 80% of what you do is relatively easy of the known quantity. It's relatively modern architectures and infrastructures, and you can upgrade, migrate, move them into the cloud, whatever it is, rehost, replatform, rearchitect, whatever it is you want to do, it's the other stuff, right? It's the stuff that always gets left behind. And that's the challenge. It's, it's getting that last bit over the line and making sure that you haven't been invested in the future while still carrying all of your legacy costs and complexity within your environment. So, um, to be quite honest, that's probably taken longer and has been more of a challenge than we thought it would be. Um, the other piece I touched on earlier on in terms of what was surprising was actually how much of, uh, your environment is actually not needed anymore. >>When you start to put a critical eye across it and understand, um, uh, ask the tough questions and start to understand exactly what, what it is you're trying to achieve. So if you ask a part of a business, do they still need this application or this service a hundred percent of the time, they will say yes until you start to lay out to them, okay, now I'm going to cost you this to migrate it or this, to run it in the future. And, you know, here's your ongoing costs and, you know, et cetera, et cetera. And then, uh, for a significant amount of those answers, you get a different response when you start to layer on the true value of it. So you start to flush out those hidden costs within the business, and you start to make some critical decisions as a company based on, uh, based on that. So that was a little tougher than we first thought and probably broader than we thought there was more of that than we anticipated, um, which actually results in a much cleaner environment, post post migration, >>You know, the old expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value Stuart and Siddique. Mainly if you can weigh in on this love to know the percentage of total cloud that you have now, versus when you started, because as you start to uncover whether it's by design for purpose, or you discover opportunity to innovate, like you guys have, I'm sure it kind of, you took on some territory inside Lyon, what percentage of cloud now versus start? >>Yeah. And at the start it was minimal, right. You know, close to zero, right. Single and single digits. Right. It was mainly SAS environments that we had, uh, sitting in clouds when we, uh, when we started, um, Doug mentioned earlier on a really significant transformation project, um, that we've undertaken and recently gone live on a multi-year one. Um, you know, that's all stood up on AWS and is a significant portion of our environment, um, in terms of what we can move to cloud. Uh, we're probably at about 80 or 90% now. And the balance bit is, um, legacy infrastructure that is just going to retire as we go through the cycle rather than migrate to the cloud. Um, so we are significantly cloud-based and, uh, you know, we're reaping the benefits of it in a year, like 2020, and makes you glad that you did all of the hard yards in the previous years when you started that business challenges thrown out as, >>So do you any common reaction still the cloud percentage penetration? >>Sorry, I didn't, I didn't guys don't, but I, I was going to say it was, I think it's like the 80 20 rule, right? We, we, we worked really hard in the, you know, I think 2018, 19 to get any person off, uh, after getting onto the cloud and, or the last year is the 20% that we have been migrating. And Stuart said like a non-athlete that is also, that's going to be the diet. And I think our next big step is going to be obviously, you know, the icing on the cake, which is to decommission all these apps as well. Right. So, you know, to get the real benefits out of, uh, the whole conservation program from a, uh, from a >>Douglas and Stewart, can you guys talk about the decision around the cloud because you guys have had success with AWS, why AWS how's that decision made? Can you guys give some insight into some of those thoughts? >>I can, I can start, start off. I think back when the decision was made and it was, Oh, it was a while back, um, you know, there's some clear advantages of moving relay, Ws, a lot of alignment with some of the significant projects and, uh, the trend, that particular one big transformation project that we've alluded to as well. Um, you know, we needed some, um, some very robust and, um, just future proof and, um, proven technology. And AWS gave that to us. We needed a lot of those blueprints to help us move down the path. We didn't want to reinvent everything. So, um, you know, having a lot of that legwork done for us and an AWS gives you that, right. And particularly when you partner up with, uh, with a company like Accenture as well, you get combinations of the technology and the skills and the knowledge to, to move you forward in that direction. >>So, um, you know, for us, it was a, uh, uh, it was a decision based on, you know, best of breed, um, you know, looking forward and, and trying to predict the future needs and, and, and kind of the environmental that we might need. Um, and, you know, partnering up with organizations that can take you on the journey. Yeah. And just to build on it. So obviously, you know, lion's like an NWS, but, you know, we knew it was a very good choice given that, um, uh, the skills and the capability that we had, as well as the assets and tools we had to get the most out of, um, out of AWS. And obviously our, our CEO globally is just spending, you know, announcement about a huge investment that we're making in cloud. Um, but you know, we've, we've worked very well. AWS, we've done some joint workshops and joint investments, um, some joint POC. So yeah, w we have a very good working relationship, AWS, and I think, um, one incident to reflect upon whether it's cyber it's and again, where we actually jointly, you know, dove in with, um, with Amazon and some of their security experts and our experts. And we're able to actually work through that with mine quite successful. So, um, you know, really good behaviors as an organization, but also really good capabilities. >>Yeah. As you guys, you're essential cloud outcomes, research shown, it's the cycle of innovation with the cloud. That's creating a lot of benefits, knowing what you guys know now, looking back certainly COVID is impacted a lot of people kind of going through the same process, knowing what you guys know now, would you advocate people to jump on this transformation journey? If so, how, and what tweaks they make, which changes, what would you advise? >>Uh, I might take that one to start with. Um, I hate to think where we would have been when, uh, COVID kicked off here in Australia and, you know, we were all sent home, literally were at work on the Friday, and then over the weekend. And then Monday, we were told not to come back into the office and all of a sudden, um, our capacity in terms of remote access and I quadrupled, or more four, five X, what we had on the Friday we needed on the Monday. And we were able to stand that up during the day Monday into Tuesday, because we were cloud-based and, uh, you know, we just spun up your instances and, uh, you know, sort of our licensing, et cetera. And we had all of our people working remotely, um, within, uh, you know, effectively one business day. Um, I know peers of mine in other organizations and industries that are relying on kind of a traditional wise and getting hardware, et cetera, that were weeks and months before they could get there the right hardware to be able to deliver to their user base. >>So, um, you know, one example where you're able to scale and, uh, um, get, uh, get value out of this platform beyond probably what was anticipated at the time you talk about, um, you know, less the, in all of these kinds of things. And you can also think of a few scenarios, but real world ones where you're getting your business back up and running in that period of time is, is just phenomenal. There's other stuff, right? There's these programs that we've rolled out, you do your sizing, um, and in the traditional world, you would just go out and buy more servers than you need. And, you know, probably never realize the full value of those, you know, the capability of those servers over the life cycle of them. Whereas, you know, in a cloud world, you put in what you think is right. And if it's not right, you pump it up a little bit when, when all of your metrics and so on, tell you that you need to bump it up. And conversely you scale it down at the same rate. So for us, with the types of challenges and programs and, uh, uh, and just business need, that's come at as this year, uh, we wouldn't have been able to do it without a strong cloud base, uh, to, uh, to move forward. >>You know, Douglas, one of the things I talked to, a lot of people on the right side of history who have been on the right wave with cloud, with the pandemic, and they're happy, they're like, and they're humble. Like, well, we're just lucky, you know, luck is preparation meets opportunity. And this is really about you guys getting in early and being prepared and readiness. This is kind of important as people realize, then you gotta be ready. I mean, it's not just, you don't get lucky by being in the right place, the right time. And there were a lot of companies were on the wrong side of history here who might get washed away. This is a super important, I think, >>To echo and kind of building on what Stewart said. I think that the reason that we've had success and I guess the momentum is we didn't just do it in isolation within it and technology. It was actually linked to broader business changes, you know, creating basically a digital platform for the entire business, moving the business, where are they going to be able to come back stronger after COVID, when they're actually set up for growth, um, and actually allows, you know, a line to achievements growth objectives, and also its ambitions as far as what it wants to do, uh, with growth in whatever they make, do with acquiring other companies and moving into different markets and launching new products. So we've actually done it in a way that is, you know, real and direct business benefit, uh, that actually enables line to grow >>General. I really appreciate you coming. I have one final question. If you can wrap up here, uh, Stuart and Douglas, you don't mind weighing in what's the priorities for the future. What's next for lion in a century >>Christmas holidays, I'll start Christmas holidays. I spent a good year and then a, and then a reset, obviously, right? So, um, you know, it's, it's figuring out, uh, transform what we've already transformed, if that makes sense. So God, a huge proportion of our services sitting in the cloud. Um, but we know we're not done even with the stuff that is in there. We need to take those next steps. We need more and more automation and orchestration. We need to, um, our environment is more future proof. We need to be able to work with the business and understand what's coming at them so that we can, um, you know, build that into, into our environment. So again, it's really transformation on top of transformation is the way that I'll describe it. And it's really an open book, right? Once you get it in and you've got the capabilities and the evolving tool sets that AWS continue to bring to the market based, um, you know, working with the partners to, to figure out how we unlock that value, um, you know, drive our costs down efficiency, uh, all of those kind of, you know, standard metrics. >>Um, but you know, we're looking for the next things to transform and showed value back out to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with and understand how we can better meet their needs. Yeah, I think just to echo that, I think it's really leveraging this and then did you capability they have and getting the most out of that investment. And then I think it's also moving to, uh, and adopting more new ways of working as far as, you know, the speed of the business, um, is getting up to speed in the market is changing. So being able to launch and do things quickly and also, um, competitive and efficient operating costs, uh, now that they're in the cloud, right? So I think it's really leveraging the most out of the platform and then, you know, being efficient in launching things. So putting them with >>Siddique, any word from you on your priorities by you see this year in folding, >>There's got to say like e-learning squares, right, for me around, you know, just journey. This is a journey to the cloud, right? >>And, uh, you know, as well dug into sort of Saturday, it's getting all, you know, different parts of the organization along the journey business to it, to your, uh, product lenders, et cetera. Right. And it takes time. It is tough, but, uh, uh, you know, you got to get started on it. And, you know, once we, once we finish off, uh, it's the realization of the benefits now that, you know, looking forward, I think for, from Alliance perspective, it is, uh, you know, once we migrate all the workloads to the cloud, it is leveraging, uh, all stack drive. And as I think Stewart said earlier, uh, with, uh, you know, the latest and greatest stuff that AWS it's basically working to see how we can really, uh, achieve more better operational excellence, uh, from a, uh, from a cloud perspective. >>Well, Stewart, thanks for coming on with a and sharing your environment and what's going on and your journey you're on the right wave. Did the work you're in, it's all coming together with faster, congratulations for your success, and, uh, really appreciate Douglas with Steve for coming on as well from essential. Thank you for coming on. Thanks, John. Okay. Just the cubes coverage of executive summit at AWS reinvent. This is where all the thought leaders share their best practices, their journeys, and of course, special programming with Accenture and the cube. I'm Sean ferry, your host, thanks for watching from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtuals coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First. We have Johan Krebbers. He is the GM digital emerging technologies and VP of it. Innovation at shell. Thank you so much for coming on the show, Johan you're welcome. And next we have Liz Dennett. She is the lead solution architect for O S D U on AWS. Thank you so much, Liz, maybe here. So I want to start our conversation by talking about OSD. You like so many great innovations. It started with a problem. Johann, what was the problem you were trying to solve at shell? We go back a couple of years, we started summer 2017, where we had a meeting with the guys from exploration in shell, and the main problem they had, of course, they got lots of lots of data, but are unable to find the right data. They need to work from all over the place and told him >>To, and we'll probably try to solve is how that person working exploration could find their proper date, not just a day, but also the date you really needed that we did probably talked about is summer 2017. And we said, okay, the only way ABC is moving forward is to start pulling that data into a single data platform. And that, that was at the time that we called it as the, you, the subsurface data universe in there was about the shell name was so in, in January, 2018, we started a project with Amazon to start grating a co fricking that building, that Stu environment, that the, the universe, so that single data level to put all your exploration and Wells data into that single environment that was intent. And every cent, um, already in March of that same year, we said, well, from Michele point of view, we will be far better off if we could make this an industry solution and not just a shelf solution, because Shelby, Shelby, if you can make an industry solution, but people are developing applications for it. >>It also is far better than for shell to say we haven't shell special solution because we don't make money out of how we start a day that we can make money out of it. We have access to the data, we can explore the data. So storing the data we should do as efficiently possibly can. So we monitor, we reach out to about eight or nine other last, uh, or I guess operators like the economics, like the tutorials, like the shepherds of this world and say, Hey, we inshallah doing this. Do you want to join this effort? And to our surprise, they all said, yes. And then in September, 2018, we had our kickoff meeting with your open group where we said, we said, okay, if you want to work together and lots of other companies, we also need to look at, okay, how, how we organize that. >>Or if you started working with lots of large companies, you need to have some legal framework around some framework around it. So that's why we went to the open group and say, okay, let's, let's form the old forum as we call it at the time. So it's September, 2080, where I did a Galleria in Houston, but the kickoff meeting for the OT four with about 10 members at the time. So that's just over two years ago, we started an exercise for me called ODU. They kicked it off. Uh, and so that's really them will be coming from and how we've got there. Also >>The origin story. Um, what, so what digging a little deeper there? What were some of the things you were trying to achieve with the OSU? >>Well, a couple of things we've tried to achieve with you, um, first is really separating data from applications for what is, what is the biggest problem we have in the subsurface space that the data and applications are all interlinked or tied together. And if, if you have them and a new company coming along and say, I have this new application and he's access to the data that is not possible because the data often interlinked with the application. So the first thing we did is really breaking the link between the application, the data as those levels, the first thing we did, secondly, put all the data to a single data platform, take the silos out what was happening in the sub-service space. They got all the data in what we call silos in small little islands out there. So what we're trying to do is first break the link to great, great. >>They put the data single day, the bathroom, and the third part, put a standard layer on top of that, it's an API layer on top to equate a platform. So we could create an ecosystem out of companies to start a valving Schoff application on top of dev data platform across you might have a data platform, but you're only successful if have a rich ecosystem of people start developing applications on top of that. And then you can export the data like small companies, last company, university, you name it, we're getting after create an ecosystem out here. So the three things were first break the link between application data, just break it and put data at the center and also make sure that data, this data structure would not be managed by one company, but it would only be met. It would be managed the data structures by the ODI forum. Secondly, then put a, the data, a single data platform certainly then has an API layer on top and then create an ecosystem. Really go for people, say, please start developing applications, because now you had access to the data. I've got the data no longer linked to somebody whose application was all freely available, but an API layer that was, that was all September, 2018, more or less. >>And hear a little bit. Can you talk a little bit about some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? Yeah, absolutely. And this whole thing is Johann said started with a challenge that was really brought out at shell. The challenges that geoscientists spend up to 70% of their time looking for data. I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out how we could address that one problem, we worked together to really understand the root cause of these challenges and working backwards from that use case OSU and OSU on AWS has really enabled customers to create solutions that span, not just this in particular problem, but can really scale to be inclusive of the entire energy value chain and deliver value from these use cases to the energy industry and beyond. Thank you, Lee, uh, Johann. So talk a little bit about Accenture's cloud first approach and how it has, uh, helped shell work faster and better with speed. >>Well, of course, access a cloud first approach only works together. It's been an Amazon environment, AWS environment. So we're really looking at, uh, at, at Accenture and others altogether helping shell in this space. Now the combination of the two is what we're really looking at, uh, where access of course can be recent knowledge student to that environment operates support knowledge, do an environment. And of course, Amazon will be doing that to today's environment that underpinning their services, et cetera. So, uh, we would expect a combination, a lot of goods when we started rolling out and put in production, the old you are three and bug because we are anus. Then when the release feed comes to the market in Q1, next year of ODU have already started going to Audi production inside shell. But as the first release, which is ready for prime time production across an enterprise will be released just before Christmas, last year when he's still in may of this year. But really three is the first release we want to use for full scale production deployment inside shell, and also the operators around the world. And there is one Amazon, sorry, at that one. Um, extensive can play a role in the ongoing, in the, in deployment building up, but also support environment. >>So one of the other things that we talk a lot about here on the cube is sustainability. And this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSD you, uh, help organizations become, how is this a greener solution for companies? >>Well, first we make it's a greatest solution because you start making a much more efficient use of your resources, which is already an important one. The second thing we're doing is also, we started ODU in framers, in the oil and gas space in the expert development space. We've grown, uh, OTU in our strategy of growth. I was, you know, also do an alternative energy sociology. We'll all start supporting next year. Things like solar farms, wind farms, uh, the, the dermatomal environment hydration. So it becomes an and an open energy data platform, not just what I want to get into sleep. That's what new industry, any type of energy industry. So our focus is to create, bring the data of all those various energy data sources to get me to a single data platform you can to use AI and other technologies on top of that, to exploit the data, to meet again into a single data platform. >>Liz, I want to ask you about security because security is, is, is such a big concern when it comes to data. How secure is the data on OSD? You, um, actually, can I talk, can I do a follow up on this sustainability talking? Oh, absolutely. By all means. I mean, I want to interject though security is absolutely our top priority. I don't mean to move away from that, but with sustainability, in addition to the benefits of the OSU data platform, when a company moves from on-prem to the cloud, they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical data center. >>Now, a recent study by four 51 research found that AWS is infrastructure is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to higher, um, server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases for 51 found that AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSU are working to support our customers is they seek to better understand their workflows and make their legacy businesses less carbon intensive. >>That's that's incorrect. Those are those statistics are incredible. Do you want to talk a little bit now about security? Absolutely. And security will always be AWS is top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy. There are the security requirements for the military, local banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build and operate each of our regions. So that customers benefit from the only commercial cloud that's hat hits service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features as well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. Johann, I want you to talk a little bit about how OSD you can be used today. Does it only handle subsurface data? >>Uh, today it's Honda's subserves or Wells data, we go to add to that production around the middle of next year. That means that the whole upstate business. So we've got goes from exploration all the way to production. You've made it together into a single data platform. So production will be added around Q3 of next year. Then a principal. We have a difficult, the elder data that single environment, and we want to extend them to other data sources or energy sources like solar farms, wind farms, uh, hydrogen, hydro, et cetera. So we're going to add a whore, a whole list of audit day energy source to them and be all the data together into a single data club. So we move from a falling guest data platform to an aniseed data platform. That's really what our objective is because the whole industry, if you look it over, look at our companies are all moving in. That same two acts of quantity of course, are very strong in oil and gas, but also increased the, got into the other energy sources like, like solar, like wind, like th like highly attended, et cetera. So we would be moving exactly. But that same method that, that, that the whole OSU can't really support at home. And as a spectrum of energy sources, >>Of course, and Liz and Johan. I want you to close us out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSD. You we'll start with you, Liz. What do you, what do you see as the future holding for this platform? Um, honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers, wherever their OSU journeys, take them, whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond, but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges, Johann first, nobody can look at any more nowadays, especially 10 years own objective is really in the next five years, you will become the key backbone for energy companies for storing your data. You are efficient intelligence and optimize the whole supply energy supply chain in this world down here, you'll uncovers Liz Dennett. Thank you so much for coming on the cube virtual I'm Rebecca Knight stay tuned for more of our coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight today we're welcoming back to Kubila. We have Kishor Dirk. He is the Accenture senior managing director cloud first global services lead. Welcome back to the show Kishore. Thank you very much. Nice to meet again. And, uh, Tristan moral horse set. He is the managing director, Accenture cloud first North America growth. Welcome back to you to trust and great to be back in grapes here again, Rebecca. Exactly. Even in this virtual format, it is good to see your faces. Um, today we're going to be talking about my nav and green cloud advisor capability. Kishor I want to start with you. So my nav is a platform that is really celebrating its first year in existence. Uh, November, 2019 is when Accenture introduced it. Uh, but it's, it has new relevance in light of this global pandemic that we are all enduring and suffering through. Tell us a little bit about the lineup platform, what it is that cloud platform to help our clients navigate the complexity of cloud and cloud decisions to make it faster. And obviously, you know, we have in the cloud, uh, you know, with >>The increased relevance and all the, especially over the last few months with the impact of COVID crisis and exhibition of digital transformation, you know, we are seeing the transformation or the acceleration to cloud much faster. This platform that you're talking about has enabled and 40 clients globally across different industries. You identify the right cloud solution, navigate the complexity, provide a cloud specific solution simulate for our clients to meet the strategy business needs, and the clients are loving it. >>I want to go to you now trust and tell us a little bit about how mine nav works and how it helps companies make good cloud choice. >>Yeah, so Rebecca, we we've talked about cloud is, is more than just infrastructure and that's what mine app tries to solve for it. It really looks at a variety of variables, including infrastructure operating model and fundamentally what client's business outcomes, um, uh, our clients are, are looking for and, and identifies the optimal solution for what they need. And we assign this to accelerate and we mentioned the pandemic. One of the big focus now is to accelerate. And so we worked through a three-step process. The first is scanning and assessing our client's infrastructure, their data landscape, their application. Second, we use our automated artificial intelligence engine to interact with. We have a wide variety and library of a collective plot expertise. And we look to recommend what is the enterprise architecture and solution. And then third, before we aligned with our clients, we look to simulate and test this scaled up model. And the simulation gives our clients a way to see what cloud is going to look like, feel like and how it's going to transform their business before they go there. >>Tell us a little bit about that in real life. Now as a company, so many of people are working remotely having to collaborate, uh, not in real life. How is that helping them right now? >>So, um, the, the pandemic has put a tremendous strain on systems, uh, because of the demand on those systems. And so we talk about resiliency. We also now need to collaborate across data across people. Um, I think all of us are calling from a variety of different places where our last year we were all at the VA cube itself. Um, and, and cloud technologies such as teams, zoom that we're we're leveraging now has fundamentally accelerated and clients are looking to onboard this for their capabilities. They're trying to accelerate their journey. They realize that now the cloud is what is going to become important for them to differentiate. Once we come out of the pandemic and the ability to collaborate with their employees, their partners, and their clients through these systems is becoming a true business differentiator for our clients. >>Keisha, I want to talk with you now about my navs multiple capabilities, um, and helping clients design and navigate their cloud journeys. Tell us a little bit about the green cloud advisor capability and its significance, particularly as so many companies are thinking more deeply and thoughtfully about sustainability. >>Yes. So since the launch of my lab, we continue to enhance, uh, capabilities for our clients. One of the significant, uh, capabilities that we have enabled is the being taught advisor today. You know, Rebecca, a lot of the businesses are more environmentally aware and are expanding efforts to decrease power consumption, uh, and obviously carbon emissions and, uh, and run a sustainable operations across every aspect of the enterprise. Uh, as a result, you're seeing an increasing trend in adoption of energy, efficient infrastructure in the global market. And one of the things that we did a lot of research we found out is that there's an ability to influence our client's carbon footprint through a better cloud solution. And that's what the internet brings to us, uh, in, in terms of a lot of the client connotation that you're seeing in Europe, North America and others, lot of our clients are accelerating to a green cloud strategy to unlock beta financial, societal and environmental benefit, uh, through obviously cloud-based circular, operational, sustainable products and services. That is something that we are enhancing my now, and we are having active client discussions at this point of time. >>So Tristan, tell us a little bit about how this capability helps clients make greener decisions. >>Yeah. Um, well, let's start about the investments from the cloud providers in renewable and sustainable energy. Um, they have most of the hyperscalers today, um, have been investing significantly on data centers that are run on renewable energy, some incredibly creative constructs on the how to do that. And sustainability is there for a key, um, key item of importance for the hyperscalers and also for our clients who now are looking for sustainable energy. And it turns out this marriage is now possible. I can, we marry the, the green capabilities of the comm providers with a sustainability agenda of our clients. And so what we look into the way the mine EF works is it looks at industry benchmarks and evaluates our current clients, um, capabilities and carpet footprint leveraging their existing data centers. We then look to model from an end-to-end perspective, how the, their journey to the cloud leveraging sustainable and, um, and data centers with renewable energy. We look at how their solution will look like and, and quantify carbon tax credits, um, improve a green index score and provide quantifiable, um, green cloud capabilities and measurable outcomes to our clients, shareholders, stakeholders, clients, and customers. Um, and our green plot advisers sustainability solutions already been implemented at three clients. And in many cases in two cases has helped them reduce the carbon footprint by up to 400% through migration from their existing data center to green cloud. Very, very, >>That is remarkable. Now tell us a little bit about the kinds of clients. Is this, is this more interesting to clients in Europe? Would you say that it's catching on in the United States? Where, what is the breakdown that you're seeing right now? >>Sustainability is becoming such a global agenda and we're seeing our clients, um, uh, tie this and put this at board level, um, uh, agenda and requirements across the globe. Um, Europe has specific constraints around data sovereignty, right, where they need their data in country, but from a green, a sustainability agenda, we see clients across all our markets, North America, Europe, and our growth markets adopt this. And we have seen case studies and all three months. >>Keisha, I want to bring you back into the conversation. Talk a little bit about how MindUP ties into Accenture's cloud first strategy, your Accenture's CEO, Julie Sweet has talked about post COVID leadership requiring every business to become a cloud first business. Tell us a little bit about how this ethos is in Accenture and how you're sort of looking outward with it too. >>So Rebecca mine is the launch pad, uh, to a cloud first transformation for our clients. Uh, Accenture, see your jewelry suite, uh, you know, shared the Accenture cloud first and our substantial investment demonstrate our commitment and is delivering greater value for our clients when they need it the most. And with the digital transformation requiring cloud at scale, you know, we're seeing that in the post COVID leadership, it requires that every business should become a cloud business. And my nap helps them get there by evaluating the cloud landscape, navigating the complexity, modeling architecting and simulating an optimal cloud solution for our clients. And as Justin was sharing a greener cloud. >>So Tristan, talk a little bit more about some of the real life use cases in terms of what are we, what are clients seeing? What are the results that they're having? >>Yes. Thank you, Rebecca. I would say two key things right around my neck. The first is the iterative process. Clients don't want to wait, um, until they get started, they want to get started and see what their journey is going to look like. And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need to move to cloud very quickly. And my nav is there to do that. So how do we do that? First is generating the business cases. Clients need to know in many cases that they have a business case by business case, we talk about the financial benefits, as well as the business outcomes, the green, green clot impact sustainability impacts with minus. We can build initial recommendations using a basic understanding of their environment and benchmarks in weeks versus months with indicative value savings in the millions of dollars arranges. >>So for example, very recently, we worked with a global oil and gas company, and in only two weeks, we're able to provide an indicative savings for $27 million over five years. This enabled the client to get started, knowing that there is a business case benefit and then iterate on it. And this iteration is, I would say the second point that is particularly important with my nav that we've seen in bank, the clients, which is, um, any journey starts with an understanding of what is the application landscape and what are we trying to do with those, these initial assessments that used to take six to eight weeks are now taking anywhere from two to four weeks. So we're seeing a 40 to 50% reduction in the initial assessment, which gets clients started in their journey. And then finally we've had discussions with all of the hyperscalers to help partner with Accenture and leverage mine after prepared their detailed business case module as they're going to clients. And as they're accelerating the client's journey, so real results, real acceleration. And is there a journey? Do I have a business case and furthermore accelerating the journey once we are by giving the ability to work in iterative approach. >>I mean, it sounds as though that the company that clients and and employees are sort of saying, this is an amazing time savings look at what I can do here in, in so much in a condensed amount of time, but in terms of getting everyone on board, one of the things we talked about last time we met, uh, Tristan was just how much, uh, how one of the obstacles is getting people to sign on and the new technologies and new platforms. Those are often the obstacles and struggles that companies face. Have you found that at all? Or what is sort of the feedback that you're getting from employers? >>Sorry. Yes. We clearly, there are always obstacles to a cloud journey. If there were an obstacles, all our clients would be, uh, already fully in the cloud. What man I gives the ability is to navigate through those, to start quickly. And then as we identify obstacles, we can simulate what things are going to look like. We can continue with certain parts of the journey while we deal with that obstacle. And it's a fundamental accelerator. Whereas in the past one, obstacle would prevent a class from starting. We can now start to address the obstacles one at a time while continuing and accelerating the contrary. That is the fundamental difference. >>Kishor I want to give you the final word here. Tell us a little bit about what is next for Accenture might have and what we'll be discussing next year at the Accenture executive summit >>Sort of echo, we are continuously evolving with our client needs and reinventing, reinventing for the future. For mine, as I've been taught advisor, our plan is to help our clients reduce carbon footprint and again, migrate to a green cloud. Uh, and additionally, we're looking at, you know, two capabilities, uh, which include sovereign cloud advisor, uh, with clients, especially in, in Europe and others are under pressure to meet, uh, stringent data norms that Kristen was talking about. And the sovereign cloud advisor health organization to create an architecture cloud architecture that complies with the green. Uh, I would say the data sovereignty norms that is out there. The other element is around data to cloud. We are seeing massive migration, uh, for, uh, for a lot of the data to cloud. And there's a lot of migration hurdles that come within that. Uh, we have expanded mine app to support assessment capabilities, uh, for, uh, assessing applications, infrastructure, but also covering the entire state, including data and the code level to determine the right cloud solution. So we are, we are pushing the boundaries on what mine app can do with mine. Have you created the ability to take the guesswork out of cloud navigate the complexity? We are roaring risks costs, and we are, you know, achieving client's static business objectives while building a sustainable alerts with being cloud >>Any platform that can take some of the guesswork out of the future. I'm I'm onboard with. Thank you so much, Tristin and Kishore. This has been a great conversation. >>Thank you. >>Stay tuned for more of the cubes coverage of the Accenture executive summit. I'm Rebecca Knight from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Hey, welcome back to the cubes coverage of 80 us reinvent 2020 virtual centric executive summit. The two great guests here to break down the analysis of the relationship with cloud and essential Brian bowhead director ahead of a century 80. It was business group at Amazon web services. And Andy T a B G the M is essentially Amazon business group lead managing director at Accenture. Uh, I'm sure you're super busy and dealing with all the action, Brian. Great to see you. Thanks for coming on. So thank you. You guys essentially has been in the spotlight this week and all through the conference around this whole digital transformation, essentially as business group is celebrating its fifth anniversary. What's new, obviously the emphasis of next gen post COVID generation, highly digital transformation, a lot happening. You got your five-year anniversary, what's new. >>Yeah, it, you know, so if you look back, it's exciting. Um, you know, so it was five years ago. Uh, it was actually October where we, where we launched the Accenture AWS business group. And if we think back five years, I think we're still at the point where a lot of customers were making that transition from, you know, should I move to cloud to how do I move to cloud? Right? And so that was one of the reasons why we launched the business group. And since, since then, certainly we've seen that transition, right? Our conversations today are very much around how do I move to cloud, help me move, help me figure out the business case and then pull together all the different pieces so I can move more quickly, uh, you know, with less risk and really achieve my business outcomes. And I would say, you know, one of the things too, that's, that's really changed over the five years. >>And what we're seeing now is when we started, right, we were focused on migration data and IOT as the big three pillars that we launched with. And those are still incredibly important to us, but just the breadth of capability and frankly, the, the, the breadth of need that we're seeing from customers. And obviously as AWS has matured over the years and launched our new capabilities, we're Eva with Accenture and in the business group, we've broadened our capabilities and deepened our capabilities over the, over the last five years as well. For instance, this year with, with COVID, especially, it's really forced our customers to think differently about their own customers or their citizens, and how do they service those citizens? So we've seen a huge acceleration around customer engagement, right? And we powered that with Accenture customer engagement platform powered by ADA, Amazon connect. And so that's been a really big trend this year. And then, you know, that broadens our capability from just a technical discussion to one where we're now really reaching out and, and, um, and helping transform and modernize that customer and citizen experience as well, which has been exciting to see. >>Yeah, Andy, I want to get your thoughts here. We've been reporting and covering essentially for years. It's not like it's new to you guys. I mean, five years is a great anniversary. You know, check is good relationship, but you guys have been doing the work you've been on the trend line. And then this hits and Andy said on his keynote and I thought he said it beautifully. And he even said it to me in my one-on-one interview with them was it's on full display right now, the whole digital transformation, everything about it is on full display and you're either were prepared for it or you kind of word, and you can see who's there. You guys have been prepared. This is not new. So give us the update from your perspective, how you're taking advantage of this, of this massive shift, highly accelerated digital transformation. >>Well, I think, I think you can be prepared, but you've also got to be prepared to always sort of, I think what we're seeing in, in, um, in, in, in, in recent times and particularly 20 w what is it I think today there are, um, full sense of the enterprise workloads, the cloud, um, you know, that leaves 96 percentile now for him. Um, and I, over the next four to >>Five years, um, we're going to see that sort of, uh, acceleration to the, to the cloud pick up, um, this year is, as Andy touched on, I think, uh, uh, on Tuesday in his, I think the pandemic is a forcing function, uh, for companies to, to really pause and think about everything from, from, you know, how they, um, manage that technology to infrastructure, to just to carotenoids where the data sets to what insights and intelligence that getting from that data. And then eventually even to, to the talent, the talent they have in the organization and how they can be competitive, um, their culture, their culture of innovation, of invention and reinvention. And so I think, I think, you know, when you, when you think of companies out there faced with these challenges, it, it forces us, it forces AWS, it forces AEG to come together and think through how can we help create value for them? How can we help help them move from sort of just causing and rethinking to having real plans in an action and that taking them, uh, into, into implementation. And so that's, that's what we're working on. Um, I think over the next five years, we're looking to just continue to come together and help these, these companies get to the cloud and get the value from the cloud because it's beyond just getting to the cloud attached to them and living in the cloud and, and getting the value from it. >>It's interesting. Andy was saying, don't just put your toe in the water. You got to go beyond the toe in the water kind of approach. Um, I want to get to that large scale cause that's the big pickup this week that I kind of walked away with was it's large scale. Acceleration's not just toe in the water experimentation. Can you guys share, what's causing this large scale end to end enterprise transformation? And what are some of the success criteria have you seen for the folks who have done that? >>Yeah. And I'll, I'll, I'll start. And at the end you can buy a lawn. So, you know, it's interesting if I look back a year ago at re-invent and when I did the cube interview, then we were talking about how the ABG, we were starting to see this shift of customers. You know, we've been working with customers for years on a single of what I'll call a single-threaded programs, right. We can do a migration, we could do SAP, we can do a data program. And then even last year, we were really starting to see customers ask. The question is like, what kind of synergies and what kind of economies of scale do I get when I start bringing these different threads together, and also realizing that it's, you know, to innovate for the business and build new applications, new capabilities. Well, that then is going to inform what data you need to, to hydrate those applications, right? Which then informs your data strategy while a lot of that data is then also embedded in your underlying applications that sit on premises. So you should be thinking through how do you get those applications into the cloud? So you need to draw that line through all of those layers. And that was already starting last year. And so last year we launched the joint transformation program with AEG. And then, so we were ready when this year happened and then it was just an acceleration. So things have been happening faster than we anticipated, >>But we knew this was going to be happening. And luckily we've been in a really good position to help some of our customers really think through all those different layers of kind of pyramid as we've been calling it along with the talent and change pieces, which are also so important as you make this transformation to cloud >>Andy, what's the success factors. Andy Jassy came on stage during the partner day, a surprise fireside chat with Doug Hume and talking about this is really an opportunity for partners to, to change the business landscape with enablement from Amazon. You guys are in a pole position to do that in the marketplace. What's the success factors that you see, >>Um, really from three, three fronts, I'd say, um, w one is the people. Um, and, and I, I, again, I think Andy touched on sort of eight, uh, success factors, uh, early in the week. And for me, it's these three areas that it sort of boils down to these three areas. Um, one is the, the, the, the people, uh, from the leaders that it's really important to set those big, bold visions point the way. And then, and then, you know, set top down goals. How are we going to measure Z almost do get what you measure, um, to be, you know, beyond the leaders, to, to the right people in the right position across the company. We we're finding a key success factor for these end to end transformations is not just the leaders, but you haven't poached across the company, working in a, in a collaborative, shared, shared success model, um, and people who are not afraid to, to invent and fail. >>And so that takes me to perhaps the second point, which is the culture, um, it's important, uh, with finding for the right conditions to be set in the company that enabled, uh, people to move at pace, move at speed, be able to fail fast, um, keep things very, very simple and just keep iterating and that sort of culture of iteration and improvement versus seeking perfection is, is super important for, for success. And then the third part of maybe touch on is, is partners. Um, I think, you know, as we move forward over the next five years, we're going to see an increasing number of players in the ecosystem in the enterprise and state. Um, you're going to see more and more SAS providers. And so it's important for companies and our joint clients out there to pick partners like, um, like AWS or, or Accenture or others, but to pick partners who have all worked together and you have built solutions together, and that allows them to get speed to value quicker. It allows them to bring in pre-assembled solutions, um, and really just drive that transformation in a quicker, it sorts of manner. >>Yeah, that's a great point worth calling out, having that partnership model that's additive and has synergy in the cloud, because one of the things that came out of this this week, this year is reinvented, is there's new things going on in the public cloud, even though hybrid is an operating model, outpost and super relevant. There, there are benefits for being in the cloud and you've got partners API, for instance, and have microservices working together. This is all new, but I got, I got to ask that on that thread, Andy, where did you see your customers going? Because I think, you know, as you work backwards from the customers, you guys do, what's their needs, how do you see them? W you know, where's the puck going? Where can they skate where the puck's going, because you can almost look forward and say, okay, I've got to build modern apps. I got to do the digital transformation. Everything is a service. I get that, but what are they, what solutions are you building for them right now to get there? >>Yeah. And, and of course, with, with, you know, industries blurring and multiple companies, it's always hard to boil down to the exact situations, but you could probably look at it from a sort of a thematic lens. And what we're seeing is as the cloud transformation journey picks up, um, from us perspective, we've seen a material shift in the solutions and problems that we're trying to address with clients that they are asking for us, uh, to, to help, uh, address is no longer just the back office, where you're sort of looking at cost and efficiency and, um, uh, driving gains from that perspective. It's beyond that, it's now materially the top line. It's, how'd you get the driving to the, you know, speed to insights, how'd you get them decomposing, uh, their application set in order to derive those insights. Um, how'd you get them, um, to, to, um, uh, sort of adopt leading edge industry solutions that give them that jump start, uh, and that accelerant to winning the customers, winning the eyeballs. >>Um, and then, and then how'd, you help drive the customer experience. We're seeing a lot of push from clients, um, or ask for help on how do I optimize my customer experience in order to retain my eyeballs. And then how do I make sure I've got a soft self-learning ecosystem of play, um, where, uh, you know, it's not just a practical experience that I can sort of keep learning and iterating, um, how I treat my, my customers, um, and a lot of that, um, that still self-learning, that comes from, you know, putting in intelligence into your, into your systems, getting an AI and ML in there. And so, as a result of that work, we're seeing a lot of push and a lot of what we're doing, uh, is pouring investment into those areas. And then finally, maybe beyond the bottom line, and the top line is how do you harden that and protect that with, um, security and resilience? So I'll probably say those are the three areas. John, >>You know, the business model side, obviously the enablement is what Amazon has. Um, we see things like SAS factory coming on board and the partner network, obviously a century is a big, huge partner of you guys. Um, the business models there, you've got I, as, as doing great with chips, you have this data modeling this data opportunity to enable these modern apps. We heard about the partner strategy for me and D um, talking to me now about how can partners within even Accenture, w w what's the business model, um, side on your side that you're enabling this. Can you just share your thoughts on that? >>Yeah, yeah. And so it's, it's interesting. I think I'm going to build it and then build a little bit on some of the things that Andy really talked about there, right? And that we, if you think of that from the partnership, we are absolutely helping our customers with kind of that it modernization piece. And we're investing a lot and there's hard work that needs to get done there. And we're investing a lot as a partnership around the tools, the assets and the methodology. So in AWS and Accenture show up together as AEG, we are executing office single blueprint with a single set of assets, so we can move fast. So we're going to continue to do that with all the hybrid announcements from this past week, those get baked into that, that migration modernization theme, but the other really important piece here as we go up the stack, Andy mentioned it, right? >>The data piece, like so much of what we're talking about here is around data and insights. Right? I did a cube interview last week with, uh, Carl hick. Um, who's the CIO from Takeda. And if you hear Christophe Weber from Takeda talk, he talks about Takeda being a data company, data and insights company. So how do we, as a partnership, again, build the capabilities and the platforms like with Accenture's applied insights platform so that we can bootstrap and really accelerate our client's journey. And then finally, on the innovation on the business front, and Andy was touching on some of these, we are investing in industry solutions and accelerators, right? Because we know that at the end of the day, a lot of these are very similar. We're talking about ingesting data, using machine learning to provide insights and then taking action. So for instance, the cognitive insurance platform that we're working together on with Accenture, if they give out property and casualty claims and think about how do we enable touchless claims using machine learning and computer vision that can assess based on an image damage, and then be able to triage that and process it accordingly, right? >>Using all the latest machine learning capabilities from AWS with that deep, um, AI machine learning data science capability from Accenture, who knows all those algorithms that need to get built and build that library by doing that, we can really help these insurance companies accelerate their transformation around how they think about claims and how they can speed those claims on behalf of their policy holder. So that's an example of a, kind of like a bottom to top, uh, view of what we're doing in the partnership to address these new needs. >>That's awesome. Andy, I want to get back to your point about culture. You mentioned it twice now. Um, talent is a big part of the game here. Andy Jassy referenced Lambda. The next generation developers were using Lambda. He talked about CIO stories around, they didn't move fast enough. They lost three years. A new person came in and made it go faster. This is a new, this is a time for a certain kind of, um, uh, professional and individual, um, to, to be part of, um, this next generation. What's the talent strategy you guys have to attract and attain the best and retain the people. How do you do it? >>Um, you know, it's, it's, um, it's an interesting one. It's, it's, it's oftentimes a, it's, it's a significant point and often overlooked. Um, you know, people, people really matter and getting the right people, um, in not just in AWS or it, but then in our customers is super important. We often find that much of our discussions with, with our clients is centered around that. And it's really a key ingredient. As you touched on, you need people who are willing to embrace change, but also people who are willing to create new, um, to invent new, to reinvent, um, and to, to keep it very simple. Um, w we're we're we're seeing increasingly that you need people that have a sort of deep learning and a deep, uh, or deep desire to keep learning and to be very curious as, as they go along. Most of all, though, I find that, um, having people who are not willing or not afraid to fail is critical, absolutely critical. Um, and I think that that's, that's, uh, a necessary ingredient that we're seeing, um, our clients needing more off, um, because if you can't start and, and, and you can't iterate, um, you know, for fear of failure, you're in trouble. And, and I think Andy touched on that you, you know, where that CIO, that you referred to last three years, um, and so you really do need people who are willing to start not afraid to start, uh, and, uh, and not afraid to lead >>Was a gut check there. I just say, you guys have a great team over there. Everyone at the center I've interviewed strong, talented, and not afraid to lean in and, and into the trends. Um, I got to ask on that front cloud first was something that was a big strategic focus for Accenture. How does that fit into your business group? That's an Amazon focused, obviously they're cloud, and now hybrid everywhere, as I say, um, how does that all work it out? >>We're super excited about our cloud first initiative, and I think it fits it, um, really, uh, perfectly it's it's, it's what we needed. It's, it's, it's a, it's another accelerant. Um, if you think of count first, what we're doing is we're, we're putting together, um, uh, you know, capability set that will help enable him to and transformations as Brian touched on, you know, help companies move from just, you know, migrating to, to, to modernizing, to driving insights, to bringing in change, um, and, and, and helping on that, on that talent side. So that's sort of component number one is how does Accenture bring the best, uh, end to end transformation capabilities to our clients? Number two is perhaps, you know, how do we, um, uh, bring together pre-assembled as Brian touched on pre-assembled industry offerings to help as an accelerant, uh, for our, for our customers three years, as we touched on earlier is, is that sort of partnership with the ecosystem. >>We're going to see an increasing number of SAS providers in an estate, in the enterprise of snakes out there. And so, you know, panto wild cloud first, and our ABG strategy is to increase our touch points in our integrations and our solutions and our offerings with the ecosystem partners out there, the ISP partners out, then the SAS providers out there. And then number four is really about, you know, how do we, um, extend the definition of the cloud? I think oftentimes people thought of the cloud just as sort of on-prem and prem. Um, but, but as Andy touched on earlier this week, you know, you've, you've got this concept of hybrid cloud and that in itself, um, uh, is, is, is, you know, being redefined as well. You know, when you've got the intelligent edge and you've got various forms of the edge. Um, so that's the fourth part of, of, uh, of occupied for strategy. And for us was super excited because all of that is highly relevant for ABG, as we look to build those capabilities as industry solutions and others, and as when to enable our customers, but also how we, you know, as we, as we look to extend how we go to market, I'll join tele PS, uh, in, uh, in our respective skews and products. >>Well, what's clear now is that people now realize that if you contain that complexity, the upside is massive. And that's great opportunity for you guys. We got to get to the final question for you guys to weigh in on, as we wrap up next five years, Brian, Andy weigh in, how do you see that playing out? What do you see this exciting, um, for the partnership and the cloud first cloud, everywhere cloud opportunities share some perspective. >>Yeah, I, I think, you know, just kinda building on that cloud first, right? What cloud first, and we were super excited when cloud first was announced and you know, what it signals to the market and what we're seeing in our customers, which has cloud really permeates everything that we're doing now. Um, and so all aspects of the business will get infused with cloud in some ways, you know, it, it touches on, on all pieces. And I think what we're going to see is just a continued acceleration and getting much more efficient about pulling together the disparate, what had been disparate pieces of these transformations, and then using automation using machine learning to go faster. Right? And so, as we started thinking about the stack, right, well, we're going to get, I know we are, as a partnership is we're already investing there and getting better and more efficient every day as the migration pieces and the moving the assets to the cloud are just going to continue to get more automated, more efficient. And those will become the economic engines that allow us to fund the differentiated, innovative activities up the stack. So I'm excited to see us kind of invest to make those, those, um, those bets accelerated for customers so that we can free up capital and resources to invest where it's going to drive the most outcome for their end customers. And I think that's going to be a big focus and that's going to have the industry, um, you know, focus. It's going to be making sure that we can >>Consume the latest and greatest of AWS as capabilities and, you know, in the areas of machine learning and analytics, but then Andy's also touched on it bringing in ecosystem partners, right? I mean, one of the most exciting wins we had this year, and this year of COVID is looking at the universe, looking at Massachusetts, the COVID track and trace solution that we put in place is a partnership between Accenture, AWS, and Salesforce, right? So again, bringing together three really leading partners who can deliver value for our customers. I think we're going to see a lot more of that as customers look to partnerships like this, to help them figure out how to bring together the best of the ecosystem to drive solutions. So I think we're going to see more of that as well. >>All right, Andy final word, your take >>Thinks of innovation is, is picking up, um, dismiss things are just going faster and faster. I'm just super excited and looking forward to the next five years as, as you know, the technology invention, um, comes out and continues to sort of set new standards from AWS. Um, and as we, as Accenture wringing, our industry capabilities, we marry the two. We, we go and help our customers super exciting time. >>Well, congratulations on the partnership. I want to say thank you to you guys, because I've reported a few times some stories around real successes around this COVID pandemic that you guys worked together on with Amazon that really changed people's lives. Uh, so congratulations on that too as well. I want to call that out. Thanks for coming >>Up. Thank you. Thanks for coming on. >>Okay. This is the cubes coverage, essentially. AWS partnership, part of a century executive summit at Atrius reinvent 2020 I'm John for your host. Thanks. >>You're watching from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Hello, and welcome back to the cubes coverage of AWS reinvent 2020. This is special programming for the century executive summit, where all the thought leaders going to extract the signal from the nose to share with you their perspective of this year's reinvent conference, as it respects the customers' digital transformation. Brian Bohan is the director and head of a center. ADA was business group at Amazon web services. Brian, great to see you. And Chris Wegman is the, uh, center, uh, Amazon business group technology lead at Accenture. Um, guys, this is about technology vision, this, this conversation, um, Chris, I want to start with you because you, Andy Jackson's keynote, you heard about the strategy of digital transformation, how you gotta lean into it. You gotta have the guts to go for it, and you got to decompose. He went everywhere. So what, what did you hear? What was striking about the keynote? Because he covered a lot of topics. Yeah. You know, it >>Was Epic, uh, as always for Mandy, a lot of topics, a lot to cover in the three hours. Uh, there was a couple of things that stood out for me, first of all, hybrid, uh, the concept, the new concept of hybrid and how Andy talked about it, you know, uh, bringing the compute and the power to all parts of the enterprise, uh, whether it be at the edge or are in the big public cloud, uh, whether it be in an outpost or wherever it might be right with containerization now, uh, you know, being able to do, uh, Amazon containerization in my data center and that that's, that's awesome. I think that's gonna make a big difference, all that being underneath the Amazon, uh, console and billing and things like that, which is great. Uh, I'll also say the, the chips, right. And I know compute is always something that, you know, we always kind of take for granted, but I think again, this year, uh, Amazon and Andy really focused on what they're doing with the chips and PR and compute, and the compute is still at the heart of everything in cloud. And that continued advancement is, is making an impact and will make a continue to make a big impact. >>Yeah, I would agree. I think one of the things that really, I mean, the container thing was, I think really kind of a nuanced point when you got Deepak sing on the opening day with Andy Jassy and he's, he runs a container group over there, you know, small little team he's on the front and front stage. That really is the key to the hybrid. And I think this showcases this new layer and taking advantage of the graviton two chips that, which I thought was huge. Brian, this is really a key part of the platform change, not change, but the continuation of AWS higher level servers building blocks that provide more capabilities, heavy lifting as they say, but the new services that are coming on top really speaks to hybrid and speaks to the edge. >>It does. Yeah. And it, it, you know, I think like Andy talks about, and we talk about, I, you know, we really want to provide choice to our customers, uh, first and foremost, and you can see that and they re uh, services. We have, we can see it in the, the hybrid options that Chris talked about, being able to run your containers through ECS or EKS anywhere I just get to the customer's choice. And one of the things that I'm excited about as you talk about going up the stack and on the edge are things will certainly outpost. Um, right. So now I'll post those launched last year, but then with the new form factors, uh, and then you look at services like Panorama, right? Being able to take computer vision and embed machine learning and computer vision, and do that as a managed capability at the edge, um, for customers. >>And so we see this across a number of industries. And so what we're really thinking about is customers no longer have to make trade-offs and have to think about those, those choices that they can really deploy, uh, natively in the cloud. And then they can take those capabilities, train those models, and then deploy them where they need to, whether that's on premises or at the edge, you know, whether it be in a factory or retail environment. When we start, I think we're really well positioned when, um, you know, hopefully next year we started seeing the travel industry rebound, um, and the, the need, you know, more than ever really to, uh, to kind of rethink about how we kind of monitor and make those environments safe. Having this kind of capability at the edge is really going to help our customers as, as we come out of this year and hopefully rebound next year. >>Yeah. Chris, I want to go back to you for a second. It's hard to hard to pick your favorite innovation from the keynote, because, you know, just reminded me that Brian just reminded me of some things I forgot happened. It was like a buffet of innovation. Some keynotes have one or two, it was like 20, you got the industrial piece that was huge. Computer vision machine learning. That's just a game changer. The connect thing came out of nowhere, in my opinion, I mean, it's a call center technology. This is boring as hell. What are you gonna do with that? It turns out it's a game changer. It's not about the calls with the contact and that's discern intermediating, um, in the stack as well. So again, a feature that looks old is actually new and relevant. What's your, what was your favorite, um, innovation? >>Uh, it it's, it's, it's hard to say. I will say my personal favorite was the, the maca last. I, I just, I think that is a phenomenal, um, uh, just addition, right? And the fact that AWS is, has worked with Apple to integrate the Nitra chip into, into, uh, you know, the iMac and offer that out. Um, you know, a lot of people are doing development, uh, on for ILS and that stuff. And that there's just gonna be a huge benefit, uh, for the development teams. But, you know, I will say, I'll come back to connect you. You mentioned it. Um, you know, but you're right. It was a, it's a boring area, but it's an area that we've seen huge success with since, since connect was launched and the additional features and the Amazon continues to bring, you know, um, obviously with, with the pandemic and now that, you know, customer engagement through the phone, uh, through omni-channel has just been critical for companies, right. >>And to be able to have those agents at home, working from home versus being in the office, it was a huge, huge advantage for, for several customers that are using connect. You know, we, we did some great stuff with some different customers, but the continue technology, like you said, the, you know, the call translation and during a call to be able to pop up those key words and have a, have a supervisor, listen is awesome. And a lot of that was some of that was already being done, but we were stitching multiple services together. Now that's right out of the box. Um, and that Google's location is only going to make that go faster and make us to be able to innovate faster for that piece of the business. >>It's interesting, you know, not to get all nerdy and, and business school life, but you've got systems of records, systems of engagement. If you look at the call center and the connect thing, what got my attention was not only the model of disintermediating, that part of the engagement in the stack, but what actually cloud does to something that's a feature or something that could be an element, like say, call center, you old days of, you know, calling an 800 number, getting some support you got in chip, you have machine learning, you actually have stuff in the, in the stack that actually makes that different now. So you w you know, the thing that impressed me was Andy was saying, you could have machine learning, detect pauses, voice inflections. So now you have technology making that more relevant and better and different. So a lot going on, this is just one example of many things that are happening from a disruption innovation standpoint. W what do you guys, what do you guys think about that? And is that like getting it right? Can you share it? >>I think, I think, I think you are right. And I think what's implied there and what you're saying, and even in the, you know, the macro S example is the ability if we're talking about features, right. Which by themselves, you're saying, Oh, wow, what's, what's so unique about that, but because it's on AWS and now, because whether you're a developer working on, you know, w with Mac iOS and you have access to the 175 plus services, that you can then weave into your new applications, talk about the connect scenario. Now we're embedding that kind of inference and machine learning to do what you say, but then your data Lake is also most likely running in AWS, right? And then the other channels, whether they be mobile channels or web channels, or in store physical channels, that data can be captured in that same machine learning could be applied there to get that full picture across the spectrum. Right? So that's the, that's the power of bringing together on AWS to access to all those different capabilities of services, and then also the where the data is, and pulling all that together, that for that end to end view, okay, >>You guys give some examples of work you've done together. I know this stuff we've reported on. Um, in the last session we talked about some of the connect stuff, but that kind of encapsulates where this, where this is all going with respect to the tech. >>Yeah. I think one of the, you know, it was called out on Doug's partner summit was, you know, is there a, uh, an SAP data Lake accelerator, right? Almost every enterprise has SAP, right. And SAP getting data out of SAP has always been a challenge, right. Um, whether it be through, you know, data warehouses and AWS, sorry, SAP BW, you know, what we've focused on is, is getting that data when you're on have SAP on AWS getting that data into the data Lake, right. And getting it into, into a model that you can pull the value out of the customers can pull the value out, use those AI models. Um, so that was one thing we worked on in the last 12 months, super excited about seeing great success with customers. Um, you know, a lot of customers had ideas. They want to do this. They had different models. What we've done is, is made it very, uh, simplified, uh, framework that allows customers to do it very quickly, get the data out there and start getting value out of it and iterating on that data. Um, we saw customers are spending way too much time trying to stitch it all together and trying to get it to work technically. Uh, and we've now cut all that out and they can immediately start getting down to, to the data and taking advantage of those, those different, um, services are out there by AWS. >>Brian, you want to weigh in as things you see as relevant, um, builds that you guys done together that kind of tease out the future and connect the dots to what's coming. >>Uh, I, you know, I'm going to use a customer example. Uh, we worked with, um, and it just came out with, with Unilever around their blue air connected, smart air purifier. And what I think is interesting about that, I think it touches on some of the themes we're talking about, as well as some of the themes we talked about in the last session, which is we started that program before the pandemic. Um, and, but, you know, Unilever recognized that they needed to differentiate their product in the marketplace, move to more of a services oriented business, which we're seeing as a trend. We, uh, we enabled this capability. So now it's a smart air purifier that can be remote manage. And now in the pandemic head, they are in a really good position, obviously with a very relevant product and capability, um, to be used. And so that data then, as we were talking about is going to reside on the cloud. And so the learning that can now happen about usage and about, you know, filter changes, et cetera, can find its way back into future iterations of that valve, that product. And I think that's, that's keeping with, you know, uh, Chris was talking about where we might be systems of record, like in SAP, how do we bring those in and then start learning from that data so that we can get better on our future iterations? >>Hey, Chris, on the last segment we did on the business mission, um, session, Andy Taylor from your team, uh, talked about partnerships within a century and working with other folks. I want to take that now on the technical side, because one of the things that we heard from, um, Doug's, um, keynote and that during the partner day was integrations and data were two big themes. When you're in the cloud, technically the integrations are different. You're going to get unique things in the public cloud that you're just not going to get on premise access to other cloud native technologies and companies. How has that, how do you see the partnering of Accenture with people within your ecosystem and how the data and the integration play together? What's your vision? >>Yeah, I think there's two parts of it. You know, one there's from a commercial standpoint, right? So marketplace, you know, you, you heard Dave talk about that in the, in the partner summit, right? That marketplace is now bringing together this ecosystem, uh, in a very easy way to consume by the customers, uh, and by the users and bringing multiple partners together. And we're working with our ecosystem to put more products out in the marketplace that are integrated together, uh, already. Um, you know, I think one from a technical perspective though, you know, if you look at Salesforce, you know, we talked a little earlier about connect another good example, technically underneath the covers, how we've integrated connect and Salesforce, some of it being prebuilt by AWS and Salesforce, other things that we've added on top of it, um, I think are good examples. And I think as these ecosystems, these IFCs put their products out there and start exposing more and more API APIs, uh, on the Amazon platform, make opening it up, having those, those prebuilt network connections there between, you know, the different VPCs and the different areas within, within a customer's network. >>Um, and having them, having that all opened up and connected and having all that networking done underneath the covers. You know, it's one thing to call the API APIs. It's one thing to have access to those. And that's been a big focus of a lot of, you know, ISBNs and customers to build those API APIs and expose them, but having that network infrastructure and being able to stay within the cloud within AWS to make those connections, the past that data, we always talk about scale, right? It's one thing if I just need to pass like a, you know, a simple user ID back and forth, right? That's, that's fine. We're not talking massive data sets, whether it be seismic data or whatever it be passing those of those large, those large data sets between customers across the Amazon network is going to, is going to open up the world. >>Yeah. I see huge possibilities there and love to keep on this story. I think it's going to be important and something to keep track of. I'm sure you guys will be on top of it. You know, one of the things I want to, um, dig into with you guys now is Andy had kind of this philosophy philosophical thing in his keynote, talk about societal change and how tough the pandemic is. Everything's on full display. Um, and this kind of brings out kind of like where we are and the truth. You look at the truth, it's a virtual event. I mean, it's a website and you got some sessions out there with doing remote best weekend. Um, and you've got software and you've got technology and, you know, the concept of a mechanism it's software, it does something, it does a purpose. Essentially. You guys have a concept called living systems where growth strategy powered by technology. How do you take the concept of a, of a living organism or a system and replace the mechanism, staleness of computing and software. And this is kind of an interesting, because we're on the cusp of a, of a major inflection point post COVID. I get the digital transformation being slow that's yes, that's happening. There's other things going on in society. What do you guys think about this living systems concept? >>Yeah, so I, you know, I'll start, but, you know, I think the living system concept, um, you know, it started out very much thinking about how do you rapidly change the system, right? And, and because of cloud, because of, of dev ops, because of, you know, all these software technologies and processes that we've created, you know, that's where it started it, making it much easier to make it a much faster being able to change rapidly, but you're right. I think as you now bring in more technologies, the AI technology self-healing technologies, again, you're hurting Indian in his keynote, talk about, you know, the, the systems and services they're building to the tech problems and, and, and, and give, uh, resolve those problems. Right. Obviously automation is a big part of that living systems, you know, being able to bring that all together and to be able to react in real time to either what a customer, you know, asks, um, you know, either through the AI models that have been generated and turning those AI models around much faster, um, and being able to get all the information that came came in in the last 20 minutes, right. >>You know, society's moving fast and changing fast. And, you know, even in one part of the world, if, um, something, you know, in 10 minutes can change and being able to have systems to react to that, learn from that and be able to pass that on to the next country, especially in this world with COVID and, you know, things changing very quickly with quickly and, and, and, um, diagnosis and, and, um, medical response, all that so quickly to be able to react to that and have systems pass that information learned from that information is going to be critical. >>That's awesome. Brian, one of the things that comes up every year is, Oh, the cloud scalable this year. I think, you know, we've, we've talked on the cube before, uh, years ago, certainly with the censure and Amazon, I think it was like three or four years ago. Yeah. The clouds horizontally scalable, but vertically specialized at the application layer. But if you look at the data Lake stuff that you guys have been doing, where you have machine learning, the data's horizontally scalable, and then you got the specialization in the app changes that changes the whole vertical thing. Like you don't need to have a whole vertical solution or do you, so how has this year's um, cloud news impacted vertical industries because it used to be, Oh, the oil and gas financial services. They've got a team for that. We've got a stack for that. Not anymore. Is it going away? What's changing. Wow. >>I, you know, I think it's a really good question. And I don't think, I think what we're saying, and I was just on a call this morning talking about banking and capital markets. And I do think the, you know, the, the challenges are still pretty sector specific. Um, but what we do see is the, the kind of commonality, when we start looking at the, and we talked about it as the industry solutions that we're building as a partnership, most of them follow the pattern of ingesting data, analyzing that data, and then being able to, uh, provide insights and an actions. Right. So if you think about creating that yeah. That kind of common chassis of that ingest the data Lake and then the machine learning, can you talk about, you know, the announces around SageMaker and being able to manage these models, what changes then really are the very specific industries algorithms that you're, you're, you're writing right within that framework. And so we're doing a lot in connect is a good example of this too, where you look at it. Yeah. Customer service is a horizontal capability that we're building out, but then when you stop it into insurance or retail banking or utilities, there are nuances then that we then extend and build so that we meet the unique needs of those, those industries. And that's usually around those, those models. >>Yeah. And I think this year was the first reinvented. I saw real products coming out that actually solve that problem. And that was their last year SageMaker was kinda moving up the stack, but now you have apps embedding machine learning directly in, and users don't even know it's in there. I mean, Christmas is kind of where it's going. Right. I mean, >>Yeah. Announcements. Right. How many, how many announcements where machine learning is just embedded in? I mean, so, you know, code guru, uh, dev ops guru Panorama, we talked about, it's just, it's just there. >>Yeah. I mean, having that knowledge about the linguistics and the metadata, knowing the, the business logic, those are important specific use cases for the vertical and you can get to it faster. Right. Chris, how is this changing on the tech side, your perspective? Yeah. >>You know, I keep coming back to, you know, AWS and cloud makes it easier, right? None of this stuff, you know, all of this stuff can be done, uh, and has some of it has been, but you know, what Amazon continues to do is make it easier to consume by the developer, by the, by the customer and to actually embedded into applications much easier than it would be if I had to go set up the stack and build it all on that and, and, and, uh, embed it. Right. So it's, shortcutting that process. And again, as these products continue to mature, right. And some of the stuff is embedded, um, it makes that process so much faster. Uh, it makes it reduces the amount of work required by the developers, uh, the engineers to get there. So I I'm expecting, you're going to see more of this. >>Right. I think you're going to see more and more of these multi connected services by AWS that has a lot of the AIML, um, pre-configured data lakes, all that kind of stuff embedded in those services. So you don't have to do it yourself and continue to go up the stack. And we was talking about, Amazon's built for builders, right. But, you know, builders, you know, um, have been super specialized in, or we're becoming, you know, as engineers, we're being asked to be bigger and bigger and to be, you know, uh, be able to do more stuff. And I think, you know, these kinds of integrated services are gonna help us do that >>And certainly needed more. Now, when you have hybrid edge that are going to be operating with microservices on a cloud model, and with all those advantages that are going to come around the corner for being in the cloud, I mean, there's going to be, I think there's going to be a whole clarity around benefits in the cloud with all these capabilities and benefits cloud guru. Thanks my favorite this year, because it just points to why that could happen. I mean, that happens because of the cloud data. If you're on premise, you may not have a little cloud guru, you got to got to get more data. So, but they're all different edge certainly will come into your vision on the edge. Chris, how do you see that evolving for customers? Because that could be complex new stuff. How is it going to get easier? >>Yeah. It's super complex now, right? I mean, you gotta design for, you know, all the different, uh, edge 5g, uh, protocols are out there and, and, and solutions. Right. You know, Amazon's simplifying that again, to come back to simplification. Right. I can, I can build an app that, that works on any 5g network that's been integrated with AWS. Right. I don't have to set up all the different layers to get back to my cloud or back to my, my bigger data side. And I was kind of choking. I don't even know where to call the cloud anymore, big cloud, which is a central and I go down and then I've got a cloud at the edge. Right. So what do I call that? >>Exactly. So, you know, again, I think it is this next generation of technology with the edge comes, right. And we put more and more data at the edge. We're asking for more and more compute at the edge, right? Whether it be industrial or, you know, for personal use or consumer use, um, you know, that processing is gonna get more and more intense, uh, to be able to manage and under a single console, under a single platform and be able to move the code that I develop across that entire platform, whether I have to go all the way down to the, you know, to the very edge, uh, at the, at the 5g level, right? Or all the way into the bigger cloud and how that process, isn't there be able to do that. Seamlessly is going to be allow the speed of development that's needed. >>Well, you guys done a great job and no better time to be a techie or interested in technology or computer science or social science for that matter. This is a really perfect storm, a lot of problems to solve a lot of things, a lot of change happening, positive change opportunities, a lot of great stuff. Uh, final question guys, five years working together now on this partnership with AWS and Accenture, um, congratulations, you guys are in pole position for the next wave coming. Um, what's exciting. You guys, Chris, what's on your mind, Brian. What's, what's getting you guys pumped up >>Again. I come back to G you know, Andy mentioned it in his keynote, right? We're seeing customers move now, right. We're seeing, you know, five years ago we knew customers were going to get a new, this. We built a partnership to enable these enterprise customers to make that, that journey. Right. But now, you know, even more, we're seeing them move at such great speed. Right. Which is super excites me. Right. Because I can see, you know, being in this for a long time, now I can see the value on the other end. And I really, we've been wanting to push our customers as fast as they can through the journey. And now they're moving out of, they're getting, they're getting the religion, they're getting there. They see, they need to do it to change your business. So that's what excites me is just the excites me. >>It's just the speed at which we're, we're in a single movement. Yeah, yeah. I'd agree with, yeah, I'd agree with that. I mean, so, you know, obviously getting, getting customers to the cloud is super important work, and we're obviously doing that and helping accelerate that, it's it, it's what we've been talking about when we're there, all the possibilities that become available right. Through the common data capabilities, the access to the 175 some-odd AWS services. And I also think, and this is, this is kind of permeated through this week at re-invent is the opportunity, especially in those industries that do have an industrial aspect, a manufacturing aspect, or a really strong physical aspect of bringing together it and operational technology and the business with all these capabilities, then I think edge and pushing machine learning down to the edge and analytics at the edge is really going to help us do that. And so I'm super excited by all that possibility is I feel like we're just scratching the surface there, >>Great time to be building out. And you know, this is the time for re reconstruction. Re-invention big themes. So many storylines in the keynote, in the events. It's going to keep us busy here. It's looking at angle in the cube for the next year. Gentlemen, thank you for coming out. I really appreciate it. Thanks. Thank you. All right. Great conversation. You're getting technical. We could've go on another 30 minutes. Lot to talk about a lot of storylines here at AWS. Reinvent 2020 at the Centure executive summit. I'm John furrier. Thanks for watching.

Published Date : Dec 10 2020

SUMMARY :

It's the cube with digital coverage Welcome to cube three 60 fives coverage of the Accenture executive summit. Thanks for having me here. impact of the COVID-19 pandemic has been, what are you hearing from clients? you know, various facets, you know, um, first and foremost, to this reasonably okay, and are, you know, launching to many companies, even the ones who have adapted reasonably well, uh, all the changes the pandemic has brought to them. in the cloud that we are going to see. Can you tell us a little bit more about what this strategy entails? all the systems under which they attract need to be liberated so that you could drive now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's Talk a little bit about how this has changed, the way you support your clients and how That is their employees, uh, because you do, across every department, I'm the agent of this change is going to be the employee's weapon, So how are you helping your clients, And that is again, the power of cloud. And the power of cloud is to get all of these capabilities from outside that employee, the employee will be more engaged in his or her job and therefore And there's this, um, you know, no more true than how So at Accenture, you have long, long, deep Stan, sorry, And through that investment, we've also made several acquisitions that you would have seen in And, uh, they're seeing you actually made a statement that five years from now, Yeah, the future to me, and this is, uh, uh, a fundamental belief that we are entering a new And the evolution that is going to happen where, you know, the human grace of mankind, I genuinely believe that cloud first is going to be in the forefront of that change It's the cube with digital coverage I want to start by asking you what it is that we mean when we say green cloud, So the magnitude of the problem that is out there and how do we pursue a green you know, when companies begin their cloud journey and then they confront, uh, And, uh, you know, We know that in the COVID era, shifting to the cloud has really become a business imperative. uh, you know, from a few manufacturers hand sanitizers and to hand sanitizers, role there, uh, you know, from, in terms of our clients, you know, there are multiple steps And in the third year and another 3 million analytics costs that are saved through right-sizing So that's that instead of it, we practice what we preach, and that is something that we take it to heart. We know that conquering this pandemic is going to take a coordinated And it's about a group of global stakeholders cooperating to simultaneously manage the uh, in, in UK to build, uh, uh, you know, uh, Microsoft teams in What do you see as the different, the financial security or agility benefits to cloud. And obviously the ecosystem partnership that we have that We, what, what do you think the next 12 to 24 months? And we all along with Accenture clients will win. Thank you so much. It's the cube with digital coverage of AWS reinvent executive And what happens when you bring together the scientific And Brian bowhead, global director, and head of the Accenture AWS business group at Amazon Um, and I think that, you know, there's a, there's a need ultimately to, And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. And I think that, you know, that's going to help us make faster, better decisions. Um, and so I think with that, you know, there's a few different, How do we re-imagine that, you know, how do ideas go from getting tested So Arjun, I want to bring you into this conversation a little bit. It was, uh, something that, you know, we had all to do differently. And maybe the third thing I would say is this one team And what I think ultimately has enabled us to do is it allowed us to move And I think if you really think about what he's talking about, Because the old ways of thinking where you've got application people and infrastructure, How will their experience of work change and how are you helping re-imagine and And it's something that, you know, I think we all have to think a lot about, I mean, And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are very Uh, and so I think that that's, you know, one, one element that, uh, can be considered. or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently the customer obsession and this idea of innovating much more quickly. and Carl mentioned some of the things that, you know, partner like AWS can bring to the table is we talk a lot about builders, And it's not just the technical people or the it people who are you know, some decisions, what we call it at Amazon or two-way doors, meaning you can go through that door, And so we chose, you know, uh, with our focus on innovation Jen, I want you to close this out here. sort of been great for me to see is that when people think about cloud, you know, Well, thank you so much. Yeah, it's been fun. And thank you for tuning into the cube. It's the cube with digital coverage Matthew, thank you for joining us. and also what were some of the challenges that you were grappling with prior to this initiative? Um, so the reason we sort of embarked So what was the main motivation for, for doing, um, you know, certainly as a, as an it leader and some of my operational colleagues, What is the art of the possible, can you tell us a little bit about why you the public sector that, you know, there are many rules and regulations quite rightly as you would expect Matthew, I want to bring you into the conversation a little bit here. to bring in a number of the different teams that we have say, cloud teams, security teams, um, I mean, so much of this is about embracing comprehensive change to experiment and innovate and Um, rather than just, you know, trying to pick It's not always a one size fits all. Obviously, you know, today what we believe is critical is making sure that we're creating something that met the forces needs, So to give you a little bit of, of context, when we, um, started And the pilot was so successful. And I think just parallel to that is the quality of our, because we had a lot of data, Seen that kind of return on investment, because what you were just describing with all the steps that we needed Um, but all the, you know, the minutes here and that certainly add up Have you seen any changes Um, but you can see the step change that is making in each aspect to the organization, And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain You know, we had lots of workshops and seminars where we all talk about, you know, see, you know, to see the stat change, you know, and, and if we, if we have any issues now it's literally, when you are trying to get everyone on board for this kind of thing? The solution itself is, um, you know, extremely large and, um, I want to hear, where do you go from here? But so, because it's apparently not that simple, but, um, you know, And I see now that we have good at embedded in operational policing for me, this is the start of our journey, in particular has brought it together because you know, COVID has been the accelerant So a number of years back, we, we looked at kind of our infrastructure in our landscape trying to figure uh, you know, start to deliver bit by bit incremental progress, uh, to get to the, of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually I want to just real quick, a redirect to you and say, you know, if all the people said, Oh yeah, And, um, you know, Australia, we had to live through Bush fires You know, we're going to get the city, you get a minute on specifically, but from your perspective, uh, Douglas, to hours and days, and, and truly allowed us to, we had to, you know, VJ things, And what specifically did you guys do at Accenture and how did it all come one of the key things that, uh, you know, we learned along this journey was that, uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment How did you address your approach to the cloud and what was your experience? And then building upon it, and then, you know, partnering with Accenture allows because the kind of, uh, you know, digital transformation, cloud transformation, learnings, um, that might different from the expectation we all been there, Hey, you know, It's, it's getting that last bit over the line and making sure that you haven't been invested in the future hundred percent of the time, they will say yes until you start to lay out to them, okay, You know, the old expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, Um, you know, that's all stood up on AWS and is a significant portion of And I think our next big step is going to be obviously, So, um, you know, having a lot of that legwork done for us and an AWS gives you that, And obviously our, our CEO globally is just spending, you know, announcement about a huge investment that we're making in cloud. a lot of people kind of going through the same process, knowing what you guys know now, And we had all of our people working remotely, um, within, uh, you know, effectively one business day. So, um, you know, one example where you're able to scale and, uh, And this is really about you guys when they're actually set up for growth, um, and actually allows, you know, a line to achievements I really appreciate you coming. to figure out how we unlock that value, um, you know, drive our costs down efficiency, to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with There's got to say like e-learning squares, right, for me around, you know, It is tough, but, uh, uh, you know, you got to get started on it. It's the cube with digital coverage of Thank you so much for coming on the show, Johan you're welcome. their proper date, not just a day, but also the date you really needed that we did probably talked about So storing the data we should do as efficiently possibly can. Or if you started working with lots of large companies, you need to have some legal framework around some framework around What were some of the things you were trying to achieve with the OSU? So the first thing we did is really breaking the link between the application, And then you can export the data like small companies, last company, standpoint in terms of what you were trying to achieve with this? a lot of goods when we started rolling out and put in production, the old you are three and bug because we are So one of the other things that we talk a lot about here on the cube is sustainability. I was, you know, also do an alternative I don't mean to move away from that, but with sustainability, in addition to the benefits purchases for 51 found that AWS performs the same task with an So that customers benefit from the only commercial cloud that's hat hits service offerings and the whole industry, if you look it over, look at our companies are all moving in. objective is really in the next five years, you will become the key backbone It's the cube with digital coverage And obviously, you know, we have in the cloud, uh, you know, with and exhibition of digital transformation, you know, we are seeing the transformation or I want to go to you now trust and tell us a little bit about how mine nav works and how it helps One of the big focus now is to accelerate. having to collaborate, uh, not in real life. They realize that now the cloud is what is going to become important for them to differentiate. Keisha, I want to talk with you now about my navs multiple capabilities, And one of the things that we did a lot of research we found out is that there's an ability to influence So Tristan, tell us a little bit about how this capability helps clients make greener on renewable energy, some incredibly creative constructs on the how to do that. Would you say that it's catching on in the United States? And we have seen case studies and all Keisha, I want to bring you back into the conversation. And with the digital transformation requiring cloud at scale, you know, we're seeing that in And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need This enabled the client to get started, knowing that there is a business Have you found that at all? What man I gives the ability is to navigate through those, to start quickly. Kishor I want to give you the final word here. and we are, you know, achieving client's static business objectives while Any platform that can take some of the guesswork out of the future. It's the cube with digital coverage of And Andy T a B G the M is essentially Amazon business group lead managing the different pieces so I can move more quickly, uh, you know, And then, you know, that broadens our capability from just a technical discussion to It's not like it's new to you guys. the cloud, um, you know, that leaves 96 percentile now for him. And so I think, I think, you know, when you, when you think of companies out there faced with these challenges, have you seen for the folks who have done that? And at the end you can buy a lawn. it along with the talent and change pieces, which are also so important as you make What's the success factors that you see, a key success factor for these end to end transformations is not just the leaders, but you And so that takes me to perhaps the second point, which is the culture, um, it's important, Because I think, you know, as you work backwards from the customers, to the, you know, speed to insights, how'd you get them decomposing, uh, their application set and the top line is how do you harden that and protect that with, um, You know, the business model side, obviously the enablement is what Amazon has. And that we, if you think of that from the partnership, And if you hear Christophe Weber from Takeda talk, that need to get built and build that library by doing that, we can really help these insurance companies strategy you guys have to attract and attain the best and retain the people. Um, you know, it's, it's, um, it's an interesting one. I just say, you guys have a great team over there. um, uh, you know, capability set that will help enable him to and transformations as Brian And then number four is really about, you know, how do we, um, extend We got to get to the final question for you guys to weigh in on, and that's going to have the industry, um, you know, focus. Consume the latest and greatest of AWS as capabilities and, you know, in the areas of machine learning and analytics, as you know, the technology invention, um, comes out and continues to sort of I want to say thank you to you guys, because I've reported a few times some stories Thanks for coming on. at Atrius reinvent 2020 I'm John for your host. It's the cube with digital coverage of the century executive summit, where all the thought leaders going to extract the signal from the nose to share with you their perspective And I know compute is always something that, you know, over there, you know, small little team he's on the front and front stage. And one of the things that I'm excited about as you talk about going up the stack and on the edge are things will um, and the, the need, you know, more than ever really to, uh, to kind of rethink about because, you know, just reminded me that Brian just reminded me of some things I forgot happened. uh, you know, the iMac and offer that out. And a lot of that was some of that was already being done, but we were stitching multiple services It's interesting, you know, not to get all nerdy and, and business school life, but you've got systems of records, and even in the, you know, the macro S example is the ability if we're talking about features, Um, in the last session we talked And getting it into, into a model that you can pull the value out of the customers can pull the value out, that kind of tease out the future and connect the dots to what's coming. And I think that's, that's keeping with, you know, uh, Chris was talking about where we might be systems of record, Hey, Chris, on the last segment we did on the business mission, um, session, Andy Taylor from your team, So marketplace, you know, you, you heard Dave talk about that in the, in the partner summit, It's one thing if I just need to pass like a, you know, a simple user ID back and forth, You know, one of the things I want to, um, dig into with you guys now is in real time to either what a customer, you know, asks, um, you know, of the world, if, um, something, you know, in 10 minutes can change and being able to have the data's horizontally scalable, and then you got the specialization in the app changes And so we're doing a lot in connect is a good example of this too, where you look at it. And that was their last year SageMaker was kinda moving up the stack, but now you have apps embedding machine learning I mean, so, you know, code guru, uh, dev ops guru Panorama, those are important specific use cases for the vertical and you can get None of this stuff, you know, all of this stuff can be done, uh, and has some of it has been, And I think, you know, these kinds of integrated services are gonna help us do that I mean, that happens because of the cloud data. I mean, you gotta design for, you know, all the different, um, you know, that processing is gonna get more and more intense, uh, um, congratulations, you guys are in pole position for the next wave coming. I come back to G you know, Andy mentioned it in his keynote, right? I mean, so, you know, obviously getting, getting customers to the cloud is super important work, And you know, this is the time for re reconstruction.

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Paul Savill, Lumen Technologies | AWS re:Invent 2020


 

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Welcome back to the cubes Coverage of AWS reinvent 2020 The digital edition. I'm Lisa Martin, and I'm welcoming back one of our Cube alumni. Paul Saville joins me the S VP of product management and services from Lumen Technologies. Paul, welcome back to the Cube. >>Thank you, Lisa. It's great to be here. >>Last time I got to go to an event was aws reinvent 2019. You were there, but when you were there, you were with centurylink Centurylink. Lumen, What's the correlation? >>Yeah, well, thanks for asking that question. Yes. So we did Rand rebrand our company to loom in technologies. And there's a reason for that because, really, a few years ago, centurylink was largely a consumer telecom business. It's roughly half of its business was in the consumer space, delivering home broadband services, voice services. The other half of the business was around enterprise services and telecom services. But now our company has grown, and we've become much more than that. Now the consumer side of our business is much smaller it's. It's less than 25% of our business overall, and we brought in many more capabilities and technologies. And so we really felt like we were at a point where we and talking to our customers and doing brand analysis around the world because we're now a global, uh, company that has operations in over 100 countries around the world. Um, we felt like we needed to change that branding to represent who we are as terms of that, that large enterprise services company that does a lot more than just telecom services. And so that's why we came up with the name of Lumen Technologies. And as I said, the consumer side, the business still has a centurylink brand. But now the Enterprise Services piece of our company is called Lumen. >>So as that's transpired during this very dynamic time, just give me a little bit of perspective from your customers. How are they embracing this reading? Because we know rebrand is far more than simply rebranding product names and things like that. >>Yes, yeah, I think our customers we're really embracing it. Well, I mean, we've got great feedback from them on the new naming approach and our customers love the name. And but they also more than just the name they love, the idea of, of what we're doing and how we're positioning, how we're transforming our company to really represent what we do as being a company that delivers a platform for managing and distributing digital applications and digital assets across the world. And as you as this audience really knows, uh, enterprises values arm or and MAWR being being determined by their digital assets, whether that is content or whether it's applications. Or it could be, um, processes and things that the intellectual property that that companies own. And when we thought about our company and what it was that we really do for our customers, it really boils down to that is that customers trust us to move their their most valuable digital assets around the world to place them where they need to be when they need to be secured them in place and remove them when they don't need them there anymore. >>And that trust is absolutely critical. I want to get your perspective on something I noticed on Lumens website saying powering progress and the promise of the fourth Industrial Revolution. First of all, what is the promise of the fourth Industrial Revolution? And how is Lumen positioned to deliver progress on it? >>Yeah, So the fourth Industrial Revolution. Some of the audience may not understand what we mean by that when there's really been been. Up to now, there have been three industrial or industrial revolutions. The last one was the advent of the Internet and electron ICS And, you know, looming in its history plays a big role in the third Industrial Revolution because of the build out of the global Internet. You know, we operate one of the largest public Internet networks in the world, and but now we see that technology is pacing. Is taking a ramp up in the next phase of leveraging technologies like artificial intelligence and machine learning i O. T technologies technologies that that require applications and data that need to be distributed in a much more wide basis because computers happening everywhere in the fourth Industrial Revolution. And when we say that we're enabling that and we're enabling the promise of that, we're looking at what we do as having a platform that enables enterprise customers to create capabilities that leverage Fourth Industrial Revolution Technologies and distribute those around the world on a dynamic basis in a real time basis, in in in the fashion of How Cloud has evolved over the last few years. >>So how are you guys working together with AWS to enable customers to be able to leverage that technology that power the ability to get data that they need all across the globe as quickly as possible? >>Yes, so we worked with AWS and a number of ways in that front. You know, of course, AWS makes some great products that are based in the cloud. And they do all these technologies that are speaking about in terms of artificial intelligence and machine learning and video analytics or things and tools that AWS is built to be run out of their out of their cloud services. But Lemon works with AWS in that distribution aspect of it, and taking those assets and those applications and making them operate on a much widely distributed basis and dropping them on customer premise locations at the deep edge in into different markets wherever it makes the most sense for customers, from a performance and economic standpoint to be running those, uh, those next generation types of applications. And so we work with in combination with a W s to build those solutions into end for customers. Lumen has a professional services I t services organization also, that helps customers put together complex solutions involving Internet of things. So we, for instance, we just deployed a factory environment that has a million square foot factory with high level of automation that's run using these types of analytics tools where we're we're putting together the integration on the factory floor back to, uh, the cloud a cloud like aws. >>So in the last, you know, nine months of the world being in such a different place with businesses overnight suddenly having to dio almost 100% remote operations, how does the technology that you just talked about? How does that facilitate a business to keep up and running to not just be able to survive and continue to pivot as they need to during this time, but also to be able to really become the drivers of tomorrow? >>Yes, you know, and from our position is having, you know, over 100,000 enterprise customers and operating in regions over the world are perspective. We've really been able to see how our customers have survived and thrived and those who have not thrived so well through this whole cove it pandemic. And, you know, one of the keys for the companies that have really kind of excelled during this time has been there how far along they were in the adoption curve of cloud technologies and things like the Fourth Industrial Revolution types of technologies. Because those companies were able to dynamically scale up re shift, their resource is they were able to act remotely and control things remotely without having to have humans on premise on site engaging. Um, you know, some of the factory things that we've seen some of the work from home situations that we've seen those companies that were not operating with the kind of flexibility and scale that the cloud environment and the the four ir environment enables have really have really struggled, while the others have really been able to step up on bond, even outperform in many ways from where they were before. >>Yeah, we've been talking for months on the Cube about this acceleration of digital transformation that this pandemic has really forced and seen those companies to your point. Those that were already poised to be agile to adopted are in a much better position. One of the companies I was talking to you recently has Webcams all over the globe, and they're providing, um, you could get it throughout your Apple TV or I think, in Amazon Fire Stick where you can have these virtual experiences going into what's going on in Paris right now, of course, helping us live vicariously since we can't travel. But that's the whole proliferation of the edge and the amount of data that's being generated and process at the edge to the cloud to the core and getting that quickly to the consumer, whether it's a business or an actual consumer, what are you guys doing to help your business is your customers leverage the edge in a in an efficient way so that this accelerated pace that we're living in is actually able to help them. Dr Value. >>Yeah, we we have seen a really uptick in terms of edge opportunities since the Kobe pandemic hit and s so I can give you a great example of one that we that we recently just publicly announced its with a interesting situation with a company called Cyber Reef. Cyber Reef Builds has security technology that they help protect school systems and kids that are now being educated at home instead of in the public schools. Physically, they're they're they're at home, and those kids need protection from the Internet because they're on the Internet all day now. And Cyber Reef provides security tools for the public school systems to help protect those Children and what they're doing and making sure that there focused on school and not, you know, getting. They're having bad actors reached them through the public Internet. They're doing that That is an edge application because they needed to place their security software control tools very close to the edge deep into these markets, with good connection into public Internet and close proximity to the eyeballs of these, uh, these schoolchildren that around in the area, and so they have deployed across the country across our footprint, their their their platform, basically on on our platform to support those deployments toe help our Children as they get educated, >>so important. And if you think about a year ago when we were all in Vegas for reinvent 2019, we wouldn't even have thought we would need something of that scale. I'm here we are with this massive need and companies like Lumet and A W s being able to enable that. Talk to me a little bit about though what you guys are doing with a W s outpost is that part of what you just talked about? >>It wasn't for that example that I just gave, but we are working a lot with AWS outpost. And so we have we see aws outpost, a za key part of our total edged portfolio of solutions that we that we deliver. We have been, uh, investing a lot in our data centers across the world, because looming has hundreds of data centers that are deeply distributed into all of these markets around the world and working with aided without the ws on certifying those locations as outpost deployment, uh, locations. We have also used that I T services organization that that can provide consultation and I t management services for our enterprise customers. Thio. We've been certifying them on outpost configurations. So we've been training our I T professionals on, uh, the AWS solution and on the outpost solution in getting those certification credentials so that we can bring joint products to market with AWS that involved outposts as part of the solution and build in the end capabilities that combine our our services and capabilities with AWS and outpost for for combined solution. >>And can that combined solution to help your customers your joint customers get faster access to their data? Because we know data volume is only going up and up and up, and businesses need to be able to gain insights in real time. Is this the technology that could help get faster insights or access data faster? >>Absolutely. You know, that's and that's one of the key value propositions of ah, a solution like an outpost. Is that because you can drop them pretty much anywhere in the world that you that you need to put compute close to the point of digital interaction? Then, uh, it makes an ideal solution for customers that, uh, that want to work in that AWS environment and also leverage all of the other tools that eight of us can bring to bear from the cloud, uh, platform that that they that they offer but yeah, the place and compute close to that. That point of digital interaction is what it's all about, and it isn't just driven by performance, and performance is a really key part of it because they wanna have that fast interaction at the edge. But there are other things there, too. I mean, sometimes there are economics that play out for many companies that just make it make more sense to act on on compute or storage that it sits, sits more centrally, too many notes that could be aggregated in a market to that one essential location. We're running across use cases where customers, uh, they want to keep that data local because of governance issues or because of privacy issues or because of some kind of a regulatory requirement that they've got that they don't. They need to know exactly where that that data resides at all times, and it needs to be localized in a certain market or country. And eso they're the types of reasons why they would want to use an outpost to really there's there numerous. >>So last question. When you're talking with customers, I imagine the conversations quite different the last nine months or so. Maybe even the level of which you're having these conversations has gone up to the C suite or maybe even to the board. What do you what's your advice to businesses in any industry that really need to move forward quickly, transform to be able to start harnessing the power that four er can deliver but are just not sure where to start. >>Yeah, so, you know, we're just my advice is that they're gonna have to embrace the future embrace that, you know, embrace change. We're Look, we we have never been in a period of time where the pace of change has been assed fast as it is now, and it's not going to slow down. And so you do have to embrace that. But when you But if you're sitting there struggling, I appreciate the dilemma that they're in because, like, Well, where do I start? What do I what do I try? The thing is that that you can you you should pick a project that you can manage and deploy it. But when you deploy it and test it, make sure that you've got really measurable results. that you have really clear KP eyes of what you're trying to achieve and what you know. Are you out for financial goals or you out for performance improvement? Are you out for I t. Greater I t agility. Build the measures around that, Then test the technology that you want to try because we find that some companies approach it and they're kind of like doing it as a science experiment. And then they go, Wow, this was This was cool. It was a good science experiment, but it didn't, but it didn't wind up. They didn't capture the the actual benefit of it. And so then they don't They can't go in and prove it in anymore. And it's kind of like it sets them back because they didn't take that extra preparation >>and businesses in any industry. Nobody has. Has the time Thio face a setback because there's gonna be somebody right behind you in the rear view mirror who's gonna be smaller, agile, more nimble to take advantage. Paul. Great advice for businesses in every industry, and thank you for talking to us about what Lumen Technologies is what you guys are doing with a W s to help customers really embrace the capabilities of the Fourth Industrial Revolution. We appreciate your time. >>All right. Thank you. And thank you to the Cuba. It's good to see you all again. >>Good to see you too. Glad you're safe. And hopefully next time we'll get to see you in person soon For Paul Saville. I'm Lisa Martin. You're watching the cubes coverage of aws reinvent 2020? Yeah.

Published Date : Dec 2 2020

SUMMARY :

It's the Cube with digital coverage You were there, but when you were there, you were with centurylink Centurylink. And so we really felt like we were at a point where we and talking Because we know rebrand is far more than simply rebranding product names and things like that. And as you as this audience really knows, And how is Lumen positioned to deliver progress on it? of the Internet and electron ICS And, you know, looming in its history plays a big role it makes the most sense for customers, from a performance and economic standpoint to be running those, some of the factory things that we've seen some of the work from home situations that we've seen those companies One of the companies I was talking to you recently has Webcams all over the globe, the Kobe pandemic hit and s so I can give you a great example of one that we that we recently Talk to me a little bit about though what you guys are doing with a W s outpost is that part of what you just talked about? that involved outposts as part of the solution and build in the end capabilities that And can that combined solution to help your customers your joint customers get faster access in the world that you that you need to put compute close to the point of digital interaction? Maybe even the level of which you're having these conversations has embrace the future embrace that, you know, embrace change. of the Fourth Industrial Revolution. It's good to see you all again. Good to see you too.

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AWS Executive Summit 2020


 

>>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to cube three 60 fives coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight. Today we are joined by a cube alum, Karthik, Lorraine. He is Accenture senior managing director and lead Accenture cloud. First, welcome back to the show Karthik. >>Thank you. Thanks for having me here. >>Always a pleasure. So I want to talk to you. You are an industry veteran, you've been in Silicon Valley for decades. Um, I want to hear from your perspective what the impact of the COVID-19 pandemic has been, what are you hearing from clients? What are they struggling with? What are their challenges that they're facing day to day? >>I think, um, COVID-19 is being a eye-opener from, you know, various facets, you know, um, first and foremost, it's a, it's a hell, um, situation that everybody's facing, which is not just, uh, highest economic bearings to it. It has enterprise, um, an organization with bedding to it. And most importantly, it's very personal to people, um, because they themselves and their friends, family near and dear ones are going through this challenge, uh, from various different dimension. But putting that aside, when you come to it from an organization enterprise standpoint, it has changed everything well, the behavior of organizations coming together, working in their campuses, working with each other as friends, family, and, uh, um, near and dear colleagues, all of them are operating differently. So that's what big change to get things done in a completely different way, from how they used to get things done. >>Number two, a lot of things that were planned for normal scenarios, like their global supply chain, how they interact with their client customers, how they go innovate with their partners on how that employees contribute to the success of an organization at all changed. And there are no data models that give them a hint of something like this for them to be prepared for this. So we are seeing organizations, um, that have adapted to this reasonably okay, and are, you know, launching to innovate faster in this. And there are organizations that have started with struggling, but are continuing to struggle. And the gap between the leaders and legs are widening. So this is creating opportunities in a different way for the leaders, um, with a lot of pivot their business, but it's also creating significant challenge for the lag guides, uh, as we defined in our future systems research that we did a year ago, uh, and those organizations are struggling further. So the gap is actually widening. >>So you just talked about the widening gap. I've talked about the tremendous uncertainty that so many companies, even the ones who have adapted reasonably well, uh, in this, in this time, talk a little bit about Accenture cloud first and why, why now? >>I think it's a great question. Um, we believe that for many of our clients COVID-19 has turned, uh, cloud from an experimentation aspiration to an origin mandate. What I mean by that is everybody has been doing something on the other end cloud. There's no company that says we don't believe in cloud are, we don't want to do cloud. It was how much they did in cloud. And they were experimenting. They were doing the new things in cloud, but they were operating a lot of their core business outside the cloud or not in the cloud. Those organizations have struggled to operate in this new normal, in a remote fashion, as well as, uh, their ability to pivot to all the changes the pandemic has brought to them. But on the other hand, the organizations that had a solid foundation in cloud were able to collect faster and not actually gone into the stage of innovating faster and driving a new behavior in the market, new behavior within their organization. >>So we are seeing that spend to make is actually fast-forwarded something that we always believed was going to happen. This, uh, uh, moving to cloud over the next decade is fast forward it to happen in the next three to five years. And it's created this moment where it's a once in an era, really replatforming of businesses in the cloud that we are going to see. And we see this moment as a cloud first moment where organizations will use cloud as the, the, the canvas and the foundation with which they're going to reimagine their business after they were born in the cloud. Uh, and this requires a whole new strategy. Uh, and as Accenture, we are getting a lot in cloud, but we thought that this is the moment where we bring all of that, gave him a piece together because we need a strategy for addressing, moving to cloud are embracing cloud in a holistic fashion. And that's what Accenture cloud first brings together a holistic strategy, a team that's 70,000 plus people that's coming together with rich cloud skills, but investing to tie in all the various capabilities of cloud to Delaware, that holistic strategy to our clients. So I want you to >>Delve into a little bit more about what this strategy actually entails. I mean, it's clearly about embracing change and being willing to experiment and having capabilities to innovate. Can you tell us a little bit more about what this strategy entails? >>Yeah. The reason why we say that as a need for strategy is like I said, cloud is not new. There's almost every customer client is doing something with the cloud, but all of them have taken different approaches to cloud and different boundaries to cloud. Some organizations say, I just need to consolidate my multiple data centers to a small data center footprint and move the nest to cloud. Certain other organizations say that well, I'm going to move certain workloads to cloud. Certain other organizations said, well, I'm going to build this Greenfield application or workload in cloud. Certain other said, um, I'm going to use the power of AI ML in the cloud to analyze my data and drive insights. But a cloud first strategy is all of this tied with the corporate strategy of the organization with an industry specific cloud journey to say, if in this current industry, if I were to be reborn in the cloud, would I do it in the exact same passion that I did in the past, which means that the products and services that they offer need to be the matching, how they interact with that customers and partners need to be revisited, how they bird and operate their IP systems need to be the, imagine how they unearthed the data from all of the systems under which they attract need to be liberated so that you could drive insights of cloud. >>First strategy hands is a corporate wide strategy, and it's a C-suite responsibility. It doesn't take the ownership away from the CIO or CIO, but the CIO is, and CDI was felt that it was just their problem and they were to solve it. And everyone as being a customer, now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's agenda, where probably the CDI is the instrument to execute that that's a holistic cloud-first strategy >>And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, as you were saying, this idea of being reborn in the cloud. So now how do I think about things? How do I communicate? How do I collaborate? How do I get done? What I need to get done. Talk a little bit about how this has changed, the way you support your clients and how Accenture cloud first is changing your approach to cloud services. >>Wonderful. Um, you know, I did not color one very important aspect in my previous question, but that's exactly what you just asked me now, which is to do all of this. I talked about all of the variables, uh, an organization or an enterprise is going to go through, but the good part is they have one constant. And what is that? That is their employees, uh, because you do, the employees are able to embrace this change. If they are able to, uh, change them, says, pivot them says retool and train themselves to be able to operate in this new cloud. First one, the ability to reimagine every function of the business would be happening at speed. And cloud first approach is to do all of this at speed, because innovation is deadly proposed there, do the rate of probability on experimentation. You need to experiment a lot for any kind of experimentation. >>There's a probability of success. Organizations need to have an ability and a mechanism for them to be able to innovate faster for which they need to experiment a lot, the more the experiment and the lower cost at which they experiment is going to help them experiment a lot. And they experiment demic speed, fail fast, succeed more. And hence, they're going to be able to operate this at speed. So the cloud-first mindset is all about speed. I'm helping the clients fast track that innovation journey, and this is going to happen. Like I said, across the enterprise and every function across every department, I'm the agent of this change is going to be the employees or weapon, race, this change through new skills and new grueling and new mindset that they need to adapt to. >>So Karthik what you're describing it, it sounds so exciting. And yet for a pandemic wary workforce, that's been working remotely that may be dealing with uncertainty if for their kid's school and for so many other aspects of their life, it sounds hard. So how are you helping your clients, employees get onboard with this? And because the change management is, is often the hardest part. >>Yeah, I think it's, again, a great question. A bottle has only so much capacity. Something got to come off for something else to go in. That's what you're saying is absolutely right. And that is again, the power of cloud. The reason why cloud is such a fundamental breakthrough technology and capability for us to succeed in this era, because it helps in various forms. What we talked so far is the power of innovation that can create, but cloud can also simplify the life of the employees in an enterprise. There are several activities and tasks that people do in managing that complex infrastructure, complex ID landscape. They used to do certain jobs and activities in a very difficult underground about with cloud has simplified. And democratised a lot of these activities. So that things which had to be done in the past, like managing the complexity of the infrastructure, keeping them up all the time, managing the, um, the obsolescence of the capabilities and technologies and infrastructure, all of that could be offloaded to the cloud. >>So that the time that is available for all of these employees can be used to further innovate. Every organization is going to spend almost the same amount of money, but rather than spending activities, by looking at the rear view mirror on keeping the lights on, they're going to spend more money, more time, more energy, and spend their skills on things that are going to add value to their organization. Because you, every innovation that an enterprise can give to their end customer need not come from that enterprise. The word of platform economy is about democratising innovation. And the power of cloud is to get all of these capabilities from outside the four walls of the enterprise, >>It will add value to the organization, but I would imagine also add value to that employee's life because that employee, the employee will be more engaged in his or her job and therefore bring more excitement and energy into her, his or her day-to-day activities too. >>Absolutely. Absolutely. And this is, this is a normal evolution we would have seen everybody would have seen in their lives, that they keep moving up the value chain of what activities that, uh, gets performed buying by those individuals. And this is, um, you know, no more true than how the United States, uh, as an economy has operated where, um, this is the power of a powerhouse of innovation, where the work that's done inside the country keeps moving up to value chain. And, um, us leverage is the global economy for a lot of things that is required to power the United States and that global economic, uh, phenomenon is very proof for an enterprise as well. There are things that an enterprise needs to do them soon. There are things an employee needs to do themselves. Um, but there are things that they could leverage from the external innovation and the power of innovation that is coming from technologies like cloud. >>So at Accenture, you have long, long, deep Stan, sorry, you have deep and long-standing relationships with many cloud service providers, including AWS. How does the Accenture cloud first strategy, how does it affect your relationships with those providers? >>Yeah, we have great relationships with cloud providers like AWS. And in fact, in the cloud world, it was one of the first, um, capability that we started about years ago, uh, when we started developing these capabilities. But five years ago, we hit a very important milestone where the two organizations came together and said that we are forging a pharma partnership with joint investments to build this partnership. And we named that as a Accenture, AWS business group ABG, uh, where we co-invest and brought skills together and develop solutions. And we will continue to do that. And through that investment, we've also made several acquisitions that you would have seen in the recent times, like, uh, an invoice and gecko that we made acquisitions in in Europe. But now we're taking this to the next level. What we are saying is two cloud first and the $3 billion investment that we are bringing in, uh, through cloud-first. >>We are going to make specific investment to create unique joint solution and landing zones foundation, um, cloud packs with which clients can accelerate their innovation or their journey to cloud first. And one great example is what we are doing with Takeda, uh, billable, pharmaceutical giant, um, between we've signed a five-year partnership. And it was out in the media just a month ago or so, where we are, the two organizations are coming together. We have created a partnership as a power of three partnership, where the three organizations are jointly hoarding hats and taking responsibility for the innovation and the leadership position that Takeda wants to get to with this. We are going to simplify their operating model and organization by providing and flexibility. We're going to provide a lot more insights. Tequila has a 230 year old organization. Imagine the amount of trapped data and intelligence that is there. >>How about bringing all of that together with the power of AWS and Accenture and Takeda to drive more customer insights, um, come up with breakthrough R and D uh, accelerate clinical trials and improve the patient experience using AI ML and edge technologies. So all of these things that we will do through this partnership with joined investment from Accenture cloud first, as well as partner like AWS, so that Takeda can realize their gain. And, uh, their senior actually made a statement that five years from now, every ticket an employee will have an AI assistant. That's going to make that beginner employee move up the value chain on how they contribute and add value to the future of tequila with the AI assistant, making them even more equipped and smarter than what they could be otherwise. >>So, one last question to close this out here. What is your future vision for, for Accenture cloud first? What are we going to be talking about at next year's Accenture executive summit? Yeah, the future >>Is going to be, um, evolving, but the part that is exciting to me, and this is, uh, uh, a fundamental belief that we are entering a new era of industrial revolution from industry first, second, and third industry. The third happened probably 20 years ago with the advent of Silicon and computers and all of that stuff that happened here in the Silicon Valley. I think the fourth industrial revolution is going to be in the cross section of, uh, physical, digital and biological boundaries. And there's a great article, um, in one economic forum that people, uh, your audience can Google and read about it. Uh, but the reason why this is very, very important is we are seeing a disturbing phenomenon that over the last 10 years are seeing a Blackwing of the, um, labor productivity and innovation, which has dropped to about 2.1%. When you see that kind of phenomenon over that longer period of time, there has to be breakthrough innovation that needs to happen to come out of this barrier and get to the next, you know, base camp, as I would call it to further this productivity, um, lack that we are seeing, and that is going to happen in the intersection of the physical, digital and biological boundaries. >>And I think cloud is going to be the connective tissue between all of these three, to be able to provide that where it's the edge, especially is good to come closer to the human lives. It's going to come from cloud. Yeah. Pick totally in your mind, you can think about cloud as central, either in a private cloud, in a data center or in a public cloud, you know, everywhere. But when you think about edge, it's going to be far reaching and coming close to where we live and maybe work and very, um, get entertained and so on and so forth. And there's good to be, uh, intervention in a positive way in the field of medicine, in the field of entertainment, in the field of, um, manufacturing in the field of, um, you know, mobility. When I say mobility, human mobility, people, transportation, and so on and so forth with all of this stuff, cloud is going to be the connective tissue and the vision of cloud first is going to be, uh, you know, blowing through this big change that is going to happen. And the evolution that is going to happen where, you know, the human grace of mankind, um, our person kind of being very gender neutral in today's world. Um, go first needs to be that beacon of, uh, creating the next generation vision for enterprises to take advantage of that kind of an exciting future. And that's why it, Accenture, are we saying that there'll be change as our, as our purpose? >>I genuinely believe that cloud first is going to be in the forefront of that change agenda, both for Accenture as well as for the rest of the work. Excellent. Let there be change, indeed. Thank you so much for joining us Karthik. A pleasure I'm Rebecca nights stay tuned for more of Q3 60 fives coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS >>Welcome everyone to the Q virtual and our coverage of the Accenture executive summit, which is part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the green cloud and joining me is Kishor Dirk. He is Accenture senior managing director cloud first global services lead. Thank you so much for coming on the show. Kishor nice to meet you. So I want to start by asking you what it is that we mean when we say green cloud, we know the sustainability is a business imperative. So many organizations around the world are committing to responsible innovation, lowering carbon emissions. But what is this? What is it? What does it mean when they talk about cloud from a sustainability perspective? I think it's about responsible innovation being cloud is a cloud first approach that has benefit the clients by helping reduce carbon emissions. Think about it this way. >>You have a large number of data centers. Each of these data centers are increasing by 14% every year. And this double digit growth. What you're seeing is these data centers and the consumption is nearly coolant to the kind of them should have a country like Spain. So the magnitude of the problem that is out there and how do we pursue a green approach. If you look at this, our Accenture analysis, in terms of the migration to public cloud, we've seen that we can reduce that by 59 million tons of CO2 per year with just the 5.9% reduction in total emissions and equates this to 22 million cars off the road. And the magnitude of reduction can go a long way in meeting climate change commitments, particularly for data sensitive. Wow, that's incredible. The numbers that you're putting forward are, are absolutely mind blowing. So how does it work? Is it a simple cloud migration? So, you know, when companies begin their cloud journey and then they confront, uh, with >>Them a lot of questions, the decision to make, uh, this particular, uh, element sustainable in the solution and benefits they drive and they have to make wise choices, and then they will gain unprecedented level of innovation leading to both a greener planet, as well as, uh, a greener balance sheet, I would say, uh, so effectively it's all about ambition, data ambition, greater the reduction in carbon emissions. So from a cloud migration perspective, we look at it as a, as a simple solution with approaches and sustainability benefits, uh, that vary based on things it's about selecting the right cloud provider, a very carbon thoughtful provider and the first step towards a sustainable cloud journey. And here we're looking at cloud operators know, obviously they have different corporate commitments towards sustainability, and that determines how they plan, how they build, uh, their, uh, uh, the data centers, how they are consumed and assumptions that operate there and how they, or they retire their data centers. >>Then, uh, the next element that you want to do is how do you build it ambition, you know, for some of the companies, uh, and average on-prem, uh, drives about 65% energy reduction and the carbon emission reduction number was 84%, which is kind of good, I would say. But then if you could go up to 98% by configuring applications to the cloud, that is significant benefit for, uh, for the board. And obviously it's a, a greener cloud that we're talking about. And then the question is, how far can you go? And, uh, you know, the, obviously the companies have to unlock greater financial societal environmental benefits, and Accenture has this cloud based circular operations and sustainable products and services that we bring into play. So it's a, it's a very thoughtful, broader approach that w bringing in, in terms of, uh, just a simple concept of cloud migration. >>So we know that in the COVID era, shifting to the cloud has really become a business imperative. How is Accenture working with its clients at a time when all of this movement has been accelerated? How do you partner and what is your approach in terms of helping them with their migrations? >>Yeah, I mean, let, let me talk a little bit about the pandemic and the crisis that is that today. And if you really look at that in terms of how we partnered with a lot of our clients in terms of the cloud first approach, I'll give you a couple of examples. We worked with rolls, Royce, MacLaren, DHL, and others, as part of the ventilator, a UK challenge consortium, again, to, uh, coordinate production of medical ventilator surgically needed for the UK health service. Many of these farms I've taken similar initiatives in, in terms of, uh, you know, from a few manufacturers hand sanitizers, and to answer it as us and again, leading passionate labels, making PPE, and again, at the UN general assembly, we launched the end-to-end integration guide that helps company is essentially to have a sustainable development goals. And that's how we are parking at a very large scale. >>Uh, and, and if you really look at how we work with our clients and what is Accenture's role there, uh, you know, from, in terms of our clients, you know, there are multiple steps that we look at. One is about planning, building, deploying, and managing an optimal green cloud solution. And Accenture has this concept of, uh, helping clients with a platform to kind of achieve that goal. And here we are having, we are having a platform or a mine app, which has a module called BGR advisor. And this is a capability that helps you provide optimal green cloud, uh, you know, a business case, and obviously a blueprint for each of our clients and right from the start in terms of how do we complete cloud migration recommendation to an improved solution, accurate accuracy to obviously bringing in the end to end perspective, uh, you know, with this green card advisor capability, we're helping our clients capture what we call as a carbon footprint for existing data centers and provide, uh, I would say the current cloud CO2 emission score that, you know, obviously helps them, uh, with carbon credits that can further that green agenda. >>So essentially this is about recommending a green index score, reducing carbon footprint for migration migrating for green cloud. And if we look at how Accenture itself is practicing what we preach, 95% of our applications are in the cloud. And this migration has helped us, uh, to lead to about $14.5 million in benefit. And in the third year and another 3 million analytics costs that are saved through right-sizing a service consumption. So it's a very broad umbrella and a footprint in terms of how we engage societaly with the UN or our clients. And what is it that we exactly bring to our clients in solving a specific problem? >>Accenture isn't is walking the walk, as you say, >>Instead of it, we practice what we preach, and that is something that we take it to heart. We want to have a responsible business and we want to practice it. And we want to advise our clients around that >>You are your own use case. And so they can, they know they can take your advice. So talk a little bit about, um, the global, the cooperation that's needed. We know that conquering this pandemic is going to take a coordinated global effort and talk a little bit about the great reset initiative. First of all, what is that? Why don't we, why don't we start there and then we can delve into it a little bit more. >>Okay. So before we get to how we are cooperating, the great reset, uh, initiative is about improving the state of the world. And it's about a group of global stakeholders cooperating to simultaneously manage the direct consequences of their COVID-19 crisis. Uh, and in spirit of this cooperation that we're seeing during COVID-19, uh, which will obviously either to post pandemic, to tackle the world's pressing issues. As I say, uh, we are increasing companies to realize a combined potential of technology and sustainable impact to use enterprise solutions, to address with urgency and scale, and, um, obviously, uh, multiple challenges that are facing our world. One of the ways that are increasing, uh, companies to reach their readiness cloud with Accenture's cloud strategy is to build a solid foundation that is resilient and will be able to faster to the current, as well as future times. Now, when you think of cloud as the foundation, uh, that drives the digital transformation, it's about scale speed, streamlining your operations, and obviously reducing costs. >>And as these businesses seize the construct of cloud first, they must remain obviously responsible and trusted. Now think about this, right, as part of our analysis, uh, that profitability can co-exist with responsible and sustainable practices. Let's say that all the data centers, uh, migrated from on-prem to cloud based, we estimate that would reduce carbon emissions globally by 60 million tons per year. Uh, and think about it this way, right? Easier metric would be taking out 22 million cars off the road. Um, the other examples that you've seen, right, in terms of the NHS work that they're doing, uh, in, in UK to build, uh, uh, you know, uh, Microsoft teams in based integration. And, uh, the platform rolled out for 1.2 million users, uh, and got 16,000 users that we were able to secure, uh, instant messages, obviously complete audio video calls and host virtual meetings across India. So, uh, this, this work that we did with NHS is, is something that we have, we are collaborating with a lot of tools and powering businesses. >>Well, you're vividly describing the business case for sustainability. What do you see as the future of cloud when thinking about it from this lens of sustainability, and also going back to what you were talking about in terms of how you are helping your, your fostering cooperation within these organizations. >>Yeah, that's a very good question. So if you look at today, right, businesses are obviously environmentally aware and they are expanding efforts to decrease power consumption, carbon emissions, and they want to run a sustainable operational efficiency across all elements of their business. And this is an increasing trend, and there is that option of energy efficient infrastructure in the global market. And this trend is the cloud first thinking. And with the right cloud migration that we've been discussing is about unlocking new opportunity, like clean energy foundations enable enabled by cloud based geographic analysis, material, waste reductions, and better data insights. And this is something that, uh, uh, will drive, uh, with obviously faster analytics platform that is out there. Now, the sustainability is actually the future of business, which is companies that are historically different, the financial security or agility benefits to cloud. Now sustainability becomes an imperative for them. And I would own experience Accenture's experience with cloud migrations. We have seen 30 to 40% total cost of ownership savings, and it's driving a greater workload, flexibility, better service, your obligation, and obviously more energy efficient, uh, public clouds that cost, uh, we'll see that, that drive a lot of these enterprise own data centers. So in our view, what we are seeing is that this, this, uh, sustainable cloud position helps, uh, helps companies to, uh, drive a lot of the goals in addition to their financial and other goods. >>So what should organizations who are, who are watching this interview and saying, Hey, I need to know more, what, what do you recommend to them? And what, where should they go to get more information on Greenplum? >>Yeah. If you wanna, if you are a business leader and you're thinking about which cloud provider is good, or how, how should applications be modernized to meet our day-to-day needs, which cloud driven innovations should be priorities. Uh, you know, that's why Accenture, uh, formed up the cloud first organization and essentially to provide the full stack of cloud services to help our clients become a cloud first business. Um, you know, it's all about excavation, uh, the digital transformation innovating faster, creating differentiated, uh, and sustainable value for our clients. And we are powering it up at 70,000 cloud professionals, $3 billion investment, and, uh, bringing together and services for our clients in terms of cloud solutions. And obviously the ecosystem partnership that we have that we are seeing today, uh, and, and the assets that help our clients realize their goals. Um, and again, to do reach out to us, uh, we can help them determine obviously, an optimal, sustainable cloud for solution that meets the business needs and being unprecedented levels of innovation. Our experience, uh, will be our advantage. And, uh, now more than ever Rebecca, >>Just closing us out here. Do you have any advice for these companies who are navigating a great deal of uncertainty? We, what, what do you think the next 12 to 24 months? What do you think that should be on the minds of CEOs as they go through? >>So, as CEO's are thinking about rapidly leveraging cloud, migrating to cloud, uh, one of the elements that we want them to be thoughtful about is can they do that, uh, with unprecedent level of innovation, but also build a greener planet and a greener balance sheet, if we can achieve this balance and kind of, uh, have a, have a world which is greener, I think the world will win. And we all along with Accenture clients will win. That's what I would say, uh, >>Optimistic outlook, and I will take it. Thank you so much. Kishor for coming on the show >>That was >>Accenture's Kishor Dirk, I'm Rebecca Knight stay tuned for more of the cube virtuals coverage of the Accenture executive summit >>Around the globe. >>It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtual and our coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the power of three. And what happens when you bring together the scientific know-how of a global bias biopharmaceutical powerhouse in Takeda, a leading cloud services provider in AWS, and Accenture's ability to innovate, execute, and deliver innovation. Joining me to talk about these things. We have Aaron, sorry, Arjun, baby. He is the senior managing director and chairman of Accenture's diamond leadership council. Welcome Arjun, Karl hick. He is the chief digital and information officer at Takeda. What is your bigger, thank you, Rebecca and Brian bowhead, global director, and head of the Accenture AWS business group at Amazon web services. Thanks so much for coming up. So, as I said, we're talking today about this relationship between, uh, your three organizations. Carl, I want to talk with you. I know you're at the beginning of your cloud journey. What was the compelling reason? What w why, why move to the cloud and why now? >>Yeah, no, thank you for the question. So, you know, as a biopharmaceutical leader, we're committed to bringing better health and a brighter future to our patients. We're doing that by translating science into some really innovative and life transporting therapies, but throughout, you know, we believe that there's a responsible use of technology, of data and of innovation. And those three ingredients are really key to helping us deliver on that promise. And so, you know, while I think, uh, I'll call it, this cloud journey is already always been a part of our strategy. Um, and we've made some pretty steady progress over the last years with a number of I'll call it diverse approaches to the digital and AI. We just weren't seeing the impact at scale that we wanted to see. Um, and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and, uh, broaden that shift. >>And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. One of those has been certainly a number of the large acquisitions we've made Shire, uh, being the most pressing example, uh, but also the global pandemic, both of those highlight the need for us to move faster, um, at the speed of cloud, ultimately. Uh, and so we started thinking outside of the box because it was taking us too long and we decided to leverage the strategic partner model. Uh, and it's giving us a chance to think about our challenges very differently. We call this the power of three, uh, and ultimately our focus is singularly on our patients. I mean, they're waiting for us. We need to get there faster. It can take years. And so I think that there is a focus on innovation, um, at a rapid speed, so we can move ultimately from treating conditions to keeping people healthy. >>So, as you are embarking on this journey, what are some of the insights you want to share about, about what you're seeing so far? >>Yeah, no, it's a great question. So, I mean, look, maybe right before I highlight some of the key insights, uh, I would say that, you know, with cloud now as the, as the launchpad for innovation, you know, our vision all along has been that in less than 10 years, we want every single to kid, uh, associate we're employed to be empowered by an AI assistant. And I think that, you know, that's going to help us make faster, better decisions. It'll help us, uh, fundamentally deliver transformative therapies and better experiences to, to that ecosystem, to our patients, to physicians, to payers, et cetera, much faster than we previously thought possible. Um, and I think that technologies like cloud and edge computing together with a very powerful I'll call it data fabric is going to help us to create this, this real-time, uh, I'll call it the digital ecosystem. >>The data has to flow ultimately seamlessly between our patients and providers or partners or researchers, et cetera. Uh, and so we've been thinking about this, uh, I'll call it, we call it sort of this pyramid, um, that helps us describe our vision. Uh, and a lot of it has to do with ultimately modernizing the foundation, modernizing and rearchitecting, the platforms that drive the company, uh, heightening our focus on data, which means that there's an accelerated shift towards, uh, enterprise data platforms and digital products. And then ultimately, uh, uh, P you know, really an engine for innovation sitting at the very top. Um, and so I think with that, you know, there's a few different, I'll call it insights that, you know, are quickly kind of come zooming into focus. I would say one is this need to collaborate very differently. Um, you know, not only internally, but you know, how do we define ultimately, and build a connected digital ecosystem with the right partners and technologies externally? >>I think the second component that maybe people don't think as much about, but, you know, I find critically important is for us to find ways of really transforming our culture. We have to unlock talent and shift the culture certainly as a large biopharmaceutical very differently. And then lastly, you've touched on it already, which is, you know, innovation at the speed of cloud. How do we re-imagine that, you know, how do ideas go from getting tested and months to kind of getting tested in days? You know, how do we collaborate very differently? Uh, and so I think those are three, uh, perhaps of the larger I'll call it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. >>So Arjun, I want to bring you into this conversation a little bit, let let's delve into those a bit. Talk first about the collaboration, uh, that Carl was referencing there. How, how have you seen that? It is enabling, uh, colleagues and teams to communicate differently and interact in new and different ways? Uh, both internally and externally, as Carl said, >>No, th thank you for that. And, um, I've got to give call a lot of credit, because as we started to think about this journey, it was clear, it was a bold ambition. It was, uh, something that, you know, we had all to do differently. And so the, the concept of the power of three that Carl has constructed has become a label for us as a way to think about what are we going to do to collectively drive this journey forward. And to me, the unique ways of collaboration means three things. The first one is that, um, what is expected is that the three parties are going to come together and it's more than just the sum of our resources. And by that, I mean that we have to bring all of ourselves, all of our collective capabilities, as an example, Amazon has amazing supply chain capabilities. >>They're one of the best at supply chain. So in addition to resources, when we have supply chain innovations, uh, that's something that they're bringing in addition to just, uh, talent and assets, similarly for Accenture, right? We do a lot, uh, in the talent space. So how do we bring our thinking as to how we apply best practices for talent to this partnership? So, um, as we think about this, so that's, that's the first one, the second one is about shared success very early on in this partnership, we started to build some foundations and actually develop seven principles that all of us would look at as the basis for this success shared success model. And we continue to hold that sort of in the forefront, as we think about this collaboration. And maybe the third thing I would say is this one team mindset. So whether it's the three of our CEOs that get together every couple of months to think about, uh, this partnership, or it is the governance model that Carl has put together, which has all three parties in the governance and every level of leadership. We always think about this as a collective group, so that we can keep that front and center. And what I think ultimately has enabled us to do is it allowed us to move at speed, be more flexible. And ultimately all we're looking at the target the same way, the North side, the same way. >>Brian, what about you? What have you observed? And are you thinking about in terms of how this is helping teams collaborate differently, >>Lillian and Arjun made some, some great points there. And I think if you really think about what he's talking about, it's that, that diversity of talent, diversity of scale and viewpoint and even culture, right? And so we see that in the power of three. And then I think if we drill down into what we see at Takeda, and frankly, Takeda was, was really, I think, pretty visionary and on their way here, right? And taking this kind of cross functional approach and applying it to how they operate day to day. So moving from a more functional view of the world to more of a product oriented view of the world, right? So when you think about we're going to be organized around a product or a service or a capability that we're going to provide to our customers or our patients or donors in this case, it implies a different structure, although altogether, and a different way of thinking, right? >>Because now you've got technical people and business experts and marketing experts, all working together in this is sort of cross collaboration. And what's great about that is it's really the only way to succeed with cloud, right? Because the old ways of thinking where you've got application people and infrastructure, people in business, people is suboptimal, right? Because we can all access this tool as these capabilities and the best way to do that. Isn't across kind of a cross-collaborative way. And so this is product oriented mindset. It's a keto was already on. I think it's allowed us to move faster in those areas. >>Carl, I want to go back to this idea of unlocking talent and culture. And this is something that both Brian and Arjun have talked about too. People are an essential part of their, at the heart of your organization. How will their experience of work change and how are you helping re-imagine and reinforce a strong organizational culture, particularly at this time when so many people are working remotely. >>Yeah. It's a great question. And it's something that, you know, I think we all have to think a lot about, I mean, I think, um, you know, driving this, this call it, this, this digital and data kind of capability building, uh, takes a lot of, a lot of thinking. So, I mean, there's a few different elements in terms of how we're tackling this one is we're recognizing, and it's not just for the technology organization or for those actors that, that we're innovating with, but it's really across all of the Cato where we're working through ways of raising what I'll call the overall digital leaders literacy of the organization, you know, what are the, you know, what are the skills that are needed almost at a baseline level, even for a global bio-pharmaceutical company and how do we deploy, I'll call it those learning resources very broadly. >>And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are very specialized skills that are needed. Uh, my organization is one of those. And so, you know, we're fostering ways in which, you know, we're very kind of quickly kind of creating, uh, avenues excitement for, for associates in that space. So one example specifically, as we use, you know, during these very much sort of remote, uh, sort of days, we, we use what we call global it meet days, and we set a day aside every single month and this last Friday, um, you know, we, we create during that time, it's time for personal development. Um, and we provide active seminars and training on things like, you know, robotic process automation, data analytics cloud, uh, in this last month we've been doing this for months and months now, but in his last month, more than 50% of my organization participated, and there's this huge positive shift, both in terms of access and excitement about really harnessing those new skills and being able to apply them. >>Uh, and so I think that that's, you know, one, one element that, uh, can be considered. And then thirdly, um, of course, every organization to work on, how do you prioritize talent, acquisition and management and competencies that you can't rescale? I mean, there are just some new capabilities that we don't have. And so there's a large focus that I have with our executive team and our CEO and thinking through those critical roles that we need to activate in order to kind of, to, to build on this, uh, this business led cloud transformation. And lastly, probably the hardest one, but the one that I'm most jazzed about is really this focus on changing the mindsets and behaviors. Um, and I think there, you know, this is where the power of three is, is really, uh, kind of coming together nicely. I mean, we're working on things like, you know, how do we create this patient obsessed curiosity, um, and really kind of unlock innovation with a real, kind of a growth mindset. >>Uh, and the level of curiosity that's needed, not to just continue to do the same things, but to really challenge the status quo. So that's one big area of focus we're having the agility to act just faster. I mean, to worry less, I guess I would say about kind of the standard chain of command, but how do you make more speedy, more courageous decisions? And this is places where we can emulate the way that a partner like AWS works, or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently to a number of partnerships that we can build. So we can break down some of these barriers and use these networks, um, whether it's within our own internal ecosystem or externally to help, to create value faster. So a lot of energy around ways of working and we'll have to check back in, but I mean, we're early in on this mindset and behavioral shift, um, but a lot of good early momentum. >>Carl you've given me a good segue to talk to Brian about innovation, because you said a lot of the things that I was the customer obsession and this idea of innovating much more quickly. Obviously now the world has its eyes on drug development, and we've all learned a lot about it, uh, in the past few months and accelerating drug development is all, uh, is of great interest to all of us. Brian, how does a transformation like this help a company's, uh, ability to become more agile and more innovative and add a quicker speed to, >>Yeah, no, absolutely. And I think some of the things that Carl talked about just now are critical to that, right? I think where sometimes folks fall short is they think, you know, we're going to roll out the technology and the technology is going to be the silver bullet where in fact it is the culture, it is, is the talent. And it's the focus on that. That's going to be, you know, the determinant of success. And I will say, you know, in this power of three arrangement and Carl talked a little bit about the pyramid, um, talent and culture and that change, and that kind of thinking about that has been a first-class citizen since the very beginning, right. That absolutely is critical for, for being there. Um, and, and so that's been, that's been key. And so we think about innovation at Amazon and AWS, and Carl mentioned some of the things that, you know, partner like AWS can bring to the table is we talk a lot about builders, right? >>So kind of obsessive about builders. Um, and, and we meet what we mean by that is we at Amazon, we hire for builders, we cultivate builders and we like to talk to our customers about it as well. And it also implies a different mindset, right? When you're a builder, you have that, that curiosity, you have that ownership, you have that stake and whatever I'm creating, I'm going to be a co-owner of this product or this service, right. Getting back to that kind of product oriented mindset. And it's not just the technical people or the it people who are builders. It is also the business people as, as Carl talked about. Right. So when we start thinking about, um, innovation again, where we see folks kind of get into a little bit of a innovation pilot paralysis, is that you can focus on the technology, but if you're not focusing on the talent and the culture and the processes and the mechanisms, you're going to be putting out technology, but you're not going to have an organization that's ready to take it and scale it and accelerate it. >>Right. And so that's, that's been absolutely critical. So just a couple of things we've been doing with, with Takeda and Decatur has really been leading the way is, think about a mechanism and a process. And it's really been working backward from the customer, right? In this case, again, the patient and the donor. And that was an easy one because the key value of Decatur is to be a patient focused bio-pharmaceutical right. So that was embedded in their DNA. So that working back from that, that patient, that donor was a key part of that process. And that's really deep in our DNA as well. And Accenture's, and so we were able to bring that together. The other one is, is, is getting used to experimenting and even perhaps failing, right. And being able to iterate and fail fast and experiment and understanding that, you know, some decisions, what we call it at Amazon are two two-way doors, meaning you can go through that door, not like what you see and turn around and go back. And cloud really helps there because the costs of experimenting and the cost of failure is so much lower than it's ever been. You can do it much faster and the implications are so much less. So just a couple of things that we've been really driving, uh, with the cadence around innovation, that's been really critical. Carl, where are you already seeing signs of success? >>Yeah, no, it's a great question. And so we chose, you know, uh, with our focus on innovation to try to unleash maybe the power of data digital in, uh, in focusing on what I call sort of a nave. And so we chose our, our, our plasma derived therapy business, um, and you know, the plasma-derived therapy business unit, it develops critical life-saving therapies for patients with rare and complex diseases. Um, but what we're doing is by bringing kind of our energy together, we're focusing on creating, I'll call it state of the art digitally connected donation centers. And we're really modernizing, you know, the, the, the donor experience right now, we're trying to, uh, improve also I'll call it the overall plasma collection process. And so we've, uh, selected a number of alcohol at a very high speed pilots that we're working through right now, specifically in this, in this area. And we're seeing >>Really great results already. Um, and so that's, that's one specific area of focus are Jen, I want you to close this out here. Any ideas, any best practices advice you would have for other pharmaceutical companies that are, that are at the early stage of their cloud journey? Sorry. Was that for me? Yes. Sorry. Origin. Yeah, no, I was breaking up a bit. No, I think they, um, the key is what's sort of been great for me to see is that when people think about cloud, you know, you always think about infrastructure technology. The reality is that the cloud is really the true enabler for innovation and innovating at scale. And, and if you think about that, right, and all the components that you need, ultimately, that's where the value is for the company, right? Because yes, you're going to get some cost synergies and that's great, but the true value is in how do we transform the organization in the case of the Qaeda and our life sciences clients, right. >>We're trying to take a 14 year process of research and development that takes billions of dollars and compress that right. Tremendous amounts of innovation opportunity. You think about the commercial aspect, lots of innovation can come there. The plasma derived therapy is a great example of how we're going to really innovate to change the trajectory of that business. So I think innovation is at the heart of what most organizations need to do. And the formula, the cocktail that the Qaeda has constructed with this footie program really has all the ingredients, um, that are required for that success. Great. Well, thank you so much. Arjun, Brian and Carl was really an enlightening conversation. Thank you. It's been a lot of, thank you. Yeah, it's been fun. Thanks Rebecca. And thank you for tuning into the cube. Virtual has coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of Accenture executive summit here at AWS reinvent. I'm your host Rebecca Knight for this segment? We have two guests. First. We have Helen Davis. She is the senior director of cloud platform services, assistant director for it and digital for the West Midlands police. Thanks so much for coming on the show, Helen, and we also have Matthew pound. He is Accenture health and public service associate director and West Midlands police account lead. Thanks so much for coming on the show. Matthew, thank you for having us. So we are going to be talking about delivering data-driven insights to the West Midlands police force. Helen, I want to start with >>You. Can you tell us a little bit about the West Midlands police force? How big is the force and also what were some of the challenges that you were grappling with prior to this initiative? >>Yeah, certainly. So Westerners police is the second largest police force in the UK, outside of the metropolitan police in London. Um, we have an excessive, um, 11,000 people work at Westman ins police serving communities, um, through, across the Midlands region. So geographically, we're quite a big area as well, as well as, um, being population, um, density, having that as a, at a high level. Um, so the reason we sort of embarked on the data-driven insights platform and it, which was a huge change for us was for a number of reasons. Um, namely we had a lot of disparate data, um, which was spread across a range of legacy systems that were many, many years old, um, with some duplication of what was being captured and no single view for offices or, um, support staff. Um, some of the access was limited. You have to be in a, in an actual police building on a desktop computer to access it. Um, other information could only reach the offices on the frontline through a telephone call back to one of our enabling services where they would do a manual checkup, um, look at the information, then call the offices back, um, and tell them what they needed to know. So it was a very long laborious, um, process and not very efficient. Um, and we certainly weren't exploiting the data that we had in a very productive way. >>So it sounds like as you're describing and an old clunky system that needed a technological, uh, reimagination, so what was the main motivation for, for doing, for making this shift? >>It was really, um, about making us more efficient and more effective in how we do how we do business. So, um, you know, certainly as a, as an it leader and sort of my operational colleagues, we recognize the benefits, um, that data and analytics could bring in, uh, in a policing environment, not something that was, um, really done in the UK at the time. You know, we have a lot of data, so we're very data rich and the information that we have, but we needed to turn it into information that was actionable. So that's where we started looking for, um, technology partners and suppliers to help us and sort of help us really with what's the art of the possible, you know, this hasn't been done before. So what could we do in this space that's appropriate for policing? >>I love that idea. What is the art of the possible, can you tell us a little bit about why you chose AWS? >>I think really, you know, as with all things and when we're procuring a partner in the public sector that, you know, there are many rules and regulations, uh, quite rightly as you would expect that to be because we're spending public money. So we have to be very, very careful and, um, it's, it's a long process and we have to be open to public scrutiny. So, um, we sort of look to everything, everything that was available as part of that process, but we recognize the benefits that Clyde would provide in this space because, you know, without moving to a cloud environment, we would literally be replacing something that was legacy with something that was a bit more modern. Um, that's not what we wanted to do. Our ambition was far greater than that. So I think, um, in terms of AWS, really, it was around the scalability, interoperability, you know, disaster things like the disaster recovery service, the fact that we can scale up and down quickly, we call it dialing up and dialing back. Um, you know, it's it's page go. So it just sort of ticked all the boxes for us. And then we went through the full procurement process, fortunately, um, it came out on top for us. So we were, we were able to move forward, but it just sort of had everything that we were looking for in that space. >>Matthew, I want to bring you into the conversation a little bit here. How are you working with a wet with the West Midlands police, sorry. And helping them implement this cloud-first journey? >>Yeah, so I guess, um, by January the West Midlands police started, um, favorite five years ago now. So, um, we set up a partnership with the force. I wanted to operate in a way that it was very different to a traditional supplier relationship. Um, secretary that the data difference insights program is, is one of many that we've been working with last nights on, um, over the last five years. Um, as having said already, um, cloud gave a number of, uh, advantages certainly from a big data perspective and the things that that enabled us today, um, I'm from an Accenture perspective that allowed us to bring in a number of the different themes that we have say, cloud teams, security teams, um, and drafted from an insurance perspective, as well as more traditional services that people would associate with the country. >>I mean, so much of this is about embracing comprehensive change to experiment and innovate and try different things. Matthew, how, how do you help, uh, an entity like West Midlands police think differently when they are, there are these ways of doing things that people are used to, how do you help them think about what is the art of the possible, as Helen said, >>There's a few things to that enable those being critical is trying to co-create solutions together. Yeah. There's no point just turning up with, um, what we think is the right answer, try and say, um, collectively work three, um, the issues that the fullest is seeing and the outcomes they're looking to achieve rather than simply focusing on a long list of requirements, I think was critical and then being really open to working together to create the right solution. Um, rather than just, you know, trying to pick something off the shelf that maybe doesn't fit the forces requirements in the way that it should too, >>Right. It's not always a one size fits all. >>Absolutely not. You know, what we believe is critical is making sure that we're creating something that met the forces needs, um, in terms of the outcomes they're looking to achieve the financial envelopes that were available, um, and how we can deliver those in a, uh, iterative agile way, um, rather than spending years and years, um, working towards an outcome, um, that is gonna update before you even get that. >>So Helen, how, how are things different? What kinds of business functions and processes have been re-imagined in, in light of this change and this shift >>It's, it's actually unrecognizable now, um, in certain areas of the business as it was before. So to give you a little bit of, of context, when we, um, started working with essentially in AWS on the data driven insights program, it was very much around providing, um, what was called locally, a wizzy tool for our intelligence analysts to interrogate data, look at data, you know, decide whether they could do anything predictive with it. And it was very much sort of a back office function to sort of tidy things up for us and make us a bit better in that, in that area or a lot better in that area. And it was rolled out to a number of offices, a small number on the front line. Um, I'm really, it was, um, in line with a mobility strategy that we, hardware officers were getting new smartphones for the first time, um, to do sort of a lot of things on, on, um, policing apps and things like that to again, to avoid them, having to keep driving back to police stations, et cetera. >>And the pilot was so successful. Every officer now has access to this data, um, on their mobile devices. So it literally went from a handful of people in an office somewhere using it to do sort of clever bang things to, um, every officer in the force, being able to access that level of data at their fingertips. Literally. So what they were touched with done before is if they needed to check and address or check details of an individual, um, just as one example, they would either have to, in many cases, go back to a police station to look it up themselves on a desktop computer. Well, they would have to make a call back to a centralized function and speak to an operator, relay the questions, either, wait for the answer or wait for a call back with the answer when those people are doing the data interrogation manually. >>So the biggest change for us is the self-service nature of the data we now have available. So officers can do it themselves on their phone, wherever they might be. So the efficiency savings from that point of view are immense. And I think just parallel to that is the quality of our, because we had a lot of data, but just because you've got a lot of data and a lot of information doesn't mean it's big data and it's valuable necessarily. Um, so again, it was having the single source of truth as we, as we call it. So you know that when you are completing those safe searches and getting the responses back, that it is the most accurate information we hold. And also you're getting it back within minutes, as opposed to, you know, half an hour, an hour or a drive back to a station. So it's making officers more efficient and it's also making them safer. The more efficient they are, the more time they have to spend out with the public doing what they, you know, we all should be doing >>That kind of return on investment because what you were just describing with all the steps that we needed to be taken in prior to this, to verify an address say, and those are precious seconds when someone's life is on the line in, in sort of in the course of everyday police work. >>Absolutely. Yeah, absolutely. It's difficult to put a price on it. It's difficult to quantify. Um, but all the, you know, the minutes here and there certainly add up to a significant amount of efficiency savings, and we've certainly been able to demonstrate the officers are spending less time up police stations as a result or more time out on the front line. Also they're safer because they can get information about what may or may not be and address what may or may not have occurred in an area before very, very quickly without having to wait. >>I do, I want to hear your observations of working so closely with this West Midlands police. Have you noticed anything about changes in its culture and its operating model in how police officers interact with one another? Have you seen any changes since this technology change? >>What's unique about the Western displaces, the buy-in from the top down, the chief and his exact team and Helen as the leader from an IOT perspective, um, the entire force is bought in. So what is a significant change program? Uh, I'm not trickles three. Um, everyone in the organization, um, change is difficult. Um, and there's a lot of time effort that's been put in to bake the technical delivery and the business change and adoption aspects around each of the projects. Um, but you can see the step change that is making in each aspect to the organization, uh, and where that's putting West Midlands police as a leader in, um, technology I'm policing in the UK. And I think globally, >>And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain intransigence in workplaces about this is just the way we've always done things and we're used to this and don't try us to get us. Don't try to get us to do anything new here. It works. How do you get the buy-in that you need to do this kind of digital transformation? >>I think it would be wrong to say it was easy. Um, um, we also have to bear in mind that this was one program in a five-year program. So there was a lot of change going on, um, both internally for some of our back office functions, as well as front tie, uh, frontline offices. So with DDI in particular, I think the stack change occurred when people could see what it could do for them. You know, we had lots of workshops and seminars where we all talk about, you know, big data and it's going to be great and it's data analytics and it's transformational, you know, and quite rightly people that are very busy doing a day job, but not necessarily technologists in the main and, you know, are particularly interested quite rightly so in what we are not dealing with the cloud, you know? And it was like, yeah, okay. >>It's one more thing. And then when they started to see on that, on their phones and what teams could do, that's when it started to sell itself. And I think that's when we started to see, you know, to see the stat change, you know, and, and if we, if we have any issues now it's literally, you know, our help desks in meltdown. Cause everyone's like, well, we call it manage without this anymore. And I think that speaks for itself. So it doesn't happen overnight. It's sort of incremental changes and then that's a step change in attitude. And when they see it working and they see the benefits, they want to use it more. And that's how it's become fundamental to all policing by itself, really, without much selling >>You, Helen just made a compelling case for how to get buy in. Have you discovered any other best practices when you are trying to get everyone on board for this kind of thing? >>We've um, we've used a lot of the traditional techniques, things around comms and engagement. We've also used things like, um, the 30 day challenge and nudge theory around how can we gradually encourage people to use things? Um, I think there's a point where all of this around, how do we just keep it simple and keep it user centric from an end user perspective? I think DDI is a great example of where the, the technology is incredibly complex. The solution itself is, um, you know, extremely large and, um, has been very difficult to, um, get delivered. But at the heart of it is a very simple front end for the user to encourage it and take that complexity away from them. Uh, I think that's been critical through the whole piece of DDR. >>One final word from Helen. I want to hear, where do you go from here? What is the longterm vision? I know that this has made productivity, um, productivity savings equivalent to 154 full-time officers. Uh, what's next, >>I think really it's around, um, exploiting what we've got. Um, I use the phrase quite a lot, dialing it up, which drives my technical architects crazy, but because it's apparently not that simple, but, um, you know, we've, we've been through significant change in the last five years and we are still continuing to batch all of those changes into everyday, um, operational policing. But what we need to see is we need to exploit and build on the investments that we've made in terms of data and claims specifically, the next step really is about expanding our pool of data and our functions. Um, so that, you know, we keep getting better and better at this. Um, the more we do, the more data we have, the more refined we can be, the more precise we are with all of our actions. Um, you know, we're always being expected to, again, look after the public purse and do more for less. And I think this is certainly an and our cloud journey and cloud first by design, which is where we are now, um, is helping us to be future-proofed. So for us, it's very much an investment. And I see now that we have good at embedded in operational policing for me, this is the start of our journey, not the end. So it's really exciting to see where we can go from here. >>Exciting times. Indeed. Thank you so much. Lily, Helen and Matthew for joining us. I really appreciate it. Thank you. And you are watching the cube stay tuned for more of the cubes coverage of the AWS reinvent Accenture executive summit. I'm Rebecca Knight from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Hi, everyone. Welcome to the cube virtual coverage of the executive summit at AWS reinvent 2020 virtual. This is the cube virtual. We can't be there in person like we are every year we have to be remote. This executive summit is with special programming supported by Accenture where the cube virtual I'm your host John for a year, we had a great panel here called uncloud first digital transformation from some experts, Stuart driver, the director of it and infrastructure and operates at lion Australia, Douglas Regan, managing director, client account lead at lion for Accenture as a deep Islam associate director application development lead for Accenture gentlemen, thanks for coming on the cube virtual that's a mouthful, all that digital, but the bottom line it's cloud transformation. This is a journey that you guys have been on together for over 10 years to be really a digital company. Now, some things have happened in the past year that kind of brings all this together. This is about the next generation organization. So I want to ask Stuart you first, if you can talk about this transformation at lion has undertaken some of the challenges and opportunities and how this year in particular has brought it together because you know, COVID has been the accelerant of digital transformation. Well, if you're 10 years in, I'm sure you're there. You're in the, uh, on that wave right now. Take a minute to explain this transformation journey. >>Yeah, sure. So number of years back, we looked at kind of our infrastructure and our landscape trying to figure out where we >>Wanted to go next. And we were very analog based and stuck in the old it groove of, you know, Capitol reef rash, um, struggling to transform, struggling to get to a digital platform and we needed to change it up so that we could become very different business to the one that we were back then obviously cloud is an accelerant to that. And we had a number of initiatives that needed a platform to build on. And a cloud infrastructure was the way that we started to do that. So we went through a number of transformation programs that we didn't want to do that in the old world. We wanted to do it in a new world. So for us, it was partnering up with a dried organizations that can take you on the journey and, uh, you know, start to deliver bit by bit incremental progress, uh, to get to the, uh, I guess the promise land. >>Um, we're not, not all the way there, but to where we're on the way along. And then when you get to some of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually change pretty quickly, um, provide capacity and, uh, and increase your environments and, you know, do the things that you need to do in a much more dynamic way than we would have been able to previously where we might've been waiting for the hardware vendors, et cetera, to deliver capacity. So for us this year, it's been a pretty strong year from an it perspective and delivering for the business needs >>Before I hit the Douglas. I want to just real quick, a redirect to you and say, you know, if all the people said, Oh yeah, you got to jump on cloud, get in early, you know, a lot of naysayers like, well, wait till to mature a little bit, really, if you got in early and you, you know, paying your dues, if you will taking that medicine with the cloud, you're really kind of peaking at the right time. Is that true? Is that one of the benefits that comes out of this getting in the cloud? Yeah, >>John, this has been an unprecedented year, right. And, um, you know, Australia, we had to live through Bush fires and then we had covert and, and then we actually had to deliver a, um, a project on very large transformational project, completely remote. And then we also had had some, some cyber challenges, which is public as well. And I don't think if we weren't moved into and enabled through the cloud, we would have been able to achieve that this year. It would have been much different, would have been very difficult to do the backing. We're able to work and partner with Amazon through this year, which is unprecedented and actually come out the other end. Then we've delivered a brand new digital capability across the entire business. Um, in many, you know, wouldn't have been impossible if we could, I guess, state in the old world, the fact that we were moved into the new Naval by the new allowed us to work in this unprecedented year. >>Just quick, what's your personal view on this? Because I've been saying on the Cuban reporting necessity is the mother of all invention and the word agility has been kicked around as kind of a cliche, Oh, it'd be agile. You know, we're going to get the city, you get a minute on specifically, but from your perspective, uh, Douglas, what does that mean to you? Because there is benefits there for being agile. And >>I mean, I think as Stuart mentioned, right, in a lot of these things we try to do and, you know, typically, you know, hardware and of the last >>To be told and, and, and always on the critical path to be done, we really didn't have that in this case, what we were doing with our projects in our deployments, right. We were able to move quickly able to make decisions in line with the business and really get things going. Right. So you see a lot of times in a traditional world, you have these inhibitors, you have these critical path, it takes weeks and months to get things done as opposed to hours and days, and truly allowed us to, we had to, you know, VJ things, move things. And, you know, we were able to do that in this environment with AWS support and the fact that we can kind of turn things off and on as quickly as we need it. >>Yeah. Cloud-scale is great for speed. So DECA, Gardez get your thoughts on this cloud first mission, you know, it, you know, the dev ops world, they saw this early that jumping in there, they saw the, the, the agility. Now the theme this year is modern applications with the COVID pandemic pressure, there's real business pressure to make that happen. How did you guys learn to get there fast? And what specifically did you guys do at Accenture and how did it all come together? Can you take us inside kind of how it played out? >>Oh, right. So yeah, we started off with, as we do in most cases with a much more bigger group, and we worked with lions functional experts and, uh, the lost knowledge that allowed the infrastructure being had. Um, we then applied our journey to cloud strategy, which basically revolves around the seminars and, and, uh, you know, the deep three steps from our perspective, uh, assessing the current environment, setting up the new cloud environment. And as we go modernizing and, and migrating these applications to the cloud now, you know, one of the key things that, uh, you know, we learned along this journey was that, you know, you can have the best plans, but bottom line that we were dealing with, we often than not have to make changes. Uh, what a lot of agility and also work with a lot of collaboration with the, uh, Lyon team, as well as, uh, uh, AWS. I think the key thing for me was being able to really bring it all together. It's not just, uh, you know, essentially mobilize it's all of us working together to make this happen. >>What were some of the learnings real quick journeys? >>So I think so the perspective of the key learnings that, you know, uh, you know, when you look back at, uh, the, the infrastructure that was that we were trying to migrate over to the cloud, a lot of the documentation, et cetera, was not available. We were having to, uh, figure out a lot of things on the fly. Now that really required us to have, uh, uh, people with deep expertise who could go into those environments and, and work out, uh, you know, the best ways to, to migrate the workloads to the cloud. Uh, I think, you know, the, the biggest thing for me was making sure all the had on that real SMEs across the board globally, that we could leverage across the various technologies, uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment with line. >>Let's do what I got to ask you. How did you address your approach to the cloud and what was your experience? >>Yeah, for me, it's around getting the foundations right. To start with and then building on them. Um, so, you know, you've gotta have your, your, your process and you've got to have your, your kind of your infrastructure there and your blueprints ready. Um, AWS do a great job of that, right. Getting the foundations right. And then building upon it, and then, you know, partnering with Accenture allows you to do that very successfully. Um, I think, um, you know, the one thing that was probably surprising to us when we started down this journey and kind of after we got a long way down the track and looking backwards is actually how much you can just turn off. Right? So a lot of stuff that you, uh, you get left with a legacy in your environment, and when you start to work through it with the types of people that civic just mentioned, you know, the technical expertise working with the business, um, you can really rationalize your environment and, uh, you know, cloud is a good opportunity to do that, to drive that legacy out. >>Um, so you know, a few things there, the other thing is, um, you've got to try and figure out the benefits that you're going to get out of moving here. So there's no point just taking something that is not delivering a huge amount of value in the traditional world, moving it into the cloud, and guess what is going to deliver the same limited amount of value. So you've got to transform it, and you've got to make sure that you build it for the future and understand exactly what you're trying to gain out of it. So again, you need a strong collaboration. You need a good partners to work with, and you need good engagement from the business as well, because the kind of, uh, you know, digital transformation, cloud transformation, isn't really an it project, I guess, fundamentally it is at the core, but it's a business project that you've got to get the whole business aligned on. You've got to make sure that your investment streams are appropriate and that you're able to understand the benefits and the value that, so you're going to drive back towards the business. >>Let's do it. If you don't mind me asking, what was some of the obstacles you encountered or learnings, um, that might different from the expectation we all been there, Hey, you know, we're going to change the world. Here's the sales pitch, here's the outcome. And then obviously things happen, you know, you learn legacy, okay. Let's put some containerization around that cloud native, um, all that rational. You're talking about what are, and you're going to have obstacles. That's how you learn. That's how perfection has developed. How, what obstacles did you come up with and how are they different from your expectations going in? >>Yeah, they're probably no different from other people that have gone down the same journey. If I'm totally honest, the, you know, 70 or 80% of what you do is relatively easy of the known quantity. It's relatively modern architectures and infrastructures, and you can upgrade, migrate, move them into the cloud, whatever it is, rehost, replatform, rearchitect, whatever it is you want to do, it's the other stuff, right? It's the stuff that always gets left behind. And that's the challenge. It's, it's getting that last bit over the line and making sure that you haven't invested in the future while still carrying all of your legacy costs and complexity within your environment. So, um, to be quite honest, that's probably taken longer and has been more of a challenge than we thought it would be. Um, the other piece I touched on earlier on in terms of what was surprising was actually how much of, uh, your environment is actually not needed anymore. >>When you start to put a critical eye across it and understand, um, uh, ask the tough questions and start to understand exactly what, what it is you're trying to achieve. So if you ask a part of a business, do they still need this application or this service a hundred percent of the time, they will say yes until you start to lay out to them, okay, now I'm going to cost you this to migrate it or this, to run it in the future. And, you know, here's your ongoing costs and, you know, et cetera, et cetera. And then, uh, for a significant amount of those answers, you get a different response when you start to layer on the true value of it. So you start to flush out those hidden costs within the business, and you start to make some critical decisions as a company based on, uh, based on that. So that was a little tougher than we first thought and probably broader than we thought there was more of that than we anticipated, um, which actually results in a much cleaner environment post and post migration. >>You know, the old expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value Stuart and Sadiq. Mainly if you can weigh in on this love to know the percentage of total cloud that you have now, versus when you started, because as you start to uncover whether it's by design for purpose, or you discover opportunities to innovate, like you guys have, I'm sure it kind of, you took on some territory inside Lyon, what percentage of cloud now versus stark? >>Yeah. At the start, it was minimal, right. You know, close to zero, right. Single and single digits. Right. It was mainly SAS environments that we had, uh, sitting in clouds when we, uh, when we started, um, Doug mentioned earlier on a really significant transformation project, um, that we've undertaken and recently gone live on a multi-year one. Um, you know, that's all stood up on AWS and is a significant portion of our environment, um, in terms of what we can move to cloud. Uh, we're probably at about 80 or 90% now. And the balanced bit is, um, legacy infrastructure that is just gonna retire as we go through the cycle rather than migrate to the cloud. Um, so we are significantly cloud-based and, uh, you know, we're reaping the benefits of it. I know you like 20, 20, I'm actually glad that you did all the hard yards in the previous years when you started that business challenges thrown out as, >>So do you any common reaction to the cloud percentage penetration? >>I mean, guys don't, but I was going to say was, I think it's like the 80 20 rule, right? We, we, we worked really hard in the, you know, I think 2018, 19 to get any person off, uh, after getting a loan, the cloud and, or the last year is the 20% that we have been migrating. And Stuart said like, uh, not that is also, that's going to be a good diet. And I think our next big step is going to be obviously, you know, the icing on the tape, which is to decommission all these apps as well. Right. So, you know, to get the real benefits out of, uh, the whole conservation program from a, uh, from a >>Douglas and Stewart, can you guys talk about the decision around the cloud because you guys have had success with AWS, why AWS how's that decision made? Can you guys give some insight into some of those thoughts? >>I can stop, start off. I think back when the decision was made and it was, it was a while back, um, you know, there's some clear advantages of moving relay, Ws, a lot of alignment with some of the significant projects and, uh, the trend, that particular one big transformation project that we've alluded to as well. Um, you know, we needed some, uh, some very robust and, um, just future proof and, um, proven technology. And they Ws gave that to us. We needed a lot of those blueprints to help us move down the path. We didn't want to reinvent everything. So, um, you know, having a lot of that legwork done for us and AWS gives you that, right. And, and particularly when you partner up with, uh, with a company like Accenture as well, you get combinations of the technology and the skills and the knowledge to, to move you forward in that direction. >>So, um, you know, for us, it was a, uh, uh, it was a decision based on, you know, best of breed, um, you know, looking forward and, and trying to predict the future needs and, and, and kind of the environmental that we might need. Um, and, you know, partnering up with organizations that can then take you on the journey. Yeah. And just to build on it. So obviously, you know, lion's like an AWS, but, you know, we knew it was a very good choice given that, um, uh, the skills and the capability that we had, as well as the assets and tools we had to get the most out of, um, AWS and obviously our, our CEO globally, you know, announcement about a huge investment that we're making in cloud. Um, but you know, we've, we've worked very well DWS, we've done some joint workshops and joint investments, um, some joint POC. So yeah, w we have a very good working relationship, AWS, and I think, um, one incident to reflect upon whether it's cyber it's and again, where we actually jointly, you know, dove in with, um, with Amazon and some of their security experts and our experts. And we're able to actually work through that with mine quite successfully. So, um, you know, really good behaviors as an organization, but also really good capabilities. >>Yeah. As you guys, you're essential cloud outcomes, research shown, it's the cycle of innovation with the cloud. That's creating a lot of benefits, knowing what you guys know now, looking back certainly COVID is impacted a lot of people kind of going through the same process, knowing what you guys know now, would you advocate people to jump on this transformation journey? If so, how, and what tweaks they make, which changes, what would you advise? >>Uh, I might take that one to start with. Um, I hate to think where we would have been when, uh, COVID kicked off here in Australia and, you know, we were all sent home, literally were at work on the Friday, and then over the weekend. And then Monday, we were told not to come back into the office and all of a sudden, um, our capacity in terms of remote access and I quadrupled, or more four, five X, uh, what we had on the Friday we needed on the Monday. And we were able to stand that up during the day Monday and into Tuesday, because we were cloud-based. And, uh, you know, we just found up your instances and, uh, you know, sort of our licensing, et cetera. And we had all of our people working remotely, um, within, uh, you know, effectively one business day. >>Um, I know peers of mine in other organizations and industries that are relying on kind of a traditional wise and getting hardware, et cetera, that were weeks and months before they could get their, the right hardware to be able to deliver to their user base. So, um, you know, one example where you're able to scale and, uh, uh, get, uh, get value out of this platform beyond probably what was anticipated at the time you talk about, um, you know, less the, in all of these kinds of things. And you can also think of a few scenarios, but real world ones where you're getting your business back up and running in that period of time is, is just phenomenal. There's other stuff, right? There's these programs that we've rolled out, you do your sizing, um, and in the traditional world, you would just go out and buy more servers than you need. >>And, you know, probably never realize the full value of those, you know, the capability of those servers over the life cycle of them. Whereas you're in a cloud world, you put in what you think is right. And if it's not right, you pump it up a little bit when, when all of your metrics and so on, tell you that you need to bump it up. And conversely you scale it down at the same rate. So for us, with the types of challenges and programs and, uh, uh, and just business need, that's come at as this year, uh, we wouldn't have been able to do it without a strong cloud base, uh, to, uh, to move forward >>Know Douglas. One of the things that I talked to, a lot of people on the right side of history who have been on the right wave with cloud, with the pandemic, and they're happy, they're like, and they're humble. Like, well, we're just lucky, you know, luck is preparation meets opportunity. And this is really about you guys getting in early and being prepared and readiness. This is kind of important as people realize, then you gotta be ready. I mean, it's not just, you don't get lucky by being in the right place, the right time. And there were a lot of companies were on the wrong side of history here who might get washed away. This is a super important, I think, >>To echo and kind of build on what Stewart said. I think that the reason that we've had success and I guess the momentum is we, we didn't just do it in isolation within it and technology. It was actually linked to broader business changes, you know, creating basically a digital platform for the entire business, moving the business, where are they going to be able to come back stronger after COVID, when they're actually set up for growth, um, and actually allows, you know, lying to achievements growth objectives, and also its ambitions as far as what it wants to do, uh, with growth in whatever they make, do with acquiring other companies and moving into different markets and launching new products. So we've actually done it in a way that is, you know, real and direct business benefit, uh, that actually enables line to grow >>General. I really appreciate you coming. I have one final question. If you can wrap up here, uh, Stuart and Douglas, you don't mind weighing in what's the priorities for the future. What's next for lion in a century >>Christmas holidays, I'll start Christmas holidays been a big deal and then a, and then a reset, obviously, right? So, um, you know, it's, it's figuring out, uh, transform what we've already transformed, if that makes sense. So God, a huge proportion of our services sitting in the cloud. Um, but we know we're not done even with the stuff that is in there. We need to take those next steps. We need more and more automation and orchestration. We need to, um, our environment, there's more future growth. We need to be able to work with the business and understand what's coming at them so that we can, um, you know, build that into, into our environment. So again, it's really transformation on top of transformation is the way that I'll describe it. And it's really an open book, right? Once you get it in and you've got the capabilities and the evolving tool sets that, uh, AWS continue to bring to the market, um, you know, working with the partners to, to figure out how we unlock that value, um, you know, drive our costs down efficiency, uh, all of those kind of, you know, standard metrics. >>Um, but you know, we're looking for the next things to transform and show value back out to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with and understand how we can better meet their needs. Yeah, I think just to echo that, I think it's really leveraging this and then did you capability they have and getting the most out of that investment. And then I think it's also moving to, uh, and adopting more new ways of working as far as, you know, the speed of the business, um, is getting up the speed of the market is changing. So being able to launch and do things quickly and also, um, competitive and efficient operating costs, uh, now that they're in the cloud, right? So I think it's really leveraging the most out of the platform and then, you know, being efficient in launching things. So putting them with the business, >>Any word from you on your priorities by you see this year in folding, >>There's got to say like e-learning squares, right, for me around, you know, just journey. This is a journey to the cloud, right. >>And, uh, you know, as well, the sort of Saturday, it's getting all, you know, different parts of the organization along the journey business to it, to your, uh, product lenders, et cetera. Right. And it takes time. It is tough, but, uh, uh, you know, you got to get started on it. And, you know, once we, once we finish off, uh, it's the realization of the benefits now that, you know, looking forward, I think for, from Alliance perspective, it is, uh, you know, once we migrate all the workloads to the cloud, it is leveraging, uh, all staff, right. And as I think students said earlier, uh, with, uh, you know, the latest and greatest stuff that AWS is basically working to see how we can really, uh, achieve more better operational excellence, uh, from a, uh, from a cloud perspective. >>Well, Stewart, thanks for coming on with a and sharing your environment and what's going on and your journey you're on the right wave. Did the work you're in, it's all coming together with faster, congratulations for your success, and, uh, really appreciate Douglas with Steve for coming on as well from Accenture. Thank you for coming on. Thanks, John. Okay. Just the cubes coverage of executive summit at AWS reinvent. This is where all the thought leaders share their best practices, their journeys, and of course, special programming with Accenture and the cube. I'm Sean ferry, your host, thanks for watching from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtuals coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First. We have Johan Krebbers. He is the GM digital emerging technologies and VP of it. Innovation at shell. Thank you so much for coming on the show, Johan you're welcome. And next we have Liz Dennett. She is the lead solution architect for O S D U on AWS. Thank you so much Liz to be here. So I want to start our conversation by talking about OSD. You like so many great innovations. It started with a problem Johan. What was the problem you were trying to solve at shell? >>Yeah, the ethical back a couple of years, we started shoving 2017 where we had a meeting with the deg, the gas exploration in shell, and the main problem they had. Of course, they got lots of lots of data, but are unable to find the right data. They need to work from all over the place. And totally >>Went to real, probably tried to solve is how that person working exploration could find their proper date, not just a day, but also the date you really needed that we did probably talked about his summer 2017. And we said, okay, they don't maybe see this moving forward is to start pulling that data into a single data platform. And that, that was at the time that we called it as the, you, the subsurface data universe in there was about the shell name was so in, in January, 2018, we started a project with Amazon to start grating a co fricking that building, that Stu environment that subserve the universe, so that single data level to put all your exploration and Wells data into that single environment that was intent. And every cent, um, already in March of that same year, we said, well, from Michelle point of view, we will be far better off if we could make this an industry solution and not just a shelf sluice, because Shelby, Shelby, if you can make an industry solution where people are developing applications for it, it also is far better than for shell to say we haven't shell special solution because we don't make money out of how we start a day that we can make money out of it. >>We have access to the data, we can explore the data. So storing the data we should do as efficiently possibly can. So we monitor, we reach out to about eight or nine other large, uh, or I guess operators like the economics, like the tutorials, like the chefs of this world and say, Hey, we inshallah doing this. Do you want to join this effort? And to our surprise, they all said, yes. And then in September, 2018, we had our kickoff meeting with your open group where we said, we said, okay, if you want to work together with lots of other companies, we also need to look at okay, how, how we organize that. Or if you started working with lots of large companies, you need to have some legal framework around some framework around it. So that's why we went to the open group and say, okay, let's, let's form the old forum as we call it at the time. So it's September, 2080, where I did a Galleria in Houston, but the kickoff meeting for the OT four with about 10 members at the time. So there's just over two years ago, we started an exercise for me called ODU, uh, kicked it off. Uh, and so that's really them will be coming from and how we've got there. Also >>The origin story. Um, what, so what digging a little deeper there? What were some of the things you were trying to achieve with the OSU? >>Well, a couple of things we've tried to achieve with you, um, first is really separating data from applications for what is, what is the biggest problem we have in the subsurface space that the data and applications are all interlinked tied together. And if, if you have them and a new company coming along and say, I have this new application and is access to the data that is not possible because the data often interlinked with the application. So the first thing we did is really breaking the link between the application, the data out as those levels, the first thing we did, secondly, put all the data to a single data platform, take the silos out what was happening in the sub-service space and know they got all the data in what we call silos in small little islands out there. So what we're trying to do is first break the link to great, great. >>They put the data single day, the bathroom, and the third part, put a standard layer on top of that, it's an API layer on top to create a platform. So we could create an ecosystem out of companies to start a valving shop application on top of dev data platform across you might have a data platform, but you're only successful. If you have a rich ecosystem of people start developing applications on top of that. And then you can export the data like small companies, last company, university, you name it, we're getting after create an ecosystem out there. So the three things were as was first break, the link between application data, just break it and put data at the center and also make sure that data, this data structure would not be managed by one company. It would only be met. It will be managed the data structures by the ODI forum. Secondly, then put a data, a single data platform certainly then has an API layer on top and then create an ecosystem. Really go for people, say, please start developing applications because now you have access to the data or the data no longer linked to somebody whose application was all freely available, but an API layer that was, that was all September, 2018, more or less >>To hear a little bit. Can you talk a little bit about some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? Yeah, absolutely. And this whole thing is Johann said started with a challenge that was really brought out at shell. The challenges that geoscientists spend up to 70% of their time looking for data. I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out how we could address that one problem, we worked together to really understand the root cause of these challenges and working backwards from that use case OSU and OSU on AWS has really enabled customers to create solutions that span, not just this in particular problem, but can really scale to be inclusive of the entire energy value chain and deliver value from these use cases to the energy industry and beyond. >>Thank you, Lee, >>Uh, Johann. So talk a little bit about Accenture's cloud first approach and how it has, uh, helped shell work faster and better with it. >>Well, of course, access a cloud first approach only works together. It's been an Amazon environment, AWS environment. So we really look at, uh, at, at Accenture and others up together helping shell in this space. Now the combination of the two is where we're really looking at, uh, where access of course can be increased knowledge student to that environment operates support knowledge to do an environment. And of course, Amazon will be doing that to this environment that underpinning their services, et cetera. So, uh, we would expect a combination, a lot of goods when we started rolling out and put in production, the old you are three and four because we are anus. Then when release feed comes to the market in Q1 next year of ODU, when he started going to Audi production inside shell, but as the first release, which is ready for prime time production across an enterprise will be released just before Christmas, last year when he's still in may of this year. But really three is the first release we want to use for full scale production deployment inside shell, and also all the operators around the world. And there is one Amazon, sorry, at that one. Um, extensive can play a role in the ongoing, in the, in deployment building up, but also support environment. >>So one of the other things that we talk a lot about here on the cube is sustainability. And this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSD you, uh, help organizations become, how is this a greener solution for companies? >>Well, first he make it's a greatest solution because you start making a much more efficient use of your resources. is already an important one. The second thing we're doing is also, we started with ODU in framers, in the oil and gas space in the expert development space. We've grown, uh, OTU in our strategy, we've grown. I was, you know, also do an alternative energy sociology. We'll all start supporting next year. Things like solar farms, wind farms, uh, the, the dermatomal environment hydration. So it becomes an and, and an open energy data platform, not just what I want to get into steep that's for new industry, any type of energy industry. So our focus is to create, bring the data of all those various energy data sources to get me to a single data platform you can to use AI and other technology on top of that, to exploit the data, to beat again into a single data platform. >>Liz, I want to ask you about security because security is, is, is such a big concern when it comes to data. How secure is the data on OSD? You, um, actually, can I talk, can I do a follow up on this sustainability talking? Oh, absolutely. By all means. I mean, I want to interject though security is absolutely our top priority. I don't mean to move away from that, but with sustainability, in addition to the benefits of the OSU data platform, when a company moves from on-prem to the cloud, they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical data center. Now, a recent study by four 51 research found that AWS is infrastructure is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to higher, um, server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases for 51 found that AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSU are working to support our customers is they seek to better understand their workflows and make their legacy businesses less carbon intensive. >>That's that's incorrect. Those are those statistics are incredible. Do you want to talk a little bit now about security? Absolutely. Security will always be AWS is top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy. There are the security requirements for the military global banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build an operate each of our regions. So that customers benefit from the only commercial cloud that's hat hits service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features as well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. Johann, I want you to talk a little bit about how OSD you can be used today. Does it only handle subsurface data? >>Uh, today it's Honda's subserves or Wells data. We got to add to that production around the middle of next year. That means that the whole upstate business. So we've got goes from exploration all the way to production. You've made it together into a single data platform. So production will be added around Q3 of next year. Then a principal. We have a difficult, the elder data that single environment, and we want to extend it then to other data sources or energy sources like solar farms, wind farms, uh, hydrogen, hydro, et cetera. So we're going to add a whore, a whole list of audit day energy source to them and be all the data together into a single data club. So we move from an all in guest data platform to an entity data platform. That's really what our objective is because the whole industry, if you look it over, look at our competition or moving in that same two acts of quantity of course, are very strong in oil and gas, but also increased the, got into other energy sources like, like solar, like wind, like th like highly attended, et cetera. So we would be moving exactly what it's saying, method that, that, that, that the whole OSU can't really support at home. And as a spectrum of energy sources, >>Of course, and Liz and Johan. I want you to close this out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSD. We'll start with you, Liz, what do you, what do you see as the future holding for this platform? Um, honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers, wherever their OSU journeys, take them, whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond, but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges, Johann first, nobody can look at any more nowadays, especially 10 years, but our objective is really in the next five years, you will become the key backbone for energy companies for store your data intelligence and optimize the whole supply energy supply chain, uh, in this world Johan Krebbers Liz Dennett. Thank you so much for coming on the cube virtual. Thank you. I'm Rebecca Knight stay tuned for more of our coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight today we're welcoming back to Cuba alum. We have Kishor Dirk. He is the Accenture senior managing director cloud first global services lead. Welcome back to the show Kishore. Thank you very much. Nice to meet again. And, uh, Tristan moral horse set. He is the managing director, Accenture cloud first North American growth. Welcome back to you to Tristin. Great to be back in grapes here again, Rebecca. Exactly. Even in this virtual format, it is good to see your faces. Um, today we're going to be talking about my NAB and green cloud advisor capability. Kishor I want to start with you. So my NAB is a platform that is really celebrating its first year in existence. Uh, November, 2019 is when Accenture introduced it. Uh, but it's, it has new relevance in light of this global pandemic that we are all enduring and suffering through. Tell us a little bit about the lineup platform, what it is that cloud platform to help our clients navigate the complexity of cloud and cloud decisions and to make it faster. And obviously, you know, we have in the cloud, uh, you know, with >>The increased relevance and all the, especially over the last few months with the impact of COVID crisis and exhibition of digital transformation, you know, we are seeing the transformation of the exhibition to cloud much faster. This platform that you're talking about has enabled hardened 40 clients globally across different industries. You identify the right cloud solution, navigate the complexity, provide a cloud specific solution simulate for our clients to meet that strategy business needs. And the clients are loving it. >>I want to go to you now trust and tell us a little bit about how my nav works and how it helps companies make good cloud choice. >>Yeah, so Rebecca, we we've talked about cloud is, is more than just infrastructure and that's what mine app tries to solve for it. It really looks at a variety of variables, including infrastructure operating model and fundamentally what clients' business outcomes, um, uh, our clients are, are looking for and, and identifies the optimal solution for what they need. And we assign this to accelerate. And we mentioned that the pandemic, one of the big focus now is to accelerate. And so we worked through a three-step process. The first is scanning and assessing our client's infrastructure, their data landscape, their application. Second, we use our automated artificial intelligence engine to interact with. We have a wide variety and library of, uh, collective plot expertise. And we look to recommend what is the enterprise architecture and solution. And then third, before we live with our clients, we look to simulate and test this scaled up model. And the simulation gives our clients a way to see what cloud is going to look like, feel like and how it's going to transform their business before they go there. >>Tell us a little bit about that in real life. Now as a company, so many of people are working remotely having to collaborate, uh, not in real life. How is that helping them right now? >>So, um, the, the pandemic has put a tremendous strain on systems, uh, because of the demand on those systems. And so we talk about resiliency. We also now need to collaborate across data across people. Um, I think all of us are calling from a variety of different places where our last year we were all at the VA cube itself. Um, and, and cloud technologies such as teams, zoom that we're we're leveraging now has fundamentally accelerated and clients are looking to onboard this for their capabilities. They're trying to accelerate their journey. They realize that now the cloud is what is going to become important for them to differentiate. Once we come out of the pandemic and the ability to collaborate with their employees, their partners, and their clients through these systems is becoming a true business differentiator for our clients. >>Keisha, I want to talk with you now about my navs multiple capabilities, um, and helping clients design and navigate their cloud journeys. Tell us a little bit about the green cloud advisor capability and its significance, particularly as so many companies are thinking more deeply and thoughtfully about sustainability. >>Yes. So since the launch of my NAB, we continue to enhance capabilities for our clients. One of the significant, uh, capabilities that we have enabled is the being or advisor today. You know, Rebecca, a lot of the businesses are more environmentally aware and are expanding efforts to decrease power consumption, uh, and obviously carbon emissions and, uh, and run a sustainable operations across every aspect of the enterprise. Uh, as a result, you're seeing an increasing trend in adoption of energy, efficient infrastructure in the global market. And one of the things that we did, a lot of research we found out is that there's an ability to influence our client's carbon footprint through a better cloud solution. And that's what we internalize, uh, brings to us, uh, in, in terms of a lot of the client connotation that you're seeing in Europe, North America and others. Lot of our clients are accelerating to a green cloud strategy to unlock greater financial societal and environmental benefit, uh, through obviously cloud-based circular, operational, sustainable products and services. That is something that we are enhancing my now, and we are having active client discussions at this point of time. >>So Tristan, tell us a little bit about how this capability helps clients make greener decisions. >>Yeah. Um, well, let's start about the investments from the cloud providers in renewable and sustainable energy. Um, they have most of the hyperscalers today, um, have been investing significantly on data centers that are run on renewable energy, some incredibly creative constructs on the, how, how to do that. And sustainability is there for a key, um, key item of importance for the hyperscalers and also for our clients who now are looking for sustainable energy. And it turns out this marriage is now possible. I can, we marry the, the green capabilities of the cloud providers with a sustainability agenda of our clients. And so what we look into the way the mind works is it looks at industry benchmarks and evaluates our current clients, um, capabilities and carpet footprint leveraging their existing data centers. We then look to model from an end-to-end perspective, how the, their journey to the cloud leveraging sustainable and, um, and data centers with renewable energy. We look at how their solution will look like and, and quantify carbon tax credits, um, improve a green index score and provide quantifiable, um, green cloud capabilities and measurable outcomes to our clients, shareholders, stakeholders, clients, and customers. Um, and our green plot advisers sustainability solutions already been implemented at three clients. And in many cases in two cases has helped them reduce the carbon footprint by up to 400% through migration from their existing data center to green cloud. Very, very, >>That is remarkable. Now tell us a little bit about the kinds of clients. Is this, is this more interesting to clients in Europe? Would you say that it's catching on in the United States? Where, what is the breakdown that you're seeing right now? >>Sustainability is becoming such a global agenda and we're seeing our clients, um, uh, tie this and put this at board level, um, uh, agenda and requirements across the globe. Um, Europe has specific constraints around data sovereignty, right, where they need their data in country, but from a green, a sustainability agenda, we see clients across all our markets, North America, Europe in our growth markets adopt this. And we have seen case studies and all three months, >>Kesha. I want to bring you back into the conversation. Talk a little bit about how MindUP ties into Accenture's cloud first strategy, your Accenture's CEO, Julie Sweet, um, has talked about post COVID leadership, requiring every business to become a cloud first business. Tell us a little bit about how this ethos is in Accenture and how you're sort of looking outward with it too. >>So Rebecca mine is the launch pad, uh, to a cloud first transformation for our clients. Uh, Accenture, see your jewelry suite, uh, shared the Accenture cloud first and our substantial investment demonstrate our commitment and is delivering greater value for our clients when they need it the most. And with the digital transformation requiring cloud at scale, you know, we're seeing that in the post COVID leadership, it requires that every business should become a cloud business. And my nap helps them get there by evaluating the cloud landscape, navigating the complexity, modeling architecting and simulating an optimal cloud solution for our clients. And as Justin was sharing a greener cloud. >>So Tristan, talk a little bit more about some of the real life use cases in terms of what are we, what are clients seeing? What are the results that they're having? >>Yes. Thank you, Rebecca. I would say two key things right around my notes. The first is the iterative process. Clients don't want to wait, um, until they get started, they want to get started and see what their journey is going to look like. And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need to move to cloud very quickly. And my nav is there to do that. So how do we do that? First is generating the business cases. Clients need to know in many cases that they have a business case by business case, we talk about the financial benefits, as well as the business outcomes, the green, green clot impact sustainability impacts with minus. We can build initial recommendations using a basic understanding of their environment and benchmarks in weeks versus months with indicative value savings in the millions of dollars arranges. >>So for example, very recently, we worked with a global oil and gas company, and in only two weeks, we're able to provide an indicative savings where $27 million over five years, this enabled the client to get started, knowing that there is a business case benefit and then iterate on it. And this iteration is, I would say the second point that is particularly important with my nav that we've seen in bank of clients, which is, um, any journey starts with an understanding of what is the application landscape and what are we trying to do with those, these initial assessments that used to take six to eight weeks are now taking anywhere from two to four weeks. So we're seeing a 40 to 50% reduction in the initial assessment, which gets clients started in their journey. And then finally we've had discussions with all of the hyperscalers to help partner with Accenture and leverage mine after prepared their detailed business case module as they're going to clients. And as they're accelerating the client's journey, so real results, real acceleration. And is there a journey? Do I have a business case and furthermore accelerating the journey once we are by giving the ability to work in iterative approach. >>I mean, it sounds as though that the company that clients and and employees are sort of saying, this is an amazing time savings look at what I can do here in, in so much in a condensed amount of time, but in terms of getting everyone on board, one of the things we talked about last time we met, uh, Tristin was just how much, uh, how one of the obstacles is getting people to sign on and the new technologies and new platforms. Those are often the obstacles and struggles that companies face. Have you found that at all? Or what is sort of the feedback that you're getting? >>Yeah, sorry. Yes. We clearly, there are always obstacles to a cloud journey. If there were an obstacles, all our clients would be, uh, already fully in the cloud. What man I gives the ability is to navigate through those, to start quickly. And then as we identify obstacles, we can simulate what things are going to look like. We can continue with certain parts of the journey while we deal with that obstacle. And it's a fundamental accelerator. Whereas in the past one, obstacle would prevent a class from starting. We can now start to address the obstacles one at a time while continuing and accelerating the contrary. That is the fundamental difference. >>Kishor I want to give you the final word here. Tell us a little bit about what is next for Accenture might have and what we'll be discussing next year at the Accenture executive summit, >>Rebecca, we are continuously evolving with our client needs and reinventing reinventing for the future. Well, mine has been toward advisor. Our plan is to help our clients reduce carbon footprint and again, migrate to a green cloud. Uh, and additionally, we're looking at, you know, two capabilities, uh, which include sovereign cloud advisor, uh, with clients, especially in, in Europe and others are under pressure to meet, uh, stringent data norms that Kristen was talking about. And the sovereign cloud advisor helps organization to create an architecture cloud architecture that complies with the green. Uh, I would say the data sovereignty norms that is out there. The other element is around data to cloud. We are seeing massive migration, uh, for, uh, for a lot of the data to cloud. And there's a lot of migration hurdles that come within that. Uh, we have expanded mine app to support assessment capabilities, uh, for, uh, assessing applications, infrastructure, but also covering the entire state, including data and the code level to determine the right cloud solution. So we are, we are pushing the boundaries on what mine app can do with mine. Have you created the ability to take the guesswork out of cloud, navigate the complexity? We are rolling risks costs, and we are, you know, achieving client's static business objectives while building a sustainable alerts with being cloud, >>Any platform that can take some of the guesswork out of the future. I am I'm on board with thank you so much, Tristin and Kishore. This has been a great conversation. Stay tuned for more of the cubes coverage of the Accenture executive summit. I'm Rebecca Knight.

Published Date : Dec 1 2020

SUMMARY :

It's the cube with digital coverage Welcome to cube three 60 fives coverage of the Accenture executive summit. Thanks for having me here. impact of the COVID-19 pandemic has been, what are you hearing from clients? you know, various facets, you know, um, first and foremost, to this reasonably okay, and are, you know, launching to So you just talked about the widening gap. all the changes the pandemic has brought to them. in the cloud that we are going to see. Can you tell us a little bit more about what this strategy entails? all of the systems under which they attract need to be liberated so that you could drive now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, That is their employees, uh, because you do, across every department, I'm the agent of this change is going to be the employees or weapon, So how are you helping your clients, And that is again, the power of cloud. And the power of cloud is to get all of these capabilities from outside that employee, the employee will be more engaged in his or her job and therefore And this is, um, you know, no more true than how So at Accenture, you have long, long, deep Stan, sorry, And in fact, in the cloud world, it was one of the first, um, And one great example is what we are doing with Takeda, uh, billable, So all of these things that we will do Yeah, the future to the next, you know, base camp, as I would call it to further this productivity, And the evolution that is going to happen where, you know, the human grace of mankind, I genuinely believe that cloud first is going to be in the forefront of that change It's the cube with digital coverage I want to start by asking you what it is that we mean when we say green cloud, magnitude of the problem that is out there and how do we pursue a green approach. Them a lot of questions, the decision to make, uh, this particular, And, uh, you know, the, obviously the companies have to unlock greater financial How do you partner and what is your approach in terms of helping them with their migrations? uh, you know, from a few manufacturers hand sanitizers, and to answer it role there, uh, you know, from, in terms of our clients, you know, there are multiple steps And in the third year and another 3 million analytics costs that are saved through right-sizing Instead of it, we practice what we preach, and that is something that we take it to heart. We know that conquering this pandemic is going to take a coordinated And it's about a group of global stakeholders cooperating to simultaneously manage the uh, in, in UK to build, uh, uh, you know, uh, Microsoft teams in What do you see as the different, the financial security or agility benefits to cloud. And obviously the ecosystem partnership that we have that We, what, what do you think the next 12 to 24 months? And we all along with Accenture clients will win. Thank you so much. It's the cube with digital coverage of AWS reinvent executive And what happens when you bring together the scientific and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and, And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. And I think that, you know, that's going to help us make faster, better decisions. Um, and so I think with that, you know, there's a few different, How do we re-imagine that, you know, how do ideas go from getting tested So Arjun, I want to bring you into this conversation a little bit, let let's delve into those a bit. It was, uh, something that, you know, we had all to do differently. And maybe the third thing I would say is this one team And I think if you really think about what he's talking about, Because the old ways of thinking where you've got application people and infrastructure, How will their experience of work change and how are you helping re-imagine and And it's something that, you know, I think we all have to think a lot about, I mean, And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are Uh, and so I think that that's, you know, one, one element that, uh, can be considered. or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently the customer obsession and this idea of innovating much more quickly. and Carl mentioned some of the things that, you know, partner like AWS can bring to the table is we talk a lot about builders, And it's not just the technical people or the it people who are And Accenture's, and so we were able to bring that together. And so we chose, you know, uh, with our focus on innovation that when people think about cloud, you know, you always think about infrastructure technology. And thank you for tuning into the cube. It's the cube with digital coverage So we are going to be talking and also what were some of the challenges that you were grappling with prior to this initiative? Um, so the reason we sort of embarked um, you know, certainly as a, as an it leader and sort of my operational colleagues, What is the art of the possible, can you tell us a little bit about why you chose the public sector that, you know, there are many rules and regulations, uh, quite rightly as you would expect Matthew, I want to bring you into the conversation a little bit here. to bring in a number of the different themes that we have say, cloud teams, security teams, um, I mean, so much of this is about embracing comprehensive change to experiment and innovate and and the outcomes they're looking to achieve rather than simply focusing on a long list of requirements, It's not always a one size fits all. um, that is gonna update before you even get that. So to give you a little bit of, of context, when we, um, started And the pilot was so successful. And I think just parallel to that is the quality of our, because we had a lot of data, That kind of return on investment because what you were just describing with all the steps that we needed Um, but all the, you know, the minutes here and there certainly add up Have you seen any changes Um, but you can see the step change that is making in each aspect to the organization, And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain You know, we had lots of workshops and seminars where we all talk about, you know, you know, to see the stat change, you know, and, and if we, if we have any issues now it's literally, when you are trying to get everyone on board for this kind of thing? The solution itself is, um, you know, extremely large and, um, I want to hear, where do you go from here? crazy, but because it's apparently not that simple, but, um, you know, And you are watching the cube stay tuned for more of the cubes coverage of the AWS in particular has brought it together because you know, COVID has been the accelerant So number of years back, we looked at kind of our infrastructure and our landscape trying to figure uh, you know, start to deliver bit by bit incremental progress, uh, to get to the, of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually I want to just real quick, a redirect to you and say, you know, if all the people said, Oh yeah, And, um, you know, Australia, we had to live through Bush fires You know, we're going to get the city, you get a minute on specifically, but from your perspective, uh, Douglas, to hours and days, and truly allowed us to, we had to, you know, VJ things, And what specifically did you guys do at Accenture and how did it all come together? the seminars and, and, uh, you know, the deep three steps from uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment How did you address your approach to the cloud and what was your experience? And then building upon it, and then, you know, partnering with Accenture allows because the kind of, uh, you know, digital transformation, cloud transformation, learnings, um, that might different from the expectation we all been there, Hey, you know, It's, it's getting that last bit over the line and making sure that you haven't invested in the future hundred percent of the time, they will say yes until you start to lay out to them, okay, You know, the old expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, Um, you know, that's all stood up on AWS and is a significant portion of And I think our next big step is going to be obviously, uh, with a company like Accenture as well, you get combinations of the technology and the skills and the So obviously, you know, lion's like an AWS, but, you know, a lot of people kind of going through the same process, knowing what you guys know now, And we had all of our people working remotely, um, within, uh, you know, effectively one business day. and in the traditional world, you would just go out and buy more servers than you need. And if it's not right, you pump it up a little bit when, when all of your metrics and so on, And this is really about you guys when they're actually set up for growth, um, and actually allows, you know, lying to achievements I really appreciate you coming. to figure out how we unlock that value, um, you know, drive our costs down efficiency, to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with There's got to say like e-learning squares, right, for me around, you know, It is tough, but, uh, uh, you know, you got to get started on it. It's the cube with digital coverage of Thank you so much for coming on the show, Johan you're welcome. Yeah, the ethical back a couple of years, we started shoving 2017 where we it also is far better than for shell to say we haven't shell special solution because we don't So storing the data we should do What were some of the things you were trying to achieve with the OSU? So the first thing we did is really breaking the link between the application, And then you can export the data like small companies, last company, standpoint in terms of what you were trying to achieve with this? uh, helped shell work faster and better with it. a lot of goods when we started rolling out and put in production, the old you are three and four because we are So one of the other things that we talk a lot about here on the cube is sustainability. I was, you know, also do an alternative energy sociology. found that AWS performs the same task with an 88% lower So that customers benefit from the only commercial cloud that's hat hits service offerings and the whole industry, if you look it over, look at our competition or moving in that same two acts of quantity of course, our objective is really in the next five years, you will become the key It's the cube with digital coverage And obviously, you know, we have in the cloud, uh, you know, with and exhibition of digital transformation, you know, we are seeing the transformation of I want to go to you now trust and tell us a little bit about how my nav works and how it helps And then third, before we live with our clients, having to collaborate, uh, not in real life. They realize that now the cloud is what is going to become important for them to differentiate. Keisha, I want to talk with you now about my navs multiple capabilities, And one of the things that we did, a lot of research we found out is that there's an ability to influence So Tristan, tell us a little bit about how this capability helps clients make greener And so what we look into the way the Would you say that it's catching on in the United States? And we have seen case studies and all I want to bring you back into the conversation. And with the digital transformation requiring cloud at scale, you know, we're seeing that in And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need So for example, very recently, we worked with a global oil and gas company, Have you found that at all? What man I gives the ability is to navigate through those, to start quickly. Kishor I want to give you the final word here. and we are, you know, achieving client's static business objectives while I am I'm on board with thank you so much,

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AWS Executive Summit 2020


 

>>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to cube three 60 fives coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight. Today we are joined by a cube alum, Karthik, Lorraine. He is Accenture senior managing director and lead Accenture cloud. First, welcome back to the show Karthik. >>Thank you. Thanks for having me here. >>Always a pleasure. So I want to talk to you. You are an industry veteran, you've been in Silicon Valley for decades. Um, I want to hear from your perspective what the impact of the COVID-19 pandemic has been, what are you hearing from clients? What are they struggling with? What are their challenges that they're facing day to day? >>I think, um, COVID-19 is being a eye-opener from, you know, various facets, you know, um, first and foremost, it's a, it's a hell, um, situation that everybody's facing, which is not just, uh, highest economic bearings to it. It has enterprise, um, an organization with bedding to it. And most importantly, it's very personal to people, um, because they themselves and their friends, family near and dear ones are going through this challenge, uh, from various different dimension. But putting that aside, when you come to it from an organization enterprise standpoint, it has changed everything well, the behavior of organizations coming together, working in their campuses, working with each other as friends, family, and, uh, um, near and dear colleagues, all of them are operating differently. So that's what big change to get things done in a completely different way, from how they used to get things done. >>Number two, a lot of things that were planned for normal scenarios, like their global supply chain, how they interact with their client customers, how they go innovate with their partners on how that employees contribute to the success of an organization at all changed. And there are no data models that give them a hint of something like this for them to be prepared for this. So we are seeing organizations, um, that have adapted to this reasonably okay, and are, you know, launching to innovate faster in this. And there are organizations that have started with struggling, but are continuing to struggle. And the gap between the leaders and legs are widening. So this is creating opportunities in a different way for the leaders, um, with a lot of pivot their business, but it's also creating significant challenge for the lag guides, uh, as we defined in our future systems research that we did a year ago, uh, and those organizations are struggling further. So the gap is actually widening. >>So you just talked about the widening gap. I've talked about the tremendous uncertainty that so many companies, even the ones who have adapted reasonably well, uh, in this, in this time, talk a little bit about Accenture cloud first and why, why now? >>I think it's a great question. Um, we believe that for many of our clients COVID-19 has turned, uh, cloud from an experimentation aspiration to an origin mandate. What I mean by that is everybody has been doing something on the other end cloud. There's no company that says we don't believe in cloud are, we don't want to do cloud. It was how much they did in cloud. And they were experimenting. They were doing the new things in cloud, but they were operating a lot of their core business outside the cloud or not in the cloud. Those organizations have struggled to operate in this new normal, in a remote fashion, as well as, uh, their ability to pivot to all the changes the pandemic has brought to them. But on the other hand, the organizations that had a solid foundation in cloud were able to collect faster and not actually gone into the stage of innovating faster and driving a new behavior in the market, new behavior within their organization. >>So we are seeing that spend to make is actually fast-forwarded something that we always believed was going to happen. This, uh, uh, moving to cloud over the next decade is fast forward it to happen in the next three to five years. And it's created this moment where it's a once in an era, really replatforming of businesses in the cloud that we are going to see. And we see this moment as a cloud first moment where organizations will use cloud as the, the, the canvas and the foundation with which they're going to reimagine their business after they were born in the cloud. Uh, and this requires a whole new strategy. Uh, and as Accenture, we are getting a lot in cloud, but we thought that this is the moment where we bring all of that, gave him a piece together because we need a strategy for addressing, moving to cloud are embracing cloud in a holistic fashion. And that's what Accenture cloud first brings together a holistic strategy, a team that's 70,000 plus people that's coming together with rich cloud skills, but investing to tie in all the various capabilities of cloud to Delaware, that holistic strategy to our clients. So I want you to >>Delve into a little bit more about what this strategy actually entails. I mean, it's clearly about embracing change and being willing to experiment and having capabilities to innovate. Can you tell us a little bit more about what this strategy entails? >>Yeah. The reason why we say that as a need for strategy is like I said, cloud is not new. There's almost every customer client is doing something with the cloud, but all of them have taken different approaches to cloud and different boundaries to cloud. Some organizations say, I just need to consolidate my multiple data centers to a small data center footprint and move the nest to cloud. Certain other organizations say that well, I'm going to move certain workloads to cloud. Certain other organizations said, well, I'm going to build this Greenfield application or workload in cloud. Certain other said, um, I'm going to use the power of AI ML in the cloud to analyze my data and drive insights. But a cloud first strategy is all of this tied with the corporate strategy of the organization with an industry specific cloud journey to say, if in this current industry, if I were to be reborn in the cloud, would I do it in the exact same passion that I did in the past, which means that the products and services that they offer need to be the matching, how they interact with that customers and partners need to be revisited, how they bird and operate their IP systems need to be the, imagine how they unearthed the data from all of the systems under which they attract need to be liberated so that you could drive insights of cloud. >>First strategy hands is a corporate wide strategy, and it's a C-suite responsibility. It doesn't take the ownership away from the CIO or CIO, but the CIO is, and CDI was felt that it was just their problem and they were to solve it. And everyone as being a customer, now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's agenda, where probably the CDI is the instrument to execute that that's a holistic cloud-first strategy >>And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, as you were saying, this idea of being reborn in the cloud. So now how do I think about things? How do I communicate? How do I collaborate? How do I get done? What I need to get done. Talk a little bit about how this has changed, the way you support your clients and how Accenture cloud first is changing your approach to cloud services. >>Wonderful. Um, you know, I did not color one very important aspect in my previous question, but that's exactly what you just asked me now, which is to do all of this. I talked about all of the variables, uh, an organization or an enterprise is going to go through, but the good part is they have one constant. And what is that? That is their employees, uh, because you do, the employees are able to embrace this change. If they are able to, uh, change them, says, pivot them says retool and train themselves to be able to operate in this new cloud. First one, the ability to reimagine every function of the business would be happening at speed. And cloud first approach is to do all of this at speed, because innovation is deadly proposed there, do the rate of probability on experimentation. You need to experiment a lot for any kind of experimentation. >>There's a probability of success. Organizations need to have an ability and a mechanism for them to be able to innovate faster for which they need to experiment a lot, the more the experiment and the lower cost at which they experiment is going to help them experiment a lot. And they experiment demic speed, fail fast, succeed more. And hence, they're going to be able to operate this at speed. So the cloud-first mindset is all about speed. I'm helping the clients fast track that innovation journey, and this is going to happen. Like I said, across the enterprise and every function across every department, I'm the agent of this change is going to be the employees or weapon, race, this change through new skills and new grueling and new mindset that they need to adapt to. >>So Karthik what you're describing it, it sounds so exciting. And yet for a pandemic wary workforce, that's been working remotely that may be dealing with uncertainty if for their kid's school and for so many other aspects of their life, it sounds hard. So how are you helping your clients, employees get onboard with this? And because the change management is, is often the hardest part. >>Yeah, I think it's, again, a great question. A bottle has only so much capacity. Something got to come off for something else to go in. That's what you're saying is absolutely right. And that is again, the power of cloud. The reason why cloud is such a fundamental breakthrough technology and capability for us to succeed in this era, because it helps in various forms. What we talked so far is the power of innovation that can create, but cloud can also simplify the life of the employees in an enterprise. There are several activities and tasks that people do in managing that complex infrastructure, complex ID landscape. They used to do certain jobs and activities in a very difficult underground about with cloud has simplified. And democratised a lot of these activities. So that things which had to be done in the past, like managing the complexity of the infrastructure, keeping them up all the time, managing the, um, the obsolescence of the capabilities and technologies and infrastructure, all of that could be offloaded to the cloud. >>So that the time that is available for all of these employees can be used to further innovate. Every organization is going to spend almost the same amount of money, but rather than spending activities, by looking at the rear view mirror on keeping the lights on, they're going to spend more money, more time, more energy, and spend their skills on things that are going to add value to their organization. Because you, every innovation that an enterprise can give to their end customer need not come from that enterprise. The word of platform economy is about democratising innovation. And the power of cloud is to get all of these capabilities from outside the four walls of the enterprise, >>It will add value to the organization, but I would imagine also add value to that employee's life because that employee, the employee will be more engaged in his or her job and therefore bring more excitement and energy into her, his or her day-to-day activities too. >>Absolutely. Absolutely. And this is, this is a normal evolution we would have seen everybody would have seen in their lives, that they keep moving up the value chain of what activities that, uh, gets performed buying by those individuals. And this is, um, you know, no more true than how the United States, uh, as an economy has operated where, um, this is the power of a powerhouse of innovation, where the work that's done inside the country keeps moving up to value chain. And, um, us leverage is the global economy for a lot of things that is required to power the United States and that global economic, uh, phenomenon is very proof for an enterprise as well. There are things that an enterprise needs to do them soon. There are things an employee needs to do themselves. Um, but there are things that they could leverage from the external innovation and the power of innovation that is coming from technologies like cloud. >>So at Accenture, you have long, long, deep Stan, sorry, you have deep and long-standing relationships with many cloud service providers, including AWS. How does the Accenture cloud first strategy, how does it affect your relationships with those providers? >>Yeah, we have great relationships with cloud providers like AWS. And in fact, in the cloud world, it was one of the first, um, capability that we started about years ago, uh, when we started developing these capabilities. But five years ago, we hit a very important milestone where the two organizations came together and said that we are forging a pharma partnership with joint investments to build this partnership. And we named that as a Accenture, AWS business group ABG, uh, where we co-invest and brought skills together and develop solutions. And we will continue to do that. And through that investment, we've also made several acquisitions that you would have seen in the recent times, like, uh, an invoice and gecko that we made acquisitions in in Europe. But now we're taking this to the next level. What we are saying is two cloud first and the $3 billion investment that we are bringing in, uh, through cloud-first. >>We are going to make specific investment to create unique joint solution and landing zones foundation, um, cloud packs with which clients can accelerate their innovation or their journey to cloud first. And one great example is what we are doing with Takeda, uh, billable, pharmaceutical giant, um, between we've signed a five-year partnership. And it was out in the media just a month ago or so, where we are, the two organizations are coming together. We have created a partnership as a power of three partnership, where the three organizations are jointly hoarding hats and taking responsibility for the innovation and the leadership position that Takeda wants to get to with this. We are going to simplify their operating model and organization by providing and flexibility. We're going to provide a lot more insights. Tequila has a 230 year old organization. Imagine the amount of trapped data and intelligence that is there. >>How about bringing all of that together with the power of AWS and Accenture and Takeda to drive more customer insights, um, come up with breakthrough R and D uh, accelerate clinical trials and improve the patient experience using AI ML and edge technologies. So all of these things that we will do through this partnership with joined investment from Accenture cloud first, as well as partner like AWS, so that Takeda can realize their gain. And, uh, their senior actually made a statement that five years from now, every ticket an employee will have an AI assistant. That's going to make that beginner employee move up the value chain on how they contribute and add value to the future of tequila with the AI assistant, making them even more equipped and smarter than what they could be otherwise. >>So, one last question to close this out here. What is your future vision for, for Accenture cloud first? What are we going to be talking about at next year's Accenture executive summit? Yeah, the future >>Is going to be, um, evolving, but the part that is exciting to me, and this is, uh, uh, a fundamental belief that we are entering a new era of industrial revolution from industry first, second, and third industry. The third happened probably 20 years ago with the advent of Silicon and computers and all of that stuff that happened here in the Silicon Valley. I think the fourth industrial revolution is going to be in the cross section of, uh, physical, digital and biological boundaries. And there's a great article, um, in one economic forum that people, uh, your audience can Google and read about it. Uh, but the reason why this is very, very important is we are seeing a disturbing phenomenon that over the last 10 years are seeing a Blackwing of the, um, labor productivity and innovation, which has dropped to about 2.1%. When you see that kind of phenomenon over that longer period of time, there has to be breakthrough innovation that needs to happen to come out of this barrier and get to the next, you know, base camp, as I would call it to further this productivity, um, lack that we are seeing, and that is going to happen in the intersection of the physical, digital and biological boundaries. >>And I think cloud is going to be the connective tissue between all of these three, to be able to provide that where it's the edge, especially is good to come closer to the human lives. It's going to come from cloud. Yeah. Pick totally in your mind, you can think about cloud as central, either in a private cloud, in a data center or in a public cloud, you know, everywhere. But when you think about edge, it's going to be far reaching and coming close to where we live and maybe work and very, um, get entertained and so on and so forth. And there's good to be, uh, intervention in a positive way in the field of medicine, in the field of entertainment, in the field of, um, manufacturing in the field of, um, you know, mobility. When I say mobility, human mobility, people, transportation, and so on and so forth with all of this stuff, cloud is going to be the connective tissue and the vision of cloud first is going to be, uh, you know, blowing through this big change that is going to happen. And the evolution that is going to happen where, you know, the human grace of mankind, um, our person kind of being very gender neutral in today's world. Um, go first needs to be that beacon of, uh, creating the next generation vision for enterprises to take advantage of that kind of an exciting future. And that's why it, Accenture, are we saying that there'll be change as our, as our purpose? >>I genuinely believe that cloud first is going to be the forefront of that change agenda, both for Accenture as well as for the rest of the work. >>Excellent. Let there be changed. Indeed. Thank you so much for joining us Karthik. A pleasure I'm Rebecca Knight stay tuned for more of Q3 60 fives coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtual and our coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the power of three. And what happens when you bring together the scientific, how of a global bias biopharmaceutical powerhouse in Takeda, a leading cloud services provider in AWS, and Accenture's ability to innovate, execute, and deliver innovation. Joining me to talk about these things. We have Aaron, sorry. Arjan Beatty. He is the senior managing director and chairman of Accenture's diamonds leadership council. Welcome Arjun. Thank you, Karl hick. He is the chief digital and information officer at Takeda. >>What is your bigger, thank you, Rebecca >>And Brian Beau Han global director and head of the Accenture AWS business group at Amazon web services. Thanks so much for coming on. Thank you. So, as I said, we're talking today about this relationship between, uh, your three organizations. Carl, I want to talk with you. I know you're at the beginning of your cloud journey. What was the compelling reason? Why w why, why move to the cloud and why now? >>Yeah, no, thank you for the question. So, you know, as a biopharmaceutical leader, we're committed to bringing better health and a brighter future to our patients. We're doing that by translating science into some really innovative and life transporting therapies, but throughout, you know, we believe that there's a responsible use of technology, of data and of innovation. And those three ingredients are really key to helping us deliver on that promise. And so, you know, while I think a I'll call it, this cloud journey is already always been a part of our strategy. Um, and we've made some pretty steady progress over the last years with a number of I'll call it diverse approaches to the digital and AI. We just weren't seeing the impact at scale that we wanted to see. Um, and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and broaden that shift. >>And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. One of those has been certainly a number of the acquisitions we've made Shire, uh, being the most pressing example, uh, but also the global pandemic, both of those highlight the need for us to move faster, um, at the speed of cloud, ultimately. Uh, and so we started thinking outside of the box because it was taking us too long and we decided to leverage the strategic partner model. Uh, and it's giving us a chance to think about our challenges very differently. We call this the power of three, uh, and ultimately our focus is singularly on our patients. I mean, they're waiting for us. We need to get there faster. It can take years. And so I think that there is a focus on innovation at a rapid speed, so we can move ultimately from treating conditions to keeping people healthy. >>So as you are embarking on this journey, what are some of the insights you want to share about, about what you're seeing so far? >>Yeah, no, it's a great question. So, I mean, look, maybe right before I highlight some of the key insights, uh, I would say that, you know, with cloud now as the, as a launchpad for innovation, you know, our vision all along has been that in less than 10 years, we want every single to kid, uh, the associate or employee to be empowered by an AI assistant. And I think that, you know, that's going to help us make faster, better decisions. That'll help us, uh, fundamentally deliver transformative therapies and better experiences to, to that ecosystem, to our patients, to physicians, to payers, et cetera, much faster than we previously thought possible. Um, and I think that technologies like cloud and edge computing together with a very powerful I'll call it data fabric is going to help us to create this, this real-time, uh, I'll call it the digital ecosystem. >>The data has to flow ultimately seamlessly between our patients and providers or partners or researchers, et cetera. Uh, and so we've been thinking about this, uh, I'll call it weekly, call up sort of this pyramid, um, that helps us describe our vision. Uh, and a lot of it has to do with ultimately modernizing the foundation, modernizing and rearchitecting, the platforms that drive the company, uh, heightening our focus on data, which means that there's an accelerated shift towards, uh, enterprise data platforms and digital products. And then ultimately, uh, uh, uh, you know, really an engine for innovation sitting at the very top. Um, and so I think with that, you know, there's a few different, I'll call it insights that, you know, are quickly kind of come zooming into focus. I would say one is this need to collaborate very differently. Um, you know, not only internally, but you know, how do we define ultimately, and build a connected digital ecosystem with the right partners and technologies externally? >>I think the second component that maybe people don't think as much about, but, you know, I find critically important is for us to find ways of really transforming our culture. We have to unlock talent and shift the culture certainly as a large biopharmaceutical very differently. And then lastly, you've touched on it already, which is, you know, innovation at the speed of cloud. How do we re-imagine that? You know, how do ideas go from getting tested in months to kind of getting tested in days? You know, how do we collaborate very differently? Uh, and so I think those are three, uh, perhaps of the larger I'll call it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. >>So Arjun, I want to bring you into this conversation a little bit. Let's, let's delve into those a bit. Talk first about the collaboration, uh, that Carl was referencing there. How, how have you seen that? It is enabling, uh, colleagues and teams to communicate differently and interact in new and different ways? Uh, both internally and externally, as Carl said, >>No, thank you for that. And, um, I've got to give call a lot of credit because as we started to think about this journey, it was clear. It was a bold ambition was, uh, something that, you know, we had all to do differently. And so the concept of the power of three that Carl has constructed has become a label for us as a way to think about what are we going to do to collectively drive this journey forward. And to me, the unique ways of collaboration means three things. The first one is that, um, what is expected is that the three parties are going to come together and it's more than just the sum of our resources. And by that, I mean that we have to bring all of ourselves, all of our collective capabilities, as an example, Amazon has amazing supply chain capabilities. They're one of the best at supply chain. >>So in addition to resources, when we have supply chain innovations, uh, that's something that they're bringing in addition to just, uh, talent and assets, similarly for Accenture, right? We do a lot, uh, in the talent space. So how do we bring our thinking as to how we apply best practices for talent to this partnership? So, um, as we think about this, so that's, that's the first one, the second one is about shared success very early on in this partnership, we started to build some foundations and actually develop seven principles that all of us would look at as the basis for this success shared success model. And we continue to hold that sort of in the forefront, as we think about this collaboration. And maybe the third thing I would say is this one team mindset. So whether it's the three of our CEOs that get together every couple of months to think about, uh, this partnership, or it is the governance model that Carl has put together, which has all three parties in the governance and every level of leadership, we always think about this as a collective group so that we can keep that front and center. >>And what I think ultimately has enabled us to do is it's allowed us to move at speed, be more flexible. And ultimately all we're looking at the target the same way, the North side, the same way, >>Brian, about you, what have you observed and what are you thinking about in terms of how this is helping teams collaborate differently? Yeah, >>Absolutely. And RJ made some, some great points there. And I think if you really think about what he's talking about, it's that, that diversity of talent, diversity of skill and viewpoint and even culture, right? And so we see that in the power of three. And then I think if we drill down into what we see at Takeda and frankly Takeda was, was really, I think, pretty visionary and on their way here, right. And taking this kind of cross-functional approach and applying it to how they operate day to day. So moving from a more functional view of the world to more of a product oriented view of the world, right? So when you think about we're going to be organized around a product or a service or a capability that we're going to provide to our customers or our patients or donors in this case, it implies a different structure all to altogether and a different way of thinking, right? >>Because now you've got technical people and business experts and marketing experts all working together in this is sort of cross collaboration. And what's great about that is it's really the only way to succeed with cloud, right? Because the old ways of thinking where you've got application people and infrastructure, people in business, people is suboptimal, right? Because we can all access this tool as these capabilities and the best way to do that. Isn't across kind of a cross collaborative way. And so this is product oriented mindset. It's a keto was already on. I think it's allowed us to move faster. >>Carl, I want to go back to this idea of unlocking talent and culture. And this is something that both Brian and Arjun have talked about too. People are an essential part of their, at the heart of your organization. How will their experience of work change and how are you helping re-imagine and reinforce a strong organizational culture, particularly at this time when so many people are working remotely. >>Yeah. It's a great question. And it's something that, you know, I think we all have to think a lot about, I mean, I think, um, you know, driving this, this color, this, this digital and data kind of capability building, uh, it takes a lot of, a lot of thinking. So, I mean, there's a few different elements in terms of how we're tackling this one is we're recognizing, and it's not just for the technology organization or for those actors that, that we're innovating with, but it's really across all of the Qaeda where we're working through ways of raising what I'll call the overall digital leaders literacy of the organization, you know, what are the, you know, what are the skills that are needed almost at a baseline level, even for a global bio-pharmaceutical company and how do we deploy, I'll call it those learning resources very broadly. >>And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are very specialized skills that are needed. Uh, my organization is one of those. And so, you know, we're fostering ways in which, you know, we're very kind of quickly kind of creating, uh, avenues excitement for, for associates in that space. So one example specifically, as we use, you know, during these, uh, very much sort of remote, uh, sort of days, we, we use what we call global it meet days, and we set a day aside every single month and this last Friday, um, you know, we, we create during that time, it's time for personal development. Um, and we provide active seminars and training on things like, you know, robotic process automation, data analytics cloud, uh, in this last month we've been doing this for months and months now, but in his last month, more than 50% of my organization participated, and there's this huge positive shift, both in terms of access and excitement about really harnessing those new skills and being able to apply them. >>Uh, and so I think that that's, you know, one, one element that can be considered. And then thirdly, um, of course every organization has to work on how do you prioritize talent, acquisition and management and competencies that you can't rescale? I mean, there are just some new capabilities that we don't have. And so there's a large focus that I have with our executive team and our CEO and thinking through those critical roles that we need to activate in order to kind of, to, to build on this, uh, this business led cloud transformation. And lastly, probably the hardest one, but the one that I'm most jazzed about is really this focus on changing the mindsets and behaviors. Um, and I think there, you know, this is where the power of three is, is really, uh, kind of coming together nicely. I mean, we're working on things like, you know, how do we create this patient obsessed curiosity, um, and really kind of unlock innovation with a real, kind of a growth mindset. >>Uh, and the level of curiosity that's needed, not to just continue to do the same things, but to really challenge the status quo. So that's one big area of focus we're having the agility to act just faster. I mean, to worry less, I guess I would say about kind of the standard chain of command, but how do you make more speedy, more courageous decisions? And this is places where we can emulate the way that a partner like AWS works, or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently to a number of partnerships that we can build. So we can break down some of these barriers and use these networks, um, whether it's within our own internal ecosystem or externally to help, to create value faster. So a lot of energy around ways of working and we'll have to check back in, but I mean, we're early in on this mindset and behavioral shift, um, but a lot of good early momentum. >>Carl you've given me a good segue to talk to Brian about innovation, because you said a lot of the things that I was the customer obsession and this idea of innovating much more quickly. Obviously now the world has its eyes on drug development, and we've all learned a lot about it, uh, in the past few months and accelerating drug development is all, uh, is of great interest to all of us. Brian, how does a transformation like this help a company's ability to become more agile and more innovative and at a quicker speed to, >>Yeah, no, absolutely. And I think some of the things that Carl talked about just now are critical to that, right? I think where sometimes folks fall short is they think, you know, we're going to roll out the technology and the is going to be the silver bullet where in fact it is the culture, it is, is the talent. And it's the focus on that. That's going to be, you know, the determinant of success. And I will say, you know, in this power of three arrangement and Carl talked a little bit about the pyramid, um, talent and culture and that change, and that kind of thinking about that has been a first-class citizen since the very beginning, right. That absolutely is critical for, for being there. Um, and so that's been, that's been key. And so we think about innovation at Amazon and AWS and Chrome mentioned some of the things that, you know, a partner like AWS brings to the table is we talk a lot about builders, right? >>So we're kind of obsessive about builders. Um, and, and we meet what we mean by that is we, we, at Amazon, we hire for builders, we cultivate builders and we like to talk to our customers about it as well. And it also implies a different mindset, right? When you're a builder, you have that, that curiosity, you have that ownership, you have that stake and whatever I'm creating, I'm going to be a co-owner of this product or this service, right. Getting back to that kind of product oriented mindset. And it's not just the technical people or the it people who are builders. It is also the business people as, as Carl talked about. Right. So when we start thinking about, um, innovation again, where we see folks kind of get into a little bit of, uh, innovation, pilot paralysis, is that you can focus on the technology, but if you're not focusing on the talent and the culture and the processes and the mechanisms, you're going to be putting out technology, but you're not going to have an organization that's ready to take it and scale it and accelerate it. >>Right. And so that's, that's been absolutely critical. So just a couple of things we've been doing with, with the Qaeda and Decatur has really been leading the way is, think about a mechanism and a process. And it's really been working backward from the customer, right? In this case, again, the patient and the donor. And that was an easy one because the key value of Decatur is to be a patient focused bio-pharmaceutical right. So that was embedded in their DNA. So that working back from that, that patient, that donor was a key part of that process. And that's really deep in our DNA as well and Accentures. And so we were able to bring that together. The other one is, is, is getting used to experimenting and even perhaps failing, right. And being able to iterate and fail fast and experiment and understanding that, you know, some decisions, what we call it at Amazon are two two-way doors, meaning you can go through that door, not like what you see and turn around and go back. And cloud really helps there because the costs of experimenting and the cost of failure is so much lower than it's ever been. You can do it much faster and the implications are so much less. So just a couple of things that we've been really driving, uh, with Decatur around innovation, that's been really critical. >>Carl, where are you already seeing signs of success? Yeah, no, it's a great question. And so we chose, you know, uh, with our focus on, on innovation to try to unleash maybe the power of data digital in, uh, in focusing on what I call sort of a nave. And so we chose our, our, our plasma derived therapy business, um, and you know, the plasma-derived therapy business unit, it develops critical life-saving therapies for patients with rare and complex diseases. Um, but what we're doing is by bringing kind of our energy together, we're focusing on creating, I'll call it state of the art digitally connected donation centers. And we're really modernizing, you know, the, the, the donor experience right now, we're trying to, uh, improve also I'll call it the overall plasma collection process. And so we've, uh, selected a number of alcohol at a very high-speed pilots that we're working through right now, specifically in this, in this area. And we're seeing really great results already. Um, and so that's, that's one specific area of focus >>Arjun. I want you to close this out here. Any ideas, any best practices advice you would have for other pharmaceutical companies that are, that are at the early stage of their cloud journey for me? Yes. >>Yeah, no, I was breaking up a bit. No, I think they, um, the key is what's sort of been great for me to see is that when people think about cloud, you know, you always think about infrastructure technology. The reality is that the cloud is really the true enabler for innovation and innovating at scale. And, and if you think about that, right, in all the components that you need, that ultimately that's where the value is for the company, right? Because yes, you're going to get some cost synergies and that's great, but the true value is in how do we transform the organization in the case of the Qaeda and the life sciences clients, right. We're trying to take a 14 year process of research and development that takes billions of dollars and compress that, right. Tremendous amounts of innovation opportunity. You think about the commercial aspect, lots of innovation can come there. The plasma derived therapy is a great example of how we're going to really innovate to change the trajectory of that business. So I think innovation is at the heart of what most organizations need to do. And the formula, the cocktail that the Qaeda has constructed with this Fuji program really has all the ingredients, um, that are required for that success. >>Great. Well, thank you so much. Arjun, Brian and Carl was really an enlightening conversation. >>Yeah, it's been fun. Thanks Rebecca. >>Thank you for tuning into the cube virtuals coverage of the Accenture executive summit from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. Welcome everyone to the cubes of Accenture >>Executive summit here at AWS reinvent. I'm your host Rebecca Knight for this segment? We have two guests. First. We have Helen Davis. She is the senior director of cloud platform services, assistant director for it and digital for the West Midlands police. Thanks so much for coming on the show, Helen, And we also have Matthew lb. He is Accenture health and public service associate director and West Midlands police account lead. Thanks so much for coming on the show. Matthew, thank you for having us. So we are going to be talking about delivering data-driven insights to the West Midlands police force. Helen, I want to start with you. Can you tell us a little bit about the West Midlands police force? How big is the force and also what were some of the challenges that you were grappling with prior to this initiative? >>Yes, certainly. So Westerners police is the second largest police force in the UK, outside of the metropolitan police in London. Um, we have an excessive, um, 11,000 people work at Westminster police serving communities, um, through, across the Midlands region. So geographically, we're quite a big area as well, as well as, um, being population, um, density, having that as a, at a high level. Um, so the reason we sort of embarked on the data-driven insights platform and it, which was a huge change for us was for a number of reasons. Um, namely we had a lot of disparate data, um, which was spread across a range of legacy systems that were many, many years old, um, with some duplication of, um, what was being captured and no single view for offices or, um, support staff. Um, some of the access was limited. You have to be in a, in an actual police building on a desktop computer to access it. Um, other information could only reach officers on the frontline through a telephone call back to one of our enabling services where they would do a manual checkup, um, look at the information, then call the offices back, um, and tell them what they needed to know. So it was a very long laborious process and not very efficient. Um, and we certainly weren't exploiting the data that we had in a very productive way. >>So it sounds like as you're describing and an old clunky system that needed a technological, uh, reimagination, so what was the main motivation for, for doing, for making this shift? >>It was really, um, about making us more efficient and more effective in how we do how we do business. So, um, you know, certainly as a, as an it leader and sort of my operational colleagues, we recognize the benefits, um, that data analytics could bring in, uh, in a policing environment, not something that was, um, really done in the UK at time. You know, we have a lot of data, so we're very data rich and the information that we have, but we needed to turn it into information that was actionable. So that's where we started looking for, um, technology partners and, um, suppliers to help us and sort of help us really with what's the art of the possible, you know, this hasn't been done before. So what could we do in this space that's appropriate for policing >>Helen? I love that idea. What is the art of the possible, can you tell us a little bit about why you chose AWS? >>I think really, you know, as with all things and when we're procuring a partner in the public sector that, you know, there are many rules and regulations quite rightly as you would expect that to be because we're spending public money. So we have to be very, very careful and, um, it's, it's a long process and we have to be open to public scrutiny. So, um, we sort of look to everything, everything that was available as part of that process, but we recognize the benefits that tide would provide in this space because, you know, without moving to a cloud environment, we would literally be replacing something that was legacy with something that was a bit more modern. Um, that's not what we wanted to do. Our ambition was far greater than that. So I think, um, in terms of AWS, really, it was around scalability, interoperability, you know, disaster things like the disaster recovery service, the fact that we can scale up and down quickly, we call it dialing up and dialing back. Um, you know, it's it's page go. So it just sort of ticked all the boxes for us. And then we went through the full procurement process, fortunately, um, it came out on top for us. So we were, we were able to move forward, but it just sort of had everything that we were looking for in that space. >>Matthew, I want to bring you into the conversation a little bit here. How are you working with the wet with the West Midlands police, sorry, and helping them implement this cloud first journey? >>Yeah, so I guess, um, by January the West Midlands police started, um, pay for five years ago now. So, um, we set up a partnership with the force I, and you to operate operation the way that was very different to a traditional supplier relationship. Um, secretary that the data difference insights program is, is one of many that we've been working with less neutral on, um, over the last five years. Um, as having said already, um, cloud gave a number of, uh, advantages certainly from a big data perspective and the things that that enabled us today, um, I'm from an Accenture perspective that allowed us to bring in a number of the different themes that we have say cloud themes, security teams, um, interacted from a design perspective, as well as more traditional services that people would associate with the country. >>So much of this is about embracing comprehensive change to experiment, innovate, and try different things. Matthew, how, how do you help an entity like West Midlands police think differently when they are, there are these ways of doing things that people are used to, how do you help them think about what is the art of the possible, as Helen said, >>There's a few things for that, you know, what's being critical is trying to co-create solutions together. Yeah. There's no point just turning up with, um, what we think is the right answer, try and say, um, collectively work through, um, the issues that the forest are seeing the outcomes they're looking to achieve rather than simply focusing on the long list of requirements I think was critical and then being really open to working together to create the right solution. Um, rather than just, you know, trying to pick something off the shelf that maybe doesn't fit the forces requirements in the way that it should to, right. It's not always a one size fits all. Obviously, you know, today what we thought was critical is making sure that we're creating something that met the forces needs, um, in terms of the outcomes they're looking to achieve the financial envelopes that were available, um, and how we can deliver those in a, uh, iterative agile way, um, rather than spending years and years, um, working towards an outcome, um, that is going to outdate before you even get that. >>How, how are things different? What kinds of business functions and processes have been re-imagined in, in light of this change and this shift >>It's, it's actually unrecognizable now, um, in certain areas of the business as it was before. So to give you a little bit of context, when we, um, started working with essentially century AWS on the data driven insights program, it was very much around providing, um, what was called locally, a wizzy tool for our intelligence analysts to interrogate data, look at data, you know, decide whether they could do anything predictive with it. And it was very much sort of a back office function to sort of tidy things up for us and make us a bit better in that, in that area or a lot better in that area. And it was rolled out to a number of offices, a small number on the front line. Um, I'm really, it was, um, in line with a mobility strategy that we, hardware officers were getting new smartphones for the first time, um, to do sort of a lot of things on, on, um, policing apps and things like that to again, to avoid them, having to keep driving back to police stations, et cetera. >>And the pilot was so successful. Every officer now has access to this data, um, on their mobile devices. So it literally went from a handful of people in an office somewhere using it to do sort of clever whizzbang things to, um, every officer in the force, being able to access that level of data at their fingertips literally. So what they would touch we've done before is if they needed to check and address or check, uh, details of an individual, um, just as one example, they would either have to, in many cases, go back to a police station to look it up themselves on a desktop computer. Well, they would have to make a call back to, um, a centralized function and speak to an operator, relay the questions either, wait for the answer or wait for a call back with the answer when those people are doing the data interrogation manually. >>So the biggest change for us is the self-service nature of the data we now have available. So officers can do it themselves on their phone, wherever they might be. So the efficiency savings, um, from that point of view are immense. And I think just parallel to that is the quality of our data because we had a lot of data, but just because you've got a lot of data and a lot of information doesn't mean it's big data and it's valuable necessarily. Um, so again, it was having the single source of truth as we, as we call it. So you know, that when you are completing those safe searches and getting the responses back, that it is the most accurate information we hold. And also you're getting it back within minutes as opposed to, you know, half an hour, an hour or a drive back to the station. So it's making officers more efficient and it's also making them safer. The more efficient they are, the more time they have to spend, um, out with the public doing what they, you know, we all should be doing. >>And have you seen that kind of return on investment because what you were just describing with all the steps that we'd needed to be taken in prior to this to verify and address say, and those are precious seconds when someone's life is on the line in, in sort of in the course of everyday police work. >>Absolutely. Yeah, absolutely. It's difficult to put a price on it. It's difficult to quantify. Um, but all the, you know, the minutes here and that certainly add up to a significant amount of efficiency savings, and we've certainly been able to demonstrate the officers are spending less time up police stations as a result and more time out on the front line. Also they're safer because they can get information about what may or may not be and address what may or may not have occurred in an area before very, very quickly without having to wait. >>Matthew, I want to hear your observations of working so closely with this West Midlands police. Have you noticed anything about changes in its culture and its operating model in how police officers interact with one another? Have you seen any changes since this technology change, >>Um, unique about the West new misplaces, the buy-in from the top, it depend on the chief and his exact team. And Helen is the leader from an IOT perspective. Um, the entire force is bought in. So what is a significant change program? Uh, uh, not trickles three. Um, everyone in the organization, um, change is difficult. Um, and there's a lot of time effort. That's been put into bake, the technical delivery and the business change and adoption aspects around each of the projects. Um, but you can see the step change that it's making in each aspect to the organization, uh, and where that's putting West Midlands police as a leader in, um, technology I'm policing in the UK. And I think globally, >>And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain intransigence in workplaces about this is just the way we've always done things and we're used to this and don't try to get us, don't try to get us to do anything new here. It works. How do you get the buy-in that you need to, to do this kind of digital transformation? >>I think it, it would be wrong to say it was easy. Um, um, we also have to bear in mind that this was one program in a five year program. So there was a lot of change going on, um, both internally for some of our back office functions, as well as front tie, uh, frontline offices. So with DDI in particular, I think the stat change occurred when people could see what it could do for them. You know, we had lots of workshops and seminars where we all talk about, you know, big data and it's going to be great and it's data analytics and it's transformational, you know, and quite rightly people that are very busy doing a day job that not necessarily technologists in the main and, you know, are particularly interested quite rightly so in what we are not dealing with the cloud, you know? >>And it was like, yeah, okay. It's one more thing. And then when they started to see on that, on their phones and what teams could do, that's when it started to sell itself. And I think that's when we started to see, you know, to see the stack change, you know, and, and if we, if we have any issues now it's literally, you know, our help desks in meltdown. Cause everyone's like, well, we call it manage without this anymore. And I think that speaks for itself. So it doesn't happen overnight. It's sort of incremental changes and then that's a step change in attitude. And when they see it working and they see the benefits, they want to use it more. And that's how it's become fundamental to our policing by itself, really without much selling >>Matthew, Helen just made a compelling case for how to get buy in. Have you discovered any other best practices when you are trying to get everyone on board for this kind of thing? >>So we've, um, we've used a lot of the traditional techniques, things around comms and engagement. We've also used things like, um, the 30 day challenge and nudge theory around how can we gradually encourage people to use things? Um, I think there's a point where all of this around, how do we just keep it simple and keep it user centric from an end user perspective? I think DDI is a great example of where the, the technology is incredibly complex. The solution itself is, um, you know, extremely large and, um, has been very difficult to, um, get delivered. But at the heart of it is a very simple front end for the user to encourage it and take that complexity away from them. Uh, I think that's been critical through the whole piece of video. >>One final word from Helen. I want to hear, where do you go from here? What is the longterm vision? I know that this made productivity, >>Um, productivity savings equivalent to 154 full-time officers. Uh, what's next, I think really it's around, um, exploiting what we've got. Um, I use the phrase quite a lot, dialing it up, which drives my technical architects crazy, but because it's apparently not that simple, but, um, you know, we've, we've been through significant change in the last five years and we are still continuing to batch all of those changes into everyday, um, operational policing. But what we need to see now is we need to exploit and build on the investments that we've made, um, in terms of data and claims specifically, the next step really is about expanding our pool of data and our functions. Um, so that, you know, we keep getting better and better, um, at this, um, the more we do, the more data we have, the more refined we can be, the more precise we are with all of our actions. >>Um, you know, we're always being expected to, again, look after the public purse and do more for less. And I think this is certainly an and our cloud journey and cloud first by design, which is where we are now, um, is helping us to be future-proofed. So for us, it's very much an investment. And I see now that we have good at embedded in operational policing for me, this is the start of our journey, not the end. So it's really exciting to see where we can go from here. Exciting times. Indeed. Thank you so much. And Matthew for joining us, I really appreciate it. And you are watching the cube stay tuned for more of the cubes coverage of the AWS reinvent Accenture executive summit. I'm Rebecca Knight from around the globe with digital coverage, >>AWS reinvent executive summit, 2020, sponsored by Accenture and AWS. Everyone. Welcome to the cube virtual coverage of the executive summit at AWS reinvent 2020 virtual. This is the cube virtual. We can't be there in person like we are every year we have to be remote. This executive summit is with special programming supported by Accenture where the cube virtual I'm your host John for a year, we had a great panel here called uncloud first digital transformation from some experts, Stuart driver, the director of it and infrastructure and operates at lion Australia, Douglas Regan, managing director, client account lead at lion for Accenture as a deep Islam associate director application development lead for Accenture gentlemen, thanks for coming on the cube virtual that's a mouthful, all that digital, but the bottom line it's cloud transformation. This is a journey that you guys have been on together for over 10 years to be really a digital company. Now, some things have happened in the past year that kind of brings all this together. This is about the next generation organization. So I want to ask Stuart you first, if you can talk about this transformation at lion has undertaken some of the challenges and opportunities and how this year in particular has brought it together because you, you know, COVID has been the accelerant of digital transformation. Well, if you're 10 years in, I'm sure you're there. You're in the, uh, uh, on that wave right now. Take a minute to explain this transformation journey. >>Yeah, sure. So number of years back, we, we looked at kind of our infrastructure and our landscape. I'm trying to figure out where we wanted to go next. And we were very analog based, um, and stuck in the old it groove of, you know, capital refresh, um, struggling to transform, struggling to get to a digital platform and we needed to change it up so that we could, uh, become very different business to the one that we were back then. Um, obviously cloud is an accelerant to that and we had a number of initiatives that needed a platform to build on. And a cloud infrastructure was the way that we started to do that. So we went through a number of transformation programs that we didn't want to do that in the old world. We wanted to do it in a new world. So for us, it was partnering up with a, you know, great organizations that can take you on the journey and, uh, you know, start to deliver a bit by bit incremental progress, uh, to get to the, uh, I guess the promise land. >>Um, we're not, uh, not all the way there, but to where we're a long way along. And then when you get to some of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually change pretty quickly, um, provide capacity and, uh, and increase your environments and, you know, do the things that you need to do in a much more dynamic way than we would have been able to previously where we might've been waiting for the hardware vendors, et cetera, to deliver capacity for us this year, it's been a pretty strong year from an it perspective and delivering for the business needs, >>Forget the Douglas. I want to just real quick and redirect to you and say, you know, for all the people who said, Oh yeah, you got to jump on cloud, get in early, you know, a lot of naysayers like, well, wait till to mature a little bit. Really, if you got in early and you paying your dues, if you will taking that medicine with the cloud, you're really kind of peaking at the right time. Is that true? Is that one of the benefits that comes out of this getting in the cloud, >>John, this has been an unprecedented year, right. And, um, you know, Australia, we had to live through Bush fires and then we had covert and, and then we actually had to deliver a, um, a project I'm very know transformational product project, completely remote. And then we also had had some, some cyber challenges, which is public as well. And I don't think if we weren't moved into and enabled through the cloud would have been able to achieve that this year. It would have been much different. It would have been very difficult to do the fact that we were able to work and partner with Amazon through this year, which is unprecedented and actually come out the other end and we've delivered a brand new digital capability across the entire business. Um, it wouldn't >>Have been impossible if we could, I guess, stayed in the old world. The fact that we moved into the new Naval by the Navy allowed us to work in this unprecedented gear >>Just quick. What's your personal view on this? Because I've been saying on the Cuban reporting, necessity's the mother of all invention and the word agility has been kicked around as kind of a cliche, Oh, it'd be agile. You know, we're gonna get to Sydney. You get a minute on specifically, but from your perspective, uh, Douglas, what does that mean to you? Because there is benefits there for being agile. And >>I mean, I think as Stuart mentioned writing, and a lot of these things we try to do and, you know, typically, you know, hardware capabilities of the last to be told and, and always the only critical path to be done. You know, we really didn't have that in this case, what we were doing with our projects in our deployments, right. We were able to move quickly able to make decisions in line with the business and really get things going, right. So you, a lot of times in a traditional world, you have these inhibitors, you have these critical path, it takes weeks and months to get things done as opposed to hours and days. And it truly allowed us to, we had to VJ things, move things. And, you know, we were able to do that in this environment with AWS to support and the fact that we can kind of turn things off and on as quickly as we need it. Yeah. >>Cloud-scale is great for speed. So DECA got, Gardez get your thoughts on this cloud first mission, you know, it, you know, the dev ops worlds, they saw this early, that jumping in there, they saw the, the, the agility. Now the theme this year is modern applications with the COVID pandemic pressure, there's real business pressure to make that happen. How did you guys learn to get there fast? And what specifically did you guys do at Accenture and how did it all come together? Can you take us inside kind of how it played out? >>All right. So we started off with us and we work with lions experts and, uh, the lost knowledge that allowed reconstructive being had. Um, we then applied our journey group cloud strategy basically revolves around the seven Oz and, and, uh, you know, the deep peaking steps from our perspective, uh, assessing the current bottom, setting up the new cloud in modern. And as we go modernizing and, and migrating these applications to the cloud now, you know, one of the things that, uh, no we did not along this journey was that, you know, you can have the best plans, but bottom of that, we were dealing with, we often than not have to make changes. Uh, what a lot of agility and also work with a lot of collaboration with the, uh, Lyon team, as well as, uh, uh, AWS. I think the key thing for me was being able to really bring it all together. It's not just, uh, you know, essentially mobilize all of us. >>What were some of the learnings real quick, your journey there? >>So I think perspective the key learnings around that, you know, uh, you know, what, when we look back at, uh, the, the infrastructure that was that we were trying to migrate over to the cloud, a lot of the documentation, et cetera, was not, uh, available. We were having to, uh, figure out a lot of things on the fly. Now that really required us to have, uh, uh, people with deep expertise who could go into those environments and, and work out, uh, you know, the best ways to, to migrate the workloads to the cloud. Uh, I think, you know, the, the biggest thing for me was making Jovi had on that real SMEs across the board globally, that we could leverage across various technologies, uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment would line >>Just do what I got to ask you. How did you address your approach to the cloud and what was your experience? >>Yeah, for me, it's around getting the foundations right. To start with and then building on them. Um, so, you know, you've got to have your, your process and you're going to have your, your kind of your infrastructure there and your blueprints ready. Um, AWS do a great job of that, right. Getting the foundations right. And then building upon it, and then, you know, partnering with Accenture allows you to do that very successfully. Um, I think, um, you know, the one thing that was probably surprising to us when we started down this journey and kind of, after we got a long way down, the track of looking backwards is actually how much you can just turn off. Right? So a lot of stuff that you, uh, you get left with a legacy in your environment, and when you start to work through it with the types of people that civic just mentioned, you know, the technical expertise working with the business, um, you can really rationalize your environment and, uh, um, you know, cloud is a good opportunity to do that, to drive that legacy out. >>Um, so you know, a few things there, the other thing is, um, you've got to try and figure out the benefits that you're going to get out of moving here. So there's no point just taking something that is not delivering a huge amount of value in the traditional world, moving it into the cloud, and guess what it's going to deliver the same limited amount of value. So you've got to transform it, and you've got to make sure that you build it for the future and understand exactly what you're trying to gain out of it. So again, you need a strong collaboration. You need a good partners to work with, and you need good engagement from the business as well, because the kind of, uh, you know, digital transformation, cloud transformation, isn't really an it project, I guess, fundamentally it is at the core, but it's a business project that you've got to get the whole business aligned on. You've got to make sure that your investment streams are appropriate and that you're able to understand the benefits and the value that you're going to drive back towards the business. >>Let's do it. If you don't mind me asking what was some of the obstacles encountered or learnings, um, that might've differed from the expectation we all been there, Hey, you know, we're going to change the world. Here's the sales pitch, here's the outcome. And then obviously things happen, you know, you learn legacy, okay. Let's put some containerization around that cloud native, um, all that rational. You're talking about what are, and you're going to have obstacles. That's how you learn. That's how perfection has developed. How, what obstacles did you come up with and how are they different from your expectations going in? >>Yeah, they're probably no different from other people that have gone down the same journey. If I'm totally honest, the, you know, 70 or 80% of what you do is relative music, because they're a known quantity, it's relatively modern architectures and infrastructures, and you can, you know, upgrade, migrate, move them into the cloud, whatever it is, rehost, replatform, rearchitect, whatever it is you want to do, it's the other stuff, right? It's the stuff that always gets left behind. And that's the challenge. It's, it's getting that last bit over the line and making sure that you haven't invested in the future while still carrying all of your legacy costs and complexity within your environment. So, um, to be quite honest, that's probably taken longer and, and has been more of a challenge than we thought it would be. Um, the other piece I touched on earlier on in terms of what was surprising was actually how much of your environment is actually not needed anymore. >>When you start to put a critical eye across it and understand, um, uh, ask the tough questions and start to understand exactly what, what it is you're trying to achieve. So if you ask a part of a business, do they still need this application or this service a hundred percent of the time, they'll say yes, until you start to lay out to them, okay, now I'm going to cost you this to migrate it or this, to run it in the future. And, you know, here's your ongoing costs and, you know, et cetera, et cetera. And then, uh, for a significant amount of those answers, you get a different response when you start to layer on the true value of it. So you start to flush out those hidden costs within the business, and you start to make some critical decisions as a company based on, uh, based on that. So that was a little tougher than we first thought and probably broader than we thought there was more of that than we anticipated, which actually resulted in a much cleaner environment post and post migration. Yeah. >>Well, expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value, uh, Stuart and Siddique. Mainly if you can weigh in on this love to know the percentage of total cloud that you have now, versus when you started, because as you start to uncover whether it's by design for purpose, or you discover opportunities to innovate, like you guys have, I'm sure it kind of, you took on some territory inside Lyon, what percentage of cloud now versus >>Yeah. At the start, it was minimal, right. You know, close to zero, right. Single and single digits. Right. It was mainly SAS environments that we had, uh, sitting in cloud when we, uh, when we started, um, Doug mentioned earlier a really significant transformation project that we've undertaken recently gone live on a multi-year one. Um, you know, that's all stood up on AWS and is a significant portion of our environment, um, in terms of what we can move to cloud. Uh, we're probably at about 80 or 90% now. And the balanced bit is, um, legacy infrastructure that is just gonna retire as we go through the cycle rather than migrate to the cloud. Um, so we are significantly cloud-based and, uh, you know, we're reaping the benefits of it in a year, like 2020, and makes you glad that you did all of the hard yards in the previous years when you start business challenges, trying out as, >>So do you get any common reaction to the cloud percentage penetration? >>Sorry, I didn't, I didn't catch that, but I, all I was going to say was, I think it's like the typical 80 20 rule, right? We, we, we worked really hard in the, you know, I think 2018, 19 to get 80% off the, uh, application onto the cloud. And over the last year is the 20% that we have been migrating. And Stuart said, right. A lot of it is also, that's going to be your diet. And I think our next big step is going to be obviously, you know, the icing on the cake, which is to decommission all of these apps as well. Right. So, you know, to get the real benefits out of, uh, out of the whole conservation program from a, uh, from a reduction of CapEx, OPEX perspective, >>Douglas and Stuart, can you guys talk about the decision around the clouds because you guys have had success with AWS? Why AWS how's that decision made? Can you guys give some insight into some of those things? >>I can, I can start, start off. I think back when the decision was made and it was, it was a while back, um, you know, there was some clear advantages of moving relay, Ws, a lot of alignment with some of the significant projects and, uh, the trend, that particular one big transformation project that we've alluded to as well. Um, you know, we needed some, um, some very robust and, um, just future proof and, and proven technology. And AWS gave that to us. We needed a lot of those blueprints to help us move down the path. We didn't want to reinvent everything. So, um, you know, having a lot of that legwork done for us and AWS gives you that, right. And particularly when you partner up with, uh, with a company like Accenture as well, you get combinations of technology and the, the skills and the knowledge to, to move you forward in that direction side. Um, you know, for us, it was a, uh, uh, it was a decision based on, you know, best of breed, um, you know, looking forward and, and trying to predict the future needs and, and, and kind of the environmental that we might need. Um, and, you know, partnering up with organizations that can then take you on the journey >>Just to build on that. So obviously, you know, lines like an antivirus, but, you know, we knew it was a very good choice given the, um, >>Uh, skills and the capability that we had, as well as the assets and tools we had to get the most out of an AWS. And obviously our CEO globally just made an announcement about a huge investment that we're making in cloud. Um, but you know, we've, we've worked very well with AWS. We've done some joint workshops and joint investments, um, some joint POC. So yeah, w we have a very good working relationship, AWS, and I think, um, one incident to reflect upon whether it's cyber it's and again, where we actually jointly, you know, dove in with, um, with Amazon and some of their security experts and our experts. And we're able to actually work through that with mine quite successful. So, um, you know, really good behaviors as an organization, but also really good capabilities. >>Yeah. As you guys, your essential cloud outcomes, research shown, it's the cycle of innovation with the cloud, that's creating a lot of benefits, knowing what you guys know now, looking back certainly COVID has impacted a lot of people kind of going through the same process, knowing what you guys know now, would you advocate people to jump on this transformation journey? If so, how, and what tweaks they make, which changes, what would you advise? >>I might take that one to start with. Um, I hate to think where we would have been when, uh, COVID kicked off here in Australia and, you know, we were all sent home, literally were at work on the Friday, and then over the weekend. And then Monday, we were told not to come back into the office and all of a sudden, um, our capacity in terms of remote access and I quadrupled, or more four, five X, what we had on the Friday we needed on the Monday. And we were able to stand that up during the day Monday into Tuesday, because we were cloud-based and, uh, you know, we just spun up your instances and, uh, you know, sort of our licensing, et cetera. And, and we had all of our people working remotely, um, within, uh, you know, effectively one business day. Um, I know peers of mine in other organizations and industries that are relying on kind of a traditional wise and getting hardware, et cetera, that were weeks and months before they could get the right hardware to be able to deliver to their user base. >>So, um, you know, one example where you're able to scale and, uh, uh, get, uh, get value out of this platform beyond probably what was anticipated at the time you talk about, um, you know, less this, the, and all of these kinds of things. And you can also think of a few scenarios, but real world ones where you're getting your business back up and running in that period of time is, is just phenomenal. There's other stuff, right? There's these programs that we've rolled out, you do your sizing, um, and in the traditional world, you would just go out and buy more servers than you need. And, you know, probably never realize the full value of those, you know, the capability of those servers over the life cycle of them. Whereas, you know, in a cloud world, you put in what you think is right. And if it's not right, you pump it up a little bit when, when all of your metrics and so on telling you that you need to bump it up and conversely Scarlett down at the same rate. So for us with the types of challenges and programs and, uh, uh, and just business need, that's come at as this year, uh, we wouldn't have been able to do it without a strong cloud base, uh, to, uh, to move forward with >>Yeah, Douglas, one of the things that I talked to, a lot of people on the right side of history who have been on the right wave with cloud, with the pandemic, and they're happy, they're like, and they're humble. Like, well, we're just lucky, you know, luck is preparation meets opportunity. And this is really about you guys getting in early and being prepared and readiness. This is kind of important as people realize, then you gotta be ready. I mean, it's not just, you don't get lucky by being in the right place, the right time. And there were a lot of companies were on the wrong side of history here who might get washed away. This is a second >>I think, to echo and kind of build on what Stewart said. I think that the reason that we've had success and I guess the momentum is we, we didn't just do it in isolation within it and technology. It was actually linked to broader business changes, you know, creating basically a digital platform for the entire business, moving the business, where are they going to be able to come back stronger after COVID, when they're actually set up for growth, um, and actually allows, you know, a line new achievements, growth objectives, and also its ambitions as far as what he wants to do, uh, with growth in whatever they may do as acquiring other companies and moving into different markets and launching new product. So we've actually done it in a way that there's, you know, real and direct business benefit, uh, that actually enables line to grow >>General. I really appreciate you coming. I have one final question. If you can wrap up here, uh, Stuart and Douglas, you don't mind waiting, and what's the priorities for the future. What's next for lion and a century >>Christmas holidays, I'll start Christmas holidays. And I spent a third year and then a, and then a reset, obviously, right? So, um, you know, it's, it's figuring out, uh, transform what we've already transformed, if that makes sense. So God, a huge proportion of our services sitting in the cloud. Um, but we know we're not done even with the stuff that is in there. We need to take those next steps. We need more and more automation and orchestration. We need to, um, our environment, there's more future growth. We need to be able to work with the business and understand what's coming at them so that we can, um, you know, build that into, into our environment. So again, it's really transformation on top of transformation is the way that I'll describe it. And it's really an open book, right? Once you get it in and you've got the capabilities and the evolving tool sets that AWS continue to bring to the market base, um, you know, working with the partners to, to figure out how we unlock that value, um, you know, drive our costs down our efficiency, uh, all of those kind of, you know, standard metrics. >>Um, but you know, we're looking for the next things to transform and show value back out to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with and understand how we can better meet their needs. Yeah, I think just to echo that, I think it's really leveraging this and then digital capability they have and getting the most out of that investment. And then I think it's also moving to, >>Uh, and adopting more new ways of working as far as, you know, the state of the business. Um, it's getting up the speed of the market is changing. So being able to launch and do things quickly and also, um, competitive and efficient operating costs, uh, now that they're in the cloud, right. So I think it's really leveraging the most out of a platform and then, you know, being efficient in launching things. So putting the, with the business, >>Cedric, any word from you on your priorities by UC this year and folding. >>Yeah. So, uh, just going to say like e-learning squares, right for me were around, you know, just journey. This is a journey to the cloud, right. And, uh, you know, as well dug into sort of Saturday, it's getting all, you know, different parts of the organization along the journey business to ID to your, uh, product windows, et cetera. Right. And it takes time with this stuff, but, uh, uh, you know, you gotta get started on it and, you know, once we, once we finish off, uh, it's the realization of the benefits now that, you know, I'm looking forward? I think for, from Alliance perspective, it's, it is, uh, you know, once we migrate all the workloads to the cloud, it is leveraging, uh, all stack drive. And as I think Stewart said earlier, uh, with, uh, you know, the latest and greatest stuff that AWS it's basically working to see how we can really, uh, achieve more better operational excellence, uh, from a, uh, from a cloud perspective. >>Well, Stewart, thanks for coming on with a century and sharing your environment and what's going on and your journey you're on the right wave. Did the work you were in that it's all coming together with faster, congratulations for your success, and really appreciate Douglas with Steve for coming on as well from Accenture. Thank you for coming on. Thanks, John. Okay. Just the cubes coverage of executive summit at AWS reinvent. This is where all the thought leaders share their best practices, their journeys, and of course, special programming with the center and the cube. I'm Sean ferry, your host, thanks for watching From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtuals coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First. We have Johan Krebbers. He is the GM digital emerging technologies and VP of it. Innovation at shell. Thank you so much for coming on the show. Johan you're welcome. And next we have Liz Dennett. She is the lead solution architect for O S D U on AWS. Thank you so much, Liz. You'll be. So I want to start our conversation by talking about OSD. You like so many great innovations. It started with a problem Johan. What was the problem you were trying to solve at shell? >>Yeah, the ethical back a couple of years, we started summer 2017, where we had a meeting with the deg, the gas exploration in shell, and the main problem they had. Of course, they got lots of lots of data, but are unable to find the right data. They need to work from once the day, this was scattered in is scattered my boss kind of Emirates all over the place and turned them into real, probably tried to solve is how that person working exploration could find their proper date, not just a day of loss of date. You really needed that we did probably talked about is summer 2017. We said, okay. The only way ABC is moving forward is to start pulling that data into a single data platform. And that, that was at the time that we called it as the, you, the subsurface data universe in there was about the shell name was so in, in January, 2018, we started a project with Amazon to start grating a freaking that building, that Stu environment that the, that universe, so that single data level to put all your exploration and Wells data into that single environment that was intent and every cent, um, already in March of that same year, we said, well, from Michele point of view, we will be far better off if we could make this an industry solution and not just a shelf solution, because Shelby, Shelby, if you can make this industry solution, but people are developing applications for it. >>It also is far better than for shell to say we haven't shell special solution because we don't make money out of how we start a day that we can make money out of, if you have access to the data, we can explore the data. So storing the data we should do as efficiently possibly can. So in March, we reached out to about eight or nine other large, uh, I gas operators, like the economics, like the totals, like the chefs of this world and say, Hey, we inshallah doing this. Do you want to join this effort? And to our surprise, they all said, yes. And then in September, 2018, we had our kickoff meeting with your open group where we said, we said, okay, if you want to work together, lots of other companies, we also need to look at, okay, how, how we organize that, or is that if you started working with lots of large companies, you need to have some legal framework around some framework around it. So that's why we went to the open group and said, okay, let's, let's form the ODU forum as we call it the time. So it's September, 2080, where I did a Galleria in Houston, but the kick off meeting for the OT four with about 10 members at the time. So there's just over two years ago, we started an exercise for me called ODU, kicked it off. Uh, and so that's really then we'll be coming from and how we got there. Also >>The origin story. Um, well, so what digging a little deeper there? What were some of the things you were trying to achieve with the OSD? >>Well, a couple of things we've tried to achieve with OSU, um, first is really separating data from applications. And what is the, what is the biggest problem we have in the subsurface space that the data and applications are all interlinked or tied together. And if you have them and a new company coming along and say, I have this new application and has access to the data that is not possible because the data often interlinked with the application. So the first thing we did is really breaking the link between the application, the data as those levels, the first thing we did, secondly, put all the data to a single data platform, take the silos out what was happening in the subsurface space. And they got all the data in what we call silos in small little islands out there. So we're trying to do is first break the link to great, great. >>They put the data in a single data bathroom, and a third part who does standard layer. On top of that, it's an API layer on top of the, a platform. So we could create an ecosystem out of companies to start developing soft applications on top of dev data platform across you might have a data platform, but you're only successful. If you have a rich ecosystem of people start developing applications on top of that. And then you can explore today, like small companies, last company, university, you name it, we're getting after create an ecosystem out here. So the three things, whereas was first break the link between application data, just break it and put data at the center and also make sure that data, this data structure would not be managed by one company. It would only be met. It will be managed the data structures by the OT forum. Secondly, then the data of single data platform certainly has an API layer on top and then create an ecosystem. Really go for people, say, please start developing applications because now you have access to the data. I've got the data no longer linked to somebody whose application was all freely available for an API layer. That was, that was all September, 2018, more or less. >>And to bring you in here a little bit, can you talk a little bit about some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? Yeah, absolutely. And this whole thing is Johan said started with a challenge that was really brought out at shell. The challenges that geo-scientists spend up to 70% of their time looking for data, I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out how we could address that one problem, we worked together to really understand the root cause of these challenges and working backwards from that use case OSU and OSU on AWS has really enabled customers to create solutions that span, not just this in particular problem, but can really scale to be inclusive of the entire energy chain and deliver value from these use cases to the energy industry and beyond. Thank you, Lee, uh, Johann. So talk a little bit about Accenture's cloud first approach and how it has, uh, helped shell work faster and better with speed. >>Well, of course, access a cloud first approach only works together in an Amazon environment, AWS environment. So we really look at, at, at, at Accenture and others altogether helping shell in this space. Now the combination of the two is what we're really looking at, uh, where access of course can be, this is not a student who that environment operates, support knowledge to an environment. And of course, Amazon would be doing that to today's environment that underpinning, uh, services, et cetera. So, uh, we would expect a combination, a lot of goods when we started rolling out and put in production, the old you are three and bubble because we are anus. Then when the release feed comes to the market in Q1 next year of ODU, when he started going to Audi production inside shell, but as the first release, which is ready for prime time production across an enterprise will be released one just before Christmas, last year when he's still in may of this year. But release three is the first release we want to use for full scale production deployment inside shell, and also all the operators around the world. And there is what Amazon, sorry. Um, extensive can play a role in the ongoing, in the, in deployment building up, but also support environment. >>So one of the other things that we talk a lot about here on the cube is sustainability. And this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSD you, uh, help organizations become, how is this a greener solution for companies? >>Well, firstly make it, it's a great solution because you start making a much more efficient use of your resources, which is, which is already an important one. The second thing they're doing is also, we started with ODU in the oil and gas space with the expert development space. We've grown, uh OTU but in our strategy of growth, OSU now also do an alternative energy sociology. We'll all start supporting next year. Things like solar farms, wind farms, uh, the, the dermatomal environment hydration. So it becomes an and, and an open energy data platform, not just for the, for the, I want to get into steam that's for new industry, any type of energy industry. So our focus is to create, bring that data of all those various energy data sources together into a single data platform. You're going to use AI and other technology on top of that to exploit the data, to meet again in a single data platform. >>Liz, I want to ask you about security because security is, is, is such a big concern when it comes to how secure is the data on OSD you, um, actually, can I talk, can I do a follow up on the sustainability talking? Oh, absolutely. By all means. I mean, I want to interject though security is absolutely our top priority. I don't mean to move away from that, but with sustainability, in addition to the benefits of the OSU data platform, when a company moves from on-prem to the cloud, they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical on-prem data center. Now, a recent study by four 51 research found that AWS is infrastructure is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to higher server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases, four 51 found that AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSU are working to support our customers is they seek to better understand their workflows and make their legacy businesses less carbon intensive. >>That's that's those are those statistics are incredible. Do you want to talk a little bit now about security? Absolutely. And security will always be AWS is top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy. There are the security requirements for the military global banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build and operate each of our regions. So that customers benefit from the only commercial cloud that's had hits service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features as well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. Johann, I want you to talk a little bit about how OSD you can be used today. Does it only handle subsurface data >>And today it's hundreds of servers or Wells data. We got to add to that production around the middle of next year. That means that the whole upstate business. So we've got, if you look at MC, obviously this goes from exploration all the way to production. You've been at the into to a single data platform. So production will be added the round Q3 of next year. Then it principal, we have a difficult, the elder data that single environment, and we want to extended them to other data sources or energy sources like solar farms, wheat farms, uh, hydrogen hydro at San Francisco. We want to add a whore or a list of other day. >>And he saw a student and B all the data together into a single data club. So we move from an fallen guest, a data platform to an energy data platform. That's really what our objective is because the whole industry we've looked at, I've looked at our company companies all moving in that same direction of quantity, of course are very strong at all, I guess, but also increase the, got into all the other energy sources like, like solar, like wind, like, like the hydrogen, et cetera. So we, we move exactly the same method that, that, that the whole OSU can really support at home. And as a spectrum of energy sources, of course, >>And Liz and Johan. I want you to close us out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSD. You we'll start with you, Liz. What do you, what do you see as the future holding for this platform? Um, honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers, wherever their OSU journeys, take them, whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond, but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges. >>Yeah. First, nobody can look that far ahead, any more nowadays, especially 10 years mean now, who knows what happens in 10 years, but if you look what our whole objective is that really in the next five years owes you will become the key backbone for energy companies for storing your data. You are efficient intelligence and optimize the whole supply energy supply chain in this world out there. >>Rubbers Liz Dennett. Thank you so much for coming on the cube virtual, >>Thank you, >>Rebecca nights, stay tuned for more of our coverage of the Accenture executive summit >>Around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight today we're welcoming back to Kubila. We have Kishor Dirk. He is the Accenture senior managing director cloud first global services lead. Welcome back to the show >>Kishore. Thank you very much. >>Nice to meet again. And, uh, Tristin moral horse set. He is the managing director, Accenture cloud first North American growth. Welcome back to YouTube. >>Great to be back in. Great to see you again, Rebecca. >>Exactly. Even in this virtual format, it is good to see your faces. Um, today we're going to be talking about my nav and green cloud advisor >>Capability. Kishor I want to start with you. So my NAB is a platform that is really celebrating its first year in existence. Uh, November, 2019 is when Accenture introduced it. Uh, but it's, it has new relevance in light of this global pandemic that we are all enduring and suffering through. Tell us a little bit about the miner platform, what it is. >>Sure, Rebecca, you know, we lost it and now 2019 and, uh, you know, it is a cloud platform to help our clients navigate the complexity of cloud and cloud decisions and to make it faster and obviously innovate in the cloud, uh, you know, with the increased relevance and all the, especially over the last few months with the impact of COVID crisis and exhibition of digital transformation, you know, we are seeing the transformation of the acceleration to cloud much faster. This platform that you're talking about has enabled hundred and 40 clients globally across different industries. You identify the right cloud solution, navigate the complexity, provide a cloud specific solution simulate for our clients to meet the strategy business needs and the clients are loving it. >>I want to go to you now trust and tell us a little bit about how my nav works and how it helps companies make good cloud choices. >>Yeah. So Rebecca we've talked about cloud is, is more than just infrastructure and that's what mine app tries to solve for. It really looks at a variety of variables, including infrastructure operating model and fundamentally what clients business outcomes, um, uh, our clients are, are looking for and, and identify as the optimal solution for what they need. And we design this to accelerate and we mentioned the pandemic. One of the big focus now is to accelerate. And so we worked through a three-step process. The first is scanning and assessing our client's infrastructure, their data landscape, their application. Second, we use our automated artificial intelligence engine to interact with. We have a wide variety and library of, uh, collective plot expertise. And we look to recommend what is the enterprise architecture and solution. And then third, before we aligned with our clients, we look to simulate and test this scaled up model. And the simulation gives our clients a wait to see what cloud is going to look like, feel like and how it's going to transform their business before they go there. >>Tell us a little bit about that in real life. Now as a company, so many of people are working remotely having to collaborate, uh, not in real life. How is that helping them right now? >>So, um, the, the pandemic has put a tremendous strain on systems, uh, because of the demand on those systems. And so we talk about resiliency. We also now need to collaborate across data across people. Um, I think all of us are calling from a variety of different places where our last year we were all at the cube itself. Um, and, and cloud technologies such as teams, zoom that we're we're leveraging now has fundamentally accelerated and clients are looking to onboard this for their capabilities. They're trying to accelerate their journey. They realize that now the cloud is what is going to become important for them to differentiate. Once we come out of the pandemic and the ability to collaborate with their employees, their partners, and their clients through these systems is becoming a true business differentiator for our clients. >>Sure. I want to talk with you now about my NABS multiple capabilities, um, and helping clients design and navigate their cloud journeys. Tell us a little bit about the green cloud advisor capability and its significance, particularly as so many companies are thinking more deeply and thoughtfully about sustainability. >>Yes. So since the launch of my NAB, we continue to enhance capabilities for our clients. One of the significant, uh, capabilities that we have enabled is the brain trust advisor today. You know, Rebecca, a lot of the businesses are more environmentally aware and are expanding efforts to decrease power consumption, uh, and obviously carbon emissions and, uh, and run a sustainable operations across every aspect of the enterprise. Uh, as a result, you're seeing an increasing trend in adoption of energy, efficient infrastructure in the global market. And one of the things that we did, a lot of research we found out is that there's an ability to influence our client's carbon footprint through a better cloud solution. And that's what we entered by brings to us, uh, in, in terms of a lot of the client connotation that you're seeing in Europe, North America and others, lot of our clients are accelerating to a green cloud strategy to unlock beta financial, societal and environmental benefit, uh, through obviously cloud-based circular, operational and sustainable products and services. That is something that, uh, we are enhancing my now and we are having active client discussions at this point of time. >>So Tristan, tell us a little bit about how this capability helps clients make greener. >>Yeah. Um, well, let's start about the investments from the cloud providers in renewable and sustainable energy. Um, they have most of the hyperscalers today, um, have been investing significantly on data centers that are run or renewable energy, some incredibly creative constructs on the how to do that. And sustainability is therefore a key, um, key item of importance for the hyperscalers and also for our clients who now are looking for sustainable energy. And it turns out this marriage is now possible. I can, we marry the, the green capabilities of the cloud providers with a sustainability agenda of our clients. And so what we look into way the mine EF works is it looks at industry benchmarks and evaluates our current clients, um, capabilities and carpet footprint leveraging their existing data centers. We then look to model from an end-to-end perspective, how the, their journey to the cloud leveraging sustainable and, um, and data centers with renewable energy. We look at how their solution will look like and, and quantify carbon tax credits, um, improve a green index score and provide quantifiable, um, green cloud capabilities and measurable outcomes to our clients, shareholders, stakeholders, clients, and customers, um, and our green plot advisors, sustainability solutions already been implemented at three clients. And in many cases in two cases has helped them reduce the carbon footprint by up to 400% through migration from their existing data center to green club. Very, very important. Yeah, >>That is remarkable. Now tell us a little bit about the kinds of clients. Is this, is this more interesting to clients in Europe? Would you say that it's catching on in the United States where we're at? What is the breakdown that you're seeing right now? >>Sustainability is becoming such a global agenda and we're seeing our clients, um, uh, tie this and put this at board level, um, uh, agenda and requirements across the globe. Um, Europe has specific constraints around data sovereignty, right, where they need their data in country, but from a green, a sustainability agenda, we see clients across all our markets, North America, Europe, and our growth markets adopt this. And we have seen case studies in all three markets >>Kisha. I want to bring you back into the conversation. Talk a little bit about how mine up ties into Accenture's cloud first strategy, your Accenture's CEO, Julie Sweet has talked about post COVID leadership requiring every business to become a cloud first business. Tell us a little bit about how this ethos is in Accenture and how you're sort of looking outward with it too. >>So Rebecca mine is the launch pad, uh, to a cloud first transformation for our clients. Uh, Accenture, see you, uh, Julie Sweet, uh, shared the Accenture cloud first and our substantial investment demonstrate our commitment and is delivering data value for our clients when they need it the most. And with the district transformation requiring cloud at scale, you know, we're seeing that in the post COVID leadership, it requires that every business should become a cloud business. And my nap helps them get there by evaluating the cloud landscape, navigating the complexity, modeling architecting and simulating an optimal cloud solution for our clients. And as Justin was sharing a greener cloud, Tristan, talk a little >>Bit more about some of the real life use cases in terms of what are we, what are clients seeing? What are the results? >>Yes, thank you, Rebecca. I would say two key things right around my now the first is the iterative process. Clients don't want to wait, um, until they get started, they want to get started and see what their journey is going to look like. And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need to move to cloud very quickly. And my nav is there to do that. So how do we do that? First is generating the business cases. Clients need to know in many cases that they have a business case by business case, we talk about the financial benefits, as well as the business outcomes, the green green cloud impact sustainability impacts with minus we can build initial recommendations using a basic understanding of their environment and benchmarks in weeks versus months with indicative value savings in the millions of dollars arranges. >>So for example, very recently, we worked with a global oil and gas company, and in only two weeks, we're able to provide an indicative savings for $27 million over five years. This enabled the client to get started, knowing that there is a business case benefit and then iterate on it. And this iteration is, I would say the second point that is particularly important with my nav that we've seen in bank, the clients, which is, um, any journey starts with an understanding of what is the application landscape and what are we trying to do with those, these initial assessments that used to take six to eight weeks are now taking anywhere from two to four weeks. So we're seeing a 40 to 50% reduction in the initial assessment, which gets clients started in their journey. And then finally we've had discussions with all of the hyperscalers to help partner with Accenture and leverage mine after prepared their detailed business case module as they're going to clients. And as they're accelerating the client's journey, so real results, real acceleration. And is there a journey? Do I have a business case and furthermore accelerating the journey once we are by giving the ability to work in an iterative approach, >>It sounds as though that the company that clients and and employees are sort of saying, this is an amazing time savings look at what I can do here in, in so much in a condensed amount of time, but in terms of getting everyone on board, one of the things we talked about last time we met, uh, Tristin was just how much, uh, how one of the obstacles is getting people to sign on and the new technologies and new platforms. Those are often the obstacles and struggles that companies face. Have you found that at all? Or what is sort of the feedback that you're getting from? >>Yeah. Sorry. Yes. We clearly, there are always obstacles to a con journey. If there weren't obstacles, all our clients would be already fully in the cloud. What man I gives the ability is to navigate through those, to start quickly. And then as we identify obstacles, we can simulate what things are going to look like. We can continue with certain parts of the journey while we deal with that obstacle. And it's a fundamental accelerator. Whereas in the past one, obstacle would prevent a class from starting. We can now start to address the obstacles one at a time while continuing and accelerating the contrary. That is the fundamental difference. Kishor I want to give you the final word here. Tell us a little bit about what is next for Accenture might have and what we'll be discussing next year at the Accenture executive summit >>Sort of echo, we are continuously evolving with our client needs and reinventing, reinventing for the future. For my advisor, our plan is to help our clients reduce carbon footprint and again, migrate to a green cloud. Uh, and additionally, we're looking at, you know, two capabilities, uh, which include sovereign cloud advisor, uh, with clients, especially in, in Europe and others are under pressure to meet stringent data norms that Kristen was talking about. And the sovereign cloud advisor health organization to create an architecture cloud architecture that complies with the green. Uh, I would say the data sound-bitey norms that is out there. The other element is around data to cloud. We are seeing massive migration, uh, for, uh, for a lot of the data to cloud. And there's a lot of migration hurdles that come within that. Uh, we have expanded mine app to support assessment capabilities, uh, for, uh, assessing applications, infrastructure, but also covering the entire state, including data and the code level to determine the right cloud solution. So we are, we are pushing the boundaries on what might have can do with mine. And we have created the ability to take the guesswork out of cloud, navigate the complexity. We are rolling risks costs, and we are achieving clients strategy, business objectives, while building a sustainable lots with being cloud, >>Any platform that can take some of the guesswork out of the future. I'm I'm on board with. Thank you so much, Kristin and Kishore. This has been a great conversation. Thank you, Rebecca. Thank you, Rebecca. Stay tuned for more of the cubes coverage of the Accenture executive summit. I'm Rebecca Knight. >>Yeah, Yeah.

Published Date : Dec 1 2020

SUMMARY :

It's the cube with digital coverage Welcome to cube three 60 fives coverage of the Accenture executive summit. Thanks for having me here. impact of the COVID-19 pandemic has been, what are you hearing from clients? you know, various facets, you know, um, first and foremost, to this reasonably okay, and are, you know, launching to So you just talked about the widening gap. all the changes the pandemic has brought to them. in the cloud that we are going to see. Can you tell us a little bit more about what this strategy entails? all of the systems under which they attract need to be liberated so that you could drive now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, the employees are able to embrace this change. across every department, I'm the agent of this change is going to be the employees or weapon, And because the change management is, is often the hardest And that is again, the power of cloud. And the power of cloud is to get all of these capabilities from outside that employee, the employee will be more engaged in his or her job and therefore And this is, um, you know, no more true than how So at Accenture, you have long, long, deep Stan, sorry, And in fact, in the cloud world, it was one of the first, um, And one great example is what we are doing with Takeda, uh, billable, to drive more customer insights, um, come up with breakthrough Yeah, the future to the next, you know, base camp, as I would call it to further this productivity, And the evolution that is going to happen where, you know, the human grace of mankind, I genuinely believe that cloud first is going to be the forefront of that change Thank you so much for joining us Karthik. It's the cube with digital coverage And what happens when you bring together the scientific, And Brian Beau Han global director and head of the Accenture AWS business group at Amazon Um, and I think that, you know, there's a, there's a need ultimately to, And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. And I think that, you know, that's going to help us make faster, better decisions. Um, and so I think with that, you know, there's a few different, it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. So Arjun, I want to bring you into this conversation a little bit. uh, something that, you know, we had all to do differently. in the governance and every level of leadership, we always think about this as a collective the same way, the North side, the same way, And I think if you really think about what he's talking about, Because the old ways of thinking where you've got application people and infrastructure, How will their experience of work change and how are you helping re-imagine and And it's something that, you know, I think we all have to think a lot about, I mean, And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are Uh, and so I think that that's, you know, one, one element that can be considered. or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently the customer obsession and this idea of innovating much more quickly. of the things that, you know, a partner like AWS brings to the table is we talk a lot about builders, And it's not just the technical people or the it people who are you know, some decisions, what we call it at Amazon are two two-way doors, meaning you can go through that door, And so we chose, you know, uh, with our focus on, I want you to close this out here. sort of been great for me to see is that when people think about cloud, you know, Well, thank you so much. Yeah, it's been fun. It's the cube with digital coverage of How big is the force and also what were some of the challenges that you were grappling with Um, so the reason we sort of embarked um, you know, certainly as a, as an it leader and sort of my operational colleagues, What is the art of the possible, can you tell us a little bit about why you the public sector that, you know, there are many rules and regulations quite rightly as you would expect Matthew, I want to bring you into the conversation a little bit here. to bring in a number of the different themes that we have say cloud themes, security teams, um, So much of this is about embracing comprehensive change to experiment, the outcomes they're looking to achieve rather than simply focusing on the long list of requirements I think was critical So to give you a little bit of context, when we, um, started And the pilot was so successful. And I think just parallel to that is the quality of our data because we had a lot of data, And have you seen that kind of return on investment because what you were just describing with all the steps Um, but all the, you know, the minutes here and that certainly add up Have you seen any changes And Helen is the leader from an IOT perspective. And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain You know, we had lots of workshops and seminars where we all talk about, you know, see, you know, to see the stack change, you know, and, and if we, if we have any issues now it's literally, when you are trying to get everyone on board for this kind of thing? the 30 day challenge and nudge theory around how can we gradually encourage people to use things? I want to hear, where do you go from here? not that simple, but, um, you know, we've, we've been through significant change in the last And I see now that we have good at embedded in operational So I want to ask Stuart you first, if you can talk about this transformation and stuck in the old it groove of, you know, capital refresh, um, of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually I want to just real quick and redirect to you and say, you know, for all the people who said, Oh yeah, And, um, you know, Australia, we had to live through Bush fires by the Navy allowed us to work in this unprecedented gear Because I've been saying on the Cuban reporting, necessity's the mother of all and always the only critical path to be done. And what specifically did you guys do at Accenture and how did it all come applications to the cloud now, you know, one of the things that, uh, no we did not along uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment How did you address your approach to the cloud and what was your experience? And then building upon it, and then, you know, partnering with Accenture allows because the kind of, uh, you know, digital transformation, cloud transformation, learnings, um, that might've differed from the expectation we all been there, Hey, you know, It's, it's getting that last bit over the line and making sure that you haven't invested in the future hundred percent of the time, they'll say yes, until you start to lay out to them, okay, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value, Um, you know, that's all stood up on AWS and is a significant portion of And I think our next big step is going to be obviously, So, um, you know, having a lot of that legwork done for us and AWS gives you that, So obviously, you know, lines like an antivirus, but, you know, we knew it was a very good So, um, you know, really good behaviors as an a lot of people kind of going through the same process, knowing what you guys know now, And, and we had all of our people working remotely, um, within, uh, you know, effectively one business day. the time you talk about, um, you know, less this, the, and all of these kinds of things. And this is really about you guys getting It was actually linked to broader business changes, you know, creating basically a digital platform Stuart and Douglas, you don't mind waiting, and what's the priorities for the future. to figure out how we unlock that value, um, you know, drive our costs down our efficiency, our customer base, um, that, uh, that we continue to, you know, sell our products to and work with Uh, and adopting more new ways of working as far as, you know, the state of the business. And it takes time with this stuff, but, uh, uh, you know, Did the work you were in that it's all coming together with faster, What was the problem you were trying to solve at shell? And that, that was at the time that we called it as the, make money out of how we start a day that we can make money out of, if you have access to the data, we can explore the data. What were some of the things you were trying to achieve with the OSD? So the first thing we did is really breaking the link between the application, I've got the data no longer linked to somebody whose application was all freely available for an API layer. And to bring you in here a little bit, can you talk a little bit about some of the imperatives from the a lot of goods when we started rolling out and put in production, the old you are three and bubble because we are So one of the other things that we talk a lot about here on the cube is sustainability. of that to exploit the data, to meet again in a single data platform. purchases, four 51 found that AWS performs the same task with an So that customers benefit from the only commercial cloud that's had hits service offerings and You've been at the into to a single data platform. And he saw a student and B all the data together into a single data club. Um, honestly, the incredibly cool thing about working at AWS is you who knows what happens in 10 years, but if you look what our whole objective is that really in the next five Thank you so much for coming on the cube virtual, It's the cube with digital coverage of He is the Accenture senior managing director cloud first global services Thank you very much. He is the managing director, Great to see you again, Rebecca. Even in this virtual format, it is good to see your faces. So my NAB is a platform that is really celebrating to make it faster and obviously innovate in the cloud, uh, you know, with the increased relevance I want to go to you now trust and tell us a little bit about how my nav works and how it helps One of the big focus now is to accelerate. having to collaborate, uh, not in real life. They realize that now the cloud is what is going to become important for them to differentiate. about the green cloud advisor capability and its significance, particularly as so many companies And one of the things that we did, a lot of research we found out is that there's an ability to influence or renewable energy, some incredibly creative constructs on the how to do that. What is the breakdown that you're seeing right now? And we have seen case studies in all I want to bring you back into the conversation. And with the district transformation requiring cloud at scale, you know, we're seeing that in And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need This enabled the client to get started, knowing that there is a business is getting people to sign on and the new technologies and new platforms. What man I gives the ability is to navigate through those, to start quickly. And the sovereign cloud advisor health organization to create an Any platform that can take some of the guesswork out of the future.

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Michael Dell, Dell Technologies | Dell Technologies World 2020


 

>> Narrator: From around the globe. It's theCUBE with digital coverage of Dell Technologies, World Digital Experience brought to you by Dell Technologies. >> And welcome back to theCUBE's coverage of the Dell Technology World Digital Experience 2020. I'm John Furrier your host of theCUBE. This is theCUBE virtual. It's a virtual event. We're not in person this year, obviously because of the COVID pandemic, our guest Michael Dell, the CEO of Dell Technologies. Great to see him back on again and remotely. Michael, sorry we couldn't be there in person but thank you for coming on virtually. Thanks for coming on. >> Great to be with you John. >> You know what a year it's been. I got to say, it's been one of those years where you don't know what's going to happen next. And it's been kind of crazy. I want to get your take on how you guys are getting through it. And specifically you guys have had great business performance. We've seen the results of what's going on with Dell Technologies, VMware, but there's a crisis. People need more machines, they need more internet access. There's a huge demand for modern applications with cloud and on-premises, not everyone's going to be there on-premises. So the workplace, the workforce, the workloads are all changing, but you hit all of them. The consumer from having a great machine, internet access, this kind of digital divide where people are remote schooling is super important. Can you talk about how you guys are doing, how the company's doing, how you're doing and what you guys are doing to help bridge this new cultural environment of this digital divide? >> Sure. So again, great to be with you and thanks for all your great coverage at Dell Technologies World. Once again this time virtually. Look, I think having a resilient supply chain is always important but these last eight months it's been incredibly important. Demand has certainly shifted around and having you know, secure remote work from anywhere has been a high priority for lots of organizations. I think something like 4.5 billion people were asked to go stay in their homes. So, you know it was work from home, learn from home, entertainment, E-commerce, telemedicine, everything went online and I think we got a glimpse of the future. And I think a lot of this actually gets carried forward. And certainly the priorities that we've been focused on, you know multicloud, app modernization and containers, the tremendous growth at the edge, data management, software defining the networks, AI, 5G, all these things I think get accelerated. So amid the tragedy and the challenges. I do think there's a great acceleration of the fourth industrial revolution. >> You brought this up last time, last year as well. And again this is pre everything's kind of going to be before COVID kind of after the COVID world, but you were kind of teasing this out last year and I want to get your thoughts because now more than ever, you mentioned some people don't have laptops to even do the remote work and remote schooling. And then internet access has been discussed for generation of having more broadband in areas that are underserved. This is a super important piece. Can you just share some of the initiatives that you guys are taking because I know you guys have some things going on, you're doing a lot of philanthropy. Again the supply chain is on the business side is super important, but you know specifically this society, how are you guys helping? >> Right. So, you know just in the United States, you've got roughly 15 million kids who don't have either the broadband access or a device. And we've got a pilot program running to begin to address this. And, you know it's part of the broader 2030 moonshot goals that we laid out, you know actually last year for the next decade. But I do think, you know what the pandemic exposed, it exposed the fault lines in our society in access to healthcare, to education, to justice and certainly, you know we have a kind of digital inequality, right? If you don't have a device and you don't have access, you're left out of economic opportunity and you know that's something we should all be focused on. We believe, our broader ecosystem can make a big difference there. And it's one of our priorities. >> You know technology has been a big enabler over the years. You know we've talked many times privately also on theCUBE around these inflection points. I mean you started Dell technologies in your dorm room and now you got kids doing stuff in the elementary, (indistinct) to the thing on space with, you know cybersecurity and space is a big trend and they're starting early in elementary school. Now you got the boardroom and everywhere in between. The tech trends are the big opportunity. You know I want to dig into it. And I want to get your thoughts because you know with cloud computing, gen one, you say check, scale, it matters. But the big wave right now is everything as a service. And so you got to be nimble. You got to be agile. But that's easy to say and hard to do. I want to get your thoughts on how you see everything as a service from platform to SaaS, to developer as a service, to cube as a service, to Dell as a service. Everything is becoming a service. What's under the covers there because it's not easy. Automation machine learning. What do you seek? This is going to get us out of the pandemic as more people are agile. Give me your thoughts. >> That's right. So, you know we've actually, as you point out, we've been at this for awhile and you know if you look on our balance sheet, you'll see almost $24 billion deferred revenues. So it's not a completely new idea to us. And we are aggressively expanding as a service. So our customers and partners can access our solutions anyway they want and we're committed to making everything that we provide available as a service. And one of the things we're talking a lot about here at Dell Technologies World is providing a consistent experience no matter where customers run their workloads. And so we've unveiled project Apex, which is really bringing together all of our as a service and cloud offerings into a consistent unified effort. We're enhancing the Dell technologies cloud console. And this is going to give customers the power to manage every aspect of their cloud journey. And as a service journey through a simple unified self service experience. We're going to be talking a lot about storage as a service. Storage is always important to Dell technologies and providing scalable lastic storage resources that can be deployed, owned and managed on premise, but owned by Dell Technologies. And we're going to bring some updates to the Dell Technologies cloud platform to make it easier, simpler to consume, lower the barriers to entry and extending our subscription availability. >> You know in the platform businesses and all the people talk about platforms. And over the years, when you have a platform business you have to kind of dog food or kind of you know, do it first before the customers dig in to using the service. You mentioned, you guys have been doing Dell as a service across your product lines, and we've documented that certainly on SiliconANGLE in theCUBE, but now you got to bring it to customers. Can you tell me how that's going because with the pandemic, some things are obviously customers need to double down on building modern apps, having programmable infrastructure. As you guys have everything as a service from the Dell side. Now the customers have to do their part. They've turned their offerings into as a service. Can you take us through trends you're seeing in your customer base around the pandemic? And you know this is a permanent is a cyclical. What's the customer impact of everything as a service. >> I think this is clearly the demand, you know trend (laughs) from customers. And, as I said we've been embracing it for some time. One of the reasons we created this project Apex is to bring it all together because I would say we want to to go faster right? (laughs) And we always want to to go faster. And the, you know what you've seen from customers in the last eight months is you kind of exposed the digitally enabled and the not so much digitally enabled. And, a lot of customers have accelerated their progress on their digital journey quite a bit during these last eight months. And, you know as I said, I think a lot of that gets carried forward. You know we ourselves, over a weekend basically said, okay everybody work from home now has worked really well. There's lots of benefits to that. There are productivity benefits, environmental benefits. And I think we're all finding ways that we could be more productive. And I think a lot of this will persist after the pandemic. >> Yeah. When we were covering VMworld just recently this event that they had the virtual event. What came out of that was the 5G trend. And some of the conversation was 5G is not a consumer app. It's really a business app. Could you share your thoughts on 5G? Because it will enable the edge, intelligent edge 5G is super important. What's your vision on how 5G will roll out? Do you agree with it more as a business app not so much consumer? >> Yeah. I mean the first application will be, hey let's have 5G phones. Great. But you really can't talk faster all right, on your 5G phone. (laughs) So what is this all about? It's about making things intelligent and having the things talk to each other and they're going to be way more things talking to each other than there are people. Imagine every arm processor or embedded processor out there in the world now being connected and intelligent, the amount of data that gets created. So it's really about connecting all the things. And that is you know incredibly exciting possibility. Organizations have to reimagine themselves. Given that future and 5G will be the digital fabric that allows this new future to be created. >> When you look at Dell Technologies out 10 years to 2030, what does it look like as you eliminate about the internet things and the edge, what's the vision for Dell 2030? >> So first I think you're going to have autonomous infrastructure and it's going to be highly distributed on the intelligent edge. And that's going to enable enormous advances in really all human endeavors and Dell Technologies is going to be the essential infrastructure company to power all of this. And, you know our moonshot goals point the way in another sense, where we talk about advancing sustainability, cultivating inclusion, transforming lives and upholding ethics and data privacy. And you know we didn't create those priorities for the last eight months, but certainly the last eight months put a real magnifying glass and exclamation point on their importance. And, you know we continue to be super optimistic about the role technology has in the world and the role that we can play in helping customers achieve that. >> And the role of cloud is cloud going to be abstracted away? Is that cloud going to continue to be a big part of it as cloud on premise, mean as these environments look more cloud-like operationally and autonomous, does that kind of go away in 10 years? Do you see that becoming just part of the resource pool? How do you view that? >> Well, clouds are infrastructure, right? So you can have a public cloud, you can have an edge cloud, a private cloud, a Telco cloud, or hybrid cloud, or multicloud, here cloud, there cloud, everywhere cloud cloud. Yet, they'll all be there, but it's basically infrastructure. And how do you make that as easy to consume and create the flexibility that enables everything. >> Yeah. And we saw that VMware, they had talked about telco cloud as a trend. We see that everything's going to be a cloud. Everything will be a service. That's our view. I want to get your thoughts on entrepreneurial thinking. You've always been an entrepreneur, even as you've got this massively billions of dollars in companies out there you're still innovating. Right now entrepreneurial thinking is needed more than ever. And can you share your advice to people out there who wanted to be more digitally enabled, who have to think about the next 10 years. What entrepreneurial thinking can they apply now? Because let's face it COVID has exposed what needs to be worked on what should not be worked on. So there's clearly a digital push there. What entrepreneurial tactics what would you share with the folks out there who really want to be on the wave here and be digitally enabled position for the future? >> Well, you know I kind of started with experiment, take a risk, find a new problem and figure out how to go solve it. And look, I continue to be inspired by all the new entrepreneurs and new companies out there being created. And while there's certainly, you know one trend in consolidation in parts of our industry, there are always new and interesting things happening in the world of technology. And that's where you see a lot of these new companies being created. And you know that always excites me. I don't see too much of a shortage of entrepreneurial thinking out there, but well you know use more of it because that's how the world pushes forward when you have people with new ideas, willing to take risks, capital available to, you know support that risk-taking, you know that's where you get new innovation. >> Yeah. I could see the opportunities executed on them. I want to get your thoughts on AI, obviously as we've seen huge backlash on some of the, with the elections here going on, and you got all the, you know, tech for good on one side, tech for bad on the other and everything in between. Technology isn't any abler. And it does have some consequences, but there's some great things going on with technology. I know you've been advocate for the past two years of specifically hardcore for technology for good. As AI becomes more prominent as machine learning and data comes into the picture, can you give your thoughts on where we are with technology for good? What are some of the highlights and what areas we need to work more on? And how has the role data and AI play in it? >> I do think technology is overwhelmingly used for good and, you know long time ago, you know fire was technology, right? Somebody came to the village and said, "Hey we got this new thing you know called fire. "And you know it can warm a home "or it could burn down the whole village." But overwhelmingly technology innovations have advanced human progress. And I only think it's accelerating from here. And as everything becomes intelligent and connected, AI is the only way to double reason over all that data, especially the streaming data in real time. And all of that is going to accrue positively to great human outcomes. And every business has to reimagine itself, to create better products and services, to create better outcomes for the students, the patients, for manufacturing to create success and competitive advantage, and you know AI machine learning. These are just tools. Sure there are always going to be challenges, but we as humans have to make sure that the tools are used overwhelmingly for good. Again, I tend to be optimistic. I think the vast majority of people do want to do good things in the world. And so prevent against the kind of worst case scenarios but, I remain optimistic. >> Why are the wheel tools? It's all about the humans running them. And that's a big impact. Michael, thanks for coming on. Really appreciate you coming on virtually with theCUBE and thanks for allowing us to be part of your virtual digital experience. For the final word just share for a minute, what people should walk away with this year. I know it's virtual. It's not face to face. It's a very intimate event when it's held face to face, but you're doing a virtual, a lot of content out there. But for the people watching, what should they walk away with this year from the Dell Technology World Digital Experience? What's the main message? >> So you know Dell Technologies wants as ever to be your best partner in the digital transformation. And we're investing heavily in multicloud, in the edge, in data management, software defining the networks, providing the compute to deal with all these enormous workloads with AI, at 5G and continuing to create this secure work from anywhere environment. So, again, thanks to our customers and partners for the tremendous trust they place in us. And we're looking forward to a great year ahead. >> Well thanks for everything that you do. I know you're just planning a lot of equipment for kids in school and for businesses and continue to innovate. You're doing your part with the supply chain. Thank you for having your team stay on that. Of course, we're doing our part trying our best to get the content out there. Thank you so much for the time, Michael. Great to see you. I hope to see you in person soon. Thank you for coming on. >> Thank you John. >> Okay, this is theCUBE covering Dell Technology World Digital Experience 2020. I'm John Furrier your host. Thanks for watching. (upbeat music)

Published Date : Oct 21 2020

SUMMARY :

brought to you by Dell obviously because of the COVID pandemic, and what you guys are doing to help bridge So, you know it was work I know you guys have some things going on, But I do think, you know And so you got to be and you know if you look And you know this is a the demand, you know And some of the conversation and having the things talk to each other And you know we didn't And how do you make And can you share your advice And you know that always excites me. And how has the role and you know AI machine learning. But for the people watching, providing the compute to deal with all to see you in person soon. I'm John Furrier your

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Chris Wegmann, Accenture & Brian Bohan, AWS | Accenture Executive Summit at AWS re:Invent 2019


 

>> Voiceover: Live from Las Vegas it's theCUBE covering AWS Executive Summit. Brought to you by Accenture. >> Welcome back everyone to theCUBE's live coverage of the Accenture Executive Summit here at AWS re:Invent. I'm your host Rebecca Knight co-hosting alongside of Donald Klein. We have two guests for this segment. We have Brian Bohan, he is the Director of the Accenture Amazon Web Services Business Group Global Lead at AWS, and Chris Wegmann, Managing Director Accenture Amazon Web Services Business Group. Oh my word (all laugh) how big are your business cards? >> Exactly >> Well welcome for both of you Thanks for coming on the show. So the relationship between AWS and Accenture is now in its 13th year. I want to hear from both of you, what's new what's exciting about the relationship and I'm going to start with you Chris. >> Yeah, so it's been 13 great years. Four years since we used the AABG, we use the acronym to make it easier to say >> Rebecca: Okay, thank you, and now you tell me. >> The Accenture AWS Business Group. So the partnership continues to get stronger, continues to grow, we've doubled down on the partnership this last year, really increasing our investment and our focus. We've done in the last year really a lot of focus around industries. So we continue to build our teams we continue to grow on the number of certified resources we have. And our clients are just eatin' that stuff up. So it just gives us more opportunity to grow. >> Ryan? >> Yeah, I mean I think you can see, it's consistent with what you see here at the event and also with Andy's keynote. The emphasis on enterprise and as we see large enterprises really accelerating to AWS, I think that's what we're seeing as well. At any given time we have hundreds of projects going on around the world, but when we formed the business group in 2015 it was really around driving really large transformations with customers and what we're seeing now is customers at the place of maturity and willing to take, embark on those journeys and I think we're really well set up to make that happen together as a partnership. >> So as you kind of enter into this new phase now of kind of working with companies, are you seeing any kind of increasing specialization in the types of companies you're working with? >> Yeah, no absolutely. So I think that's why the answer's really exciting. So I think if you look across this is fairly typical. We started out in a lot of horizontal capability areas and they're still incredibly important to us around data and SAP, mass migrations and these are areas we continue to invest in and we tend to get even more specialized as we do so, but we're also seeing this last year is getting more industry focused. So as we move up the stack and we start talking about cloud native development, we start talking about machine learning and analytics, customer care has become a really interesting thing. So you see a lot of companies, whether it be tire companies, CPG companies, moving from products companies extending into services, it completely changes how they think about customer care and how they need to understand their data and understand their customers. So necessarily as you move up that stack, you have to have that deep domain expertise and so what's fantastic is we have great technology, we're building out some teams with domain expertise, but Accenture has got thousands of people with this expertise. So it's again this kind of combining of strengths that we're able to bring to the table for our customers. >> Yeah we saw when we started the group, we knew Accenture's strong position in industries, right. Our deep industry knowledge, knowing those industries really well we knew they would come together at some point, the technology and industry. And we've seen that over the last 12 months really start to take effect. Companies are now specifically thinking about how they leverage Amazon for their specifically industry solutions and capabilities, and we're just going after that. >> So Andy Jassy in his fireside chat this morning talked about innovation at AWS and he said, we're a big company but we need to think of ourselves as a big startup. So here are two big companies, how do you innovate together what is your relationship like? I mean you said it's 13 great years, but what's your creative process? >> So I'll take a stab. So first of all, I'll say that in recognition of that we actually on our team, and this year into some light of and Chris mentioned a doubling down the partnership, we're growing the team we have on the AWS side to support the partnership. And with some of the things we're doing in addition to adding industry folks, is I've added a full time team to focus on innovation. And it's innovation with customers but it's also all the mechanisms we use. So if you think about with AWS, a lot of customers come to us and want to understand how does Amazon innovate, what is our culture of innovation? So at Amazon we have a program that we've rolled out around that. Accenture also has many mechanisms around innovation. Small teams driving very agile projects, and it's our job, that team's job and my team to go around and pull the best of breed across the world and make sure that we're delivering that to clients every single day. And so more and more clients want to see not just the outputs, but they want us to imbed in their teams and also show them by doing. So yes, give us the deliverable but we want to build the muscle around what Accenture and AWS can do together around innovation. So that's more and more what we see. >> Yeah and we follow the Amazon principles, right. The principles that Andy talks about that are core to innovation there, we follow them. From the beginning when we started this partnership we started working backwards, what we wanted it to be in five, ten years and we follow those. So our teams act that way, they work that way, they follow those day to day out and it makes us, it allows us to integrate well into AWS into the AWS people around the world. For Accenture it gives us, our people a insight into how AWS does it, and then we can share that with our customers as well. >> Interesting, so Chris you've been doing this a long time. Right, okay and so, and you guys have been collaborating for a long time, when Amazon first started there was a whole new breed of companies they were coming out, we'd call kind of born in the cloud. Companies that were agile and fast moving, taking advantage of a lot of the technology stack to do things that a lot of legacy companies couldn't do. Now we're starting to see what has been termed kind of companies being reborn in the cloud, right. Older, leg--, you know older companies now that are transforming moving their workloads to the cloud and then getting new types of capabilities. I'm wondering in your work, are you seeing some examples of companies that are kind of undergoing that kind of transformation? >> Yeah absolutely. I think we see what we would call an epic disruption of these companies right. It's happening, it's been happening for awhile. I think they've gotten, they've looked at Amazon now more as not just a cloud, and not just infrastructure, going up the stack and doing that. So they're going through these transformations and we see them balancing between moving their workloads to AWS versus innovating. And also changing, they've realized they have to change the organization to go along with that. It's just not moving and acting in the same old way so we're seeing agile and cloud come together to drive that transformation. So I would say almost every customer we're seeing today is going through that transformation in some form or fashion >> Yeah, I would say that's also a really interesting change Again, years ago we were, if you were focused on a mass migration today, the conversation is if you're a pharmaceutical company how do you get your pipeline of therapeutics out to market faster, right? How do you start thinking about patients differently or patient services, the data you have on those patients how do you integrate further into the value chain and to providers and payers and get that information. So, and what happens, what you find is to be able to deliver say precision medicine and pharmaceutical you need to rethink about your data, then you have to look at your application portfolio and say, okay what does that need to look like to support this completely new paradigm serving our patients? And that's what ends up pulling the workloads through to support these new business initiatives. So I think that's a bit of a difference that we've been seeing as well in the last couple years. >> One of the messages we're hearing is that journeys of the cloud really represents the fourth industrial revolution. I'm wondering, in terms of the pace of innovation are there any new technologies that maybe even just from a couple of years ago that are just table stakes today? >> Yeah no, I think the table stakes, AI and ML are quickly becoming table stakes, right. And that's what I love about AWS, they make the stuff easy to consume. Right, SageMaker and that stuff. Last year I was able to go in through DeepRacer and going through that I was able to do a model in 30 minutes. I don't do a lot of coding anymore these days, but on a plane I was able to create my first model. And so that stuff is becoming table stakes. They're making it very easy, so there is no excuse to not do ML or AI in your application. I don't need a separate set of data scientists sitting off to the side. So that to me, and data in the cloud, right. So the data being there so I can consume it in AI and ML that's table stakes, there is no more hey, I'm just only going to put what I don't care about, or what I want to low cost data store, it's table stakes to have that data there, accessible to your people 24-7. >> And what does that mean for your workforce? Because as you said, these are now basics. You need to know how to use these tools and be willing to experiment with these technologies. How do you make sure your workforce has the right skills and the right mentality and approach? >> So one of the things I talked a little bit about DeepRacer last year when DeepRacer came out, I was sitting there kind of scratching my head and saying, what is this, right? It's a glorified RC car. And one of my team members was texting me and saying, we've got to do this. And what that, we've run a private league, and what that's done is it's taken well over 1400 people who never knew what machine learning, R-reinforcement learning was and got them engaged in doing it. So now they've got that experience, they're now hungry for more knowledge through a fun activity, a competition. You know we're all very competitive people at Accenture, so that was just, it caught on amazing, it was amazing just around the world at how these people took onto it and why our employees took onto it. >> Yeah, the person who won that league, so it was across 30 different innovation centers at Accenture, plus hundreds of people virtually building cars, and the guy who won it out of Kronsberg, Germany had never touched AWS the day before. And I dunno if this is true, the story's great, he supposedly wrote his model on the train to the innovation center that day, he ran the model and came up like four one hundredths of a second off the world record. So great example, yeah, of somebody who wasn't in the AWS kind ecosystem at Accenture, got turned on my this new technology, this new capability, dove in and now he's enabled, right. And we talk about innovation, so innovation is also like I said, not just what you're delivering for the client but how you're doing it. So that same team actually who started the DeepRacer league down in Australia, they've been creating what they call a hackathon as a service. So working with customers, not just doing slideware and going through courseware, but getting folks in a room like this and you've seen it here at the event, have a business problem that you want to solve, get a bunch of people in a room, business people, technology people, and hack away. In a low risk environment that's collaborative where you can share and you're learning by doing. So we're seeing a lot of that, and so you've got to really, like think of new ways that you're going to enable the workforce especially if you hope to scale this. >> So one of the things obviously that Accenture brings to the table, AWS got a global platform but you're a consulting firm with global reach. And everybody wants to use data in new ways but how you use data in different regions and different localities can vary. So how are you working with customers to be able to kind of enable that? >> Yeah, so obviously a lot of different regulations, country by country, and they're changing very rapidly so we have to stay on top of it. One of the things we've done is through our we formed a state of business group last year. We've completely focused on data. Includes AABG folks, Amazon folks, but they're very regionally based. So we stood up a lighthouse here in North America, in New Jersey, and the experts sitting in that are very well versed in what North America or the US is doing around data privacy and security and things like that. So they're taking what they learned, the same thing, we opened it in London last, a few weeks ago in Canada, other places. So we're definitely taking a regional focus but we're making sure through the partnership that the techniques, the tooling, the capabilities are being pushed down into those groups. So they're taking all that experience and that knowledge but putting a local slant to it and making sure it's locally compatible. >> Yeah, I mean what's interesting too is you talk about, I mean data we're seeing this take off in every industry and it's so critical, but two of the areas that the data business group is seeing the most traction actually are financial services and life sciences pharmaceutical health care. So you would think, those are two of the most regulated industries in the world, extremely sensitive data, you wouldn't think those would be the ones out in front but they are, and because there's so much value to be had. So even in Europe, working with pharmaceutical companies there together, and their R and D process around patient services and being able to use native data lakes on AWS, use machine learning to gain new insights in terms of how therapeutics are working on patient populations, right. And so this is again, very sensitive information but hugely valuable, and Accenture through this business group has all the capabilities so that we can have the best of both worlds, right. And have it accessible, analyze it in AWS but have it secure as well. >> And a lot of research show, actually the constraints can power innovation. The fact that it, because it is so sensitive and there are these regulatory concerns around it that that in fact enables people to be more, they're forced to be more creative. >> Yeah, and it's the old, you know cars didn't go fast until they put brakes on them, kind of a thing, right. And we see that, absolutely. And I think that sort to thing is, big enterprise customers, they want to move fast but they're public companies, they have to ensure that they're mitigating risk. So again we're investing a lot in moving fast but doing it in a way that controls risk and is able to kind of give them the assurances that they need. >> And definitely the platformed has helped, right. Amazon investing in that platform, bringing the tools like you saw on Andy's keynote, some things around the S3 bucket, you know those type of things. Those are enabling, and those regulations, us to deal with those regulations much faster and less work on our side to build the things that are need to meet those regulations. So definitely the platform growing and expanding is definitely helping us go faster. >> That's a great point, right. I mean because also if you have, you know whether your data, your applications in your on-premises environment chances are you don't have the granular visibility that you would like into that environment, whereas you move it into AWS, you have all these tools to really get as granular as you want and really understand your environment and make sure that you have control over it. So it really creates a new paradigm for that. >> One of the things that really struck me during Andy's keynote yesterday, Andy Jassy's keynote, was the fact when we was announcing all these, this dizzying number of new products and services >> Brian: I'm not sure how he does that (all laugh) >> I know, just how many of them rely on the technology ecosystem to be successful. So can you just riff on that a little bit about how really the landscape for technology has changed so dramatically in the sense that all these companies need to cooperate and collaborate, and here we are. You two, you're a living and breathing example. >> Absolutely, you know I think you'll hear Andy say it, is the right tool for the right job. AWS, we're very much about giving customers choice. So there's a lot of options and you know we went through all the different database options that we have. So they're very specific to specific use cases. Now that also implies that you have to know which tools to use for the right job and you have to have very skilled craftsmen. So that's where we rely on partners like Accenture who have those skilled craftsmen, in addition to our own to really extend that. And then you look at the ISV ecosystem, right and some of those ISVs and our technology partners who've done an amazing job of taking our capabilities but then extending them further into whatever domain that they're very expert in, and there's a very specific IP delivers extra value to their customers. And so that's what, we want to give all this choice, whether it's a customer, or a technology partner, a consultancy like Accenture can really thrive. >> And I think if you walk through the show floor you see what these companies are doing. And they're not afraid to innovate and they're not afraid to take on some of the bigger challenges out there because they don't have to invest in the platform underneath. They're able to start with something that's solid, known, recognized by the market, right. No one is going to get in trouble for building something on AWS. So they're taking that and taking the next level and you're right, the partnerships between 'em we see if you just walk down there, you see them talking, you see them collaborating and saying, oh well I'm doing this, if we integrate this, can we do this differently? So you know I think we're only going to see more of that. And we're going to see it more industry focused, coming back to what we were talking about earlier. We're going to see more things stand up in the industries. We've seen this with FinServ, we've seen this you know but I think across all the industries we're going to see more of this collaboration. >> Yeah, I agree, in fact I have someone on my team now that's new this year to focus exclusively on we'll call the power of three. So it's AWS, Accenture, and plus a technology partner. And so if you go in the Executive Summit, Salesforce being a really obviously example, right. Accenture's got very large successful Salesforce practice very important partner of AWS's, how can we come together and drive more value for our customers by figuring out solutions. You know we announced at Dreamforce, the connect integration with Salesforce that's a perfect example, right. So the end-to-end customer care I talked about earlier, even more powerful, we can bring that power of three together. >> So going into the 13th year, lucky 13 (laughs) what are some of the things we're going to be talking about at next year's Executive Summit? What are some of the things you're most looking forward to in the coming year? >> I have to say machine learning and AI. And I have to say Outposts is probably the third of my, I think I live the quantum computing stuff, and Accenture has been doing a lot of research and a lot of work in quantum computing. We were super excited to see what was announced, I guess Monday, and so we're super excited about that but I think that's a little farther out. I think the ML, the AI, the new things in SageMaker are super exciting and I think are only going to make that stuff go faster. So I think that's all we're going to be talking about next year I think we're going to be talking about all the new models that have been created, all the new problems that have been solved, and just a new paradigm in computing off of that stuff 'cause it's getting simpler to use, faster to use, and cheaper to use so that's what I'm most excited about. >> Yeah, I mean I think it's just, these announcements yesterday just continue to remove barriers, and so you think about the announcement with Verizon around 5G, so now the possibilities that opens up in terms of the applications and the analysis and the machine learning that can get pushed down to the edge is really amazing. And I think what's going to be fun is, we work with customers to figure out what these services should look like, but even at launch we're not sure how they're going to be used. So now it's going to be really exciting turning all these developers, all the Accenture developers, loose on this and just let's see what we create together. >> In 2020 all the developers are loose, I love it. (all laugh) Brian, Chris thank you so much for coming on theCUBE again. That was a really great conversation. >> Well, thanks for having us >> Thanks for having us >> I'm Rebecca Knight for Donald Klein. Stay tuned for more of theCUBE's live coverage of the Accenture Executive Summit coming up in just a little bit. (electronic music)

Published Date : Dec 5 2019

SUMMARY :

Brought to you by Accenture. of the Accenture Executive Summit here at AWS re:Invent. and I'm going to start with you Chris. to make it easier to say So the partnership continues to get stronger, I think you can see, it's consistent with what you see here and how they need to understand their data and we're just going after that. So here are two big companies, how do you innovate together but it's also all the mechanisms we use. that are core to innovation there, we follow them. kind of companies being reborn in the cloud, right. the organization to go along with that. So, and what happens, what you find is One of the messages we're hearing So that to me, and data in the cloud, right. has the right skills and the right mentality and approach? So one of the things I talked a little bit about DeepRacer and the guy who won it out of Kronsberg, Germany So one of the things obviously that Accenture the same thing, we opened it in London last, and being able to use native data lakes on AWS, that that in fact enables people to be more, Yeah, and it's the old, you know bringing the tools like you saw on Andy's keynote, and make sure that you have control over it. on the technology ecosystem to be successful. and you have to have very skilled craftsmen. and they're not afraid to take on So the end-to-end customer care I talked about earlier, And I have to say Outposts is probably the third of my, and the machine learning that can In 2020 all the developers are loose, I love it. of the Accenture Executive Summit

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Amol Phadke, Accenture & Greg Sly, Verizon | Accenture Executive Summit at AWS reInvent 2019


 

>>Bach from Las Vegas. It's the Q covered AWS executive summit brought to you by extension. >>Welcome back everyone to the cubes live coverage of the Excenture executive summit here at AWS. Reinvent from Las Vegas, Nevada. I'm your host, Rebecca Knight. We are joined by two guests for this segment. We have Greg sly, he is the SVP platform and infrastructure at Verizon. Thank you so much for coming on Greg. Thank you. Happy to be here and almost sad. K he is the managing director, Accenture global network services. Thank you so much. I'm all so Greg, I want to start with you wanting, everyone knows Verizon, it's a household brand. Tell our viewers a little bit just about how big you are, what countries you're in your reach. >>Okay. Well we're a global company. There's about 135 ish thousand employees in the company. The brands and they're, you know, they include Yahoo and AOL and HuffPost and riot and others. So we have a much more global reach with some of those brands overseas for is obviously very well known in the U S and overseas as well. And that's really where our big plays are. Now. We're big in Asia as well with our eCommerce sites and stuff. So it's, it's, it's global and it's everywhere. So, >>so give our viewers an overview of this current state of where you are in your journey to the cloud, the cloud effication of Verizon. >>Sure. So the last probably two years we've really put a lot of focus into moving out of our data centers and into the cloud. We focused primarily on workloads that are right for the cloud because we as during this journey we went, there's obviously huge data lakes and huge amounts of data equipped over two exabytes of data. And trying to move that to the cloud is obviously takes some time. But a lot of our front end apps from anything from, you know, where your order, your phone or where you order services to, whether you're on Yahoo fantasy sports or on finance page, those, those things tend to work well in the cloud and they're built for the cloud for very bursty type workflows. So we spend a lot of time moving a lot of our applications plus all the new Greenfield applications up into the cloud. So we're, we're considerable way down the path now on that. We're now getting to the tail end with these kind of massive data sets on what's our next step for those. And that's what we're working on now. >>Um, well I want to bring you into this conversation a little. What, what are you seeing right now across cross industry, the current state of deployments? >>Yeah, so I mean, just building on what Greg said it's almost a third wave of cloudification that we see now. So you know that we had the desegregation of hardware and software and most operators started to go globally towards cloud and then they sort of had the second way, which was really the own private cloud infrastructures. And now because we are here, you can see clearly the amount of public cloud infrastructure that's starting to come in and become relevant to this deployment. So it's almost a third wave where I see a lot of our clients globally looking at hybrid cloud type models for. And >>that really accelerates that cloudification journey because now you see a lot of workloads moving to a hybrid cloud environment. Just by the size of the ecosystem of suppliers and partners that are involved. We give you a sense of how accelerated this has become. I mean, the last three years I've seen in this event doubling of the number of partners who are just moving their workloads, whether it's compute, storage network to a hybrid cloud in one. So that acceleration has started and we expect in the next two to three years this will become mainstream. That I'm always right. We're been down that exact same journey where we've, we've done a lot of things up into the cloud like in AWS now, but we've also done a private cloud which enabled us as more like a development or a on-prem tool that allowed us to build, learn, and take applications that were not really ready for the cloud, are native for the cloud, build them on prem, wherever, a little bit more freedom to do some things and then learn and then move them up to the public cloud. So we've been down that exact same journey. >>So I also want to ask about a buzzword here, five G five G the arrival of five G. what it means to your industry and whether or not being in the cloud is ness is a necessary prerequisite to really capture all the benefits. >>I'm going to start on me. Sure, go ahead. No, I was just saying if you look at 5g, the reason it's so fundamentally different from previous generations is because 5g opens up a bunch of use cases that traditional TG for genetics did not and the size and skin of those use cases including like billions of devices and having really cool use cases like gaming and health and automotive and robotics in 10 places a huge burden on an infrastructure, which means cloudification does become a massive requisite. The level of skill size devices, latency profiles is something you only get when you are on a cloud infrastructure. So Greg, I agree 100% and this is going to drive new innovation that we've never seen before as we obviously being Verizon. 5g is one of our big, big bats. Obviously. That's one of the things that Andy and Hans talked about yesterday at the announcement here at reinvent and where we're seeing now with clarification, it's, it's literally I think one of the cornerstones of how it's going to work because we're going to have to put so much out to the far edge and out into as close to the customers as we can. >>The only way you're going to do that is through the cloud and using the cloud services like outpost and other services to push that out close to the, to our customers. So 5g and cloud are synonymous. They're going to go hand in hand. It's the only way it's going to work. And when, if I just save one last thing on what Greg said, cloudification was happening anyways and it was a great efficiency driver for all organizations. Five G's almost come in and lit a match and said, here's a lot of revenue opportunities that you can get on top and that has just accelerated >>the whole thing with distribution of five G and cloud. So that that's going to happen. >>Yeah, I think we're really only seeing the beginning. It's so early on in 5g and the journey to the cloud that I think next year's reinvent and the year after that I think we're going to look back and say this was really just the very beginning of what we're learning, what this technology can do for the world. >>I want to ask about innovation and this is something that Andy Jassy talked about in his fireside chat this morning is how AWS maintains its startup mentality even though it is of course a enormous company. How does, how do you think about innovation and approach innovation at Verizon? How do you make sure you are continuing to experiment and push boundaries even though you are a large and complex organization yourself? >>It's a good question. That's something we are always pushing. I think it starts from the top with Hans, he's, he's made one of his key pillars of innovation, of what we have to drive, listening to our customers and building on what they need, but we've spent a lot of time on redefining how we work to adapt to the cloud. So the days of in the past of, you know, we'll do one release every quarter, it's now how many releases a day can you do? And the only way you can do that innovation through bucket testing, through AB testing is literally embracing the cloud and doing small tests here and there on stuff. So it's really now learning from the internet startups, trying to keep that startup mentality in a company the size that's 137,000 employees. But it's building that culture and I think Hans has been a great leader to really drive that, that different way of working. So, >>um, well we've seen a dizzying number of announcements from AWS, new products and new services that are coming out. What are, what is most caught your attention and how are you thinking about how to help clients capture the benefits of what AWS is offering? >>You know, the thing that struck me yesterday when I was looking at the keynote was this is probably the first time there is a recognition in the industry that it's an ecosystem play. And what I mean by that is a lot of the challenges that were seen in the last couple of years around getting 5g mainstream, getting all these things in the market was who does it, who supports them and this whole ecosystem and yesterday's announcement where you know Andy enhance and other carriers like water, phone and so on are coming in and saying, you know what? Let's do this together. Let's collaborate. To me that really hit the Mark because as you start building specific use cases to make this real for a consumer like us, you will see that an ecosystem plays the only way to make this a reality. And that's what really struck me. If you look at Waveland, if you look at local zones, all the announcements that were done yesterday, all of them require app development communities, escalates session partnerships. It requires hardware partnerships, services firms. It requires of omic Accenture to come in and do this secret sauce. So there's lot of things that have to >>be done there. And I believe that's what really caught my eye, that it's an ecosystem. Now you have the amount of collaboration going forward. Is going to be unprecedented because no one company is going to be able to do all of it. >>So how do we, you're both technology veterans. I mean you're just babes. You're, you're just teenagers of course. But thinking about how different it is today versus when you were just beginning your careers in terms of, I mean we have this idea of this cutthroat competitive world of technology, but as you said, there is, these companies need each other. I mean they're there, they're competing of course, but they also desperately need each other to make sure their business models are successful. So can you just describe this landscape for, for our viewers in terms of what you've seen as changes and whether or not these changes are for the good? >>Well, starting in the mainframe days, which is where I started and then kind of went wound, don't, you know, windows NT and the distributed compute, you're right, it was very do it ourselves. We're the only ones that could do it. You have to hide everything from all your competitors because we're providing a solution and nobody sees anybody else a secret sauce. And obviously protecting IP was key. Now we've seen open source take a much broader stroke across the canvas and we've also now everyone's got what are we best at and how do we use that rather than trying to be all things to everybody and building partnerships. So you're right, we have partnerships with company that we compete with, but we also have relationships. We need to work together to make this happen. So it is completely different from what it was 10 years ago, 20 years ago on how you're collaborating on one part of a company who should come. >>Competing is one area, but you're actually collaborating to build a product to go to market together at another one. So it's really interesting. I mean the market forces have changed dramatically. I mean, I remember when I was in my telecom operator days with BT, we used to as great selling or love technology, we used to start in the labs and in the labs we use engineering was a sort of bread and butter. And then this focus on customer centricity in the last couple of years around so much choice, so much availability of solutions in the market. And as Greg said, the collaboration is a must do now. And that's why that focus changed for us. And I see now this customer centricity becoming so important that what does the end user really want? And then that comes with it and realization that says, okay, I am not able to provide this by myself, but I do know how to solve for it. >>And that's when you have to bring in others who can create a solution. You're absolutely right because you know, 10 years ago, 1520 years ago, technology was still so new. Most people weren't comfortable yet and really knew what it could do or what they wanted. And it was a room full of architects designing what it was going to be. Now it's a room full of customers telling you what they want and going out. So it's completely changed now where we'll build what the customer, what we think the customer needs. Now we're building what the customer tells us they want. So it's been a one 80 >>so Greg, I know before the cameras were rolling, you were talking about how you'd been to this conference years ago and now just the growth that it has experienced has really shocked your, your sphere system. Um, what kinds of conversations are you having? What are the messages that you're hearing, a particular letter that are particularly resonant to you right now? This idea of the fourth industrial revolution. Do you buy it? >>I absolutely buy it and it's not just drinking the Koolaid because I work at Verizon. It's actually seeing what's possible in health. What's possible in gaming, automotive industry. Like you were saying at the beginning, it's one thing that struck me in Pedder was through the conversation we were having of how many people I've met here and when I was walking through the expo downstairs I was like, Oh, we have a relationship with them now. We have relationship with them. There's like half the floor down there that we have some sort of relationship with that were other customer or a partner or providing services to that. It's, it's, it's changed where before you'd have a booth and you're like, how many people can we get over there? Now it's like how do we get a booth with our partners that we can talk about a common solution that we're providing back? >>So it's, it's been amazing from like it reinvent four or five years ago it was like one hotel was still pretty full up to like four or five hotels now with with 65,000 people or something. It's, it's amazing. But, but the conversations before too used to be, we can only talk if we go into a private room over here. It's now that there's so many people and so many conversations and they're like, Oh let me pull them all in. Let me pull Rebecca cause we're all talking about the same thing now. So it's become more open. There's still sure there's IP and things we have to protect and we all have our company strategies, but there's now there's so much collaboration, there's a lot more conversations going on now. I mean the focus will now move to how do we operationalize this industrial revolution because that's where a lot of engineering horsepower, a lot of scaling would have to happen in terms of, it would be great to launch health as a service or gaming as a service and all of these things. >>But you know when things go wrong, which Deville in the early years of adoption, somebody is going to have to take the call, somebody is going to have to manage the customers. Somebody who's going to have to, because that's where the test would happen in terms of okay this is going to stick and this is going to work. So to me the next two to three years of this event will be around how do I operationalize and scale what we've now started? Cause I think that's where the rubber is going to hit the road. And I think even at Accenture we see this with all our work. It's moving more and more towards how do I monetize the use cases, how do I now build on it? How do I implement at scale? So that's, that's really what I see happening >>coming up. We were, we're on, we're on the cusp of 2020 there's so many new emerging technologies and of course the old technologies which are still pretty new machine learning, AI, IOT. What are some of the exciting trends that you're looking at coming in next year and the next three to five years in terms of your business and an industry wide? Two ML? >>Well for me there's obviously the stuff that we're talking about with five G and waving, but one that really struck me at this conference was how we're going to be treating data differently or I should say storage of data differently. Where before it was like buy huge storage devices and you'd have petabytes and petabytes or exabytes of data in a data somewhere, data centers somewhere. It's now distributed out to the far edge. It's, it's going to be much more in the cloud, much more dispersed. Obviously that's going to bring challenges around, you know, with, with GDPR, with, with, you know, the, the California protection act, all of those that are coming as well of how we're going to deal with that. So absolutely the 5g and the announcements went on yesterday. But in my slice of the world, looking at how are we going to manage, transform, handle, distribute data and how we're going to protect user's privacy through all of that is really interesting. And I think a new field that we're, it's just changing so rapidly day to day >>and one that's really part of our national conversation too in terms of privacy and security. >>Well I think to me the key trend would be adjacencies. And what I mean by that is we've always been a little bit siloed traditionally in terms of, you know, there is a telco industry solution and then there is a mining solution and then there is a automotive solution, right? And the technology is blurring these lines. Now, you know, like as Greg said, I can have a intelligent 5g conversation with a gentleman, car manufacturing company that I wouldn't have dreamed of having a couple of years ago. So that trend is set to accelerate because 5g edge compute, all of these things are going to be more and more applicable to adjacent industries. And this is why I always believe the telecom sector has a pivotal role, almost a orchestrator role that says as these industries look for solutions we have those, we just haven't adapted and customized are social. That I think would be a big trend. I see other industries are going to cash in on what we've done. >>I'm all, Greg, thank you so much for coming on the cube. A really fascinating conversation. Oh, pleasure. I'm Rebecca Knight. Stay tuned for more of the cubes live coverage of the Accenture executive summit. Coming up in just a little bit.

Published Date : Dec 4 2019

SUMMARY :

executive summit brought to you by extension. I'm all so Greg, I want to start with you wanting, So we have a much more global reach with some of those so give our viewers an overview of this current state of where you are in your journey are right for the cloud because we as during this journey we went, there's obviously huge data lakes and huge What, what are you seeing right now across cross industry, And now because we are here, you can see clearly the amount of public cloud I mean, the last three years I've seen in this event doubling of the number of partners So I also want to ask about a buzzword here, five G five G the arrival of five G. what So Greg, I agree 100% and this is going to drive new Five G's almost come in and lit a match and said, here's a lot of revenue opportunities that you can So that that's going to happen. It's so early on in 5g and the journey to the cloud How does, how do you think about innovation and approach innovation at Verizon? And the only way you can do that innovation through bucket testing, through AB testing is literally help clients capture the benefits of what AWS is offering? by that is a lot of the challenges that were seen in the last couple of years around And I believe that's what really caught my eye, that it's an ecosystem. So can you just describe this landscape for, for our viewers in terms of don't, you know, windows NT and the distributed compute, you're right, it was very do And I see now this customer centricity becoming so important that what And that's when you have to bring in others who can create a solution. so Greg, I know before the cameras were rolling, you were talking about how you'd been to this conference years ago There's like half the floor down there that we have some sort of relationship with that were other customer or a partner I mean the focus will now move to how So to me the next two to three years of this event will be around how do I operationalize and scale and of course the old technologies which are still pretty new machine learning, AI, Obviously that's going to bring challenges around, you know, with, I see other industries are going to cash in on what we've done. I'm all, Greg, thank you so much for coming on the cube.

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Matt Cain, Couchbase | CUBEConversation, November 2019


 

(upbeat music) >> From our studios in the heart of Silicone Valley Palo Alto, California. This is a CUBE conversation. >> Hello everyone. Welcome to this CUBE conversation here at our Palo Alto CUBE studios. I'm John Furrier, host of theCUBE. Got a great conversation here with Matt Cain, CEO of Couchbase. Matt, welcome to theCUBE. >> John, thanks for having me here. >> So it's great to have you on because we've been following Couchbase really from the beginning but in 2011 that was the big movement with Couchbase and Membase coming together. Since then quite a tear. Couple of things, one from a business standpoint, good mix of you guys. And then you've got the cloud trend just absolute change the game with scale. So enterprise is now a reeling, cloud is there, the roll of data's changed. Now data's now a part of everything. This has been a big part of the successful companies in this next cloud 2.0 or this next shift. Give us an update on Couchbase. What's going on with the company? You've been the CEO for a couple of years, what's new? >> Yeah, so I'm 2 1/2 years in, John. It's been a great ride so far. Let's talk a little bit about how successful the company is and then we'll spend some time on the market. We just finished the first half of our fiscal year and the business is on a phenomenal trajectory. We're up 70% year on year. Average contract values up 50%. Total contract value up over 100%. We now call 30% of the Fortune 100 customers. So in terms of business success we're really proud of what we're able to do and the problems that we're solving for our customers. The backdrop, and what we're so excited about is the market transition that we're participating in. And it's our belief at Couchbase that the world of databases represents the single biggest market transition that's going to occur in technology over the next couple years. And I think there are two fundamental drivers behind that transition which you talked about. One of them is a technology disruption and the other is business disruption. On the business side we believe deeply in digital transformation or the fourth industrial revolution. And we spend our time going around the world talking to enterprise customers and everyone of 'em is figuring out how to use technology to get closer to their customers and change their business. In order to do that they need to build next generation applications that change our customer experience as both professionals and our personal lives. To enable that though, you need a completely different approach to the database. And how you manage the underlying data to enable those experiences and Couchbase sits at the intersection of those two transitions. >> Want to get into some of the database software dynamics from being a software company, a database company. You guys are, you're on a good wave, you've got a good surfboard as we say in California. But the couple of things I want to get your thoughts on, you see the database market like the oracles of the world. The database that rules the world, that's changed. Now there's multiple databases out there. Different needs for different workloads. And then you've got open-source. So you've got the two things going on I want to get your reaction to. One is the changing landscape of the database market. And two, the impact of open-source because both have been changing and growing and evolving. What's your reaction to those two dynamics? >> So let's talk databases first. I think to reflect on databases one needs to think about the applications that those databases have been architected to support. And if you look at legacy solutions, legacy systems, it was really built on relational technology. And the applications those were optimized for and have been really running for the last many decades were big monolithic applications. And I like to say the implementation of one of those at a large financial firm in New York probably wasn't much different than a consumer company in Seattle. That is changing now in the world of microservices and customer experiences and applications demand a different type of database. And so as we think about what is an application literally everything that we do between the human world and the digital world goes via an application. Whether it's our, you know, checking our banking statements, how we engage with our health care provider, how we travel, how we buy things, whether we're in a store or we're doing it from the comfort of our home. Everything is via an application and what we've come to expect is I want that application to work my way which is different than your way. Well that's a very different thing than legacy applications that were built for CRM or ERP and so databases are going through this big transformation because of that business transition that I talked about where we as consumer are demanding different ways of engaging. And if you look at enterprise success in digital transformation it's very tied to the experiences that they're creating which necessitate a database that is capable of handling those. So we're seeing a massive shift in database technologies or proliferation of new companies that are supporting next generation applications. With respect to open-source, when I talk to enterprises they want the flexibility of a new way of acquiring technology. And people are very used to, "I want to examine things "in the way I want to learn about it. "And I want to play with technology "to make sure that it's going to meet my needs." In the case of databases, does it have the scale and performance? Does it have the usability? And so as an open-source company we want to enable our application developers, our enterprise architects, our dev-ops teams to use the technology and see what's it like. And I think enterprises really appreciate that model. So I think open-source is not only unique to databases, it's how enterprises want to-- >> And certainly is growing and changing as well. So you mentioned open-source and databases. I want to get your thoughts on the cloud impact because if you look at the success of Amazon which I call them the leaders and they won the cloud 1.0 game, or the first inning, or the first game of the double header as some say. APIs led itself well to decoupling and creating highly cohesive workloads. Using APIs and (mumbles). There you got to store data in the databases. You might have one workload with one database and another workload using other databases. So have you have a diverse database landscape. >> For sure. >> So that's kind of out there. So if that's the case how do I as an enterprise deal with this because now I'm thinking, "Okay, I want to stitch it all together. "I got to maintain security. "Now I'm dealing with multiple clouds." It's become a discussion and design point for dealing with all these new dimensions. What's the mind of the customer in all this? >> Yeah, and on top of that I want to do it without dramatically increasing my total cost of ownership. And so I talk a lot to enterprises that represent that very challenge. What they say is I have to change the customer experience. In order to do that I need to understand who they are. What are their preferences? What inventory do I have as an organization? What do I have in physical locations? What we talk about is different data silos. And the reality is data has been in those silos for a long time and in some cases it's not coming out anytime soon. So one of the new approaches with data platforms is how do I take advantage of existing investment and infrastructure and layer in new technology platforms that can sit between the application and the legacy systems? And then you can suck that data into a data store that is helping feed the applications on a real time basis whether that's in the cloud or out to the edge. And Couchbase is one of the examples of a database that can handle that but can handle it at scale unlike any other company on the planet. So when we talk to customers it's how do you extract all that different information which has rich potential if they application logic can present it in a way that's customized but do that in a way that's constantly on, available from anywhere in the network topology and reliable. So it is a challenge and it's one of the greatest computer science challenges in the enterprise right now. >> On that point I want to ask you, what's the number one story or trend that people should be paying attention to? >> Yeah, so you asked a question on cloud, which I think is fundamental, and enterprise is like pay as you go models and utilization based economics which make complete sense. A lot of the architecture therefor is being driven in a centralized manor. So bring information into centralized cloud take advantage of bundling effects. I believe that one of the best kept secrets if you will or biggest trends that people aren't spending as much time on is edge. If you think about us in this studio right now there isn't a cloud sitting behind us and yet you're working on your machine, I was on my device a moment ago and I'm expecting real time information across all my applications. We are constantly manipulating, moving, accessing data and we expect to be able to do that at all times. Well in order to do that at the scale in which we're talking you have to have database technology at the edge. And by definition if you're expecting a roundtrip of data processing, which you're potentially doing, is increasing latency. And that's if you have a reliable connection. If you don't have a reliable connection you're dead in the water with it with that application. So if you think about the future of healthcare, if you think about next generation retail, if you think about connected homes and connected cars, the reality is we're going to expect massive processing of data out at the edge. And I think data platform companies have to be mindful of what they're architecting for. Now Couchbase is uniquely positioned in NoSQL databases that we can run in any public cloud and we can run that same platform out to the edge and orchestrate the movement of applications and data between every point of the network topology. And that's when our enterprises say, "Wow, this is game changing technology "that allows me to serve my customers "the way they want to be served." >> Most people might not know this about you, and I'm going to put you on the spot here, is that you had almost a 10 year run at Cisco. >> Yeah, that's right. >> From the 2000 timeframe. Those were the years that Cisco was cutting its teeth into going from running the internet routes to building application layers and staring see... And the debate at that time was should Cisco move up the stack. I'm sure you were involved in a lot of those conversations. They never did and they're kind of staying in their swim lane. But the network is the network and we're in a distributed network with the cloud, so the question is what is the edge now? So is the edge just the network edge? Is it the persons body? Is it the wearable? How do you guys define the edge? >> I think the edge is constantly being pushed further and further, right? One of the things that we talk a lot about is mobile devices, right? If we think about the device that we as humans ultimately touch at the end where we're not dependent on sensors and things, it is our mobile devices and we all know the impact that's had. I'd be willing to bet you that cup of coffee that you have Couchbase database running in your mobile device because we can actually embed it inside the application and allow the application architect to determine how much data you want to use. But the way we've architected things is we think for the future. This isn't just mobile devices, this is the ability to put things directly into sensors. And if we think about how applications are working the amount of data that you can draw with machine learning algorithms, which we've enabled in our latest release, imagine a world where we're embedding a database instance inside of a sensor. So companies aren't quite there today, but we're not that far off where that's going to be the case. >> Well I bring up the Cisco example because you obviously at that time the challenge was moving packets around from point A to point B. You mentioned storage, you store things from here to there. Move packets around in point A to point B. That's the general construct. But when we think about data they're not packets you're talking about sometimes megabytes and betabytes of data. So the general theme is don't move data around the network. How does that impact your business? How does that impact a customer? Because okay they maybe have campuses or wide area networks or SD-WAN, whatever they got. They still want a instrument, they still want to run compute at the edge, but moving the data around has become persona non gratae in **. So how do people get around that? What's the design point? >> So you and I remember these examples when we use to go into conference rooms and ask for ethernet cables, right? The days of what is my wifi connectivity weren't there yet. If we think about that philosophical challenge that was I'm used to a certain experience with connectivity, how do I enable that same connectivity and performance as I get further and further away from the central topology? And so what we did at Cisco is put more and more sophistication into branch routing and make sure that we had reliability and performance between all points of the topology. The reality is if you were to take that same design approach to databases, what you end up with is that centralized cloud model which a lot of companies have chosen. The problem with it occurs when you're running truly business critical applications that demand real-time performance and processing of massive applications. And so-- >> Like what, retail? >> Yeah. So at Couchbase what we've decided to do is take the data logic where the data resides. So we actually now call four of the top 10 retailers in the world customers. And what they are doing is changing our experience as consumers. Omnichannel. When I walk into a store, imagine if you're at a do-it-yourself retailer, somethings popped off the back of your washing machine and you say, "I don't know how old the washing machine is. "I don't know what the part is." Go into one of these mega stores that we know, with the application now via Couchbase in a mobile phone I could take a picture of that. With machine learning algorithms I'm now running technology to say, "Do I have this in inventory?" "What is it compatible with?" "Oh, and it happens to be on aisle 5." Or, "We don't have it and we're going to ship it out." I mean that's game-changing stuff. Well to enable that use case I need to understand who you are. I need to know what you've bought before. I need to understand our product catalog, what things are compatible with. You're literally storing, in that case, three or four billion instances in a data store that you need to access on a real-time basis. >> In milliseconds. >> In less than 2 1/2 second millisecond response rates. To make the challenge even more exciting, those customers come to us and they say, "Well what if there's a hurricane?" "What if there is no internet connectivity?" "What if I don't have a cellular connection?" I still want my users to have a great customer experience. Well now all of a sudden that isn't an extension of a cloud, that becomes it's own cloud. Now to orchestrate the movement of information and applications from that point and have consistency across all your other stores, you need to figure out orchestrating applications, orchestrating massive amounts of data, having consistency. And so the way to do it, bring the data logic where the data resides and then really understand how applications want to move things around. >> So first of all, my database antenna goes up. The comparison of the old days was you had to go to a database, run packets across the network, access the database, do a lookup, send it back and then go back again. >> Right, right. And that's not possible. That's interesting modern approach. But you also mentioned all that complexity that's involved in that. Okay, no power or no connectivity you have to have an almost a private cloud instance right there. I mean this is complex. >> Very complex. >> And this is some of the kinds of things we saw with the recent Jedi proposal that Amazon and Microsoft fought over. Microsoft won to deal with the battle fields. All this complexity where there's no bandwidth, you got to have the data stored locally, it's got to use the back hall properly. So there's a lot of things going on in the system. There's a lot to keep track of. How do you guys manage that from a product standpoint because there's somethings are out of your control. >> Yeah. >> How does Couchbase make that scale work? >> So that's a great question. Let me again complete the problem statement which is databases need to account for all that complexity but application developers and dev-ops teams don't want to deal with the specifics of a database. And so when we're selling into enterprises at this magnitude we need to be very relevant to application developers where they want speed and agility and familiarity of tools they know and yet we need to have the robustness and completeness of a platform that can literally run business critical applications. And so part of the power of Couchbase is that we engineer with extreme elegance, that we put a lot of that sophistication into the database and our job is to write the code that manages that complexity. But what we also do is we go to enterprise and we say we give you the full power of this NoSQL engine that is in memory, shared nothing, scale out, highest performance on the planet but we allow you all the power and familiarity of the language you know which is SQL. You've got this, I'm sure back to your database education you were familiar with, SQLs a programing language, well there's an entire world of database people and architects that understand that as an interface. So how do I account for that complexity but then go to you and say, "You know that language "that you've been speaking the whole time "talking to your old database? "Well you can speak with that same language "on your new database." And that's how you can really break through enabling customers to modernize their applications with all this complexity but do so in a way that they're comfortable with and is aligned to the skills that they-- >> So you extract away the interface, or language NoSQL I know there are others and modernize onto the covers? >> Correct. >> And at scale? >> At the highest scale. >> All right, I got to ask you about multi-cloud because multi-cloud is something that we were talking before we came on camera around cloud sprawl, inheriting clouds, M&A. Companies have multiple clouds they're dealing with but no one's, well my opinion, no one's architecting to build the best multi-cloud system. They're dealing with multi-clouds and design point which you mentioned which is interesting. I want to get your thoughts on this because you're hearing a lot of multi-cloud buzz. And it's a reality but it's also a challenge for application developers. And I want to get your thoughts on this. How should people thinking about multi-cloud in your opinion? >> Yeah, so my perspective starts with what we hear from our customers. And our customers say for truly business critical applications that they are running their business on, whether it's core booking engines, customer platforms, the touchpoint between users and stores, they say, "Look, I need to design a system "that's reliable and higher performing "and public cloud is a reality. "At the same time I have legacy data center on-prem, "I've got things out at the edge," and so they have to architect a multi-cloud, hybrid cloud, and distributed environment. And so depending on the layer of the stack that you're in I think the cloud companies would talk about their multi-cloud strategy. I come at it a different way which is how do we build a data platform that supports the applications that demand a hybrid multi-cloud environment? And so when we have a certain application that's running on-prem, how do we alive for a reliable failover instance to be running in a public cloud? To me that is truly fulfilling on the demands that enterprises have. And so I think multi-cloud is a strategy of all enterprises. Giving the flexibility with things like Kubernetes to avoid cloud lock in. Making sure your system can handle migration of workloads and active, active, active, passive scenario. I think that's our approach to multi-cloud. >> It's interesting, again back to this Jedi thing which was front and center in the news. Kind of speaks to the modern era of what the needs are. The Department of Defense has a multi-cloud strategy, they have multiple clouds, and well turns out Microsoft might be the sole source. But their idea was it's okay to have a sole source cloud for a workload but still deal within a multi-cloud framework. What's your thoughts on this? Some people are saying, "Hey, if you've got a workload "that runs great on cloud, do it." >> Yeah. I don't want to make that decision for the enterprise, I want them to determine what the best instance is based on the application that they're enabling. So I ask all my enterprise customers, "How many applications do you have in your environment?" Thousands of applications. It would be wrong for me to go dictate and say, "Well I have the answer "for every one of those applications." Instead we want to build a sophisticated platform that says look, if these are the requirements, the performance requirements, run your database in this instance and you determine if that's the best for you. If you have a legacy application that needs an underlying mainframe or relational database, that's fine. We're not asking you to forklift upgrade that. Put the database in there that's going to give you the performance and requirements you want. And so again, it's where do application developers want to stand up their application for the best performance? I'll tell you what, in the 2 1/2 years I've been at Couchbase I've sat down with Fortune 100 CIOs that have absolutely told me, "Here is our cloud strategy "with public cloud vendor number one." Come back two years later and they said, "We have shifted for X, Y, and Z reason "and we are going to public cloud vendor number two." If we had chosen one specific deployment and not given thought to how enterprises are eventually going to want to have that flexibility we would be having a very different conversation. And so when we talk about we're enterprise class, multi-cloud to edge, NoSQL database, it's giving enterprises this flexibility at a database-- >> So on that example of I went with cloud number one and then moved to cloud number two, was that a I'm stopping with cloud one going to cloud two or I'm going to move a little bit to cloud two or both? >> I think it varies depending on the CIO that you're talking to. It could be they didn't handle GDPR the way I wanted to or it could be they're not deployed in a certain geographic reason. It could be-- >> Capabilities issue. >> Capabilities. Could be business relationship. You know, I have a particular commercial relationship over here therefor I have an incentive to move here. Some of 'em have dual strategies, so I think it's very dangerous for companies like us to try to-- >> Beauty's in the eye of the beholder as I always say with cloud. You pick your cloud based on what you're trying to do. Final question, security obviously, cloud security you're seeing. Amazon just had a recent even called re:Inforce which was I think the first cloud security show, RSA, there's a bunch of other shows that go on, they're all different. But security clearly is being baked in everywhere. Kind of like data, kind of horizontally embedded, need real time, you need a lot of complexity involved. They want to make it easier. What's your view on how security is playing out for Couchbase? >> Look, it's a paramount design principle for us. And we think that to build a database for business critical applications you need to have reliability, you need to have performance, you need to have scalability, you have to have security. So it's part of how we think about every component from cloud to edge and everything in between. How do we have encryption? How do we have multi-factor authentication? How do we ensure that not just securing the data itself, but how do we give the operational controls to the database teams to orchestrate the movement of data and synchronize it in a reliable way. So absolutely important to us because it's important to our customers. >> Awesome. Matt Cain, CEO of Couchbase here inside theCUBE for CUBE conversation. Matt, I want to give you a chance to get the plug in for the company. Give the pitch if I'm a customer or prospect. Hey Couchbase I heard a little buzz. You guys got momentum going on, got good references. What's the pitch to me? >> Yeah so look, Couchbase is the only company on the planet that can make the following claim. We bring the best of NoSQL with the power and familiarity of SQL in one elegant solution from the public cloud to the edge. So let me walk through that. Our architecture was enabled for the highest performance in the world. Billions of documents. We have a customer who on a daily basis is running 8 million operations per second with less than two millisecond response time. Their business is running on Couchbase. You can't do that if you have the best data schema, the architecture for scalability, scale out, do that at high total cost of ownership. At the same time we want to bring the familiarity of programing languages that people know so that application developers don't have a big barrier to entry in deploying Couchbase. And that's where we've uniquely enabled the SQL query language for both query's, our operational analytics capability, that combination is extremely powerful. To be able to run in anyone of the public clouds, which we do via the marketplace or customers bring in their own nodes to their instances knowing that that's a changing thing per our conversation. But having a seamless integrated platform where you can run the same query in the public cloud as you can at the edge and then synchronizing that back together, that is a very powerful thing. One elegant platform we have, you know, we're a multi-model database. We can run a key-value cache, we can run a JSON database. We give you advanced querying, we give you indexing. To do that in one integrated platform no one else has thought about that and future proof their solution. Let me give you an example of how that all wraps up. One of the more innovative industries right now believe it or not, are cruise lines. And so we talk about digital transformation which is by definition customer experience. Well if you're in the cruise line business, if you're not creating a great customer experience, it's not like airline travel where you've got to get from point A to point B so you chose the best. This is I'm opting for an experience if this isn't great. so one of the most leading edge cruise lines out there has deployed Couchbase and they give every passenger a wearable. That wearable now fundamentally changes the interface between me as a passenger and the physical boat, the digital services, and the other people on the ship. And this is in a world... It's a floating device. There is no cloud, there is no cellular connections. So let's say we happen to be on the same ship. We end up at sports bar after we drop our family off, maybe we're talking databases, maybe we're talking something else. And we have beer, we have a second beer, what we don't know is that this cruise line is using our device. They know who we are, they know where we are, they're using geospatial technology back in e-commerce. They have a hypothesis that we're now friends, right? Or at least maybe we want to see each other again. Unbeknownst to us the next day we get a promotion that says 50% off at the sports bar for the next game. Wow that's great, I'm going to go. And then I run into you and it's like, "Wow, what are the chances that I run into you?" Well the chances in the old world very slim. The chances in new world very good. If I had little kids the digital content in the cabin is different. If there's a movie getting out how it navigates me around the ship is different. All of this is empowered by massive amounts of data processing, data collection and they've embedded that now in a device. Now if you're in that business and now you've got weeks worth of information on what we like, ship comes back to shore, how do you take all that information, extract it back to a cloud, improve the algorithm, start to offer different shipping option. They're literally changing the physical display of the boats to optimize customer experience. So think about that. Power of processing massive amounts of information in real time. If I'm getting a promotion and it's too late and I miss a game, does me no good. The combination of all those different data silos, right? Doing that where application developers can be agile and swift and make changes in an innovative way and stay ahead of their competition. Cloud to edge. Right? I mean that's literally a ship comes back, it goes to cloud, it enables it in this consistent... We're the only company on the planet that can do that. >> Lot of complexity involved. >> Yeah. >> Awesome. Quick plug. Are you guys hiring? What's going on with the company? What are you looking for? >> As quickly as possible. Based on our conversation earlier and your knowledge of databases, we're looking for quota carriers and engineers. So if you want to come on over we're-- >> I was thinking about the cruise ship and having a couple of beers with you watching some sports. My (mumbles) says >> Sounds like sports-- >> "Hey John's had so many beers "why don't you hit the tables?" >> Sounds like-- >> "We'll take your money." >> Sound like more a rep than an engineer. (both laughing) >> Matt, thanks for coming to theCUBE. Really appreciate it. Matt Cain, CEO of Couchbase. I'm John Furrier with theCUBE. Thanks for watching. (upbeat music)

Published Date : Nov 7 2019

SUMMARY :

in the heart of Silicone Valley Palo Alto, California. Welcome to this CUBE conversation So it's great to have you on and the problems that we're solving for our customers. But the couple of things I want to get your thoughts on, and have been really running for the last many decades of the double header as some say. So if that's the case how do I as an enterprise And Couchbase is one of the examples I believe that one of the best kept secrets if you will and I'm going to put you on the spot here, So is the edge just the network edge? the amount of data that you can draw So the general theme is and make sure that we had reliability and performance I need to understand who you are. And so the way to do it, The comparison of the old days you have to have an almost a private cloud How do you guys manage that from a product standpoint of the language you know which is SQL. All right, I got to ask you about multi-cloud And so depending on the layer of the stack that you're in Kind of speaks to the modern era of what the needs are. that's going to give you the performance that you're talking to. over here therefor I have an incentive to move here. Beauty's in the eye of the beholder the movement of data What's the pitch to me? of the boats to optimize customer experience. What are you looking for? So if you want to come on over we're-- and having a couple of beers with you Sound like more a rep than an engineer. Matt, thanks for coming to theCUBE.

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Ken Eisner, Director, AWS | AWS Public Sector Summit 2019


 

>> live from Washington, D. C. It's the Cube covering a ws public sector summit by Amazon Web services. >> Welcome back, everyone to our nation's capital. We are the Cube. We are live at A W s Public Sector summit. I'm your host Rebecca Night, along with my co host, John Farrier. We're joined by Ken Eisner Director Worldwide Educational programs at a WS Thanks so much for coming on the show >> you for having me. >> So tell our viewers a little bit. About what? What you do as the director of educational programs. Sure, I head >> up a program called a Ws Educate a ws educate is Amazon's global initiative to provide students and teachers around the world with the resource is that they need really to propel students into this awesome field of cloud computing. We launched it back in May of 2,015 and we did it to fill this demand. If we look at it today, what kind of right in the midst of this fourth industrial revolution is changing the means of production obviously in the digital on cloud space, But it's also creating this new worker class all around. Yeah, the cloud Advanced services like machine learning I robotics, I ot and so on. And if you looked at the employer demand, um, Cloud computing has been the number one linked in skill for the past four years in a row. We look at cloud computing. We kind of divide into four families. Software development, cloud architecture, the data world, you know, like machine learning I data science, business intelligence and Alex and then the middle school opportunities like technical customer support, age and cybersecurity, which can range all the way from middle school of Ph. D. But yet the timeto hire these people has grown up dramatically. Glass door as study of companies over there platform between two thousand 92 1,050 18 and show that the timeto higher had increased by 80%. Yet just think about that we talk about I mean, this conference is all about innovation. If you don't have builders, if you don't have innovators, how the heck Kenya Kenya innovate? >> Can I gotta ask you, Andy, just to have known him for over eight years and reporting on him and covering it was on when when everyone didn't understand yet what it was. Now everyone kind of does our congratulations and success. But to see him on stage, talk passionately about education. Yeah, mean and knowing Andy means it's kind of boiled up because he's very reserved, very conservative guy, pragmatic. But for him to be overtly projecting, his opinion around education, which was really yeah, pretty critical means something's going on. This is a huge issue not just in politics, riel, state, local areas where education, where >> the root of income inequality it's it's a lot of. >> There's a lot of challenges. People just aren't ready for these new types of jobs that are coming out that >> pay well, by the way. And this is Elliott >> of him out there that are unfilled for the first time, there are more jobs unfilled than there are candidates for them. You're solving this problem. Tell us what's going on in Amazon. Why the fewer what's going on with all this? Why everyone's so jacked up >> a great point. I, Andy, I think, said that education is at a crisis point today and really talked about that racial inequality piece way. Timeto hire people in the software development space Cloud architecture um technical called cloud Support Age. It's incredibly long so that it's just creating excess costs into the system, but were so passionate, like if you look at going to the cloud, Amazon wants to disrupt areas where we do not see that progress happening. Education is an area that's in vast need for disruption. There are people were doing amazing stuff. We've heard from Cal Poly. We've heard from Yeah, Arizona State. Carnegie Mellon. There's Joseph Alan at North Northeastern. >> People are >> doing great stuff. We're looking at you some places that are doing dual enrollment programs between high school and community in college and higher ed. But we're not moving fast enough, but you guys >> are provided with educate your program. This is people can walk in the front door without any kind of going through gatekeepers or any kind of getting college. This is straight up from the front, or they could be dropouts that could be post college re Skilling. Whatever it is, they could walk in the front door and get skilled up through educators that correct, >> we send people the ws educate dot com. All you need is some element of being in school activity, or you won't be going back from Re Skilling perspective and you came free access into resource is whether your student teacher get free access into content. That's map two jobs, because again, would you people warm from the education way? All want enlightenment contributors to sai all important, But >> really they >> want careers and all the stats gallop ransom good stats about both what, yet students and what industry wants. They want them to be aligned to jobs. And we're seeing that there's a man >> my master was specifically If I'm unemployed and I want to work, what can I do? I walk into you, You can go >> right on and we can you sign up, we'll give you access to these online cloud. Career pathways will give you micro credentials so we can bad you credential you against you We belong something on Samarian Robo maker. So individual services and full pathways. >> So this a >> direct door for someone unemployed We're going to get some work and a high paying job, >> right? Right. Absolutely. >> We and we also >> give you free access into a ws because we know that hands on practice doing real world applications is just vital. So we >> will do that end. By the way, at the end of >> this, we have a job board Amazon customer In part of our job, we're all saying >> these air >> jobs are super high in demand. You can apply to get a job as an intern or as a full time. Are you through our job? >> This is what people don't know about Rebecca. The war is not out there, and this is the people. Some of the problems. This is a solution >> exactly, but I actually want to get drilled down a little bit. This initiative is not just for grown ups. It's it's for Kimmie. This is for you. Kid starts in kindergarten, So I'm really interested to hear what you're doing and how you're thinking about really starting with the little kids and particularly underrepresented minorities and women who are not. There were also under representative in the in the cloud industry how you're thinking expansively about getting more of those people into these jacks. And actually, it's still >> Day one within all y'all way started with Way started with 18 and older because we saw that as the Keith the key lever into that audience and start with computer science but we've expanded greatly. Our wee last year reinvent, We introduced pathways for students 14 over and cloud literacy materials such as a cloud inventor, Cloud Explorer and Cloud Builder. Back to really get at those young audiences. We've introduced dual enrollment stuff that happens between high school community college or high school in higher ed, and we're working on partnerships with scratch First Robotics Project lead the way that introduced, whether it's blocked based coding, robotics were finding robotics is such a huge door opener again, not just for technically and >> get into it absolutely, because it's hands on >> stuff is relevant. They weren't relevant stuff that they can touch that. They can feel that they can open their browser, make something happen, build a mobile application. But they also want tohave pathways into the future. They want to see something that they can. Eventually you'll wind up in and a ws the cloud just makes it real, because you, Khun do real worlds stuff from a browser by working with the first robot. Biotics are using scratch toe develop Ai ai extensions in recognition and Lex and Polly and so on. So we've entered into partnerships with him right toe. Open up those doors and create that long term engagement and pipe on into the high demand jobs of tomorrow. >> What do you do in terms of the colleges that you mentioned and you mention Northeastern and Cal Poly Arizona State? What? What are you seeing? Is the most exciting innovations there. >> Yes. So, first of all, we happen to be it. We're in over 24 100 institutions around the world. We actually, by the way, began in the U. S. And was 65% us. Now it's actually 35% US 65% outside. We're in 200 countries and territories around the world. But institutions such as the doing amazing stuff Polo chow at a Georgia Tech. Things that he's doing with visual ization on top of a ws is absolutely amazing. We launched a cloud Ambassador program to reward and recognize the top faculty from around the world. They're truly doing amazing stuff, but even more, we're seeing the output from students. There was a student, Alfredo Cologne. He was lived in Puerto Rico, devastated by Hurricane Maria. So lost his, you know, economic mobility came to Florida and started taking classes at local schools. He found a ws educate and just dove headlong into it. Did eight Pathways and then applied for a job in Dev Ops at Universal Studios and received a job. He is one of my favorite evangelists, but and it's not just that higher ed. We found community college students. We launched a duel enrolment with between Santa Monica College and Roosevelt High School in Los Angeles, focusing again a majority minority students, largely Hispanic, in that community. Um, and Michael Brown, you finish the cloud computing certificate, applied for an internship, a mission clouds so again a partner of ours and became a God. Hey, guys, internship And they start a whole program around. So not only were seeing your excitement out of the institutions, which we are, but we're also seeing Simon. Our students and businesses all want to get involved in this hiring brigade. >> Can I gotta ask. We're learning so much about Amazon would cover him for a long time. You know all the key buzzwords. Yeah, raise the bar all these terms working backwards. So >> tell us about what's your >> working backwards plan? Because you have a great mission and we applaud. I think it's a super critical. I think it's so under promoted. I think we'll do our best to kind of promote. It's really valuable to society and getting people their jobs. Yeah, but it's a great opportunity, you know, itself. But what's your goal? What's your What's your objective? How you gonna get there, What your priorities, What do you what do you what do you need >> to wear? A pure educational workforce? And today our job is to work backwards from employers and this cloud opportunity, >> the thing that we >> care about our customers still remains or student on DH. So we want to give excessive mobility to students into these fields in cloud computing, not just today and tomorrow. That requires a lot that requires machine lurking in the algorithm that you that changed the learning objectives you based on career, so content maps to thes careers, and we're gonna be working with educational institutions on that recruited does. Recruiting doesn't do an effective job at matching students into jobs. >> Are we >> looking at all of just the elite institutions as signals for that? That's a big >> students are your customer and customer, but older in support systems that that support you, right? Like Cal Poly and others to me. >> Luli. We've also got governments. So we were down in Louisiana just some last month, and Governor Bel Edwards said, We're going to state why with a WS educates cloud degree program across all of their community college system across the University of Louisiana State system and into K 12 because we believe in those long term pathways. Never before have governors have ministers of country were being with the Ministry of Education for Singapore in Indonesia, and we're working deep into India. Never had they been more aligned toe workforce development. It creates huge unrest. We've seen this in Spain and Greece we see in the U. S. But it's also this economic imperative, and Andy is right. Education is at a crisis. Education is not solving the needs of all their constituents, but also industries to blame. We haven't been deeply partnered with education. That partnership is such a huge part of >> this structural things of involved in the educational system. It's Lanier's Internets nonlinear got progressions air differently. This is an opportunity because I think if the it's just like competition, Hey, if the U. S Department of Education not get their act together. People aren't going to go to school. I mean, Peter Thiel, another political spectrums, was paying people not to go to college when I was a little different radical view Andy over here saying, Look at it. That's why you >> see the >> data points starting to boil up. I see some of my younger son's friends all saying questioning right what they could get on YouTube. What's accessible now, Thinking Lor, You can learn about anything digitally now. This is totally People are starting to realize that I might not need to be in college or I might not need to be learning this. I can go direct >> and we pay lip >> service to lifelong education if you end. If you terminally end education at X year, well, you know what's what's hap happening with the rest of your life? We need to be lifelong learners. And, yes, we need to have off ramps and the on ramps throughout our education. Thie. Other thing is, it's not just skill, it's the skills are important, and we need to have people were certified in various a ws skills and come but we also need to focus on those competencies. Education does a good job around critical decision making skills and stuff like, um, collaboration. But >> do they really >> do a good job at inventing? Simplified? >> Do they teach kids >> to fam? Are we walking kids to >> social emotional, you know? >> Absolutely. Are we teaching? Were kids have tio think big to move >> fast and have that bias for action? >> I think that I want to have fun doing it way. Alright, well, so fun having you on the show. A great conversation. >> Thank you. I appreciate it. >> I'm Rebecca Knight for John. For your you are watching the cube. Stay tuned.

Published Date : Jun 12 2019

SUMMARY :

live from Washington, D. C. It's the Cube covering We are the Cube. What you do as the director of educational programs. 1,050 18 and show that the timeto higher had increased But for him to be overtly projecting, There's a lot of challenges. And this is Elliott Why the fewer what's it's just creating excess costs into the system, but were so passionate, We're looking at you some places that are doing dual enrollment programs This is people can walk in the front door without any and you came free access into resource is whether your student teacher get free access into They want them to be aligned to jobs. right on and we can you sign up, we'll give you access to these online cloud. Absolutely. give you free access into a ws because we know that hands on practice doing By the way, at the end of Are you through our job? Some of the problems. This initiative is not just for grown ups. the key lever into that audience and start with computer science but we've expanded term engagement and pipe on into the high demand jobs of tomorrow. What do you do in terms of the colleges that you mentioned and you mention Northeastern and Cal Poly Arizona State? Um, and Michael Brown, you finish the cloud computing certificate, raise the bar all these terms working backwards. Yeah, but it's a great opportunity, you know, itself. that you that changed the learning objectives you based on career, Like Cal Poly and others to me. Education is not solving the needs of all their constituents, Hey, if the U. S Department of Education not get their act together. need to be in college or I might not need to be learning this. service to lifelong education if you end. Were kids have tio think big to move Alright, well, so fun having you on the show. I appreciate it. For your you are watching the cube.

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Keynote Analysis | Fortinet Accelerate 2019


 

>> Announcer: Live from Orlando, Florida it's theCUBE covering Accelerate19. Brought to you by Fortinet. >> Welcome to theCUBE's coverage of Fortinet Accelerate 2019 live from Orlando, Florida. I'm Lisa Martin with Peter Burris. Peter, it's great to be with you our third year co-hosting Accelerate together. >> Indeed, Lisa. >> So we moved from, they've moved from Vegas to Orlando, hence we did so we had a little bit of a longer flight to get here. Just came from the Keynote session. We were talkin' about the loud music kind of getting the energy going. I appreciated that as part of my caffeination (laughs) energy this morning but a lot of numbers shared from Fortinet Accelerate. 4,000 or so attendees here today from 40 different countries. They gave a lot of information about how strong their revenue has been, $1.8 billion, up 20% year on year. Lots of customers added. What were some of the takeaways from you from this morning's keynote session? >> I think it's, I got three things, I think, Lisa. Number one is that you've heard the expression, skating to where the puck's going to go. Fortinet is one of those companies that has succeeded in skating to where the puck is going to go. Clearly cloud is not a architectural or strategy for centralizing computing. It's a strategy for, in a controlled coherent way, greater distribution of computing including all the way out to the edge. There's going to be a magnificent number of new kinds of architectures created but the central feature of all of them is going to be high performance, highly flexible software-defined networking that has to have security built into it and Fortinet's at the vanguard of that. The second thing I'd say is that we talk a lot about software defined wide-area networking and software-defined networking and software-defined infrastructure and that's great but it ultimately has to run on some type of hardware if it's going to work. And one of the advantages of introducing advanced ACICS is that you can boost up the amount of performance that your stuff can run in and I find it interesting that there's a clear relationship between Fortinet's ability to bring out more powerful hardware and its ability to add additional functionality within its own stack but also grow the size of its ecosystem. And I think it's going to be very interesting over the next few years to discover where that tension is going to go between having access to more hardware because you've designed it and the whole concept of scale. My guess is that Fortinet's growth and Fortinet's footprint is going to be more than big enough to sustain its hardware so that it can continue to drive that kind of advantage. And the last thing that I'd say is that the prevalence and centrality of networking within cloud computing ultimately means that there's going to be a broad class of audiences going to be paying close attention to it. And in the Keynotes this morning we heard a lot of great talk that was really hitting the network professional and the people that serve that network professional and the security professional. But Fortinet's going to have to expand its conversation to business people and explain why digital business is inherently a deeply networked structure and also to application developers. Fortinet is talking about how the network and security are going to come together which has a lot of institutional and other implications but ultimately that combination of resources is going to be very attractive to developers in the long run who don't necessarily like security and therefore security's always been a bull time. So if Fortinet can start attracting developers into that vision and into that fold so the network, the combined network security platform, becomes more developer-friendly we may see some fascinating new classes of applications emerge as a consequence of Fortinet's hardware, market and innovation leadership. >> One of the things that they talked about this morning was some of the tenets that were discussed at Davos 2019 just 10 weeks ago. They talked about education, ecosystem and technology, and then showed a slide. Patrice Perche, the executive senior vice president of sales said, hey we were talking about this last year. They talked about education and what they're doing to not only address the major skills gap in cybersecurity, what they're doing even to help veterans, but from an education perspective, rather from an ecosystem perspective, this open ecosystem. They talked about this massive expansion of fabric-ready partners and technology connector partners as well as of course the technology in which Ken Xie, CEO and founder of Fortinet, was the speaker at Davos. So they really talked about sort of, hey, last year here we were talking about these three pillars of cybersecurity at the heart of the fourth industrial revolution and look where we are now. So they sort of set themselves up as being, I wouldn't say predictors of what's happening, but certainly at the leading edge, and then as you were talking about a minute ago, from a competitive perspective, talked a lot this morning about where they are positioned in the market against their competitors, even down from the number of patents that they have to the number of say Gartner Magic Quadrants that they've participated in so they clearly are positioning themselves as a leader and from the vibe that I got was a lot of confidence in that competitive positioning. >> Yeah and I think it's well deserved. So you mentioned the skills gap. They mentioned, Fortinet mentioned that there's three and a half million more open positions for cybersecurity experts than there are people to fulfill it and they're talking about how they're training NSEs at the rate of about, or they're going to, you know, have trained 300,000 by the end of the year. So they're clearly taking, putting their money where their mouth is on that front. It's interesting that people, all of us, tend to talk about AI as a foregone conclusion, without recognizing the deep interrelationship between people and technology and how people ultimately will gate the adoption of technology, and that's really what's innovation's about is how fast you embed it in a business, in a community, so that they change their behaviors. And so the need for greater cybersecurity, numbers of cybersecurity people, is a going to be a major barrier, it's going to be a major constraint on how fast a lot of new technologies get introduced. And you know, Fortinet clearly has recognized that, as have other network players, who are seeing that their total addressable market is going to be shaped strongly in the future by how fast security becomes embedded within the core infrastructure so that more applications, more complex processes, more institutions of businesses, can be built in that network. You know there is one thing I think that we're going to, that I think we need to listen to today because well Fortinet has been at the vanguard of a lot of these trends, you know, having that hardware that opens up additional footprint that they can put more software and software function into, there still is a lot of new technology coming in the cloud. When you start talking about containers and Kubernetes, those are not just going to be technologies that operate at the cluster level. They're also going to be embedded down into system software as well so to bring that kind of cloud operating model so that you have, you can just install the software that you need, and it's going to be interesting to see how Fortinet over the next few years, I don't want to say skinnies up, but targets some of its core software functionality so that it becomes more cloud-like in how it's managed, its implementations, how it's updated, how fast patches and fixes are handled. That's going to be a major source of pressure and a major source of tension in the entire software-defined marketplace but especially in the software-defined networking marketplace. >> One of the things Ken Xie talked about cloud versus edge and actually said, kind of, edge will eat the cloud. We have, we live, every business lives in this hybrid multi-cloud world with millions of IoT devices and mobile and operational technology that's taking advantage of being connected over IP. From your perspective, kind of dig into what Ken Xie was talking about with edge eating cloud and companies having to push security out, not just, I shouldn't say push it out to the edge, but as you were saying earlier and they say, it needs to be embedded everywhere. What are your thoughts on that? >> Well I think I would say I had some disagreements with him on some of that but I also think he extended the conversation greatly. And the disagreements are mainly kind of nit-picky things. So let me explain what I mean by that. There's some analyst somewhere, some venture capitalist somewhere that coined the term that the edge is going to eat the cloud, and, you know, that's one of those false dichotomies. I mean, it's a ridiculous statement. There's no reason to say that kind of stuff. The edge is going to reshape the cloud. The cloud is going to move to the edge. The notion of fog computing is ridiculous because you need clarity, incredible clarity at the edge. And I think that's what Ken was trying to get to, the idea that the edge has to be more clear, that the same concepts of security, the same notions of security, discovery, visibility, has to be absolutely clear at the edge. There can be no fog, it must be clear. And the cloud is going to move there, the cloud operating model's going to move there and networking is absolutely going to be a central feature of how that happens. Now one of the things that I'm not sure if it was Ken or if was the Head of Products who said it, but the notion of the edge becoming defined in part by different zones of trust is, I think, very, very interesting. We think at Wikibon, we think that there will be this notion of what we call a data zone where we will have edge computing defined by what data needs to be proximate to whatever action is being supported at the edge and it is an action that is the central feature of that but related to that is what trust is required for that action to be competent? And by that I mean, you know, not only worrying about what resources have access to it but can we actually say that is a competent action, that is a trustworthy action, that agency, that sense of agency is acceptable to the business? So this notion of trust as being one of the defining characteristics that differentiates different classes of edge I think is very interesting and very smart and is going to become one of the key issues that businesses have to think about when they think about their overall edge architectures. But to come back to your core point, we can call it, we can say that the edge is going to eat the cloud if we want to. I mean, who cares? I'd rather say that if software's going to eat the world it's going to eat it at the edge and where we put software we need to put trust and we need to put networking that can handle that level of trust and with high performance security in place. And I think that's very consistent with what we heard this morning. >> So you brought up AI a minute ago and one of the things that, now the Keynote is still going on. I think there's a panel that's happening right now with their CISO. AI is something that we talk about at every event. There are many angles to look at AI, the good, the bad, the ugly, the in between. I wanted to get your perspective on, and we talked about the skills gap a minute ago, how do you think that companies like Fortinet and that their customers in every industry can leverage AI to help mitigate some of the concerns with, you mentioned, the 3.5 million open positions. >> Well there's an enormous number of use cases of AI obviously. There is AI machine learning being used to identify patterns of behavior that then can feed a system that has a very, very simple monitor, action, response kind of an interaction, kind of a feedback loop. So that's definitely going to be an important element of how the edge evolves in the future, having greater, the ability to model more complex environmental issues, more complex, you know, intrinsic issues so that you get the right action from some of these devices, from some of these censors, from some of these actuators. So that's going to be important and even there we still need to make sure that we are, appropriately, as we talked about, defining that trust zone and recognizing that we can't have disconnected security capabilities if we have connected resources and devices. The second thing is the whole notion of augmented AI which is the AI being used to limit the number of options that a human being faces as they make a decision. So that instead of thinking about AI taking action we instead think of AI, taking action and that's it, we think of AI as taking an action on limiting the number of options that a person or a group of people face to try to streamline the rate at which the decision and subsequent action can get taken. And there, too, the ability to understand access controls, who has visibility into it, how we sustain that, how we sustain the data, how we are able to audit things over time, is going to be crucially important. Now will that find itself into how networking works? Absolutely because in many network operating centers, at least, say, five, six years ago, you'd have a room full of people sitting at computer terminals looking at these enormous screens and watching these events go by and the effort to correlate when there was a problem often took hours. And now we can start to see AI being increasingly embedded with the machine learning and other types of algorithms level to try to limit the complexity that a person faces so you can the better response, more accurate response and more auditable response to potential problems. And Fortinet is clearly taking advantage of that. Now, the whole Fortiguard Labs and their ability to have, you know, they've put a lot of devices out there. Those devices run very fast, they have a little bit of additional performance, so they can monitor things a little bit more richly, send it back and then do phenomenal analysis on how their customer base is being engaged by good and bad traffic. And that leads to Fortinet becoming an active participant, not just at an AI level but also at a human being level to help their customers, to help shape their customer responses to challenges that are network-based. >> And that's the key there, the human interaction, 'cause as we know, humans are the biggest security breach, starting from basic passwords being 1, 2, 3, 4, 5, 6, 7, 8, 9. Well, Peter-- >> Oh, we shouldn't do that? >> (laughs) You know, put an exclamation point at the end, you'll be fine. Peter and I have a great day coming ahead. We've got guests from Fortinet. We've got their CEO Ken Xie, their CISO Phil Quade is going to be on, Derek Manky with Fortiguard Labs talking about the 100 billion events that they're analyzing and helping their customers to use that data. We've got customers from Siemens and some of their partners including one of their newest alliance partners, Symantec. So stick around. Peter and I will be covering Fortinet Accelerate19 all day here from Orlando, Florida. For Peter Burris, I'm Lisa Martin. Thanks for watching theCUBE. (techno music)

Published Date : Apr 9 2019

SUMMARY :

Brought to you by Fortinet. Peter, it's great to be with you our third year kind of getting the energy going. And I think it's going to be very interesting One of the things that they talked about this morning and it's going to be interesting to see how Fortinet it needs to be embedded everywhere. that the edge is going to eat the cloud, and one of the things that, and their ability to have, you know, And that's the key there, the human interaction, and helping their customers to use that data.

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Gurmeet Mangat, GE Renewable Energy | Smartsheet ENGAGE'18


 

>> Live from Bellevue, Washington it's theCUBE. Covering Smartsheet Engage '18. Brought to you by Smartsheet. >> Welcome back to theCUBE. We are live at Smartsheet Engage 2018 in Bellevue, Washington. I am Lisa Martin with Jeff Frick, and we've had a great day talking with Smartsheet executives, analysts, users, and we're excited to welcome to theCube for the first time, Gurmeet Mangat, the site manager Wind Power Generation at GE Renewable Energy. Gurmeet, great to have you on the program. >> Thank you Lisa, thank you Jeff. I'm really happy to be here. >> So you're a user of Smartsheet, but you're also a renegade. So before we get into your renegade status, tell us a little bit about GE Renewable Energy and your role. You got a big role as site manager. What, 75 turbines across multiple locations? So let's talk about GE Renewable Energy and your role as site manager. >> Sure, no problem. So GE Renewable Energy. One of our missions statements is to unleash limitless energy. How we do that, we harness the power of the sun, the water, and the wind. So try to produce clean efficient energy to power countries, homes, businesses, whatever needs that powered energy. As a manager I manage, like you said three wind farms, three different customers. A very complex role to have. I'm coming right from not just operations, human resources, financials. So everything's required of someone like me to manage that business end to end. It's a challenge, at the same time I seek opportunity in a lot of what's going on and leveraging Smartsheet as one of the tools. It's something I've been using over the past year to optimize the business and run those turbines. >> So it's so funny because I would say GE turbine farms and GE engines are the most quoted, often referenced IOT devices in this next gen conversation about IOT and data and how much data they throw off of any other kind of product out there, and you're sitting right in the middle of it actually managing the real machines and managing the real data. >> Yeah, exactly. So I mean the, the machines themselves are highly automated. They're spinning out a lot of data and we've got great systems in place to manage that information. Make it transferrable, viewable to a lot of the people that need it. The opportunity is not necessarily in the equipment that GE manufactures but the back-end business that drives that manufacturing, that drives those services. That's where, again we leveraged Smartsheet over the last year to close a lot of data quality issues. We're ruling out and canceling a lot of the human error of the process steps that we're seeing in a lot of businesses today. We're really taking the initiative of managing our data, bringing us, making us actually competitive in the fourth industrial revolution. I mean I've had a strong believe that if you're not managing your data correctly today, you'll market yourself out of the business, you won't stay ahead of the game. So I think, like I was saying before the biggest opportunity right now is the back-end of the business. Smart GE does a great job at manufacturing and producing high quality products. I think there's huge opportunity in saving the back end and optimizing the process that runs that. >> When you say the back end, there's always a lot of conversation about you know going from reactive to predictive to prescriptive. Analytics, again everybody likes to talk about keeping the turbine up. Are you talking about those types of processes or is it more, you know how that energy is fed into the grid and more kind of the connection to the broader ecosystem, when you say back end? >> Let's talk about the proactive and reactive situation, 'cause that's really what we're trying to drive. >> Okay. >> There can be particular cases where a turbine could fail in the middle of winter, a high-wind season and the visibility's not great. So what we've done is we've taken Smartsheet. We've given our technicians a mobile application tool to collect data as they visit turbines. We're taking information within Smartsheet, we aggregate it, we quantify it, and now we're able to predict turbine behavior based on this information. A little bit faster than some of the tools that GE provides today. A perfect example is about a month ago we determined that a turbine needed a quarter of a million dollar repair before any GE tool told us that. That was simply because of giving our technicians a tool, which is a Smartsheet webform and telling us what happens everyday you visit that turbine. That goes into the background. We take the information, aggregate it into a dashboard viewings. That gives us a great visual control and visual aid of our business. >> That visibility-- >> I was going to say, is he collecting different data, or are you processing it in a different way with the tooling that you set up with Smartsheet that gives you that visibility? >> They are, so we are collecting different data. So GE gives us a lot of data on our turbine health efficiency, how it's operating. It might quantify the number of faults per megawatt hour and per (mumbles) it for us for example. But what we're creating with Smartsheet is we're creating our own organic KPIs I'll call them, some metrics that we are creating ourselves to try to drive different behavior. So when the techs go in, we talk about parts consumptions, for example. So if this part's been consumed 20 times over the last month, you've got to ask why. You know, why do you keep visiting this turbine to do that. So that visibility drives a different discussion now, so now we can engage with engineers with different type, different information. They might be able to say, "Okay, "you know what, you guys got some good data here. "We think you're right. "We should execute this repair." >> So, that example that you gave and give me the number again that working with Smartsheets your team was able to find a, what did you say, a $250 million? >> $250,000 repair. >> Thousand dollar repair. >> That's the cost of the repair, but it's a proactive repair versus reactive so now we're not facing a long wait time, finding a crane, bringing a crane on site, getting the paperwork in place to get the job done 'cause it's not an easy repair. >> But there's a very impressive snowball effect of the benefits back to the business. You've found it faster. You were able to get, you know the parts needed faster, repair it faster. Clearly that goes all the way back up the chain from a revenue perspective. >> Absolutely. >> But you, when I alluded to you earlier, this renegade status, you brought Smartsheet in from your previous job and you've said, "This has enabled us "to find something faster than "our brand of technology's product would have been "able to do." Talk to us about this conviction that you brought in and is it kind of becoming viral within GE Renewable Energy yet? >> Good question. It's becoming viral, a lot of people are listening now. So we've talked to GE digital VPs. I've talked to the ERP providers in Europe, what they're doing with GE. So we've essentially, I call it a success story. They're not going to adopt Smartsheet. They want to build their own enterprise solution but, the reason why I call it a success story is because I've changed the way that they are thinking today. >> That's huge. Cultural change? >> I've presented a solution to them. I've essentially told them, you need to give us something that works for us faster. If you do this, it gives managers capacity to improve your business, really develop people that are working underneath you, engage them, empower them, and move the business forward not on a typical five year plan that most businesses have in place. But it's a step change. >> Right, right. >> It takes you year over year and you're stepping every year to something new, and I think in today's day and age with how fast things are moving, you need that. >> And I'm curious to unpack a little bit on this example where you said you know, it's this failing part that was giving you a leading indicator that there was a bigger problem. So that was just kind of a different way to look at the solution, right? You're identifying kind of a stupid consumption pattern on a spare part that shouldn't happen as opposed to the core data that's coming off that machine and that's what gave you kind of the unique insights. Does that come from you? Does that come techs who are in the field and have kind of a sense of, "Maybe we should be looking at this, "maybe we should be looking at that." How do you start to empower people or where do some of these different kind of points of view that then can be backed up with data in the Smartsheet process come from? >> So, it's all techs. (clears throat) Coming into the job last year, I asked one of the techs, I said, "Why are you going to this turbine?" And the question why is such a powerful question to ask. They said, "We're going to fix this." So what happened last time? They had no idea. So I said, "There's no "information to support your visit today? "And you don't understand why you're going today." They said, "As a result of something that was not "done correctly before." So we fixed that part first. We started giving them the information upfront. We gave them a tool to collect the data. So now they are empowered to provide very direct feedback to myself as a manager and even to an engineering team, like in New York for example. Something technicians never felt empowered to do before. They are the driving factors for those data collection, the decision making. I definitely appreciate that by giving them feedback on a daily basis, that what you guys are doing is changing the way that we manage the business. It's a very driven culture change by the front line. It's not something that I'm pushing down. I'm asking them to help me push it upwards to the senior level. >> And they've got to love it. They've got to love thinking that they've actually got input as opposed to just being called to go out and fix things when it breaks. >> Exactly. They're driving their day. They can go to work in the morning. They can look at the whole personality of a turbine, what's outstanding, what was done last time and the conversations are very quick in the morning. It used to be a 7 o'clock startup. They're not driving out 'til eight, 8:30, nine o'clock by the time they get their stuff together. I mean we're averaging a seven am to about 7:30 departure now. >> So each person is saving 60 to 90 minutes everyday. >> Every day now departure. >> That's a big roll up. In fact, I was looking at some of the productivity stats that Smartsheet talks about on their website and they say an average per, individual user of Smartsheet will save about 300 hours a year. An organization can save up to 60,000 hours a year. >> I believe that. That's believable. I mean there's, just a technical aspect of managing a turbine. If we even talk about you know issuing a purchase order. Managing contractor labor, invoices. The tool that we're using today is a complete end to end P & L management tool. So it takes invoicing from subcontractors, labor. We are inventory tracking, we are tracking any health and safety issues. Everything from end to end, so it's really done a great job for us. >> That's all built within your Smartsheet? >> Correct. >> Wow. >> And it's all mobile, so. I mean I'm not at my site this week, but on a daily basis I have visibility to my business. You're talking about 70, 80 plus machines, that's over you know about a hundred million dollars in assets that have to be managed effectively, efficiently, and correctly. >> You have visibility into everyday from wherever you are? >> Exactly, yes. >> That's a huge transformation. So we talked about you being a renegade and other groups within GE on divisions that are curious about this. I'm curious, have you heard anything today that they have announced that excites you, or maybe was any of this part of a feedback that you provided, as we've heard all day Jeff that they're very responsive to customer feedback in terms of product innovation. Anything you're going to go back to the office and be excited, like the next generation or what's coming available soon? Is it going to enable me to do X-Y-Z now? >> That's a good question. So GE is a very tough company to change. There will be a lot of takeaways from this trip and when I go head back. After the last conversation I had with GE digital and the team, they are going to hire a new resource and set budget aside to help close the gaps that we've identified. So I think after this visit and some of the things I've learned throughout the conference and when I head back I'll only be able to identify a few more gaps that they need to fill, and I'll push that up to them probably in the next week when I get back there and hopefully they can appreciate that candid feedback and take that and run with it. >> But you were able to fund your existing project just out of your own discretionary funds? >> Exactly. I mean that's one of the benefits of Smartsheet. It costs really nothing to create something, and my job is to manage wind farms, so I've taken initiative to create, I call it a mini-ERP system using Smartsheet with an associate of mine, and it's an organic creation. It didn't take us, I mean to run three wind farms, I started last April, it probably took us less than six months to create a working system. That's awesome feedback for Smartsheet, their tools are very user-friendly. It's lightweight, it takes away the fear of coding that Excel gives to some people. If you're a new user of any application you can kind of walk into it and run with it. That's one of the reasons why we took it from nothing to something in such a short period of time. >> Wow. >> That's a ground swell in action that has some significant results. But you'd better be careful. I'm imagining your success is going to go so viral, you're going to have way more than 75 turbines and three wind farms >> That's possible. >> to manage. (laughs) >> There's been a recent acquisition and there's other sites around me that my boss is, or my directors said, "Hey, what are you doing next week?" >> Oh! (laughs) >> "Let's go visit this site for a few minutes." Okay, I know what you're getting at. >> Kind of a good problem to have, but thanks so much for stopping by and sharing with us what you're doing as a renegade. It seems pretty contagious. >> Appreciate it, thank you for having me. >> Thanks. >> Thanks. >> For Jeff Frick I'm Lisa Martin and you're watching theCUBE live from Smartsheet Engage 2018. Stick around, Jeff and I will be back to wrap up the show in just a minute. (digital music)

Published Date : Oct 2 2018

SUMMARY :

Brought to you by Smartsheet. Gurmeet, great to have you on the program. I'm really happy to be here. So before we get into your renegade status, manage that business end to end. are the most quoted, often referenced IOT devices that GE manufactures but the back-end business to the broader ecosystem, when you say back end? Let's talk about the proactive and reactive and the visibility's not great. It might quantify the number of faults repair. getting the paperwork in place to get the job done Clearly that goes all the way back up the chain Talk to us about this conviction that you brought in I've talked to the ERP providers in Europe, That's huge. and move the business forward to something new, So that was just kind of a different way So now they are empowered to to go out and fix things when it breaks. and the conversations are very quick in the morning. productivity stats that Smartsheet talks about Everything from end to end, that have to be managed of a feedback that you provided, that they need to fill, that Excel gives to some people. That's a ground swell in action that has to manage. Okay, I know what you're good problem to have, but thanks so much and you're watching theCUBE live from

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Zaman Zaman, Founder & CEO at Skiplino & Alharith Alatawi, ONEGCC | AWS Summit Bahrain


 

>> Live from Bahrain, it's theCUBE, covering AWS Summit, Bahrain. Brought to you by Amazon Web Services. >> Okay, welcome back everyone. We are here live in Bahrain for Amazon's Web Service Summit in the Middle East, really built around the big announcement around their region coming which would open up in Q1 2019. And Amazon full force here and really bringing together a combination of cloud-computing, cloud-native, together with the community and entrepreneurship here. And of course we wanted to save the best for last of the day interview, the entrepreneurs themselves are going to tell a straight scoop what's happening 'cause it's a lot of action here. Alharith Alatawi, who is the CEO of ONEGCC and Zaman Zaman, founder and CEO of Skiplino. Welcome to theCUBE. Thanks for coming on. >> Thank you for having us. >> Thank you for having us. >> So I got to say, I was watching you guys yesterday in your little, and then Bahrain, you're on your best behavior. You didn't chirp too loud, but I can see the energy in the entrepreneurs. You know there's real entrepreneurs in the room when you can see the energy, right? And all the executives were in there, and you've got the Amazon, so you're on your best behavior banging your fists on the door. You guys are doing some good work, so congratulations. >> Thank you very much. >> So what's the real deal? What's it like here? I mean I know it's tough to get access to capital, but the government's bringing some capital to the table, there's momentum, there's opportunities. What's the straight scoop here? >> So for the past three years, when Start-up Bahrain started, there's been tremendous support from the government because they really want to see this, what they're calling the Fourth Industrial Revolution, they want it to happen. They're pushing for it. They're pushing technology start-ups. And we were really blessed to be, I mean to have started just a few months before that, so we're riding an amazing wave. We've been getting a lot of support from Tamkeen, a lot of legislation support from the government, the EDB obviously have been doing a massive job in trying to support us, getting us business. And I mean since we started til today, we've at least doubled or even tripled the amount of clients we have. And there's a lot of attention now to technology start-ups. And I think as a growing sector, Bahrain, we're really reaping the fruits of it. >> And what is your start-up, ONEGCC? Just take a minute to explain what your start-up's doing, how many people you've got going on, the stage of the opportunity. >> So before I founded or co-founded ONEGCC, I was in an investment firm, and one of our investments was in Saudi. It was called a mega-recruitment company. And what we were trying to do is, we had 500,000 work permits. We had to bring a bunch of people and start outsourcing them to companies, but the Ministry of Labor still wanted us to maintain Saudization within these companies that we're working with. And it was a very tough challenge trying to find the right GCC nationals, the right Saudis. I mean 40% of them hold degrees in Humanitarian Islamic Studies, so how do you place all of these when most of the jobs that are being offered are in construction, retail, and other services? So that's when we started ONEGCC. We said you know what, we'll hire people based on skills rather than their job titles or academic background. And that's really where we started ONEGCC. >> So it solves your own problem? >> Exactly. >> You had a little pain there. >> Well today it's our own problem. >> Yeah, now you have a bigger problem. It's called growth. >> (laughs) Yeah, but tomorrow it's going to become a global problem with AI and smart machines wiping out almost maybe 70%. >> So how many people involved in the start-up? What's the stage, would you call it? >> So today we have 18 employees. We're still early stage, but we're growing as well as we can. >> Great. Tell us about your story here. >> Well, mine was a multi-lingual intelligent queue management system. So we realized there was a gap in the market. >> First, explain what a queue management system is, and remember 'queue' is not an American word. That's an English word, or international word. Queue is 'line' they call it in America. >> Okay, let's say line management. >> But we're talking about physical standing in line at the bank. >> Yes. When you go there, you actually take a token and wait. So we realized it was a problem not only in Bahrain. It was a global problem. What we did was, we went to investigate the issue. How it started was, I went to a bank a day before I traveled, and I had to wait for one hour and forty-five minutes just to clear a check. So I found that not acceptable. So what we did was go study the markets. And we realized that was like three or four players controlling the market for the past thirty years. Some people tried to do it cloud-based, but they didn't get it right because they didn't cater to those segments, which is the large B2B clients that need to scale or have a large number of branches. So when we decided to go and build it on the cloud, we realized that there is no performance management on each agent that is live and was streamed. So when we built the reports, we realized that most of it is bottlenecks that can be solved with AI or machine learning. So we incorporated that into Skiplino. Now Skiplino has around 2,500 companies from around the globe in 196 countries. And it's now in 69 languages. >> That's amazing. How many people in your opportunity, working with you? >> Including founders, we're around 15. >> Fifteen, great. Well congratulations, and one of the things I wanted to kind of get here while we're broadcasting around the continent and around cloud is, I live in Silicon Valley, so everyone's got the entrepreneurial bug going on, but you have successes and failures. That's the way it works. You've got to try something and hit the homeruns once in a while, but you got to get a couple base hits. It's really hard. I mean people don't understand how hard it is, right? If they've never done it, it's hard as hell. So, but having the ecosystem support is key, but Start-up Bahrain is doing some good work with EDB. What is the key requirement and what's the need? Where is it working, are you guys seeing on the ground here? Because the community's there and that's a check. That's hard to do. I mean robust entrepreneur community's good, and there's money. So now you've just got to fill in the blank. What is the cloud going to bring you guys? What are you guys hoping for? What do you want to see? >> Of course with the cloud, the best thing that comes with the cloud is scalability, for us. In effect, we're removing the unpremised queue management systems businesses, but the good thing that's happening in Bahrain, and around the GCC too, is ministries and governments are more receptive for additional transformation, and they know that's the only way to keep up. So actually we're the first cloud-based service the Bahraini government used. >> And you're using Amazon now? >> No, (laughs) we're actually a Microsoft concept partner. >> Oh, okay. >> We're the first. >> Are you using Azure? >> Yes. >> Okay, makes sense. Great partner. >> Because we usually deal with banks and telecoms. Microsoft always has a foot in the door there, but we are thinking of having an AWS structure, too. >> It's okay, use it here. It is what it is, a multi-cloud world we're living in. How about your solution? >> So actually we were in the first cohort of C5 Accelerate, which is a program supported by AWS, so we are on AWS, and obviously for us, as a start-up, setting up in the beginning, we have limited resources, and setting up on the cloud just makes it so much easier. >> Yeah, a no-brainer. Not a decision. >> Exactly. >> You got to go to cloud. If you do a start-up and you're not on the cloud, you're spending too much cash. >> (laughs) Exactly. >> It's just the way it is. It's the dumbest thing you should ever do. Unless there's a prototype and you want it next to you, like a puppy and a dog or whatever pet, kind of thing, a security issue. Other than that, there's no reason. >> And it's faster to set up. It's easier for us to reach a wider audience. When we do reach the wider audience- >> What do you think about the show here? What was your walk-away? Obviously you guys are in the middle of the community. We're here for the first time. I was really impressed and I learned a lot, and I made some observations that I didn't expect to have that were really positive. It was a good experience for me, but you guys live it every day. Amazon's in town. There's good dynamics going on. What's your impression? >> Impression on what? >> This show, Amazon's presence, the community coming together. Everyone came here from the gulf states. >> I think one of the main things that we needed to happen in the system is that mind shift. So corporates to start adopting start-up technologies, and for investors who are used to investing in traditional investments and real estate to start actually investing in start-ups. So I think AWS really helped in that mind shift. I think the work that EDB is doing also is helping that mind shift. Now we're seeing more angel investors who are interested in getting into the tech start-up space and more corporates are willing to adopt our technologies, even though they're fairly new. >> Your thoughts on the show? >> It definitely shined a spotlight on Bahrain. Getting Amazon to open AWS in Bahrain is, first of all, we're getting a lot of talent that's going to come in and be trained to set up. So it's a huge- >> It's like you guys are standing around. The metaphor, I'm imagining, you're standing around, you're working on some things, you're hustling, you're scrapping, you're smart. And then all of a sudden, a big resource generator just pops down and says, hey entrepreneurs, I was built for you. >> Yeah. >> And you're there and now you're present at creation. And when you're present at creation of a movement that has this much growth because let's face it, this is going to be growth, and you guys are going to be the leaders. >> Yeah. >> Hopefully. >> So you got to pay it forward. You have big responsibilities. >> Hopefully. >> And you going to make some money along the way, too. I mean, you know the old expression. >> No pressure, huh? (laughs) >> You know the expression, "Hang around the barber shop, "you'll get a haircut." So this is, "Hang around the cloud, "you're going to create some value." So you've got to capture it. So this is the dynamic that I see as an entrepreneur. I was like, damn, if I lived here, I'd be setting up shop. I'd have five companies going on. I'd be telling all my friends to come on in. >> Because you're in the ground floor right now. >> You're present at creation. We're going to start covering you guys, and do some work with you guys. I'm already convinced. >> It's a big wave, and we're happy to be riding it. >> We're going to collaborate with you guys. I think it's a really unique thing. I mean at this scale, it's unprecedented. I mean this is Amazon. I mean in the U.S. everyone is jockeying for where Amazon's next headquarters is going to be, and literally, people are freaking out, like, come to my state. Because they know, with it come jobs, services. It's like putting up a sports stadium, and all of a sudden there's all these new things around it, right? >> Sure. >> It's going on, >> Exactly. >> So this is going to be a big opportunity. >> It's huge. >> For start-ups. So you guys are going to be reaping the rewards. >> Hopefully. >> You hungry? >> We are. (all laughing) >> You have no idea. >> I'm from California. In America, it's like we call it the wave. Get your surfboard, get out there. A lot of sets coming in. So congratulations. Thanks for sharing. >> Thank you very much. >> Thank you for coming to Bahrain. It's a pleasure having you. >> Looking forward to working more with you guys. >> Definitely a pleasure. >> Thank you, John. >> Okay, we're here in Bahrain. That's a wrap. We're wrapping up with the founders and CEOs. This is the entrepreneurial action here and the signs are all pointing towards growth. Amazon Web Service is going to bring cultural revolution, economic, society, people, all going to be coming here, for the region, not just Bahrain, but all around the region. I'm John Furrier with theCUBE. Thanks for watching.

Published Date : Sep 30 2018

SUMMARY :

Brought to you by Amazon Web Services. of the day interview, the So I got to say, I was but the government's bringing So for the past three years, the stage of the opportunity. and start outsourcing them to companies, Yeah, now you have a bigger problem. it's going to become a global problem So today we have 18 employees. Tell us about your story here. So we realized there and remember 'queue' is at the bank. and build it on the cloud, How many people in your What is the cloud going to bring you guys? and around the GCC too, No, (laughs) we're actually Okay, makes sense. foot in the door there, It is what it is, a multi-cloud So actually we were in the Yeah, a no-brainer. You got to go to cloud. It's the dumbest thing you should ever do. And it's faster to set up. We're here for the first time. Everyone came here from the gulf states. in the system is that mind shift. that's going to come in It's like you guys are standing around. and you guys are going to be the leaders. So you got to pay it forward. money along the way, too. You know the expression, Because you're in the We're going to start covering you guys, It's a big wave, and I mean in the U.S. everyone is jockeying So this is going to So you guys are going to We are. In America, it's like we call it the wave. Thank you for coming to Bahrain. Looking forward to and the signs are all

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Paul Appleby, Kinetica | theCUBE NYC 2018


 

>> Live from New York, it's the Cube (funky music) covering the Cube New York City 2018 brought to you by SiliconANGLE Media and its ecosystem partners. (funky music) >> Everyone welcome back to theCUBE live in New York City for Cube NYC. This is our live broadcast - two days of coverage around the big data world, AI, the future of Cloud analytics. I'm John Furrier, my cohost Peter Burris. Our next guest is Paul Appleby, CEO Kinetica. Thanks for coming back to theCUBE - good to see you. >> Great to be back again and great to visit in New York City - it's incredible to be here on this really important week. >> Last time we chatted was in our big data Silicon Valley event, which is going to be renamed Cube SV, because it's not just data anymore; there's a lot of Cloud involved, a lot of new infrastructure. But analytics has certainly changed. What's your perspective now in New York as you're in here hearing all the stories around the show and you talk to customers - what's the update from your perspective? Because certainly we're hearing a lot of Cloud this year - Cloud, multi Cloud, analytics, and eyeing infrastructure, proof in the pudding, that kind of thing. >> I'm going to come back to the Cloud thing because I think that's really important. We have shifted to this sort of hybrid multi Cloud world, and that's our future - there is no doubt about it, and that's right across all spectre of computing, not just as it relates to data. But I think this evolution of data has continued this journey that we've all been on from whatever you want to call it - systems or record - to the world of big data where we're trying to gain insights out of this massive oceans of data. But we're in a world today where we're leveraging the power of analytics and intelligence, AI machine learning, to make fundamental decisions that drive some action. Now that action may be to a human to make a decision to interact more effectively with a customer, or it could be to a machine to automate some process. And we're seeing this fundamental shift towards a focus on that problem, and associated with that, we're leveraging the power of Cloud, AI, ML, and all the rest of it. >> And the human role in all this has been talked about. I've seen in the US in the political landscape, data for good, we see Facebook up there being basically litigated publicly in front of the Senate around the role of data and the elections. People are talking in the industry about the role of humans with machines is super important. This is now coming back as a front and center issue of hey, machines do great intelligence, but what about the human piece? What's your view on the human interaction component, whether it's the curation piece, the role of the citizen analyst, or whatever we're calling it these days, and what machines do to supplement that? >> Really good question - I've spent a lot of time thinking about this. I've had the incredible privilege of being able to attend the World Economic Forum for the last five years, and this particular topic of how Robotics Automation Artificial Intelligence machine learning is impacting economies, societies, and ultimately the nature of work has been a really big thread there for a number of years. I've formed a fundamental view: first of all, any technology can be used for good purposes and bad purposes, and it's - >> It always is. >> And it always is, and it's incumbent upon society and government to apply the appropriate levels of regulation, and for corporations to obviously behave the right way, but setting aside those topics - because we could spend hours talking about those alone - there is a fundamental issue, and this is this kind of conversation about what a lot of people like to describe as the fourth industrial revolution. I've spent a lot of time, because you hear people bandy that around - what do they really mean, and what are we really talking about? I've looked at every point in time where there's been an industrial revolution - there's been a fundamental shift of work that was done by humans that's now done by machines. There's been a societal uproar, and there're being new forms of work created, and society's evolved. What I look at today is yes, there's a responsibility and a regular treaside to this, but there's also a responsibility in business and society to prepare our workers and our kids for new forms of work, cause that's what I really think we should be thinking about - what are the new forms of work that are actually unlocked by these technologies, rather than what are the roles that are displaced by this steam powered engine. (laughs softly) >> Well, Paul, we totally agree with you. There's one other step in this process. It kind of anticipates each of these revolutions, and that is there is a process of new classes of asset formation. Mhm. So if you go back to when we put new power trains inside row houses to facilitate the industrial revolution in the early 1800s, and you could say the same thing about transportation, and what the trains did and whatnot. There's always this process of new asset formation that presaged some of these changes. Today it's data - data's an asset cause businesses ultimately institutionalize, or re institutionalize, their work around what they regard as valuable. Now, when we start talking about machines telling other machines what to do, or providing options or paring off options for humans so they have clear sets of things that they can take on, speed becomes a crucial issue, right? At the end of the day, all of this is going to come back to how fast can you process data? Talk to us a little bit about how that dynamic and what you guys are doing to make it possible is impacting business choices. >> Two really important things to unpack there, and one I think I'd love to touch on later, which is data as an asset class and how corporations should treat data. You talk about speed, and I want to talk about speed in the context of perishability, because the truth is if you're going to drive these incredible insights, whether it's related to a cyber threat, or a terrorist threat, or an opportunity to expand your relationship with a customer, or to make a critical decision in a motor vehicle in an autonomous operating mode, these things are about taking massive volumes of streaming data, running analytics in real time, and making decisions in real time. These are not about gleaning insights from historic pools or oceans of data; this is about making decisions that are fundamental to - >> Right now. >> The environment that you're in right now. You think about the autonomous car - great example of the industrial Internet, one we all love to talk about. The mechanical problems associated with autonomy have been solved, fundamentally sensors in cars, and the automated processes related to that. The decisioning engines - they need to be applied at scale in millions of vehicles in real time. That's an extreme data problem. The biggest problem solved there is data, and then over time, societal and regulatory change means that this is going to take some time before it comes to fruition. >> We were just saying - I think it was 100 Teslas generating 100 terabytes of data a day based on streams from its fleet of cars its customers have. >> We firmly believe that longer term, when you get to true autonomy, each car will probably generate around ten terabytes of data a day. That is an extremely complex problem to solve, because at the end of the day, this thinking that you're able to drive that data back to some centralized brain to be making those decisions for and on behalf of the cars is just fundamentally flawed. It has to happen in the car itself. >> Totally agree. >> This is putting super computers inside cars. >> Which is kind of happening - in fact, that 100 terabytes a day is in fact the data that does get back to Tesla. >> Yeah. >> As you said, there's probably 90% of the data is staying inside the car, which is unbelievable scale. >> So the question I wanted to ask you - you mentioned the industrial revolution, so every time there's a new revolution, there's an uproar, you mentioned. But there's also a step up of new capabilities, so if there's new work being developed, usually entrepreneur activity - weird entrepreneurs figured out that everyone says they're not weird anymore; it's great. But there's a step up of new capability that's built. Someone else says hey, the way we used to do databases and networks was great for moving one gig Ethernet on top of the rack; now you got 10 terabytes coming off a car or wireless spectrum. We got to rethink spectrum, or we got to rethink database. Let's use some of these GPUs - so a new step up of suppliers have to come in to support the new work. What's your vision on some of those things that are happening now - that you think people aren't yet seeing? What are some of those new step up functions? Is it on the database side, is it on the network, is it on the 5G - where's the action? >> Wow. Because who's going to support the Teslas? (Paul laughs) Who's going to support the new mobile revolution, the new iPhones the size of my two hands put together? What's your thoughts on that? >> The answer is all of the above. Let me talk about that and what I mean by that. Because you're looking at it from the technology perspective, I'd love to come back and talk about the human perspective as well, but from the technology perspective, of course leveraging power is going to be fundamental to this, because if you think about the types of use cases where you're going to have to be gigathreading queries against massive volumes of data, both static and streaming, you can't do that with historic technology, so that's going to be a critical part of it. The other part of it that we haven't mentioned a lot here but I think we should bring into it is if you think about these types of industrial Internet use cases, or IOT - even consumer Internet IOT related use cases - a lot of the decisioning has to occur out of the H. It cannot occur in a central facility, so it means actually putting the AI or ML engine inside the vehicle, or inside the cell phone tower, or inside the oil rig, and that is going to be a really big part of you know, shifting back to this very distributive model of machine lining in AI, which brings very complex questions in of how you drive governance - (John chuckles) >> And orchestration around employing Ai and ML models at massive scale, out to edge devices. >> Inferencing at the edge, certainly. It's going to be interesting to see what happens with training - we know that some of the original training will happen at the center, but some of that maintenance training? It's going to be interesting to see where that actually - it's probably going to be a split function, but you're going to need really high performing databases across the board, and I think that's one of the big answers, John, is that everybody says oh, it's all going to be in software. It's going to be a lot of hard word answers. >> Yep. >> Well the whole idea is just it's provocative to think about it and also intoxicating if you also want to go down that rabbit hole... If you think about that car, okay, if they're going to be doing century machine learning at the edge - okay, what data are you working off of? There's got to be some storage, and then what about real time data coming from other either horizontally scalable data sets. (laughs) So the question is, what do they have access to? Are they optimized for the decision making at that time? >> Mhm. >> Again, talk about the future of work - this is a big piece, but this is the human piece as well. >> Yeah. >> Are our kids going to be in a multi massive, multi player online game called Life? >> They are. >> They are now. They're on Fortnite, they're on Call of Duty, and all this gaming culture. >> But I think this is one of the interesting things, because there's a very strong correlation between information theory and thermodynamics. >> Mhm. >> They're the same exact - in physics, they are the identical algorithms and the identical equations. There's not a lot of difference, and you go back to the original revolution, you have a series of row houses, you put a power supply all the way down, you can run a bunch of looms. The big issue is entropy - how much heat are you generating? How do you get greater efficiency out of that single power supply? Same thing today: we're worried about the amount of cost, the amount of energy, the amount of administrative overhead associated with using data as an asset, and the faster the database, the more natural it is, the more easy it is to administer, the more easy it is to apply to a lot of different cases, the better. And it's going to be very, very interesting over the next few year to see how - Does database come in memory? Does database stay out over there? A lot of questions are going to be answered in the next couple years as we try to think about where these information transducers actually reside, and how they do their job. >> Yeah, and that's going to be driven yes, partially by the technology, but more importantly by the problems that we're solving. Here we are in New York City - you look at financial services. There are two massive factors in financial services going on what is the digital bank of the future look like, and how the banks interact with their customers, and how you get that true one-to-one engagement, which historically has been virtually impossible for companies that have millions or tens of millions of customers, so fundamental transformation of customer engagement driven by these advanced or excelerated analytics engines, and the pair of AI and ML, but then on the other side if you start looking at really incredibly important things for the banks like risk and spread, historically because of the volumes of data, it's been virtually impossible for them to present their employees with a true picture of those things. Now, with these accelerated technologies, you can take all the historic trading data, and all of the real time trading data, smash that together, and run real time analytics to make the right decisions in the moment of interaction with a customer, and that is incredibly powerful for both the customer, but also for the bank in mitigating risk, and they're the sorts of things we're doing with banks up and down the city here in New York, and of course, right around the world. >> So here's a question for you, so with that in mind - this is kind of more of a thought exercise - will banks even be around in 20 years? >> Wow. (laughs) >> I mean, you've got block chains saying we're going to have new crypto models here, if you take this Tesla with ten terabytes going out every second or whatever that number is. If that's the complex problem, banking should be really easy to solve. >> I think it's incumbent on boards in every industry, not just banking, to think about what existential threats exist, because there are incredibly powerful, successful companies that have gone out of existence because of fundamental shifts and buying behaviors or technologies - I think banks need to be concerned. >> Every industry needs to be concerned. >> Every industry needs to be concerned. >> At the end of the day, every board needs to better understand how they can reduce their assets specificities, right? How they can have their assets be more fungible and more applicable or appropriable to multiple different activities? Think about a future where data and digital assets are a dominant feature of business. Asset specificities go down; today their very definition of vertical industry is defined by the assets associated with bottling, the assets associated with flying, the assets associated with any number of other things. As aspect specialist needs to go down because of data, it changes even the definition of industry, let alone banking. >> Yeah, and auto industry's a great example. Will we own cars in the future? Will we confirm them as a service? >> Exactly. >> Car order manufacturers need to come to terms with that. The banks need to come to terms with the fact that the fundamental infrastructure for payments, whether it's domestic or global, will change. I mean, it is going to change. >> It's changing. It's changing. >> It has to change, and it's in the process of changing, and I'm not talking about crypto, you know, what form of digital currency exists in the future, we can argue about forever, but a fundamental underlying platform for real time exchange - that's just the future. Now, what does that mean for banks that rely heavily on payments as part of their core driver of profitability? Now that's a really important thing to come to terms with. >> Or going back to the point you made earlier. We may not have banks, but we have bankers. There's still going to be people who're providing advice in council, helping the folks understand what businesses to buy, what businesses to sell. So whatever industry they're in, we will still have the people that bring the extra taste to the data. >> Okay, we got to break it there, we've run out of time. Paul, love to chat further about future banking, all this other stuff, and also, as we live in a connected world, what does that mean? We're obviously connected to data; we certainly know there's gonnna be a ton of data. We're bringing that to you here, New York City, with Cube NYC. Stay with us for more coverage after the short break. (funky music)

Published Date : Sep 13 2018

SUMMARY :

brought to you by SiliconANGLE Media Thanks for coming back to theCUBE - good to see you. in New York City - it's incredible to be here around the show and you talk to customers - Now that action may be to a human to make a decision about the role of humans with machines is super important. to attend the World Economic Forum for the last and government to apply the appropriate levels At the end of the day, all of this is going to come back to and one I think I'd love to touch on later, and the automated processes related to that. based on streams from its fleet of cars because at the end of the day, a day is in fact the data that does get back to Tesla. is staying inside the car, which is unbelievable scale. So the question I wanted to ask you - Who's going to support the new mobile revolution, a lot of the decisioning has to occur out of the H. at massive scale, out to edge devices. It's going to be interesting to see what happens There's got to be some storage, and then what about Again, talk about the future of work - this is and all this gaming culture. But I think this is one of the interesting things, the more easy it is to administer, the more easy it is and all of the real time trading data, Wow. If that's the complex problem, or technologies - I think banks need to be concerned. the assets associated with bottling, Yeah, and auto industry's a great example. The banks need to come to terms with the fact It's changing. Now that's a really important thing to come to terms with. Or going back to the point you made earlier. We're bringing that to you here,

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Lenovo Transform 2.0 Keynote | Lenovo Transform 2018


 

(electronic dance music) (Intel Jingle) (ethereal electronic dance music) ♪ Okay ♪ (upbeat techno dance music) ♪ Oh oh oh oh ♪ ♪ Oh oh oh oh ♪ ♪ Oh oh oh oh oh ♪ ♪ Oh oh oh oh ♪ ♪ Oh oh oh oh oh ♪ ♪ Take it back take it back ♪ ♪ Take it back ♪ ♪ Take it back take it back ♪ ♪ Take it back ♪ ♪ Take it back take it back ♪ ♪ Yeah everybody get loose yeah ♪ ♪ Yeah ♪ ♪ Ye-yeah yeah ♪ ♪ Yeah yeah ♪ ♪ Everybody everybody yeah ♪ ♪ Whoo whoo ♪ ♪ Whoo whoo ♪ ♪ Whoo yeah ♪ ♪ Everybody get loose whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ >> As a courtesy to the presenters and those around you, please silence all mobile devices, thank you. (electronic dance music) ♪ Everybody get loose ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ (upbeat salsa music) ♪ Ha ha ha ♪ ♪ Ah ♪ ♪ Ha ha ha ♪ ♪ So happy ♪ ♪ Whoo whoo ♪ (female singer scatting) >> Ladies and gentlemen, please take your seats. Our program will begin momentarily. ♪ Hey ♪ (female singer scatting) (male singer scatting) ♪ Hey ♪ ♪ Whoo ♪ (female singer scatting) (electronic dance music) ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ Red don't go ♪ ♪ All hands are in don't go ♪ ♪ In don't go ♪ ♪ Oh red go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ All hands are red don't go ♪ ♪ All hands are in red red red red ♪ ♪ All hands are in don't go ♪ ♪ All hands are in red go ♪ >> Ladies and gentlemen, there are available seats. Towards house left, house left there are available seats. If you are please standing, we ask that you please take an available seat. We will begin momentarily, thank you. ♪ Let go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ (upbeat electronic dance music) ♪ Just make me ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ I live ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ Hey ♪ ♪ Yeah ♪ ♪ Oh ♪ ♪ Ah ♪ ♪ Ah ah ah ah ah ah ♪ ♪ Just make me ♪ ♪ Just make me ♪ (bouncy techno music) >> Ladies and gentlemen, once again we ask that you please take the available seats to your left, house left, there are many available seats. If you are standing, please make your way there. The program will begin momentarily, thank you. Good morning! This is Lenovo Transform 2.0! (keyboard clicks) >> Progress. Why do we always talk about it in the future? When will it finally get here? We don't progress when it's ready for us. We need it when we're ready, and we're ready now. Our hospitals and their patients need it now, our businesses and their customers need it now, our cities and their citizens need it now. To deliver intelligent transformation, we need to build it into the products and solutions we make every day. At Lenovo, we're designing the systems to fight disease, power businesses, and help you reach more customers, end-to-end security solutions to protect your data and your companies reputation. We're making IT departments more agile and cost efficient. We're revolutionizing how kids learn with VR. We're designing smart devices and software that transform the way you collaborate, because technology shouldn't just power industries, it should power people. While everybody else is talking about tomorrow, we'll keep building today, because the progress we need can't wait for the future. >> Please welcome to the stage Lenovo's Rod Lappen! (electronic dance music) (audience applauding) >> Alright. Good morning everyone! >> Good morning. >> Ooh, that was pretty good actually, I'll give it one more shot. Good morning everyone! >> Good morning! >> Oh, that's much better! Hope everyone's had a great morning. Welcome very much to the second Lenovo Transform event here in New York. I think when I got up just now on the steps I realized there's probably one thing in common all of us have in this room including myself which is, absolutely no one has a clue what I'm going to say today. So, I'm hoping very much that we get through this thing very quickly and crisply. I love this town, love New York, and you're going to hear us talk a little bit about New York as we get through here, but just before we get started I'm going to ask anyone who's standing up the back, there are plenty of seats down here, and down here on the right hand side, I think he called it house left is the professional way of calling it, but these steps to my right, your left, get up here, let's get you all seated down so that you can actually sit down during the keynote session for us. Last year we had our very first Lenovo Transform. We had about 400 people. It was here in New York, fantastic event, today, over 1,000 people. We have over 62 different technology demonstrations and about 15 breakout sessions, which I'll talk you through a little bit later on as well, so it's a much bigger event. Next year we're definitely going to be shooting for over 2,000 people as Lenovo really transforms and starts to address a lot of the technology that our commercial customers are really looking for. We were however hampered last year by a storm, I don't know if those of you who were with us last year will remember, we had a storm on the evening before Transform last year in New York, and obviously the day that it actually occurred, and we had lots of logistics. Our media people from AMIA were coming in. They took the, the plane was circling around New York for a long time, and Kamran Amini, our General Manager of our Data Center Infrastructure Group, probably one of our largest groups in the Lenovo DCG business, took 17 hours to get from Raleigh, North Carolina to New York, 17 hours, I think it takes seven or eight hours to drive. Took him 17 hours by plane to get here. And then of course this year, we have Florence. And so, obviously the hurricane Florence down there in the Carolinas right now, we tried to help, but still Kamran has made it today. Unfortunately, very tragically, we were hoping he wouldn't, but he's here today to do a big presentation a little bit later on as well. However, I do want to say, obviously, Florence is a very serious tragedy and we have to take it very serious. We got, our headquarters is in Raleigh, North Carolina. While it looks like the hurricane is just missing it's heading a little bit southeast, all of our thoughts and prayers and well wishes are obviously with everyone in the Carolinas on behalf of Lenovo, everyone at our headquarters, everyone throughout the Carolinas, we want to make sure everyone stays safe and out of harm's way. We have a great mixture today in the crowd of all customers, partners, industry analysts, media, as well as our financial analysts from all around the world. There's over 30 countries represented here and people who are here to listen to both YY, Kirk, and Christian Teismann speak today. And so, it's going to be a really really exciting day, and I really appreciate everyone coming in from all around the world. So, a big round of applause for everyone whose come in. (audience applauding) We have a great agenda for you today, and it starts obviously a very consistent format which worked very successful for us last year, and that's obviously our keynote. You'll hear from YY, our CEO, talk a little bit about the vision he has in the industry and how he sees Lenovo's turned the corner and really driving some great strategy to address our customer's needs. Kirk Skaugen, our Executive Vice President of DCG, will be up talking about how we've transformed the DCG business and once again are hitting record growth ratios for our DCG business. And then you'll hear from Christian Teismann, our SVP and General Manager for our commercial business, get up and talk about everything that's going on in our IDG business. There's really exciting stuff going on there and obviously ThinkPad being the cornerstone of that I'm sure he's going to talk to us about a couple surprises in that space as well. Then we've got some great breakout sessions, I mentioned before, 15 breakout sessions, so while this keynote section goes until about 11:30, once we get through that, please go over and explore, and have a look at all of the breakout sessions. We have all of our subject matter experts from both our PC, NBG, and our DCG businesses out to showcase what we're doing as an organization to better address your needs. And then obviously we have the technology pieces that I've also spoken about, 62 different technology displays there arranged from everything IoT, 5G, NFV, everything that's really cool and hot in the industry right now is going to be on display up there, and I really encourage all of you to get up there. So, I'm going to have a quick video to show you from some of the setup yesterday on a couple of the 62 technology displays we've got on up on stage. Okay let's go, so we've got a demonstrations to show you today, one of the greats one here is the one we've done with NC State, a high-performance computing artificial intelligence demonstration of fresh produce. It's about modeling the population growth of the planet, and how we're going to supply water and food as we go forward. Whoo. Oh, that is not an apple. Okay. (woman laughs) Second one over here is really, hey Jonas, how are you? Is really around virtual reality, and how we look at one of the most amazing sites we've got, as an install on our high-performance computing practice here globally. And you can see, obviously, that this is the Barcelona supercomputer, and, where else in New York can you get access to being able to see something like that so easily? Only here at Lenovo Transform. Whoo, okay. (audience applauding) So there's two examples of some of the technology. We're really encouraging everyone in the room after the keynote to flow into that space and really get engaged, and interact with a lot of the technology we've got up there. It seems I need to also do something about my fashion, I've just realized I've worn a vest two days in a row, so I've got to work on that as well. Alright so listen, the last thing on the agenda, we've gone through the breakout sessions and the demo, tonight at four o'clock, there's about 400 of you registered to be on the cruise boat with us, the doors will open behind me. the boat is literally at the pier right behind us. You need to make sure you're on the boat for 4:00 p.m. this evening. Outside of that, I want everyone to have a great time today, really enjoy the experience, make it as experiential as you possibly can, get out there and really get in and touch the technology. There's some really cool AI displays up there for us all to get involved in as well. So ladies and gentlemen, without further adieu, it gives me great pleasure to introduce to you a lover of tennis, as some of you would've heard last year at Lenovo Transform, as well as a lover of technology, Lenovo, and of course, New York City. I am obviously very pleasured to introduce to you Yang Yuanqing, our CEO, as we like to call him, YY. (audience applauding) (upbeat funky music) >> Good morning, everyone. >> Good morning. >> Thank you Rod for that introduction. Welcome to New York City. So, this is the second year in a row we host our Transform event here, because New York is indeed one of the most transformative cities in the world. Last year on this stage, I spoke about the Fourth Industrial Revolution, and our vision around the intelligent transformation, how it would fundamentally change the nature of business and the customer relationships. And why preparing for this transformation is the key for the future of our company. And in the last year I can assure you, we were being very busy doing just that, from searching and bringing global talents around the world to the way we think about every product and every investment we make. I was here in New York just a month ago to announce our fiscal year Q1 earnings, which was a good day for us. I think now the world believes it when we say Lenovo has truly turned the corner to a new phase of growth and a new phase of acceleration in executing the transformation strategy. That's clear to me is that the last few years of a purposeful disruption at Lenovo have led us to a point where we can now claim leadership of the coming intelligent transformation. People often asked me, what is the intelligent transformation? I was saying this way. This is the unlimited potential of the Fourth Industrial Revolution driven by artificial intelligence being realized, ordering a pizza through our speaker, and locking the door with a look, letting your car drive itself back to your home. This indeed reflect the power of AI, but it just the surface of it. The true impact of AI will not only make our homes smarter and offices more efficient, but we are also completely transformed every value chip in every industry. However, to realize these amazing possibilities, we will need a structure built around the key components, and one that touches every part of all our lives. First of all, explosions in new technology always lead to new structures. This has happened many times before. In the early 20th century, thousands of companies provided a telephone service. City streets across the US looked like this, and now bundles of a microscopic fiber running from city to city bring the world closer together. Here's what a driving was like in the US, up until 1950s. Good luck finding your way. (audience laughs) And today, millions of vehicles are organized and routed daily, making the world more efficient. Structure is vital, from fiber cables and the interstate highways, to our cells bounded together to create humans. Thankfully the structure for intelligent transformation has emerged, and it is just as revolutionary. What does this new structure look like? We believe there are three key building blocks, data, computing power, and algorithms. Ever wondered what is it behind intelligent transformation? What is fueling this miracle of human possibility? Data. As the Internet becomes ubiquitous, not only PCs, mobile phones, have come online and been generating data. Today it is the cameras in this room, the climate controls in our offices, or the smart displays in our kitchens at home. The number of smart devices worldwide will reach over 20 billion in 2020, more than double the number in 2017. These devices and the sensors are connected and generating massive amount of data. By 2020, the amount of data generated will be 57 times more than all the grains of sand on Earth. This data will not only make devices smarter, but will also fuel the intelligence of our homes, offices, and entire industries. Then we need engines to turn the fuel into power, and the engine is actually the computing power. Last but not least the advanced algorithms combined with Big Data technology and industry know how will form vertical industrial intelligence and produce valuable insights for every value chain in every industry. When these three building blocks all come together, it will change the world. At Lenovo, we have each of these elements of intelligent transformations in a single place. We have built our business around the new structure of intelligent transformation, especially with mobile and the data center now firmly part of our business. I'm often asked why did you acquire these businesses? Why has a Lenovo gone into so many fields? People ask the same questions of the companies that become the leaders of the information technology revolution, or the third industrial transformation. They were the companies that saw the future and what the future required, and I believe Lenovo is the company today. From largest portfolio of devices in the world, leadership in the data center field, to the algorithm-powered intelligent vertical solutions, and not to mention the strong partnership Lenovo has built over decades. We are the only company that can unify all these essential assets and deliver end to end solutions. Let's look at each part. We now understand the important importance data plays as fuel in intelligent transformation. Hundreds of billions of devices and smart IoTs in the world are generating better and powering the intelligence. Who makes these devices in large volume and variety? Who puts these devices into people's home, offices, manufacturing lines, and in their hands? Lenovo definitely has the front row seats here. We are number one in PCs and tablets. We also produces smart phones, smart speakers, smart displays. AR/VR headsets, as well as commercial IoTs. All of these smart devices, or smart IoTs are linked to each other and to the cloud. In fact, we have more than 20 manufacturing facilities in China, US, Brazil, Japan, India, Mexico, Germany, and more, producing various devices around the clock. We actually make four devices every second, and 37 motherboards every minute. So, this factory located in my hometown, Hu-fi, China, is actually the largest laptop factory in the world, with more than three million square feet. So, this is as big as 42 soccer fields. Our scale and the larger portfolio of devices gives us access to massive amount of data, which very few companies can say. So, why is the ability to scale so critical? Let's look again at our example from before. The early days of telephone, dozens of service providers but only a few companies could survive consolidation and become the leader. The same was true for the third Industrial Revolution. Only a few companies could scale, only a few could survive to lead. Now the building blocks of the next revolution are locking into place. The (mumbles) will go to those who can operate at the scale. So, who could foresee the total integration of cloud, network, and the device, need to deliver intelligent transformation. Lenovo is that company. We are ready to scale. Next, our computing power. Computing power is provided in two ways. On one hand, the modern supercomputers are providing the brute force to quickly analyze the massive data like never before. On the other hand the cloud computing data centers with the server storage networking capabilities, and any computing IoT's, gateways, and miniservers are making computing available everywhere. Did you know, Lenovo is number one provider of super computers worldwide? 170 of the top 500 supercomputers, run on Lenovo. We hold 89 World Records in key workloads. We are number one in x86 server reliability for five years running, according to ITIC. a respected provider of industry research. We are also the fastest growing provider of hyperscale public cloud, hyper-converged and aggressively growing in edge computing. cur-ges target, we are expand on this point soon. And finally to run these individual nodes into our symphony, we must transform the data and utilize the computing power with advanced algorithms. Manufactured, industry maintenance, healthcare, education, retail, and more, so many industries are on the edge of intelligent transformation to improve efficiency and provide the better products and services. We are creating advanced algorithms and the big data tools combined with industry know-how to provide intelligent vertical solutions for several industries. In fact, we studied at Lenovo first. Our IT and research teams partnered with our global supply chain to develop an AI that improved our demand forecasting accuracy. Beyond managing our own supply chain we have offered our deep learning supply focused solution to other manufacturing companies to improve their efficiency. In the best case, we have improved the demand, focused the accuracy by 30 points to nearly 90 percent, for Baosteel, the largest of steel manufacturer in China, covering the world as well. Led by Lenovo research, we launched the industry-leading commercial ready AR headset, DaystAR, partnering with companies like the ones in this room. This technology is being used to revolutionize the way companies service utility, and even our jet engines. Using our workstations, servers, and award-winning imaging processing algorithms, we have partnered with hospitals to process complex CT scan data in minutes. So, this enable the doctors to more successfully detect the tumors, and it increases the success rate of cancer diagnosis all around the world. We are also piloting our smart IoT driven warehouse solution with one of the world's largest retail companies to greatly improve the efficiency. So, the opportunities are endless. This is where Lenovo will truly shine. When we combine the industry know-how of our customers with our end-to-end technology offerings, our intelligent vertical solutions like this are growing, which Kirk and Christian will share more. Now, what will drive this transformation even faster? The speed at which our networks operate, specifically 5G. You may know that Lenovo just launched the first-ever 5G smartphone, our Moto Z3, with the new 5G Moto model. We are partnering with multiple major network providers like Verizon, China Mobile. With the 5G model scheduled to ship early next year, we will be the first company to provide a 5G mobile experience to any users, customers. This is amazing innovation. You don't have to buy a new phone, just the 5G clip on. What can I say, except wow. (audience laughs) 5G is 10 times the fast faster than 4G. Its download speed will transform how people engage with the world, driverless car, new types of smart wearables, gaming, home security, industrial intelligence, all will be transformed. Finally, accelerating with partners, as ready as we are at Lenovo, we need partners to unlock our full potential, partners here to create with us the edge of the intelligent transformation. The opportunities of intelligent transformation are too profound, the scale is too vast. No company can drive it alone fully. We are eager to collaborate with all partners that can help bring our vision to life. We are dedicated to open partnerships, dedicated to cross-border collaboration, unify the standards, share the advantage, and market the synergies. We partner with the biggest names in the industry, Intel, Microsoft, AMD, Qualcomm, Google, Amazon, and Disney. We also find and partner with the smaller innovators as well. We're building the ultimate partner experience, open, shared, collaborative, diverse. So, everything is in place for intelligent transformation on a global scale. Smart devices are everywhere, the infrastructure is in place, networks are accelerating, and the industries demand to be more intelligent, and Lenovo is at the center of it all. We are helping to drive change with the hundreds of companies, companies just like yours, every day. We are your partner for intelligent transformation. Transformation never stops. This is what you will hear from Kirk, including details about Lenovo NetApp global partnership we just announced this morning. We've made the investments in every single aspect of the technology. We have the end-to-end resources to meet your end-to-end needs. As you attend the breakout session this afternoon, I hope you see for yourself how much Lenovo has transformed as a company this past year, and how we truly are delivering a future of intelligent transformation. Now, let me invite to the stage Kirk Skaugen, our president of Data Center growth to tell you about the exciting transformation happening in the global Data C enter market. Thank you. (audience applauding) (upbeat music) >> Well, good morning. >> Good morning. >> Good morning! >> Good morning! >> Excellent, well, I'm pleased to be here this morning to talk about how we're transforming the Data Center and taking you as our customers through your own intelligent transformation journey. Last year I stood up here at Transform 1.0, and we were proud to announce the largest Data Center portfolio in Lenovo's history, so I thought I'd start today and talk about the portfolio and the progress that we've made over the last year, and the strategies that we have going forward in phase 2.0 of Lenovo's transformation to be one of the largest data center companies in the world. We had an audacious vision that we talked about last year, and that is to be the most trusted data center provider in the world, empowering customers through the new IT, intelligent transformation. And now as the world's largest supercomputer provider, giving something back to humanity, is very important this week with the hurricanes now hitting North Carolina's coast, but we take this most trusted aspect very seriously, whether it's delivering the highest quality products on time to you as customers with the highest levels of security, or whether it's how we partner with our channel partners and our suppliers each and every day. You know we're in a unique world where we're going from hundreds of millions of PCs, and then over the next 25 years to hundred billions of connected devices, so each and every one of you is going through this intelligent transformation journey, and in many aspects were very early in that cycle. And we're going to talk today about our role as the largest supercomputer provider, and how we're solving humanity's greatest challenges. Last year we talked about two special milestones, the 25th anniversary of ThinkPad, but also the 25th anniversary of Lenovo with our IBM heritage in x86 computing. I joined the workforce in 1992 out of college, and the IBM first personal server was launching at the same time with an OS2 operating system and a free mouse when you bought the server as a marketing campaign. (audience laughing) But what I want to be very clear today, is that the innovation engine is alive and well at Lenovo, and it's really built on the culture that we're building as a company. All of these awards at the bottom are things that we earned over the last year at Lenovo. As a Fortune now 240 company, larger than companies like Nike, or AMEX, or Coca-Cola. The one I'm probably most proud of is Forbes first list of the top 2,000 globally regarded companies. This was something where 15,000 respondents in 60 countries voted based on ethics, trustworthiness, social conduct, company as an employer, and the overall company performance, and Lenovo was ranked number 27 of 2000 companies by our peer group, but we also now one of-- (audience applauding) But we also got a perfect score in the LGBTQ Equality Index, exemplifying the diversity internally. We're number 82 in the top working companies for mothers, top working companies for fathers, top 100 companies for sustainability. If you saw that factory, it's filled with solar panels on the top of that. And now again, one of the top global brands in the world. So, innovation is built on a customer foundation of trust. We also said last year that we'd be crossing an amazing milestone. So we did, over the last 12 months ship our 20 millionth x86 server. So, thank you very much to our customers for this milestone. (audience applauding) So, let me recap some of the transformation elements that have happened over the last year. Last year I talked about a lot of brand confusion, because we had the ThinkServer brand from the legacy Lenovo, the System x, from IBM, we had acquired a number of networking companies, like BLADE Network Technologies, et cetera, et cetera. Over the last year we've been ramping based on two brand structures, ThinkAgile for next generation IT, and all of our software-defined infrastructure products and ThinkSystem as the world's highest performance, highest reliable x86 server brand, but for servers, for storage, and for networking. We have transformed every single aspect of the customer experience. A year and a half ago, we had four different global channel programs around the world. Typically we're about twice the mix to our channel partners of any of our competitors, so this was really important to fix. We now have a single global Channel program, and have technically certified over 11,000 partners to be technical experts on our product line to deliver better solutions to our customer base. Gardner recently recognized Lenovo as the 26th ranked supply chain in the world. And, that's a pretty big honor, when you're up there with Amazon and Walmart and others, but in tech, we now are in the top five supply chains. You saw the factory network from YY, and today we'll be talking about product shipping in more than 160 countries, and I know there's people here that I've met already this morning, from India, from South Africa, from Brazil and China. We announced new Premier Support services, enabling you to go directly to local language support in nine languages in 49 countries in the world, going directly to a native speaker level three support engineer. And today we have more than 10,000 support specialists supporting our products in over 160 countries. We've delivered three times the number of engineered solutions to deliver a solutions orientation, whether it's on HANA, or SQL Server, or Oracle, et cetera, and we've completely reengaged our system integrator channel. Last year we had the CIO of DXE on stage, and here we're talking about more than 175 percent growth through our system integrator channel in the last year alone as we've brought that back and really built strong relationships there. So, thank you very much for amazing work here on the customer experience. (audience applauding) We also transformed our leadership. We thought it was extremely important with a focus on diversity, to have diverse talent from the legacy IBM, the legacy Lenovo, but also outside the industry. We made about 19 executive changes in the DCG group. This is the most senior leadership team within DCG, all which are newly on board, either from our outside competitors mainly over the last year. About 50 percent of our executives were now hired internally, 50 percent externally, and 31 percent of those new executives are diverse, representing the diversity of our global customer base and gender. So welcome, and most of them you're going to be able to meet over here in the breakout sessions later today. (audience applauding) But some things haven't changed, they're just keeping getting better within Lenovo. So, last year I got up and said we were committed with the new ThinkSystem brand to be a world performance leader. You're going to see that we're sponsoring Ducati for MotoGP. You saw the Ferrari out there with Formula One. That's not a surprise. We want the Lenovo ThinkSystem and ThinkAgile brands to be synonymous with world record performance. So in the last year we've gone from 39 to 89 world records, and partners like Intel would tell you, we now have four times the number of world record workloads on Lenovo hardware than any other server company on the planet today, with more than 89 world records across HPC, Java, database, transaction processing, et cetera. And we're proud to have just brought on Doug Fisher from Intel Corporation who had about 10-17,000 people on any given year working for him in workload optimizations across all of our software. It's just another testament to the leadership team we're bringing in to keep focusing on world-class performance software and solutions. We also per ITIC, are the number one now in x86 server reliability five years running. So, this is a survey where CIOs are in a blind survey asked to submit their reliability of their uptime on their x86 server equipment over the last 365 days. And you can see from 2016 to 2017 the downtime, there was over four hours as noted by the 750 CXOs in more than 20 countries is about one percent for the Lenovo products, and is getting worse generation from generation as we went from Broadwell to Pearlie. So we're taking our reliability, which was really paramount in the IBM System X heritage, and ensuring that we don't just recognize high performance but we recognize the highest level of reliability for mission-critical workloads. And what that translates into is that we at once again have been ranked number one in customer satisfaction from you our customers in 19 of 22 attributes, in North America in 18 of 22. This is a survey by TVR across hundreds of customers of us and our top competitors. This is the ninth consecutive study that we've been ranked number one in customer satisfaction, so we're taking this extremely seriously, and in fact YY now has increased the compensation of every single Lenovo employee. Up to 40 percent of their compensation bonus this year is going to be based on customer metrics like quality, order to ship, and things of this nature. So, we're really putting every employee focused on customer centricity this year. So, the summary on Transform 1.0 is that every aspect of what you knew about Lenovo's data center group has transformed, from the culture to the branding to dedicated sales and marketing, supply chain and quality groups, to a worldwide channel program and certifications, to new system integrator relationships, and to the new leadership team. So, rather than me just talk about it, I thought I'd share a quick video about what we've done over the last year, if you could run the video please. Turn around for a second. (epic music) (audience applauds) Okay. So, thank you to all our customers that allowed us to publicly display their logos in that video. So, what that means for you as investors, and for the investor community out there is, that our customers have responded, that this year Gardner just published that we are the fastest growing server company in the top 10, with 39 percent growth quarter-on-quarter, and 49 percent growth year-on-year. If you look at the progress we've made since the transformation the last three quarters publicly, we've grown 17 percent, then 44 percent, then 68 percent year on year in revenue, and I can tell you this quarter I'm as confident as ever in the financials around the DCG group, and it hasn't been in one area. You're going to see breakout sessions from hyperscale, software-defined, and flash, which are all growing more than a 100 percent year-on-year, supercomputing which we'll talk about shortly, now number one, and then ultimately from profitability, delivering five consecutive quarters of pre-tax profit increase, so I think, thank you very much to the customer base who's been working with us through this transformation journey. So, you're here to really hear what's next on 2.0, and that's what I'm excited to talk about today. Last year I came up with an audacious goal that we would become the largest supercomputer company on the planet by 2020, and this graph represents since the acquisition of the IBM System x business how far we were behind being the number one supercomputer. When we started we were 182 positions behind, even with the acquisition for example of SGI from HP, we've now accomplished our goal actually two years ahead of time. We're now the largest supercomputer company in the world. About one in every four supercomputers, 117 on the list, are now Lenovo computers, and you saw in the video where the universities are said, but I think what I'm most proud of is when your customers rank you as the best. So the awards at the bottom here, are actually Readers Choice from the last International Supercomputing Show where the scientific researchers on these computers ranked their vendors, and we were actually rated the number one server technology in supercomputing with our ThinkSystem SD530, and the number one storage technology with our ThinkSystem DSS-G, but more importantly what we're doing with the technology. You're going to see we won best in life sciences, best in data analytics, and best in collaboration as well, so you're going to see all of that in our breakout sessions. As you saw in the video now, 17 of the top 25 research institutions in the world are now running Lenovo supercomputers. And again coming from Raleigh and watching that hurricane come across the Atlantic, there are eight supercomputers crunching all of those models you see from Germany to Malaysia to Canada, and we're happy to have a SciNet from University of Toronto here with us in our breakout session to talk about what they're doing on climate modeling as well. But we're not stopping there. We just announced our new Neptune warm water cooling technology, which won the International Supercomputing Vendor Showdown, the first time we've won that best of show in 25 years, and we've now installed this. We're building out LRZ in Germany, the first ever warm water cooling in Peking University, at the India Space Propulsion Laboratory, at the Malaysian Weather and Meteorological Society, at Uninett, at the largest supercomputer in Norway, T-Systems, University of Birmingham. This is truly amazing technology where we're actually using water to cool the machine to deliver a significantly more energy-efficient computer. Super important, when we're looking at global warming and some of the electric bills can be millions of dollars just for one computer, and could actually power a small city just with the technology from the computer. We've built AI centers now in Morrisville, Stuttgart, Taipei, and Beijing, where customers can bring their AI workloads in with experts from Intel, from Nvidia, from our FPGA partners, to work on their workloads, and how they can best implement artificial intelligence. And we also this year launched LICO which is Lenovo Intelligent Compute Orchestrator software, and it's a software solution that simplifies the management and use of distributed clusters in both HPC and AI model development. So, what it enables you to do is take a single cluster, and run both HPC and AI workloads on it simultaneously, delivering better TCO for your environment, so check out LICO as well. A lot of the customers here and Wall Street are very excited and using it already. And we talked about solving humanity's greatest challenges. In the breakout session, you're going to have a virtual reality experience where you're going to be able to walk through what as was just ranked the world's most beautiful data center, the Barcelona Supercomputer. So, you can actually walk through one of the largest supercomputers in the world from Barcelona. You can see the work we're doing with NC State where we're going to have to grow the food supply of the world by 50 percent, and there's not enough fresh water in the world in the right places to actually make all those crops grow between now and 2055, so you're going to see the progression of how they're mapping the entire globe and the water around the world, how to build out the crop population over time using AI. You're going to see our work with Vestas is this largest supercomputer provider in the wind turbine areas, how they're working on wind energy, and then with University College London, how they're working on some of the toughest particle physics calculations in the world. So again, lots of opportunity here. Take advantage of it in the breakout sessions. Okay, let me transition to hyperscale. So in hyperscale now, we have completely transformed our business model. We are now powering six of the top 10 hyperscalers in the world, which is a significant difference from where we were two years ago. And the reason we're doing that, is we've coined a term called ODM+. We believe that hyperscalers want more procurement power than an ODM, and Lenovo is doing about $18 billion of procurement a year. They want a broader global supply chain that they can get from a local system integrator. We're more than 160 countries around the world, but they want the same world-class quality and reliability like they get from an MNC. So, what we're doing now is instead of just taking off the shelf motherboards from somewhere, we're starting with a blank sheet of paper, we're working with the customer base on customized SKUs and you can see we already are developing 33 custom solutions for the largest hyperscalers in the world. And then we're not just running notebooks through this factory where YY said, we're running 37 notebook boards a minute, we're now putting in tens and tens and tens of thousands of server board capacity per month into this same factory, so absolutely we can compete with the most aggressive ODM's in the world, but it's not just putting these things in in the motherboard side, we're also building out these systems all around the world, India, Brazil, Hungary, Mexico, China. This is an example of a new hyperscale customer we've had this last year, 34,000 servers we delivered in the first six months. The next 34,000 servers we delivered in 68 days. The next 34,000 servers we delivered in 35 days, with more than 99 percent on-time delivery to 35 data centers in 14 countries as diverse as South Africa, India, China, Brazil, et cetera. And I'm really ashamed to say it was 99.3, because we did have a forklift driver who rammed their forklift right through the middle of the one of the server racks. (audience laughing) At JFK Airport that we had to respond to, but I think this gives you a perspective of what it is to be a top five global supply chain and technology. So last year, I said we would invest significantly in IP, in joint ventures, and M and A to compete in software defined, in networking, and in storage, so I wanted to give you an update on that as well. Our newest software-defined partnership is with Cloudistics, enabling a fully composable cloud infrastructure. It's an exclusive agreement, you can see them here. I think Nag, our founder, is going to be here today, with a significant Lenovo investment in the company. So, this new ThinkAgile CP series delivers the simplicity of the public cloud, on-premise with exceptional support and a marketplace of essential enterprise applications all with a single click deployment. So simply put, we're delivering a private cloud with a premium experience. It's simple in that you need no specialists to deploy it. An IT generalist can set it up and manage it. It's agile in that you can provision dozens of workloads in minutes, and it's transformative in that you get all of the goodness of public cloud on-prem in a private cloud to unlock opportunity for use. So, we're extremely excited about the ThinkAgile CP series that's now shipping into the marketplace. Beyond that we're aggressively ramping, and we're either doubling, tripling, or quadrupling our market share as customers move from traditional server technology to software-defined technology. With Nutanix we've been public, growing about more than 150 percent year-on-year, with Nutanix as their fastest growing Nutanix partner, but today I want to set another audacious goal. I believe we cannot just be Nutanix's fastest growing partner but we can become their largest partner within two years. On Microsoft, we are already four times our market share on Azure stack of our traditional business. We were the first to launch our ThinkAgile on Broadwell and on Skylake with the Azure Stack Infrastructure. And on VMware we're about twice our market segment share. We were the first to deliver an Intel-optimized Optane-certified VSAN node. And with Optane technology, we're delivering 50 percent more VM density than any competitive SSD system in the marketplace, about 10 times lower latency, four times the performance of any SSD system out there, and Lenovo's first to market on that. And at VMworld you saw CEO Pat Gelsinger of VMware talked about project dimension, which is Edge as a service, and we're the only OEM beyond the Dell family that is participating today in project dimension. Beyond that you're going to see a number of other partnerships we have. I'm excited that we have the city of Bogota Columbia here, an eight million person city, where we announced a 3,000 camera video surveillance solution last month. With pivot three you're going to see city of Bogota in our breakout sessions. You're going to see a new partnership with Veeam around backup that's launching today. You're going to see partnerships with scale computing in IoT and hyper-converged infrastructure working on some of the largest retailers in the world. So again, everything out in the breakout session. Transitioning to storage and data management, it's been a great year for Lenovo, more than a 100 percent growth year-on-year, 2X market growth in flash arrays. IDC just reported 30 percent growth in storage, number one in price performance in the world and the best HPC storage product in the top 500 with our ThinkSystem DSS G, so strong coverage, but I'm excited today to announce for Transform 2.0 that Lenovo is launching the largest data management and storage portfolio in our 25-year data center history. (audience applauding) So a year ago, the largest server portfolio, becoming the largest fastest growing server OEM, today the largest storage portfolio, but as you saw this morning we're not doing it alone. Today Lenovo and NetApp, two global powerhouses are joining forces to deliver a multi-billion dollar global alliance in data management and storage to help customers through their intelligent transformation. As the fastest growing worldwide server leader and one of the fastest growing flash array and data management companies in the world, we're going to deliver more choice to customers than ever before, global scale that's never been seen, supply chain efficiencies, and rapidly accelerating innovation and solutions. So, let me unwrap this a little bit for you and talk about what we're announcing today. First, it's the largest portfolio in our history. You're going to see not just storage solutions launching today but a set of solution recipes from NetApp that are going to make Lenovo server and NetApp or Lenovo storage work better together. The announcement enables Lenovo to go from covering 15 percent of the global storage market to more than 90 percent of the global storage market and distribute these products in more than 160 countries around the world. So we're launching today, 10 new storage platforms, the ThinkSystem DE and ThinkSystem DM platforms. They're going to be centrally managed, so the same XClarity management that you've been using for server, you can now use across all of your storage platforms as well, and it'll be supported by the same 10,000 plus service personnel that are giving outstanding customer support to you today on the server side. And we didn't come up with this in the last month or the last quarter. We're announcing availability in ordering today and shipments tomorrow of the first products in this portfolio, so we're excited today that it's not just a future announcement but something you as customers can take advantage of immediately. (audience applauding) The second part of the announcement is we are announcing a joint venture in China. Not only will this be a multi-billion dollar global partnership, but Lenovo will be a 51 percent owner, NetApp a 49 percent owner of a new joint venture in China with the goal of becoming in the top three storage companies in the largest data and storage market in the world. We will deliver our R and D in China for China, pooling our IP and resources together, and delivering a single route to market through a complementary channel, not just in China but worldwide. And in the future I just want to tell everyone this is phase one. There is so much exciting stuff. We're going to be on the stage over the next year talking to you about around integrated solutions, next-generation technologies, and further synergies and collaborations. So, rather than just have me talk about it, I'd like to welcome to the stage our new partner NetApp and Brad Anderson who's the senior vice president and general manager of NetApp Cloud Infrastructure. (upbeat music) (audience applauding) >> Thank You Kirk. >> So Brad, we've known each other a long time. It's an exciting day. I'm going to give you the stage and allow you to say NetApp's perspective on this announcement. >> Very good, thank you very much, Kirk. Kirk and I go back to I think 1994, so hey good morning and welcome. My name is Brad Anderson. I manage the Cloud Infrastructure Group at NetApp, and I am honored and privileged to be here at Lenovo Transform, particularly today on today's announcement. Now, you've heard a lot about digital transformation about how companies have to transform their IT to compete in today's global environment. And today's announcement with the partnership between NetApp and Lenovo is what that's all about. This is the joining of two global leaders bringing innovative technology in a simplified solution to help customers modernize their IT and accelerate their global digital transformations. Drawing on the strengths of both companies, Lenovo's high performance compute world-class supply chain, and NetApp's hybrid cloud data management, hybrid flash and all flash storage solutions and products. And both companies providing our customers with the global scale for them to be able to meet their transformation goals. At NetApp, we're very excited. This is a quote from George Kurian our CEO. George spent all day yesterday with YY and Kirk, and would have been here today if it hadn't been also our shareholders meeting in California, but I want to just convey how excited we are for all across NetApp with this partnership. This is a partnership between two companies with tremendous market momentum. Kirk took you through all the amazing results that Lenovo has accomplished, number one in supercomputing, number one in performance, number one in x86 reliability, number one in x86 customers sat, number five in supply chain, really impressive and congratulations. Like Lenovo, NetApp is also on a transformation journey, from a storage company to the data authority in hybrid cloud, and we've seen some pretty impressive momentum as well. Just last week we became number one in all flash arrays worldwide, catching EMC and Dell, and we plan to keep on going by them, as we help customers modernize their their data centers with cloud connected flash. We have strategic partnerships with the largest hyperscalers to provide cloud native data services around the globe and we are having success helping our customers build their own private clouds with just, with a new disruptive hyper-converged technology that allows them to operate just like hyperscalers. These three initiatives has fueled NetApp's transformation, and has enabled our customers to change the world with data. And oh by the way, it has also fueled us to have meet or have beaten Wall Street's expectations for nine quarters in a row. These are two companies with tremendous market momentum. We are also building this partnership for long term success. We think about this as phase one and there are two important components to phase one. Kirk took you through them but let me just review them. Part one, the establishment of a multi-year commitment and a collaboration agreement to offer Lenovo branded flash products globally, and as Kurt said in 160 countries. Part two, the formation of a joint venture in PRC, People's Republic of China, that will provide long term commitment, joint product development, and increase go-to-market investment to meet the unique needs to China. Both companies will put in storage technologies and storage expertise to form an independent JV that establishes a data management company in China for China. And while we can dream about what phase two looks like, our entire focus is on making phase one incredibly successful and I'm pleased to repeat what Kirk, is that the first products are orderable and shippable this week in 160 different countries, and you will see our two companies focusing on the here and now. On our joint go to market strategy, you'll see us working together to drive strategic alignment, focused execution, strong governance, and realistic expectations and milestones. And it starts with the success of our customers and our channel partners is job one. Enabling customers to modernize their legacy IT with complete data center solutions, ensuring that our customers get the best from both companies, new offerings the fuel business success, efficiencies to reinvest in game-changing initiatives, and new solutions for new mission-critical applications like data analytics, IoT, artificial intelligence, and machine learning. Channel partners are also top of mind for both our two companies. We are committed to the success of our existing and our future channel partners. For NetApp channel partners, it is new pathways to new segments and to new customers. For Lenovo's channel partners, it is the competitive weapons that now allows you to compete and more importantly win against Dell, EMC, and HP. And the good news for both companies is that our channel partner ecosystem is highly complementary with minimal overlap. Today is the first day of a very exciting partnership, of a partnership that will better serve our customers today and will provide new opportunities to both our companies and to our partners, new products to our customers globally and in China. I am personally very excited. I will be on the board of the JV. And so, I look forward to working with you, partnering with you and serving you as we go forward, and with that, I'd like to invite Kirk back up. (audience applauding) >> Thank you. >> Thank you. >> Well, thank you, Brad. I think it's an exciting overview, and these products will be manufactured in China, in Mexico, in Hungary, and around the world, enabling this amazing supply chain we talked about to deliver in over 160 countries. So thank you Brad, thank you George, for the amazing partnership. So again, that's not all. In Transform 2.0, last year, we talked about the joint ventures that were coming. I want to give you a sneak peek at what you should expect at future Lenovo events around the world. We have this Transform in Beijing in a couple weeks. We'll then be repeating this in 20 different locations roughly around the world over the next year, and I'm excited probably more than ever about what else is coming. Let's talk about Telco 5G and network function virtualization. Today, Motorola phones are certified on 46 global networks. We launched the world's first 5G upgradable phone here in the United States with Verizon. Lenovo DCG sells to 58 telecommunication providers around the world. At Mobile World Congress in Barcelona and Shanghai, you saw China Telecom and China Mobile in the Lenovo booth, China Telecom showing a video broadband remote access server, a VBRAS, with video streaming demonstrations with 2x less jitter than they had seen before. You saw China Mobile with a virtual remote access network, a VRAN, with greater than 10 times the throughput and 10x lower latency running on Lenovo. And this year, we'll be launching a new NFV company, a software company in China for China to drive the entire NFV stack, delivering not just hardware solutions, but software solutions, and we've recently hired a new CEO. You're going to hear more about that over the next several quarters. Very exciting as we try to drive new economics into the networks to deliver these 20 billion devices. We're going to need new economics that I think Lenovo can uniquely deliver. The second on IoT and edge, we've integrated on the device side into our intelligent devices group. With everything that's going to consume electricity computes and communicates, Lenovo is in a unique position on the device side to take advantage of the communications from Motorola and being one of the largest device companies in the world. But this year, we're also going to roll out a comprehensive set of edge gateways and ruggedized industrial servers and edge servers and ISP appliances for the edge and for IoT. So look for that as well. And then lastly, as a service, you're going to see Lenovo delivering hardware as a service, device as a service, infrastructure as a service, software as a service, and hardware as a service, not just as a glorified leasing contract, but with IP, we've developed true flexible metering capability that enables you to scale up and scale down freely and paying strictly based on usage, and we'll be having those announcements within this fiscal year. So Transform 2.0, lots to talk about, NetApp the big news of the day, but a lot more to come over the next year from the Data Center group. So in summary, I'm excited that we have a lot of customers that are going to be on stage with us that you saw in the video. Lots of testimonials so that you can talk to colleagues of yourself. Alamos Gold from Canada, a Canadian gold producer, Caligo for data optimization and privacy, SciNet, the largest supercomputer we've ever put into North America, and the largest in Canada at the University of Toronto will be here talking about climate change. City of Bogota again with our hyper-converged solutions around smart city putting in 3,000 cameras for criminal detection, license plate detection, et cetera, and then more from a channel mid market perspective, Jerry's Foods, which is from my home state of Wisconsin, and Minnesota which has about 57 stores in the specialty foods market, and how they're leveraging our IoT solutions as well. So again, about five times the number of demos that we had last year. So in summary, first and foremost to the customers, thank you for your business. It's been a great journey and I think we're on a tremendous role. You saw from last year, we're trying to build credibility with you. After the largest server portfolio, we're now the fastest-growing server OEM per Gardner, number one in performance, number one in reliability, number one in customer satisfaction, number one in supercomputing. Today, the largest storage portfolio in our history, with the goal of becoming the fastest growing storage company in the world, top three in China, multibillion-dollar collaboration with NetApp. And the transformation is going to continue with new edge gateways, edge servers, NFV solutions, telecommunications infrastructure, and hardware as a service with dynamic metering. So thank you for your time. I've looked forward to meeting many of you over the next day. We appreciate your business, and with that, I'd like to bring up Rod Lappen to introduce our next speaker. Rod? (audience applauding) >> Thanks, boss, well done. Alright ladies and gentlemen. No real secret there. I think we've heard why I might talk about the fourth Industrial Revolution in data and exactly what's going on with that. You've heard Kirk with some amazing announcements, obviously now with our NetApp partnership, talk about 5G, NFV, cloud, artificial intelligence, I think we've hit just about all the key hot topics. It's with great pleasure that I now bring up on stage Mr. Christian Teismann, our senior vice president and general manager of commercial business for both our PCs and our IoT business, so Christian Teismann. (techno music) Here, take that. >> Thank you. I think I'll need that. >> Okay, Christian, so obviously just before we get down, you and I last year, we had a bit of a chat about being in New York. >> Exports. >> You were an expat in New York for a long time. >> That's true. >> And now, you've moved from New York. You're in Munich? >> Yep. >> How does that feel? >> Well Munich is a wonderful city, and it's a great place to live and raise kids, but you know there's no place in the world like New York. >> Right. >> And I miss it a lot, quite frankly. >> So what exactly do you miss in New York? >> Well there's a lot of things in New York that are unique, but I know you spent some time in Japan, but I still believe the best sushi in the world is still in New York City. (all laughing) >> I will beg to differ. I will beg to differ. I think Mr. Guchi-san from Softbank is here somewhere. He will get up an argue very quickly that Japan definitely has better sushi than New York. But obviously you know, it's a very very special place, and I have had sushi here, it's been fantastic. What about Munich? Anything else that you like in Munich? >> Well I mean in Munich, we have pork knuckles. >> Pork knuckles. (Christian laughing) Very similar sushi. >> What is also very fantastic, but we have the real, the real Oktoberfest in Munich, and it starts next week, mid-September, and I think it's unique in the world. So it's very special as well. >> Oktoberfest. >> Yes. >> Unfortunately, I'm not going this year, 'cause you didn't invite me, but-- (audience chuckling) How about, I think you've got a bit of a secret in relation to Oktoberfest, probably not in Munich, however. >> It's a secret, yes, but-- >> Are you going to share? >> Well I mean-- >> See how I'm putting you on the spot? >> In the 10 years, while living here in New York, I was a regular visitor of the Oktoberfest at the Lower East Side in Avenue C at Zum Schneider, where I actually met my wife, and she's German. >> Very good. So, how about a big round of applause? (audience applauding) Not so much for Christian, but more I think, obviously for his wife, who obviously had been drinking and consequently ended up with you. (all laughing) See you later, mate. >> That's the beauty about Oktoberfest, but yes. So first of all, good morning to everybody, and great to be back here in New York for a second Transform event. New York clearly is the melting pot of the world in terms of culture, nations, but also business professionals from all kind of different industries, and having this event here in New York City I believe is manifesting what we are trying to do here at Lenovo, is transform every aspect of our business and helping our customers on the journey of intelligent transformation. Last year, in our transformation on the device business, I talked about how the PC is transforming to personalized computing, and we've made a lot of progress in that journey over the last 12 months. One major change that we have made is we combined all our device business under one roof. So basically PCs, smart devices, and smart phones are now under the roof and under the intelligent device group. But from my perspective makes a lot of sense, because at the end of the day, all devices connect in the modern world into the cloud and are operating in a seamless way. But we are also moving from a device business what is mainly a hardware focus historically, more and more also into a solutions business, and I will give you during my speech a little bit of a sense of what we are trying to do, as we are trying to bring all these components closer together, and specifically also with our strengths on the data center side really build end-to-end customer solution. Ultimately, what we want to do is make our business, our customer's businesses faster, safer, and ultimately smarter as well. So I want to look a little bit back, because I really believe it's important to understand what's going on today on the device side. Many of us have still grown up with phones with terminals, ultimately getting their first desktop, their first laptop, their first mobile phone, and ultimately smartphone. Emails and internet improved our speed, how we could operate together, but still we were defined by linear technology advances. Today, the world has changed completely. Technology itself is not a limiting factor anymore. It is how we use technology going forward. The Internet is pervasive, and we are not yet there that we are always connected, but we are nearly always connected, and we are moving to the stage, that everything is getting connected all the time. Sharing experiences is the most driving force in our behavior. In our private life, sharing pictures, videos constantly, real-time around the world, with our friends and with our family, and you see the same behavior actually happening in the business life as well. Collaboration is the number-one topic if it comes down to workplace, and video and instant messaging, things that are coming from the consumer side are dominating the way we are operating in the commercial business as well. Most important beside technology, that a new generation of workforce has completely changed the way we are working. As the famous workforce the first generation of Millennials that have now fully entered in the global workforce, and the next generation, it's called Generation Z, is already starting to enter the global workforce. By 2025, 75 percent of the world's workforce will be composed out of two of these generations. Why is this so important? These two generations have been growing up using state-of-the-art IT technology during their private life, during their education, school and study, and are taking these learnings and taking these behaviors in the commercial workspace. And this is the number one force of change that we are seeing in the moment. Diverse workforces are driving this change in the IT spectrum, and for years in many of our customers' focus was their customer focus. Customer experience also in Lenovo is the most important thing, but we've realized that our own human capital is equally valuable in our customer relationships, and employee experience is becoming a very important thing for many of our customers, and equally for Lenovo as well. As you have heard YY, as we heard from YY, Lenovo is focused on intelligent transformation. What that means for us in the intelligent device business is ultimately starting with putting intelligence in all of our devices, smartify every single one of our devices, adding value to our customers, traditionally IT departments, but also focusing on their end users and building products that make their end users more productive. And as a world leader in commercial devices with more than 33 percent market share, we can solve problems been even better than any other company in the world. So, let's talk about transformation of productivity first. We are in a device-led world. Everything we do is connected. There's more interaction with devices than ever, but also with spaces who are increasingly becoming smart and intelligent. YY said it, by 2020 we have more than 20 billion connected devices in the world, and it will grow exponentially from there on. And users have unique personal choices for technology, and that's very important to recognize, and we call this concept a digital wardrobe. And it means that every single end-user in the commercial business is composing his personal wardrobe on an ongoing basis and is reconfiguring it based on the work he's doing and based where he's going and based what task he is doing. I would ask all of you to put out all the devices you're carrying in your pockets and in your bags. You will see a lot of you are using phones, tablets, laptops, but also cameras and even smartwatches. They're all different, but they have one underlying technology that is bringing it all together. Recognizing digital wardrobe dynamics is a core factor for us to put all the devices under one roof in IDG, one business group that is dedicated to end-user solutions across mobile, PC, but also software services and imaging, to emerging technologies like AR, VR, IoT, and ultimately a AI as well. A couple of years back there was a big debate around bring-your-own-device, what was called consumerization. Today consumerization does not exist anymore, because consumerization has happened into every single device we build in our commercial business. End users and commercial customers today do expect superior display performance, superior audio, microphone, voice, and touch quality, and have it all connected and working seamlessly together in an ease of use space. We are already deep in the journey of personalized computing today. But the center point of it has been for the last 25 years, the mobile PC, that we have perfected over the last 25 years, and has been the undisputed leader in mobility computing. We believe in the commercial business, the ThinkPad is still the core device of a digital wardrobe, and we continue to drive the success of the ThinkPad in the marketplace. We've sold more than 140 million over the last 26 years, and even last year we exceeded nearly 11 million units. That is about 21 ThinkPads per minute, or one Thinkpad every three seconds that we are shipping out in the market. It's the number one commercial PC in the world. It has gotten countless awards but we felt last year after Transform we need to build a step further, in really tailoring the ThinkPad towards the need of the future. So, we announced a new line of X1 Carbon and Yoga at CES the Consumer Electronics Show. And the reason is not we want to sell to consumer, but that we do recognize that a lot of CIOs and IT decision makers need to understand what consumers are really doing in terms of technology to make them successful. So, let's take a look at the video. (suspenseful music) >> When you're the number one business laptop of all time, your only competition is yourself. (wall shattering) And, that's different. Different, like resisting heat, ice, dust, and spills. Different, like sharper, brighter OLA display. The trackpoint that reinvented controls, and a carbon fiber roll cage to protect what's inside, built by an engineering and design team, doing the impossible for the last 25 years. This is the number one business laptop of all time, but it's not a laptop. It's a ThinkPad. (audience applauding) >> Thank you very much. And we are very proud that Lenovo ThinkPad has been selected as the best laptop in the world in the second year in a row. I think it's a wonderful tribute to what our engineers have been done on this one. And users do want awesome displays. They want the best possible audio, voice, and touch control, but some users they want more. What they want is super power, and I'm really proud to announce our newest member of the X1 family, and that's the X1 extreme. It's exceptionally featured. It has six core I9 intel chipset, the highest performance you get in the commercial space. It has Nvidia XTX graphic, it is a 4K UHD display with HDR with Dolby vision and Dolby Atmos Audio, two terabyte in SSD, so it is really the absolute Ferrari in terms of building high performance commercial computer. Of course it has touch and voice, but it is one thing. It has so much performance that it serves also a purpose that is not typical for commercial, and I know there's a lot of secret gamers also here in this room. So you see, by really bringing technology together in the commercial space, you're creating productivity solutions of one of a kind. But there's another category of products from a productivity perspective that is incredibly important in our commercial business, and that is the workstation business . Clearly workstations are very specifically designed computers for very advanced high-performance workloads, serving designers, architects, researchers, developers, or data analysts. And power and performance is not just about the performance itself. It has to be tailored towards the specific use case, and traditionally these products have a similar size, like a server. They are running on Intel Xeon technology, and they are equally complex to manufacture. We have now created a new category as the ultra mobile workstation, and I'm very proud that we can announce here the lightest mobile workstation in the industry. It is so powerful that it really can run AI and big data analysis. And with this performance you can go really close where you need this power, to the sensors, into the cars, or into the manufacturing places where you not only wannna read the sensors but get real-time analytics out of these sensors. To build a machine like this one you need customers who are really challenging you to the limit. and we're very happy that we had a customer who went on this journey with us, and ultimately jointly with us created this product. So, let's take a look at the video. (suspenseful music) >> My world involves pathfinding both the hardware needs to the various work sites throughout the company, and then finding an appropriate model of desktop, laptop, or workstation to match those needs. My first impressions when I first seen the ThinkPad P1 was I didn't actually believe that we could get everything that I was asked for inside something as small and light in comparison to other mobile workstations. That was one of the I can't believe this is real sort of moments for me. (engine roars) >> Well, it's better than general when you're going around in the wind tunnel, which isn't alway easy, and going on a track is not necessarily the best bet, so having a lightweight very powerful laptop is extremely useful. It can take a Xeon processor, which can support ECC from when we try to load a full car, and when we're analyzing live simulation results. through and RCFT post processor or example. It needs a pretty powerful machine. >> It's come a long way to be able to deliver this. I hate to use the word game changer, but it is that for us. >> Aston Martin has got a lot of different projects going. There's some pretty exciting projects and a pretty versatile range coming out. Having Lenovo as a partner is certainly going to ensure that future. (engine roars) (audience applauds) >> So, don't you think the Aston Martin design and the ThinkPad design fit very well together? (audience laughs) So if Q, would get a new laptop, I think you would get a ThinkPad X P1. So, I want to switch gears a little bit, and go into something in terms of productivity that is not necessarily on top of the mind or every end user but I believe it's on top of the mind of every C-level executive and of every CEO. Security is the number one threat in terms of potential risk in your business and the cost of cybersecurity is estimated by 2020 around six trillion dollars. That's more than the GDP of Japan and we've seen a significant amount of data breach incidents already this years. Now, they're threatening to take companies out of business and that are threatening companies to lose a huge amount of sensitive customer data or internal data. At Lenovo, we are taking security very, very seriously, and we run a very deep analysis, around our own security capabilities in the products that we are building. And we are announcing today a new brand under the Think umbrella that is called ThinkShield. Our goal is to build the world's most secure PC, and ultimately the most secure devices in the industry. And when we looked at this end-to-end, there is no silver bullet around security. You have to go through every aspect where security breaches can potentially happen. That is why we have changed the whole organization, how we look at security in our device business, and really have it grouped under one complete ecosystem of solutions, Security is always something where you constantly are getting challenged with the next potential breach the next potential technology flaw. As we keep innovating and as we keep integrating, a lot of our partners' software and hardware components into our products. So for us, it's really very important that we partner with companies like Intel, Microsoft, Coronet, Absolute, and many others to really as an example to drive full encryption on all the data seamlessly, to have multi-factor authentication to protect your users' identity, to protect you in unsecured Wi-Fi locations, or even simple things like innovation on the device itself, to and an example protect the camera, against usage with a little thing like a thinkShutter that you can shut off the camera. SO what I want to show you here, is this is the full portfolio of ThinkShield that we are announcing today. This is clearly not something I can even read to you today, but I believe it shows you the breadth of security management that we are announcing today. There are four key pillars in managing security end-to-end. The first one is your data, and this has a lot of aspects around the hardware and the software itself. The second is identity. The third is the security around online, and ultimately the device itself. So, there is a breakout on security and ThinkShield today, available in the afternoon, and encourage you to really take a deeper look at this one. The first pillar around productivity was the device, and around the device. The second major pillar that we are seeing in terms of intelligent transformation is the workspace itself. Employees of a new generation have a very different habit how they work. They split their time between travel, working remotely but if they do come in the office, they expect a very different office environment than what they've seen in the past in cubicles or small offices. They come into the office to collaborate, and they want to create ideas, and they really work in cross-functional teams, and they want to do it instantly. And what we've seen is there is a huge amount of investment that companies are doing today in reconfiguring real estate reconfiguring offices. And most of these kind of things are moving to a digital platform. And what we are doing, is we want to build an entire set of solutions that are just focused on making the workspace more productive for remote workforce, and to create technology that allow people to work anywhere and connect instantly. And the core of this is that we need to be, the productivity of the employee as high as possible, and make it for him as easy as possible to use these kind of technologies. Last year in Transform, I announced that we will enter the smart office space. By the end of last year, we brought the first product into the market. It's called the Hub 500. It's already deployed in thousands of our customers, and it's uniquely focused on Microsoft Skype for Business, and making meeting instantly happen. And the product is very successful in the market. What we are announcing today is the next generation of this product, what is the Hub 700, what has a fantastic audio quality. It has far few microphones, and it is usable in small office environment, as well as in major conference rooms, but the most important part of this new announcement is that we are also announcing a software platform, and this software platform allows you to run multiple video conferencing software solutions on the same platform. Many of you may have standardized for one software solution or for another one, but as you are moving in a world of collaborating instantly with partners, customers, suppliers, you always will face multiple software standards in your company, and Lenovo is uniquely positioned but providing a middleware platform for the device to really enable multiple of these UX interfaces. And there's more to come and we will add additional UX interfaces on an ongoing base, based on our customer requirements. But this software does not only help to create a better experience and a higher productivity in the conference room or the huddle room itself. It really will allow you ultimately to manage all your conference rooms in the company in one instance. And you can run AI technologies around how to increase productivity utilization of your entire conference room ecosystem in your company. You will see a lot more devices coming from the node in this space, around intelligent screens, cameras, and so on, and so on. The idea is really that Lenovo will become a core provider in the whole movement into the smart office space. But it's great if you have hardware and software that is really supporting the approach of modern IT, but one component that Kirk also mentioned is absolutely critical, that we are providing this to you in an as a service approach. Get it what you want, when you need it, and pay it in the amount that you're really using it. And within UIT there is also I think a new philosophy around IT management, where you're much more focused on the value that you are consuming instead of investing into technology. We are launched as a service two years back and we already have a significant number of customers running PC as a service, but we believe as a service will stretch far more than just the PC device. It will go into categories like smart office. It might go even into categories like phone, and it will definitely go also in categories like storage and server in terms of capacity management. I want to highlight three offerings that we are also displaying today that are sort of building blocks in terms of how we really run as a service. The first one is that we collaborated intensively over the last year with Microsoft to be the launch pilot for their Autopilot offering, basically deploying images easily in the same approach like you would deploy a new phone on the network. The purpose really is to make new imaging and enabling new PC as seamless as it's used to be in the phone industry, and we have a complete set of offerings, and already a significant number customers have deployed Autopilot with Lenovo. The second major offering is Premier Support, like in the in the server business, where Premier Support is absolutely critical to run critical infrastructure, we see a lot of our customers do want to have Premier Support for their end users, so they can be back into work basically instantly, and that you have the highest possible instant repair on every single device. And then finally we have a significant amount of time invested into understanding how the software as a service really can get into one philosophy. And many of you already are consuming software as a service in many different contracts from many different vendors, but what we've created is one platform that really can manage this all together. All these things are the foundation for a device as a service offering that really can manage this end-to-end. So, implementing an intelligent workplace can be really a daunting prospect depending on where you're starting from, and how big your company ultimately is. But how do you manage the transformation of technology workspace if you're present in 50 or more countries and you run an infrastructure for more than 100,000 people? Michelin, famous for their tires, infamous for their Michelin star restaurant rating, especially in New York, and instantly recognizable by the Michelin Man, has just doing that. Please welcome with me Damon McIntyre from Michelin to talk to us about the challenges and transforming collaboration and productivity. (audience applauding) (electronic dance music) Thank you, David. >> Thank you, thank you very much. >> We on? >> So, how do you feel here? >> Well good, I want to thank you first of all for your partnership and the devices you create that helped us design, manufacture, and distribute the best tire in the world, okay? I just had to say it and put out there, alright. And I was wondering, were those Michelin tires on that Aston Martin? >> I'm pretty sure there is no other tire that would fit to that. >> Yeah, no, thank you, thank you again, and thank you for the introduction. >> So, when we talk about the transformation happening really in the workplace, the most tangible transformation that you actually see is the drastic change that companies are doing physically. They're breaking down walls. They're removing cubes, and they're moving to flexible layouts, new desks, new huddle rooms, open spaces, but the underlying technology for that is clearly not so visible very often. So, tell us about Michelin's strategy, and the technology you are deploying to really enable this corporation. >> So we, so let me give a little bit a history about the company to understand the daunting tasks that we had before us. So we have over 114,000 people in the company under 170 nationalities, okay? If you go to the corporate office in France, it's Clermont. It's about 3,000 executives and directors, and what have you in the marketing, sales, all the way up to the chain of the global CIO, right? Inside of the Americas, we merged in Americas about three years ago. Now we have the Americas zone. There's about 28,000 employees across the Americas, so it's really, it's really hard in a lot of cases. You start looking at the different areas that you lose time, and you lose you know, your productivity and what have you, so there, it's when we looked at different aspects of how we were going to manage the meeting rooms, right? because we have opened up our areas of workspace, our CIO, CEOs in our zones will no longer have an office. They'll sit out in front of everybody else and mingle with the crowd. So, how do you take those spaces that were originally used by an individual but now turn them into like meeting rooms? So, we went through a large process, and looked at the Hub 500, and that really met our needs, because at the end of the day what we noticed was, it was it was just it just worked, okay? We've just added it to the catalog, so we're going to be deploying it very soon, and I just want to again point that I know everybody struggles with this, and if you look at all the minutes that you lose in starting up a meeting, and we know you know what I'm talking about when I say this, it equates to many many many dollars, okay? And so at the end the day, this product helps us to be more efficient in starting up the meeting, and more productive during the meeting. >> Okay, it's very good to hear. Another major trend we are seeing in IT departments is taking a more hands-off approach to hardware. We're seeing new technologies enable IT to create a more efficient model, how IT gets hardware in the hands of end-users, and how they are ultimately supporting themselves. So what's your strategy around the lifecycle management of the devices? >> So yeah you mentioned, again, we'll go back to the 114,000 employees in the company, right? You imagine looking at all the devices we use. I'm not going to get into the number of devices we have, but we have a set number that we use, and we have to go through a process of deploying these devices, which we right now service our own image. We build our images, we service them through our help desk and all that process, and we go through it. If you imagine deploying 25,000 PCs in a year, okay? The time and the daunting task that's behind all that, you can probably add up to 20 or 30 people just full-time doing that, okay? So, with partnering with Lenovo and their excellent technology, their technical teams, and putting together the whole process of how we do imaging, it now lifts that burden off of our folks, and it shifts it into a more automated process through the cloud, okay? And, it's with the Autopilot on the end of the project, we'll have Autopilot fully engaged, but what I really appreciate is how Lenovo really, really kind of got with us, and partnered with us for the whole process. I mean it wasn't just a partner between Michelin and Lenovo. Microsoft was also partnered during that whole process, and it really was a good project that we put together, and we hope to have something in a full production mode next year for sure. >> So, David thank you very, very much to be here with us on stage. What I really want to say, customers like you, who are always challenging us on every single aspect of our capabilities really do make the big difference for us to get better every single day and we really appreciate the partnership. >> Yeah, and I would like to say this is that I am, I'm doing what he's exactly said he just said. I am challenging Lenovo to show us how we can innovate in our work space with your devices, right? That's a challenge, and it's going to be starting up next year for sure. We've done some in the past, but I'm really going to challenge you, and my whole aspect about how to do that is bring you into our workspace. Show you how we make how we go through the process of making tires and all that process, and how we distribute those tires, so you can brainstorm, come back to the table and say, here's a device that can do exactly what you're doing right now, better, more efficient, and save money, so thank you. >> Thank you very much, David. (audience applauding) Well it's sometimes really refreshing to get a very challenging customers feedback. And you know, we will continue to grow this business together, and I'm very confident that your challenge will ultimately help to make our products even more seamless together. So, as we now covered productivity and how we are really improving our devices itself, and the transformation around the workplace, there is one pillar left I want to talk about, and that's really, how do we make businesses smarter than ever? What that really means is, that we are on a journey on trying to understand our customer's business, deeper than ever, understanding our customer's processes even better than ever, and trying to understand how we can help our customers to become more competitive by injecting state-of-the-art technology in this intelligent transformation process, into core processes. But this cannot be done without talking about a fundamental and that is the journey towards 5G. I really believe that 5G is changing everything the way we are operating devices today, because they will be connected in a way like it has never done before. YY talked about you know, 20 times 10 times the amount of performance. There are other studies that talk about even 200 times the performance, how you can use these devices. What it will lead to ultimately is that we will build devices that will be always connected to the cloud. And, we are preparing for this, and Kirk already talked about, and how many operators in the world we already present with our Moto phones, with how many Telcos we are working already on the backend, and we are working on the device side on integrating 5G basically into every single one of our product in the future. One of the areas that will benefit hugely from always connected is the world of virtual reality and augmented reality. And I'm going to pick here one example, and that is that we have created a commercial VR solution for classrooms and education, and basically using consumer type of product like our Mirage Solo with Daydream and put a solution around this one that enables teachers and schools to use these products in the classroom experience. So, students now can have immersive learning. They can studying sciences. They can look at environmental issues. They can exploring their careers, or they can even taking a tour in the next college they're going to go after this one. And no matter what grade level, this is how people will continue to learn in the future. It's quite a departure from the old world of textbooks. In our area that we are looking is IoT, And as YY already elaborated, we are clearly learning from our own processes around how we improve our supply chain and manufacturing and how we improve also retail experience and warehousing, and we are working with some of the largest companies in the world on pilots, on deploying IoT solutions to make their businesses, their processes, and their businesses, you know, more competitive, and some of them you can see in the demo environment. Lenovo itself already is managing 55 million devices in an IoT fashion connecting to our own cloud, and constantly improving the experience by learning from the behavior of these devices in an IoT way, and we are collecting significant amount of data to really improve the performance of these systems and our future generations of products on a ongoing base. We have a very strong partnership with a company called ADLINK from Taiwan that is one of the leading manufacturers of manufacturing PC and hardened devices to create solutions on the IoT platform. The next area that we are very actively investing in is commercial augmented reality. I believe augmented reality has by far more opportunity in commercial than virtual reality, because it has the potential to ultimately improve every single business process of commercial customers. Imagine in the future how complex surgeries can be simplified by basically having real-time augmented reality information about the surgery, by having people connecting into a virtual surgery, and supporting the surgery around the world. Visit a furniture store in the future and see how this furniture looks in your home instantly. Doing some maintenance on some devices yourself by just calling the company and getting an online manual into an augmented reality device. Lenovo is exploring all kinds of possibilities, and you will see a solution very soon from Lenovo. Early when we talked about smart office, I talked about the importance of creating a software platform that really run all these use cases for a smart office. We are creating a similar platform for augmented reality where companies can develop and run all their argumented reality use cases. So you will see that early in 2019 we will announce an augmented reality device, as well as an augmented reality platform. So, I know you're very interested on what exactly we are rolling out, so we will have a first prototype view available there. It's still a codename project on the horizon, and we will announce it ultimately in 2019, but I think it's good for you to take a look what we are doing here. So, I just wanted to give you a peek on what we are working beyond smart office and the device productivity in terms of really how we make businesses smarter. It's really about increasing productivity, providing you the most secure solutions, increase workplace collaboration, increase IT efficiency, using new computing devices and software and services to make business smarter in the future. There's no other company that will enable to offer what we do in commercial. No company has the breadth of commercial devices, software solutions, and the same data center capabilities, and no other company can do more for your intelligent transformation than Lenovo. Thank you very much. (audience applauding) >> Thanks mate, give me that. I need that. Alright, ladies and gentlemen, we are done. So firstly, I've got a couple of little housekeeping pieces at the end of this and then we can go straight into going and experiencing some of the technology we've got on the left-hand side of the room here. So, I want to thank Christian obviously. Christian, awesome as always, some great announcements there. I love the P1. I actually like the Aston Martin a little bit better, but I'll take either if you want to give me one for free. I'll take it. We heard from YY obviously about the industry and how the the fourth Industrial Revolution is impacting us all from a digital transformation perspective, and obviously Kirk on DCG, the great NetApp announcement, which is going to be really exciting, actually that Twitter and some of the social media panels are absolutely going crazy, so it's good to see that the industry is really taking some impact. Some of the publications are really great, so thank you for the media who are obviously in the room publishing right no. But now, I really want to say it's all of your turn. So, all of you up the back there who are having coffee, it's your turn now. I want everyone who's sitting down here after this event move into there, and really take advantage of the 15 breakouts that we've got set there. There are four breakout sessions from a time perspective. I want to try and get you all out there at least to use up three of them and use your fourth one to get out and actually experience some of the technology. So, you've got four breakout sessions. A lot of the breakout sessions are actually done twice. If you have not downloaded the app, please download the app so you can actually see what time things are going on and make sure you're registering correctly. There's a lot of great experience of stuff out there for you to go do. I've got one quick video to show you on some of the technology we've got and then we're about to close. Alright, here we are acting crazy. Now, you can see obviously, artificial intelligence machine learning in the browser. God, I hate that dance, I'm not a Millenial at all. It's effectively going to be implemented by healthcare. I want you to come around and test that out. Look at these two guys. This looks like a Lenovo management meeting to be honest with you. These two guys are actually concentrating, using their brain power to race each others in cars. You got to come past and give that a try. Give that a try obviously. Fantastic event here, lots of technology for you to experience, and great partners that have been involved as well. And so, from a Lenovo perspective, we've had some great alliance partners contribute, including obviously our number one partner, Intel, who's been a really big loyal contributor to us, and been a real part of our success here at Transform. Excellent, so please, you've just seen a little bit of tech out there that you can go and play with. I really want you, I mean go put on those black things, like Scott Hawkins our chief marketing officer from Lenovo's DCG business was doing and racing around this little car with his concentration not using his hands. He said it's really good actually, but as soon as someone comes up to speak to him, his car stops, so you got to try and do better. You got to try and prove if you can multitask or not. Get up there and concentrate and talk at the same time. 62 different breakouts up there. I'm not going to go into too much detai, but you can see we've got a very, very unusual numbering system, 18 to 18.8. I think over here we've got a 4849. There's a 4114. And then up here we've got a 46.1 and a 46.2. So, you need the decoder ring to be able to understand it. Get over there have a lot of fun. Remember the boat leaves today at 4:00 o'clock, right behind us at the pier right behind us here. There's 400 of us registered. Go onto the app and let us know if there's more people coming. It's going to be a great event out there on the Hudson River. Ladies and gentlemen that is the end of your keynote. I want to thank you all for being patient and thank all of our speakers today. Have a great have a great day, thank you very much. (audience applauding) (upbeat music) ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ba do ♪

Published Date : Sep 13 2018

SUMMARY :

and those around you, Ladies and gentlemen, we ask that you please take an available seat. Ladies and gentlemen, once again we ask and software that transform the way you collaborate, Good morning everyone! Ooh, that was pretty good actually, and have a look at all of the breakout sessions. and the industries demand to be more intelligent, and the strategies that we have going forward I'm going to give you the stage and allow you to say is that the first products are orderable and being one of the largest device companies in the world. and exactly what's going on with that. I think I'll need that. Okay, Christian, so obviously just before we get down, You're in Munich? and it's a great place to live and raise kids, And I miss it a lot, but I still believe the best sushi in the world and I have had sushi here, it's been fantastic. (Christian laughing) the real Oktoberfest in Munich, in relation to Oktoberfest, at the Lower East Side in Avenue C at Zum Schneider, and consequently ended up with you. and is reconfiguring it based on the work he's doing and a carbon fiber roll cage to protect what's inside, and that is the workstation business . and then finding an appropriate model of desktop, in the wind tunnel, which isn't alway easy, I hate to use the word game changer, is certainly going to ensure that future. And the core of this is that we need to be, and distribute the best tire in the world, okay? that would fit to that. and thank you for the introduction. and the technology you are deploying and more productive during the meeting. how IT gets hardware in the hands of end-users, You imagine looking at all the devices we use. and we really appreciate the partnership. and it's going to be starting up next year for sure. and how many operators in the world Ladies and gentlemen that is the end of your keynote.

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Keynote Analysis | PTC Liveworx 2018


 

>> From Boston Massachusetts, it's The Cube! Covering LiveWorx 18. Brought to you by PTC. >> Welcome to Boston everybody. You're watching The Cube, the leader in live tech coverage. And we're here with a special presentation in coverage of the LiveWorx show sponsored by PTC of Needham, soon to be of Boston. My name is Dave Vellante. I'm here with my co-host Stu Miniman. And Stu, this is quite a show. There's 6,000 people here. Jim Heppelmann this morning was up giving the keynote. PTC is a company that kind of hit the doldrums in the early 2000s. A company that as manufacturing moved offshore, its core business was CAD software for manufacturers, and it went through a pretty dramatic transformation that we're going to be talking about today. Well, fast forward 10 years, 12 years, 15 years on, this company is smokin, the stock's up 50 percent this year. They got a billion dollars plus in revenue. They're growing at 10 to 15 percent a year. They've shifted their software business from a perpetual software license to a recurring revenue model. And they're booming. And we're here at the original site of The Cube, as you remember well in 2010, the Boston Convention Center down at the seaport. And Stu, what are your initial impressions of LiveWorx? >> Yeah, it's great to be here, Dave. Good to be here with you and they dub this the largest digital transformation conference in the world. (laughing) So, I mean, Dave, you and I have been to much bigger conferences and we've been to a lot of conferences that are talking about digital transformation. But, IOT, AI, Augmented Reality, Block Chain, Robotics, all of these things really are about software, it's about digital transformation, and a really interesting space as you mentioned kind of the legacy of PTC. I have been around long enough. I remember when we used to call them Parametric Technologies. They kind of rebranded themselves as PTC. Windchill brings back some memories for me. When I worked for a high tech manufacturing company, it was that's the life cycle management tool that we used back in the early 2000s. So, I had a little bit of background in them. And, as you said, they're based in Needham, and they're moving to the Seaport. Hot area, especially, as we've said Dave, Boston has the opportunity to be the hub of IOT. And it's companies like PTC that are going to help bring those partnerships and lots of companies to an event like this. >> Well PTC has always been an inquisitive company, as you were pointing out to me off camera. They brought Prime Computer, Computer Vision. A number of acquisitions that they made back in the late 90s, which essentially didn't pan out the way they had hoped. But now again, fast forward to the modern era, Jim Heppelmann came in I think around 2010, exceeded ThingWorx, a company called Cold Light, Kept Ware is another company that they purchased. And took these really sort of independent software components and put them together and created a platform. Everybody talks about platform. We'll be talking about that a lot today, where the number of customers and partners of PTC. And we even have some folks from PTC on. But, basically, talking about digital transformation earlier, Stu, IOT is a huge tailwind for a company like PTC. But they had to really deliberately pivot to take advantage of this market. And if you think about it, yes, it's about connecting and instrumenting devices and machines, it's about reaching them, creating whatever wireless connections. But it's also about the data. We talk about that all the time. And constructing data that goes from edge to core, and even into the cloud, whether that cloud's on prem or in the data center. So you're seeing the transformation of this company. Obviously, I talked about some of the financials. We'll go into some of that. But an evolving ecosystem we heard Accenture's here, Infosys is here, Deloitte is here. As I like to say, the SI's like to eat at the trough. If the SI's are here, that means there's money here, right? >> Yeah Dave and actually a number that jumped out at me when Microsoft was up on stage, and it wasn't that Microsoft is investing five billion dollars in diode, the number that caught my ear was the 20 to 25 partners that it takes to deploy a single IOT solution. So, anybody that's been in tech for a long time, when you see these complicated stack solutions, the SIs need to be here. It takes a long time to work through them, and integration is a big challenge. How do I get all of these pieces together? It's not something that I just tit buy off the shelf. It's not shrink wrap software. This is complicated solution. It is very fragmented in how we make them up. Very specific to the industry that we're building, so really fascinating stuff that's going on. But we are still very early in the life-cycle of IOT. Huge, huge, huge opportunities but big players like Microsoft, like Google, like Amazon are going to be here making sure that they're going to simplify that environment over time. Huge, you know Dave, what's the original forecast I think we did at Wiki Bon, was a 1.2 trillion dollar opportunity, which most of that, that was actually for the industrial Internet, which is not the commercial things that we think about all the time, when we talk about the home sensors and some of the things, some of the consumer stuff, but also the industrial here. >> Well, I think a couple of key points that you're making here. First of all, the market is absolutely enormous. It's almost impossible to size. I mean you're talking about a trillion dollars in sort of spending on hardware, software, services, virtually everything. But to your point, Stu. It's highly highly fragmented, virtually every industry. And a lot of different segmented technologies. But it's also important to point out this is the mashing together of operations technology, OT with Information Technology, IT, and those four leading companies IT is actually leaning in and embracing this notion of edge, computing, and IOT. Now, I wouldn't even say that IT and OT are Hatfield and McCoy's. They're not. They're parts of the organization that don't talk to each other. So they are cultural differences. They use different languages. They think differently. One is largely engineers who make machines work. The other IT guys, which we obviously know what they do, they keep information technology systems running. They deploy a lot of new IT projects. So, really different worlds that have to start coming together. Jim Heppelmann today I thought did a really good job in his keynote. He talked about innovation. Usually you start with okay we're here at point A, we want to go here. We want to get to point B. And we're going to take a straight line and have a bunch of linear steps and milestones to get there. He pointed out that innovation today is really sort of a non-linear process. And he talked about the combinatorial effects of really three things. Machines, or the physical, computers and humans. Machines are strong, they can do heavy lifting. Computers are fast, and they can do repetitive tasks very accurately. And humans are creative. And he talked about innovation in this new world coming together by combining those three aspects, finding new ways to attack problems, to solve nature's challenges. And bringing nature into that problem solving. He gave a lot of examples of how mother nature mimicking mother nature is now possible with AI and other technologies. Pretty cool. >> Yeah, absolutely Dave. I'm sure we'll be talking a lot today about the fourth Industrial Revolution. A lot of discussion as to what jobs are Robots going to take. I look around the show floor here and there's a lot of cool robotics going on. But as Eric Manou said and Aaron McAfee, the folks from MIT that we've interviewed a couple of times talked about the second machine age. Really the marring of people and machines that are going to be powerful. And absolutely Jim Heppelmann talked about that a lot. It's humans, it's physical, and it's digital. Putting those together and then, the other thing that he talked about is we're talking a lot about voice lightly with all of these assistants, but, you're really limited as to how much input and how fast you can take information in from an auditory standpoint. I mean, I know that I listen to podcasts at 1.5 to 2 X to try to get more information in faster, but it is sight that we're going to get 80 percent of the information in, and therefore, it's the VR and AR that are huge opportunities. I know when I've been talking to some of the large manufacturers, what they used to have in written documentations and then they went digital with, they're now getting you inside to be able to configure the systems with the hollow lens, or some of the AR headsets, the VR headsets, to be able to play with that. So, we're really early but excited to see where this technology has come so far. >> Yeah, we're seeing a lot of practical applications of VR and AR. We go to a lot of these shows and they'll have the demos, and you go, okay, what will I do with this? Well, you're really seeing here at LiveWorx some of the things you actually can do. One good example I thought they did was BEA Systems up in Nashua, actually showing the folks that are doing the manufacturing, little tutorial in how to do that. We're going to see some surgical examples today. Remote surgery. There are thousands, literally thousands of examples. In the time we have remaining, I want to just do the rundown on PTC. Cause it really is quite an amazing transformation story. You're talking about a company with 1.1 billion dollars in revenue. Their aspiration is by 2021 to be a two billion dollar company. They're growing at ten percent a year, their software business has grown at 12 to 15 percent a year. 15 percent is that annual recurring revenue. So this is an example of a company that has successfully shifted from that perpetual model to that recurring model. They got 200 million dollars this year in free cash flow. Their stock, as I said, is up 50 percent this year. They got 350 million dollars in cash, but they just got a billion dollar investment from Rockwell Automation that took about 8.4 percent of the company given them an implied evaluation of almost 11 billion dollars, which has got a little uplift from the stock market there. They're selling a lot of seven figure deals. Really, the core is manufacturing product life-cycle management, CAD. That's the stuff that we know PTC well from. And I talked about some of those acquisitions that they made. They sell products like Creo, which is their 3D CAD software. I think they're on Rev five or six by now. So they've taken their sort of legacy software and sort of updated that for the digital world. >> Yep ,it is version five that they were just announced today. Talking about really the 3D effort they're doing there. Some partnerships around it, and like every other software Dave that we've been hearing about AI is getting infused in here because with so many devices and so much data, we really need the machines to help us process that and do things that humans can't keep up with. >> And the ecosystem's grown. This is a complicated marketplace. If you look at the Gartner Magic Quadrant, there is no leader, even though PTC is the leader. But there is no leader. They're all sort of in the lower right, PTC is up highest. GE is interestingly is not in there, because it doesn't have an on prem solution. I don't know why GE doesn't have an on prem solution. And I don't know why they're not in there. >> Is there another version of the magic quadrant that includes the Amazons and GEs of the world? >> I don't know. So that's kind of interesting. We'll try to unpack that as we go on here. PTC announced today a relationship with a company called Ansys, which does simulation software. Normally, simulation comes sort of after the design. They're bringing those two worlds together. The CAD design piece and the simulation piece, sort of closer to real time. So, there's a lot of stuff going on. As you said, it's data, analytics, edge computing. It's cloud, it's on prim, it's block chain for security. We haven't talked about security. A lot bigger threat metrix, so block chain comes into play. >> Yeah, Dave. I saw a great joke. Do you realize that the S in IOT stands for security? Did you know that? (laughing) Oh wait, there's no S in IOT. Well, that's the point. >> All right, good. So Stu and I will be here all day today. This is actually a three day conference. The Cube will only be there for day one. Keep right there everybody. And we'll be right back. You're watching The Cube, Live from Liveworx in Boston. (upbeat music)

Published Date : Jun 18 2018

SUMMARY :

Brought to you by PTC. kind of hit the doldrums kind of the legacy of PTC. We talk about that all the time. the SIs need to be here. And he talked about the I mean, I know that I listen to podcasts that are doing the manufacturing, Talking about really the 3D And the ecosystem's grown. sort of after the design. Well, that's the point. So Stu and I will be here all day today.

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Emile Delam, Crypto Rally | Blockchain Week NYC 2018


 

(exciting music) >> Announcer: From New York it's The Cube. Covering Blockchain Week. Now here's John Furrier. >> Hello everyone, welcome back this is The Cube. I'm John Furrier your co-host here. Host here in New York City for Consensus 2018 part of Blockchain Week, New York And we have Mimi Delam who is also the Co-Founder of the Crypto Rally Project. We just had your partner on welcome to The Cube. >> Thank you so very much for having me here. I'm really grateful. So yeah lovely to see you in New York. >> Great to see you and I love the project we just heard the details about the Crypto Rally. >> That's correct. >> So what's your take on it. I mean it's exciting, what's your role? >> I mean besides being super exciting for us it's a very new way of us making a huge impact and a difference in the Blockchain world for the people who are around here taking it to another level through the media. And the sponsorships. I mean my role personally is that I'm a co-founder from the very nice team of the girls. Gaile, Agne and and me and a couple more people involved. We are very happy to take it to another level. We want people to have just a way of life so we're trying to make it. >> I love the excitement of the project and you guys have a great team but I love the international perspective. You guys were in London. And you came from Lithuania. >> Exactly. >> And London so it's going to start in London or Lithuania? Where's the rally going to start? >> Okay I'll tell you all in the details. So we started, I mean me, myself I lived for many years in London and our founder Agne been living there for many years as well, we started our Crypto Rally in Lithuania in July it's going to take place and then afterwards we're taking it to Dubai. The rest of the world countries who are very happy to take the country, sorry, we're very happy to take the place in the Cryptos and we're going to travel all around the world with this inception. It's like Formula One it starts from one place right now it's all around the world. >> And what's the goal to have fun? Educate people on Crypto? What's the objective? >> Objective is of course to educate the people for them to be a part of the Blockchain and a part of the something which is coming up new. We want to make sure that people are aware of the new world because it's very clear the fourth industrial revolution is coming, 3.0 life is totally different we cannot be living the same way any more. And of course we want to have fun. >> All right now what's it like in Lithuania right now? What's the culture for the Blockchain? Are people, must be exciting, what's the vibe? >> I'll tell you Lithuania is extremely educated and very high tech and fast moving so for us it's very important to make the spirit, the small country but it's very easy to communicate and make everything ready. We are very well known in the blocked in world and we want to take it to another level. Of course as I mentioned we're going to the different countries, we're bringing the concept over there. We're very happy to host in a different places. So that's our aim, just to the spread the world. >> Maybe you can help us bring The Cube to Lithuania? We need some hosts. >> We definitely would love to do that. >> Well you're a natural host and great mission. I love what you're doing. What's it like here in New York for you? What's your observation? What are you seeing? Do you like the content? Have you met some cool people? What's it like explain for people who aren't here? >> Okay. >> What's it like? >> So Consensus itself is one of the most exclusive, unique opportunities to be a part in the event. There are so many fascinating people. Very educated and forward thinkers, like mind blowing ideas just around the places. There are so many people. It's impossible to even get a track of it. I'm very excited to be in New York because to be a part of this event makes a huge difference and I'm just fascinated about every single day what is going on it's a whole week of events, whole week of the communication and meetings non-stop. And then. >> Social too. >> It's very social and people are very happy to hear about Crypto Rally. >> What's your favorite thing here in the event? What's, what do you like the best? What was your number one thing? >> I mean I like to be interviewed by you. (laughs) >> Oh, ticket. >> Bingo there it is, The Cube number one. Thank you for saying that. >> Thank you so much. >> Besides The Cube interview? (laughs) What session? The people, parties, was there any special moment so far that you think is a highlight besides The Cube interview? >> I mean to be honest I really do enjoy the after parties where the people are becoming more open because the first part, bit of the day is a lot of business going on. >> Yep. >> And then afterwards you're going to the more personal relationships and then becoming a little bit of the friendly. And obviously this is exactly what we want to replicate in the Crypto Rally if that makes sense. >> Yeah. >> Because we want to have four days events to start from, meet the people hang out with them, have a good business interaction with them and educate each other. That's what I love about after, afternoon parties over here. >> Yeah it's good. >> Because you know about. >> You want to meet people's soul, get to know who they are. >> Exactly, exactly it's nice to have a good connection and connectivity. >> Yeah. >> People have a great energy here and it's like the brightest minds are meeting here. Which is beautiful. >> Love your energy Mimi, love to have you on. What URL can we get the information at for the Crypto Rally? >> All right so guys right now you have to go to www.Cryptorally2018.com, #CryptoRally2018 or @Cryptorally2018. Please join us and tweet or telegram and all around the social media we're happy to be. >> How can someone get involved? How do sponsors get involved? How do people get involved in the project? >> I mean you have to apply for it. We are taking as well, we are taking it through the application process because we want to build a very community based first Crypto Rally. The, I mean just go on the website, reach us out, we're very happy to talk with everybody right now we want to have a community. We want to bring it to another level and I mean. >> Of course. >> I mean that's how it works right? >> We support you. We'll be a media sponsor, a media supporter. Thank you for coming on. >> Thank you so very much. >> Nice to see you. >> For having me. >> You're very welcome >> Really thank you very much. >> You're welcome, great energy great voice, love the new talent coming into the New York scene, bringing the global perspective here. Really exciting ecosystem that's developing, great tight knit community here in The Cube. Mimi you're part of it, you guys are doing great work. Love your mission. I'm John Furrier on the ground here in the open. Here in New York City at the Hilton in Mid-Town Manhattan for Consensus 2018. More coverage after this break, thanks for watching. (exciting music)

Published Date : May 18 2018

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Announcer: From New York it's The Cube. of the Crypto Rally Project. Thank you so very much for having me here. Great to see you and I love the project I mean it's exciting, what's your role? and a difference in the Blockchain world I love the excitement of the project and you guys the country, sorry, we're very happy to take the for them to be a part of the Blockchain and a part of the to make the spirit, the small country but it's very easy Maybe you can help us bring The Cube to Lithuania? love to do that. What are you seeing? So Consensus itself is one of the most exclusive, It's very social and people are very happy to hear I mean I like to be Thank you for saying that. I mean to be honest I really do enjoy the after parties in the Crypto Rally if that makes sense. four days events to start from, meet the people people's soul, get to know who they are. Exactly, exactly it's nice to have a good connection the brightest minds are meeting here. love to have you on. the social media we're happy the application process because we want to build a very Thank you for coming on. I'm John Furrier on the ground here in the open.

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Data Science for All: It's a Whole New Game


 

>> There's a movement that's sweeping across businesses everywhere here in this country and around the world. And it's all about data. Today businesses are being inundated with data. To the tune of over two and a half million gigabytes that'll be generated in the next 60 seconds alone. What do you do with all that data? To extract insights you typically turn to a data scientist. But not necessarily anymore. At least not exclusively. Today the ability to extract value from data is becoming a shared mission. A team effort that spans the organization extending far more widely than ever before. Today, data science is being democratized. >> Data Sciences for All: It's a Whole New Game. >> Welcome everyone, I'm Katie Linendoll. I'm a technology expert writer and I love reporting on all things tech. My fascination with tech started very young. I began coding when I was 12. Received my networking certs by 18 and a degree in IT and new media from Rochester Institute of Technology. So as you can tell, technology has always been a sure passion of mine. Having grown up in the digital age, I love having a career that keeps me at the forefront of science and technology innovations. I spend equal time in the field being hands on as I do on my laptop conducting in depth research. Whether I'm diving underwater with NASA astronauts, witnessing the new ways which mobile technology can help rebuild the Philippine's economy in the wake of super typhoons, or sharing a first look at the newest iPhones on The Today Show, yesterday, I'm always on the hunt for the latest and greatest tech stories. And that's what brought me here. I'll be your host for the next hour and as we explore the new phenomenon that is taking businesses around the world by storm. And data science continues to become democratized and extends beyond the domain of the data scientist. And why there's also a mandate for all of us to become data literate. Now that data science for all drives our AI culture. And we're going to be able to take to the streets and go behind the scenes as we uncover the factors that are fueling this phenomenon and giving rise to a movement that is reshaping how businesses leverage data. And putting organizations on the road to AI. So coming up, I'll be doing interviews with data scientists. We'll see real world demos and take a look at how IBM is changing the game with an open data science platform. We'll also be joined by legendary statistician Nate Silver, founder and editor-in-chief of FiveThirtyEight. Who will shed light on how a data driven mindset is changing everything from business to our culture. We also have a few people who are joining us in our studio, so thank you guys for joining us. Come on, I can do better than that, right? Live studio audience, the fun stuff. And for all of you during the program, I want to remind you to join that conversation on social media using the hashtag DSforAll, it's data science for all. Share your thoughts on what data science and AI means to you and your business. And, let's dive into a whole new game of data science. Now I'd like to welcome my co-host General Manager IBM Analytics, Rob Thomas. >> Hello, Katie. >> Come on guys. >> Yeah, seriously. >> No one's allowed to be quiet during this show, okay? >> Right. >> Or, I'll start calling people out. So Rob, thank you so much. I think you know this conversation, we're calling it a data explosion happening right now. And it's nothing new. And when you and I chatted about it. You've been talking about this for years. You have to ask, is this old news at this point? >> Yeah, I mean, well first of all, the data explosion is not coming, it's here. And everybody's in the middle of it right now. What is different is the economics have changed. And the scale and complexity of the data that organizations are having to deal with has changed. And to this day, 80% of the data in the world still sits behind corporate firewalls. So, that's becoming a problem. It's becoming unmanageable. IT struggles to manage it. The business can't get everything they need. Consumers can't consume it when they want. So we have a challenge here. >> It's challenging in the world of unmanageable. Crazy complexity. If I'm sitting here as an IT manager of my business, I'm probably thinking to myself, this is incredibly frustrating. How in the world am I going to get control of all this data? And probably not just me thinking it. Many individuals here as well. >> Yeah, indeed. Everybody's thinking about how am I going to put data to work in my organization in a way I haven't done before. Look, you've got to have the right expertise, the right tools. The other thing that's happening in the market right now is clients are dealing with multi cloud environments. So data behind the firewall in private cloud, multiple public clouds. And they have to find a way. How am I going to pull meaning out of this data? And that brings us to data science and AI. That's how you get there. >> I understand the data science part but I think we're all starting to hear more about AI. And it's incredible that this buzz word is happening. How do businesses adopt to this AI growth and boom and trend that's happening in this world right now? >> Well, let me define it this way. Data science is a discipline. And machine learning is one technique. And then AI puts both machine learning into practice and applies it to the business. So this is really about how getting your business where it needs to go. And to get to an AI future, you have to lay a data foundation today. I love the phrase, "there's no AI without IA." That means you're not going to get to AI unless you have the right information architecture to start with. >> Can you elaborate though in terms of how businesses can really adopt AI and get started. >> Look, I think there's four things you have to do if you're serious about AI. One is you need a strategy for data acquisition. Two is you need a modern data architecture. Three is you need pervasive automation. And four is you got to expand job roles in the organization. >> Data acquisition. First pillar in this you just discussed. Can we start there and explain why it's so critical in this process? >> Yeah, so let's think about how data acquisition has evolved through the years. 15 years ago, data acquisition was about how do I get data in and out of my ERP system? And that was pretty much solved. Then the mobile revolution happens. And suddenly you've got structured and non-structured data. More than you've ever dealt with. And now you get to where we are today. You're talking terabytes, petabytes of data. >> [Katie] Yottabytes, I heard that word the other day. >> I heard that too. >> Didn't even know what it meant. >> You know how many zeros that is? >> I thought we were in Star Wars. >> Yeah, I think it's a lot of zeroes. >> Yodabytes, it's new. >> So, it's becoming more and more complex in terms of how you acquire data. So that's the new data landscape that every client is dealing with. And if you don't have a strategy for how you acquire that and manage it, you're not going to get to that AI future. >> So a natural segue, if you are one of these businesses, how do you build for the data landscape? >> Yeah, so the question I always hear from customers is we need to evolve our data architecture to be ready for AI. And the way I think about that is it's really about moving from static data repositories to more of a fluid data layer. >> And we continue with the architecture. New data architecture is an interesting buzz word to hear. But it's also one of the four pillars. So if you could dive in there. >> Yeah, I mean it's a new twist on what I would call some core data science concepts. For example, you have to leverage tools with a modern, centralized data warehouse. But your data warehouse can't be stagnant to just what's right there. So you need a way to federate data across different environments. You need to be able to bring your analytics to the data because it's most efficient that way. And ultimately, it's about building an optimized data platform that is designed for data science and AI. Which means it has to be a lot more flexible than what clients have had in the past. >> All right. So we've laid out what you need for driving automation. But where does the machine learning kick in? >> Machine learning is what gives you the ability to automate tasks. And I think about machine learning. It's about predicting and automating. And this will really change the roles of data professionals and IT professionals. For example, a data scientist cannot possibly know every algorithm or every model that they could use. So we can automate the process of algorithm selection. Another example is things like automated data matching. Or metadata creation. Some of these things may not be exciting but they're hugely practical. And so when you think about the real use cases that are driving return on investment today, it's things like that. It's automating the mundane tasks. >> Let's go ahead and come back to something that you mentioned earlier because it's fascinating to be talking about this AI journey, but also significant is the new job roles. And what are those other participants in the analytics pipeline? >> Yeah I think we're just at the start of this idea of new job roles. We have data scientists. We have data engineers. Now you see machine learning engineers. Application developers. What's really happening is that data scientists are no longer allowed to work in their own silo. And so the new job roles is about how does everybody have data first in their mind? And then they're using tools to automate data science, to automate building machine learning into applications. So roles are going to change dramatically in organizations. >> I think that's confusing though because we have several organizations who saying is that highly specialized roles, just for data science? Or is it applicable to everybody across the board? >> Yeah, and that's the big question, right? Cause everybody's thinking how will this apply? Do I want this to be just a small set of people in the organization that will do this? But, our view is data science has to for everybody. It's about bring data science to everybody as a shared mission across the organization. Everybody in the company has to be data literate. And participate in this journey. >> So overall, group effort, has to be a common goal, and we all need to be data literate across the board. >> Absolutely. >> Done deal. But at the end of the day, it's kind of not an easy task. >> It's not. It's not easy but it's maybe not as big of a shift as you would think. Because you have to put data in the hands of people that can do something with it. So, it's very basic. Give access to data. Data's often locked up in a lot of organizations today. Give people the right tools. Embrace the idea of choice or diversity in terms of those tools. That gets you started on this path. >> It's interesting to hear you say essentially you need to train everyone though across the board when it comes to data literacy. And I think people that are coming into the work force don't necessarily have a background or a degree in data science. So how do you manage? >> Yeah, so in many cases that's true. I will tell you some universities are doing amazing work here. One example, University of California Berkeley. They offer a course for all majors. So no matter what you're majoring in, you have a course on foundations of data science. How do you bring data science to every role? So it's starting to happen. We at IBM provide data science courses through CognitiveClass.ai. It's for everybody. It's free. And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. The key point is this though. It's more about attitude than it is aptitude. I think anybody can figure this out. But it's about the attitude to say we're putting data first and we're going to figure out how to make this real in our organization. >> I also have to give a shout out to my alma mater because I have heard that there is an offering in MS in data analytics. And they are always on the forefront of new technologies and new majors and on trend. And I've heard that the placement behind those jobs, people graduating with the MS is high. >> I'm sure it's very high. >> So go Tigers. All right, tangential. Let me get back to something else you touched on earlier because you mentioned that a number of customers ask you how in the world do I get started with AI? It's an overwhelming question. Where do you even begin? What do you tell them? >> Yeah, well things are moving really fast. But the good thing is most organizations I see, they're already on the path, even if they don't know it. They might have a BI practice in place. They've got data warehouses. They've got data lakes. Let me give you an example. AMC Networks. They produce a lot of the shows that I'm sure you watch Katie. >> [Katie] Yes, Breaking Bad, Walking Dead, any fans? >> [Rob] Yeah, we've got a few. >> [Katie] Well you taught me something I didn't even know. Because it's amazing how we have all these different industries, but yet media in itself is impacted too. And this is a good example. >> Absolutely. So, AMC Networks, think about it. They've got ads to place. They want to track viewer behavior. What do people like? What do they dislike? So they have to optimize every aspect of their business from marketing campaigns to promotions to scheduling to ads. And their goal was transform data into business insights and really take the burden off of their IT team that was heavily burdened by obviously a huge increase in data. So their VP of BI took the approach of using machine learning to process large volumes of data. They used a platform that was designed for AI and data processing. It's the IBM analytics system where it's a data warehouse, data science tools are built in. It has in memory data processing. And just like that, they were ready for AI. And they're already seeing that impact in their business. >> Do you think a movement of that nature kind of presses other media conglomerates and organizations to say we need to be doing this too? >> I think it's inevitable that everybody, you're either going to be playing, you're either going to be leading, or you'll be playing catch up. And so, as we talk to clients we think about how do you start down this path now, even if you have to iterate over time? Because otherwise you're going to wake up and you're going to be behind. >> One thing worth noting is we've talked about analytics to the data. It's analytics first to the data, not the other way around. >> Right. So, look. We as a practice, we say you want to bring data to where the data sits. Because it's a lot more efficient that way. It gets you better outcomes in terms of how you train models and it's more efficient. And we think that leads to better outcomes. Other organization will say, "Hey move the data around." And everything becomes a big data movement exercise. But once an organization has started down this path, they're starting to get predictions, they want to do it where it's really easy. And that means analytics applied right where the data sits. >> And worth talking about the role of the data scientist in all of this. It's been called the hot job of the decade. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. >> Yes. >> I want to see this on the cover of Vogue. Like I want to see the first data scientist. Female preferred, on the cover of Vogue. That would be amazing. >> Perhaps you can. >> People agree. So what changes for them? Is this challenging in terms of we talk data science for all. Where do all the data science, is it data science for everyone? And how does it change everything? >> Well, I think of it this way. AI gives software super powers. It really does. It changes the nature of software. And at the center of that is data scientists. So, a data scientist has a set of powers that they've never had before in any organization. And that's why it's a hot profession. Now, on one hand, this has been around for a while. We've had actuaries. We've had statisticians that have really transformed industries. But there are a few things that are new now. We have new tools. New languages. Broader recognition of this need. And while it's important to recognize this critical skill set, you can't just limit it to a few people. This is about scaling it across the organization. And truly making it accessible to all. >> So then do we need more data scientists? Or is this something you train like you said, across the board? >> Well, I think you want to do a little bit of both. We want more. But, we can also train more and make the ones we have more productive. The way I think about it is there's kind of two markets here. And we call it clickers and coders. >> [Katie] I like that. That's good. >> So, let's talk about what that means. So clickers are basically somebody that wants to use tools. Create models visually. It's drag and drop. Something that's very intuitive. Those are the clickers. Nothing wrong with that. It's been valuable for years. There's a new crop of data scientists. They want to code. They want to build with the latest open source tools. They want to write in Python or R. These are the coders. And both approaches are viable. Both approaches are critical. Organizations have to have a way to meet the needs of both of those types. And there's not a lot of things available today that do that. >> Well let's keep going on that. Because I hear you talking about the data scientists role and how it's critical to success, but with the new tools, data science and analytics skills can extend beyond the domain of just the data scientist. >> That's right. So look, we're unifying coders and clickers into a single platform, which we call IBM Data Science Experience. And as the demand for data science expertise grows, so does the need for these kind of tools. To bring them into the same environment. And my view is if you have the right platform, it enables the organization to collaborate. And suddenly you've changed the nature of data science from an individual sport to a team sport. >> So as somebody that, my background is in IT, the question is really is this an additional piece of what IT needs to do in 2017 and beyond? Or is it just another line item to the budget? >> So I'm afraid that some people might view it that way. As just another line item. But, I would challenge that and say data science is going to reinvent IT. It's going to change the nature of IT. And every organization needs to think about what are the skills that are critical? How do we engage a broader team to do this? Because once they get there, this is the chance to reinvent how they're performing IT. >> [Katie] Challenging or not? >> Look it's all a big challenge. Think about everything IT organizations have been through. Some of them were late to things like mobile, but then they caught up. Some were late to cloud, but then they caught up. I would just urge people, don't be late to data science. Use this as your chance to reinvent IT. Start with this notion of clickers and coders. This is a seminal moment. Much like mobile and cloud was. So don't be late. >> And I think it's critical because it could be so costly to wait. And Rob and I were even chatting earlier how data analytics is just moving into all different kinds of industries. And I can tell you even personally being effected by how important the analysis is in working in pediatric cancer for the last seven years. I personally implement virtual reality headsets to pediatric cancer hospitals across the country. And it's great. And it's working phenomenally. And the kids are amazed. And the staff is amazed. But the phase two of this project is putting in little metrics in the hardware that gather the breathing, the heart rate to show that we have data. Proof that we can hand over to the hospitals to continue making this program a success. So just in-- >> That's a great example. >> An interesting example. >> Saving lives? >> Yes. >> That's also applying a lot of what we talked about. >> Exciting stuff in the world of data science. >> Yes. Look, I just add this is an existential moment for every organization. Because what you do in this area is probably going to define how competitive you are going forward. And think about if you don't do something. What if one of your competitors goes and creates an application that's more engaging with clients? So my recommendation is start small. Experiment. Learn. Iterate on projects. Define the business outcomes. Then scale up. It's very doable. But you've got to take the first step. >> First step always critical. And now we're going to get to the fun hands on part of our story. Because in just a moment we're going to take a closer look at what data science can deliver. And where organizations are trying to get to. All right. Thank you Rob and now we've been joined by Siva Anne who is going to help us navigate this demo. First, welcome Siva. Give him a big round of applause. Yeah. All right, Rob break down what we're going to be looking at. You take over this demo. >> All right. So this is going to be pretty interesting. So Siva is going to take us through. So he's going to play the role of a financial adviser. Who wants to help better serve clients through recommendations. And I'm going to really illustrate three things. One is how do you federate data from multiple data sources? Inside the firewall, outside the firewall. How do you apply machine learning to predict and to automate? And then how do you move analytics closer to your data? So, what you're seeing here is a custom application for an investment firm. So, Siva, our financial adviser, welcome. So you can see at the top, we've got market data. We pulled that from an external source. And then we've got Siva's calendar in the middle. He's got clients on the right side. So page down, what else do you see down there Siva? >> [Siva] I can see the recent market news. And in here I can see that JP Morgan is calling for a US dollar rebound in the second half of the year. And, I have upcoming meeting with Leo Rakes. I can get-- >> [Rob] So let's go in there. Why don't you click on Leo Rakes. So, you're sitting at your desk, you're deciding how you're going to spend the day. You know you have a meeting with Leo. So you click on it. You immediately see, all right, so what do we know about him? We've got data governance implemented. So we know his age, we know his degree. We can see he's not that aggressive of a trader. Only six trades in the last few years. But then where it gets interesting is you go to the bottom. You start to see predicted industry affinity. Where did that come from? How do we have that? >> [Siva] So these green lines and red arrows here indicate the trending affinity of Leo Rakes for particular industry stocks. What we've done here is we've built machine learning models using customer's demographic data, his stock portfolios, and browsing behavior to build a model which can predict his affinity for a particular industry. >> [Rob] Interesting. So, I like to think of this, we call it celebrity experiences. So how do you treat every customer like they're a celebrity? So to some extent, we're reading his mind. Because without asking him, we know that he's going to have an affinity for auto stocks. So we go down. Now we look at his portfolio. You can see okay, he's got some different holdings. He's got Amazon, Google, Apple, and then he's got RACE, which is the ticker for Ferrari. You can see that's done incredibly well. And so, as a financial adviser, you look at this and you say, all right, we know he loves auto stocks. Ferrari's done very well. Let's create a hedge. Like what kind of security would interest him as a hedge against his position for Ferrari? Could we go figure that out? >> [Siva] Yes. Given I know that he's gotten an affinity for auto stocks, and I also see that Ferrari has got some terminus gains, I want to lock in these gains by hedging. And I want to do that by picking a auto stock which has got negative correlation with Ferrari. >> [Rob] So this is where we get to the idea of in database analytics. Cause you start clicking that and immediately we're getting instant answers of what's happening. So what did we find here? We're going to compare Ferrari and Honda. >> [Siva] I'm going to compare Ferrari with Honda. And what I see here instantly is that Honda has got a negative correlation with Ferrari, which makes it a perfect mix for his stock portfolio. Given he has an affinity for auto stocks and it correlates negatively with Ferrari. >> [Rob] These are very powerful tools at the hand of a financial adviser. You think about it. As a financial adviser, you wouldn't think about federating data, machine learning, pretty powerful. >> [Siva] Yes. So what we have seen here is that using the common SQL engine, we've been able to federate queries across multiple data sources. Db2 Warehouse in the cloud, IBM's Integrated Analytic System, and Hortonworks powered Hadoop platform for the new speeds. We've been able to use machine learning to derive innovative insights about his stock affinities. And drive the machine learning into the appliance. Closer to where the data resides to deliver high performance analytics. >> [Rob] At scale? >> [Siva] We're able to run millions of these correlations across stocks, currency, other factors. And even score hundreds of customers for their affinities on a daily basis. >> That's great. Siva, thank you for playing the role of financial adviser. So I just want to recap briefly. Cause this really powerful technology that's really simple. So we federated, we aggregated multiple data sources from all over the web and internal systems. And public cloud systems. Machine learning models were built that predicted Leo's affinity for a certain industry. In this case, automotive. And then you see when you deploy analytics next to your data, even a financial adviser, just with the click of a button is getting instant answers so they can go be more productive in their next meeting. This whole idea of celebrity experiences for your customer, that's available for everybody, if you take advantage of these types of capabilities. Katie, I'll hand it back to you. >> Good stuff. Thank you Rob. Thank you Siva. Powerful demonstration on what we've been talking about all afternoon. And thank you again to Siva for helping us navigate. Should be give him one more round of applause? We're going to be back in just a moment to look at how we operationalize all of this data. But in first, here's a message from me. If you're a part of a line of business, your main fear is disruption. You know data is the new goal that can create huge amounts of value. So does your competition. And they may be beating you to it. You're convinced there are new business models and revenue sources hidden in all the data. You just need to figure out how to leverage it. But with the scarcity of data scientists, you really can't rely solely on them. You may need more people throughout the organization that have the ability to extract value from data. And as a data science leader or data scientist, you have a lot of the same concerns. You spend way too much time looking for, prepping, and interpreting data and waiting for models to train. You know you need to operationalize the work you do to provide business value faster. What you want is an easier way to do data prep. And rapidly build models that can be easily deployed, monitored and automatically updated. So whether you're a data scientist, data science leader, or in a line of business, what's the solution? What'll it take to transform the way you work? That's what we're going to explore next. All right, now it's time to delve deeper into the nuts and bolts. The nitty gritty of operationalizing data science and creating a data driven culture. How do you actually do that? Well that's what these experts are here to share with us. I'm joined by Nir Kaldero, who's head of data science at Galvanize, which is an education and training organization. Tricia Wang, who is co-founder of Sudden Compass, a consultancy that helps companies understand people with data. And last, but certainly not least, Michael Li, founder and CEO of Data Incubator, which is a data science train company. All right guys. Shall we get right to it? >> All right. >> So data explosion happening right now. And we are seeing it across the board. I just shared an example of how it's impacting my philanthropic work in pediatric cancer. But you guys each have so many unique roles in your business life. How are you seeing it just blow up in your fields? Nir, your thing? >> Yeah, for example like in Galvanize we train many Fortune 500 companies. And just by looking at the demand of companies that wants us to help them go through this digital transformation is mind-blowing. Data point by itself. >> Okay. Well what we're seeing what's going on is that data science like as a theme, is that it's actually for everyone now. But what's happening is that it's actually meeting non technical people. But what we're seeing is that when non technical people are implementing these tools or coming at these tools without a base line of data literacy, they're often times using it in ways that distance themselves from the customer. Because they're implementing data science tools without a clear purpose, without a clear problem. And so what we do at Sudden Compass is that we work with companies to help them embrace and understand the complexity of their customers. Because often times they are misusing data science to try and flatten their understanding of the customer. As if you can just do more traditional marketing. Where you're putting people into boxes. And I think the whole ROI of data is that you can now understand people's relationships at a much more complex level at a greater scale before. But we have to do this with basic data literacy. And this has to involve technical and non technical people. >> Well you can have all the data in the world, and I think it speaks to, if you're not doing the proper movement with it, forget it. It means nothing at the same time. >> No absolutely. I mean, I think that when you look at the huge explosion in data, that comes with it a huge explosion in data experts. Right, we call them data scientists, data analysts. And sometimes they're people who are very, very talented, like the people here. But sometimes you have people who are maybe re-branding themselves, right? Trying to move up their title one notch to try to attract that higher salary. And I think that that's one of the things that customers are coming to us for, right? They're saying, hey look, there are a lot of people that call themselves data scientists, but we can't really distinguish. So, we have sort of run a fellowship where you help companies hire from a really talented group of folks, who are also truly data scientists and who know all those kind of really important data science tools. And we also help companies internally. Fortune 500 companies who are looking to grow that data science practice that they have. And we help clients like McKinsey, BCG, Bain, train up their customers, also their clients, also their workers to be more data talented. And to build up that data science capabilities. >> And Nir, this is something you work with a lot. A lot of Fortune 500 companies. And when we were speaking earlier, you were saying many of these companies can be in a panic. >> Yeah. >> Explain that. >> Yeah, so you know, not all Fortune 500 companies are fully data driven. And we know that the winners in this fourth industrial revolution, which I like to call the machine intelligence revolution, will be companies who navigate and transform their organization to unlock the power of data science and machine learning. And the companies that are not like that. Or not utilize data science and predictive power well, will pretty much get shredded. So they are in a panic. >> Tricia, companies have to deal with data behind the firewall and in the new multi cloud world. How do organizations start to become driven right to the core? >> I think the most urgent question to become data driven that companies should be asking is how do I bring the complex reality that our customers are experiencing on the ground in to a corporate office? Into the data models. So that question is critical because that's how you actually prevent any big data disasters. And that's how you leverage big data. Because when your data models are really far from your human models, that's when you're going to do things that are really far off from how, it's going to not feel right. That's when Tesco had their terrible big data disaster that they're still recovering from. And so that's why I think it's really important to understand that when you implement big data, you have to further embrace thick data. The qualitative, the emotional stuff, that is difficult to quantify. But then comes the difficult art and science that I think is the next level of data science. Which is that getting non technical and technical people together to ask how do we find those unknown nuggets of insights that are difficult to quantify? Then, how do we do the next step of figuring out how do you mathematically scale those insights into a data model? So that actually is reflective of human understanding? And then we can start making decisions at scale. But you have to have that first. >> That's absolutely right. And I think that when we think about what it means to be a data scientist, right? I always think about it in these sort of three pillars. You have the math side. You have to have that kind of stats, hardcore machine learning background. You have the programming side. You don't work with small amounts of data. You work with large amounts of data. You've got to be able to type the code to make those computers run. But then the last part is that human element. You have to understand the domain expertise. You have to understand what it is that I'm actually analyzing. What's the business proposition? And how are the clients, how are the users actually interacting with the system? That human element that you were talking about. And I think having somebody who understands all of those and not just in isolation, but is able to marry that understanding across those different topics, that's what makes a data scientist. >> But I find that we don't have people with those skill sets. And right now the way I see teams being set up inside companies is that they're creating these isolated data unicorns. These data scientists that have graduated from your programs, which are great. But, they don't involve the people who are the domain experts. They don't involve the designers, the consumer insight people, the people, the salespeople. The people who spend time with the customers day in and day out. Somehow they're left out of the room. They're consulted, but they're not a stakeholder. >> Can I actually >> Yeah, yeah please. >> Can I actually give a quick example? So for example, we at Galvanize train the executives and the managers. And then the technical people, the data scientists and the analysts. But in order to actually see all of the RY behind the data, you also have to have a creative fluid conversation between non technical and technical people. And this is a major trend now. And there's a major gap. And we need to increase awareness and kind of like create a new, kind of like environment where technical people also talks seamlessly with non technical ones. >> [Tricia] We call-- >> That's one of the things that we see a lot. Is one of the trends in-- >> A major trend. >> data science training is it's not just for the data science technical experts. It's not just for one type of person. So a lot of the training we do is sort of data engineers. People who are more on the software engineering side learning more about the stats of math. And then people who are sort of traditionally on the stat side learning more about the engineering. And then managers and people who are data analysts learning about both. >> Michael, I think you said something that was of interest too because I think we can look at IBM Watson as an example. And working in healthcare. The human component. Because often times we talk about machine learning and AI, and data and you get worried that you still need that human component. Especially in the world of healthcare. And I think that's a very strong point when it comes to the data analysis side. Is there any particular example you can speak to of that? >> So I think that there was this really excellent paper a while ago talking about all the neuro net stuff and trained on textual data. So looking at sort of different corpuses. And they found that these models were highly, highly sexist. They would read these corpuses and it's not because neuro nets themselves are sexist. It's because they're reading the things that we write. And it turns out that we write kind of sexist things. And they would sort of find all these patterns in there that were sort of latent, that had a lot of sort of things that maybe we would cringe at if we sort of saw. And I think that's one of the really important aspects of the human element, right? It's being able to come in and sort of say like, okay, I know what the biases of the system are, I know what the biases of the tools are. I need to figure out how to use that to make the tools, make the world a better place. And like another area where this comes up all the time is lending, right? So the federal government has said, and we have a lot of clients in the financial services space, so they're constantly under these kind of rules that they can't make discriminatory lending practices based on a whole set of protected categories. Race, sex, gender, things like that. But, it's very easy when you train a model on credit scores to pick that up. And then to have a model that's inadvertently sexist or racist. And that's where you need the human element to come back in and say okay, look, you're using the classic example would be zip code, you're using zip code as a variable. But when you look at it, zip codes actually highly correlated with race. And you can't do that. So you may inadvertently by sort of following the math and being a little naive about the problem, inadvertently introduce something really horrible into a model and that's where you need a human element to sort of step in and say, okay hold on. Slow things down. This isn't the right way to go. >> And the people who have -- >> I feel like, I can feel her ready to respond. >> Yes, I'm ready. >> She's like let me have at it. >> And the people here it is. And the people who are really great at providing that human intelligence are social scientists. We are trained to look for bias and to understand bias in data. Whether it's quantitative or qualitative. And I really think that we're going to have less of these kind of problems if we had more integrated teams. If it was a mandate from leadership to say no data science team should be without a social scientist, ethnographer, or qualitative researcher of some kind, to be able to help see these biases. >> The talent piece is actually the most crucial-- >> Yeah. >> one here. If you look about how to enable machine intelligence in organization there are the pillars that I have in my head which is the culture, the talent and the technology infrastructure. And I believe and I saw in working very closely with the Fortune 100 and 200 companies that the talent piece is actually the most important crucial hard to get. >> [Tricia] I totally agree. >> It's absolutely true. Yeah, no I mean I think that's sort of like how we came up with our business model. Companies were basically saying hey, I can't hire data scientists. And so we have a fellowship where we get 2,000 applicants each quarter. We take the top 2% and then we sort of train them up. And we work with hiring companies who then want to hire from that population. And so we're sort of helping them solve that problem. And the other half of it is really around training. Cause with a lot of industries, especially if you're sort of in a more regulated industry, there's a lot of nuances to what you're doing. And the fastest way to develop that data science or AI talent may not necessarily be to hire folks who are coming out of a PhD program. It may be to take folks internally who have a lot of that domain knowledge that you have and get them trained up on those data science techniques. So we've had large insurance companies come to us and say hey look, we hire three or four folks from you a quarter. That doesn't move the needle for us. What we really need is take the thousand actuaries and statisticians that we have and get all of them trained up to become a data scientist and become data literate in this new open source world. >> [Katie] Go ahead. >> All right, ladies first. >> Go ahead. >> Are you sure? >> No please, fight first. >> Go ahead. >> Go ahead Nir. >> So this is actually a trend that we have been seeing in the past year or so that companies kind of like start to look how to upscale and look for talent within the organization. So they can actually move them to become more literate and navigate 'em from analyst to data scientist. And from data scientist to machine learner. So this is actually a trend that is happening already for a year or so. >> Yeah, but I also find that after they've gone through that training in getting people skilled up in data science, the next problem that I get is executives coming to say we've invested in all of this. We're still not moving the needle. We've already invested in the right tools. We've gotten the right skills. We have enough scale of people who have these skills. Why are we not moving the needle? And what I explain to them is look, you're still making decisions in the same way. And you're still not involving enough of the non technical people. Especially from marketing, which is now, the CMO's are much more responsible for driving growth in their companies now. But often times it's so hard to change the old way of marketing, which is still like very segmentation. You know, demographic variable based, and we're trying to move people to say no, you have to understand the complexity of customers and not put them in boxes. >> And I think underlying a lot of this discussion is this question of culture, right? >> Yes. >> Absolutely. >> How do you build a data driven culture? And I think that that culture question, one of the ways that comes up quite often in especially in large, Fortune 500 enterprises, is that they are very, they're not very comfortable with sort of example, open source architecture. Open source tools. And there is some sort of residual bias that that's somehow dangerous. So security vulnerability. And I think that that's part of the cultural challenge that they often have in terms of how do I build a more data driven organization? Well a lot of the talent really wants to use these kind of tools. And I mean, just to give you an example, we are partnering with one of the major cloud providers to sort of help make open source tools more user friendly on their platform. So trying to help them attract the best technologists to use their platform because they want and they understand the value of having that kind of open source technology work seamlessly on their platforms. So I think that just sort of goes to show you how important open source is in this movement. And how much large companies and Fortune 500 companies and a lot of the ones we work with have to embrace that. >> Yeah, and I'm seeing it in our work. Even when we're working with Fortune 500 companies, is that they've already gone through the first phase of data science work. Where I explain it was all about the tools and getting the right tools and architecture in place. And then companies started moving into getting the right skill set in place. Getting the right talent. And what you're talking about with culture is really where I think we're talking about the third phase of data science, which is looking at communication of these technical frameworks so that we can get non technical people really comfortable in the same room with data scientists. That is going to be the phase, that's really where I see the pain point. And that's why at Sudden Compass, we're really dedicated to working with each other to figure out how do we solve this problem now? >> And I think that communication between the technical stakeholders and management and leadership. That's a very critical piece of this. You can't have a successful data science organization without that. >> Absolutely. >> And I think that actually some of the most popular trainings we've had recently are from managers and executives who are looking to say, how do I become more data savvy? How do I figure out what is this data science thing and how do I communicate with my data scientists? >> You guys made this way too easy. I was just going to get some popcorn and watch it play out. >> Nir, last 30 seconds. I want to leave you with an opportunity to, anything you want to add to this conversation? >> I think one thing to conclude is to say that companies that are not data driven is about time to hit refresh and figure how they transition the organization to become data driven. To become agile and nimble so they can actually see what opportunities from this important industrial revolution. Otherwise, unfortunately they will have hard time to survive. >> [Katie] All agreed? >> [Tricia] Absolutely, you're right. >> Michael, Trish, Nir, thank you so much. Fascinating discussion. And thank you guys again for joining us. We will be right back with another great demo. Right after this. >> Thank you Katie. >> Once again, thank you for an excellent discussion. Weren't they great guys? And thank you for everyone who's tuning in on the live webcast. As you can hear, we have an amazing studio audience here. And we're going to keep things moving. I'm now joined by Daniel Hernandez and Siva Anne. And we're going to turn our attention to how you can deliver on what they're talking about using data science experience to do data science faster. >> Thank you Katie. Siva and I are going to spend the next 10 minutes showing you how you can deliver on what they were saying using the IBM Data Science Experience to do data science faster. We'll demonstrate through new features we introduced this week how teams can work together more effectively across the entire analytics life cycle. How you can take advantage of any and all data no matter where it is and what it is. How you could use your favorite tools from open source. And finally how you could build models anywhere and employ them close to where your data is. Remember the financial adviser app Rob showed you? To build an app like that, we needed a team of data scientists, developers, data engineers, and IT staff to collaborate. We do this in the Data Science Experience through a concept we call projects. When I create a new project, I can now use the new Github integration feature. We're doing for data science what we've been doing for developers for years. Distributed teams can work together on analytics projects. And take advantage of Github's version management and change management features. This is a huge deal. Let's explore the project we created for the financial adviser app. As you can see, our data engineer Joane, our developer Rob, and others are collaborating this project. Joane got things started by bringing together the trusted data sources we need to build the app. Taking a closer look at the data, we see that our customer and profile data is stored on our recently announced IBM Integrated Analytics System, which runs safely behind our firewall. We also needed macro economic data, which she was able to find in the Federal Reserve. And she stored it in our Db2 Warehouse on Cloud. And finally, she selected stock news data from NASDAQ.com and landed that in a Hadoop cluster, which happens to be powered by Hortonworks. We added a new feature to the Data Science Experience so that when it's installed with Hortonworks, it automatically uses a need of security and governance controls within the cluster so your data is always secure and safe. Now we want to show you the news data we stored in the Hortonworks cluster. This is the mean administrative console. It's powered by an open source project called Ambari. And here's the news data. It's in parquet files stored in HDFS, which happens to be a distributive file system. To get the data from NASDAQ into our cluster, we used IBM's BigIntegrate and BigQuality to create automatic data pipelines that acquire, cleanse, and ingest that news data. Once the data's available, we use IBM's Big SQL to query that data using SQL statements that are much like the ones we would use for any relation of data, including the data that we have in the Integrated Analytics System and Db2 Warehouse on Cloud. This and the federation capabilities that Big SQL offers dramatically simplifies data acquisition. Now we want to show you how we support a brand new tool that we're excited about. Since we launched last summer, the Data Science Experience has supported Jupyter and R for data analysis and visualization. In this week's update, we deeply integrated another great open source project called Apache Zeppelin. It's known for having great visualization support, advanced collaboration features, and is growing in popularity amongst the data science community. This is an example of Apache Zeppelin and the notebook we created through it to explore some of our data. Notice how wonderful and easy the data visualizations are. Now we want to walk you through the Jupyter notebook we created to explore our customer preference for stocks. We use notebooks to understand and explore data. To identify the features that have some predictive power. Ultimately, we're trying to assess what ultimately is driving customer stock preference. Here we did the analysis to identify the attributes of customers that are likely to purchase auto stocks. We used this understanding to build our machine learning model. For building machine learning models, we've always had tools integrated into the Data Science Experience. But sometimes you need to use tools you already invested in. Like our very own SPSS as well as SAS. Through new import feature, you can easily import those models created with those tools. This helps you avoid vendor lock-in, and simplify the development, training, deployment, and management of all your models. To build the models we used in app, we could have coded, but we prefer a visual experience. We used our customer profile data in the Integrated Analytic System. Used the Auto Data Preparation to cleanse our data. Choose the binary classification algorithms. Let the Data Science Experience evaluate between logistic regression and gradient boosted tree. It's doing the heavy work for us. As you can see here, the Data Science Experience generated performance metrics that show us that the gradient boosted tree is the best performing algorithm for the data we gave it. Once we save this model, it's automatically deployed and available for developers to use. Any application developer can take this endpoint and consume it like they would any other API inside of the apps they built. We've made training and creating machine learning models super simple. But what about the operations? A lot of companies are struggling to ensure their model performance remains high over time. In our financial adviser app, we know that customer data changes constantly, so we need to always monitor model performance and ensure that our models are retrained as is necessary. This is a dashboard that shows the performance of our models and lets our teams monitor and retrain those models so that they're always performing to our standards. So far we've been showing you the Data Science Experience available behind the firewall that we're using to build and train models. Through a new publish feature, you can build models and deploy them anywhere. In another environment, private, public, or anywhere else with just a few clicks. So here we're publishing our model to the Watson machine learning service. It happens to be in the IBM cloud. And also deeply integrated with our Data Science Experience. After publishing and switching to the Watson machine learning service, you can see that our stock affinity and model that we just published is there and ready for use. So this is incredibly important. I just want to say it again. The Data Science Experience allows you to train models behind your own firewall, take advantage of your proprietary and sensitive data, and then deploy those models wherever you want with ease. So summarize what we just showed you. First, IBM's Data Science Experience supports all teams. You saw how our data engineer populated our project with trusted data sets. Our data scientists developed, trained, and tested a machine learning model. Our developers used APIs to integrate machine learning into their apps. And how IT can use our Integrated Model Management dashboard to monitor and manage model performance. Second, we support all data. On premises, in the cloud, structured, unstructured, inside of your firewall, and outside of it. We help you bring analytics and governance to where your data is. Third, we support all tools. The data science tools that you depend on are readily available and deeply integrated. This includes capabilities from great partners like Hortonworks. And powerful tools like our very own IBM SPSS. And fourth, and finally, we support all deployments. You can build your models anywhere, and deploy them right next to where your data is. Whether that's in the public cloud, private cloud, or even on the world's most reliable transaction platform, IBM z. So see for yourself. Go to the Data Science Experience website, take us for a spin. And if you happen to be ready right now, our recently created Data Science Elite Team can help you get started and run experiments alongside you with no charge. Thank you very much. >> Thank you very much Daniel. It seems like a great time to get started. And thanks to Siva for taking us through it. Rob and I will be back in just a moment to add some perspective right after this. All right, once again joined by Rob Thomas. And Rob obviously we got a lot of information here. >> Yes, we've covered a lot of ground. >> This is intense. You got to break it down for me cause I think we zoom out and see the big picture. What better data science can deliver to a business? Why is this so important? I mean we've heard it through and through. >> Yeah, well, I heard it a couple times. But it starts with businesses have to embrace a data driven culture. And it is a change. And we need to make data accessible with the right tools in a collaborative culture because we've got diverse skill sets in every organization. But data driven companies succeed when data science tools are in the hands of everyone. And I think that's a new thought. I think most companies think just get your data scientist some tools, you'll be fine. This is about tools in the hands of everyone. I think the panel did a great job of describing about how we get to data science for all. Building a data culture, making it a part of your everyday operations, and the highlights of what Daniel just showed us, that's some pretty cool features for how organizations can get to this, which is you can see IBM's Data Science Experience, how that supports all teams. You saw data analysts, data scientists, application developer, IT staff, all working together. Second, you saw how we support all tools. And your choice of tools. So the most popular data science libraries integrated into one platform. And we saw some new capabilities that help companies avoid lock-in, where you can import existing models created from specialist tools like SPSS or others. And then deploy them and manage them inside of Data Science Experience. That's pretty interesting. And lastly, you see we continue to build on this best of open tools. Partnering with companies like H2O, Hortonworks, and others. Third, you can see how you use all data no matter where it lives. That's a key challenge every organization's going to face. Private, public, federating all data sources. We announced new integration with the Hortonworks data platform where we deploy machine learning models where your data resides. That's been a key theme. Analytics where the data is. And lastly, supporting all types of deployments. Deploy them in your Hadoop cluster. Deploy them in your Integrated Analytic System. Or deploy them in z, just to name a few. A lot of different options here. But look, don't believe anything I say. Go try it for yourself. Data Science Experience, anybody can use it. Go to datascience.ibm.com and look, if you want to start right now, we just created a team that we call Data Science Elite. These are the best data scientists in the world that will come sit down with you and co-create solutions, models, and prove out a proof of concept. >> Good stuff. Thank you Rob. So you might be asking what does an organization look like that embraces data science for all? And how could it transform your role? I'm going to head back to the office and check it out. Let's start with the perspective of the line of business. What's changed? Well, now you're starting to explore new business models. You've uncovered opportunities for new revenue sources and all that hidden data. And being disrupted is no longer keeping you up at night. As a data science leader, you're beginning to collaborate with a line of business to better understand and translate the objectives into the models that are being built. Your data scientists are also starting to collaborate with the less technical team members and analysts who are working closest to the business problem. And as a data scientist, you stop feeling like you're falling behind. Open source tools are keeping you current. You're also starting to operationalize the work that you do. And you get to do more of what you love. Explore data, build models, put your models into production, and create business impact. All in all, it's not a bad scenario. Thanks. All right. We are back and coming up next, oh this is a special time right now. Cause we got a great guest speaker. New York Magazine called him the spreadsheet psychic and number crunching prodigy who went from correctly forecasting baseball games to correctly forecasting presidential elections. He even invented a proprietary algorithm called PECOTA for predicting future performance by baseball players and teams. And his New York Times bestselling book, The Signal and the Noise was named by Amazon.com as the number one best non-fiction book of 2012. He's currently the Editor in Chief of the award winning website, FiveThirtyEight and appears on ESPN as an on air commentator. Big round of applause. My pleasure to welcome Nate Silver. >> Thank you. We met backstage. >> Yes. >> It feels weird to re-shake your hand, but you know, for the audience. >> I had to give the intense firm grip. >> Definitely. >> The ninja grip. So you and I have crossed paths kind of digitally in the past, which it really interesting, is I started my career at ESPN. And I started as a production assistant, then later back on air for sports technology. And I go to you to talk about sports because-- >> Yeah. >> Wow, has ESPN upped their game in terms of understanding the importance of data and analytics. And what it brings. Not just to MLB, but across the board. >> No, it's really infused into the way they present the broadcast. You'll have win probability on the bottom line. And they'll incorporate FiveThirtyEight metrics into how they cover college football for example. So, ESPN ... Sports is maybe the perfect, if you're a data scientist, like the perfect kind of test case. And the reason being that sports consists of problems that have rules. And have structure. And when problems have rules and structure, then it's a lot easier to work with. So it's a great way to kind of improve your skills as a data scientist. Of course, there are also important real world problems that are more open ended, and those present different types of challenges. But it's such a natural fit. The teams. Think about the teams playing the World Series tonight. The Dodgers and the Astros are both like very data driven, especially Houston. Golden State Warriors, the NBA Champions, extremely data driven. New England Patriots, relative to an NFL team, it's shifted a little bit, the NFL bar is lower. But the Patriots are certainly very analytical in how they make decisions. So, you can't talk about sports without talking about analytics. >> And I was going to save the baseball question for later. Cause we are moments away from game seven. >> Yeah. >> Is everyone else watching game seven? It's been an incredible series. Probably one of the best of all time. >> Yeah, I mean-- >> You have a prediction here? >> You can mention that too. So I don't have a prediction. FiveThirtyEight has the Dodgers with a 60% chance of winning. >> [Katie] LA Fans. >> So you have two teams that are about equal. But the Dodgers pitching staff is in better shape at the moment. The end of a seven game series. And they're at home. >> But the statistics behind the two teams is pretty incredible. >> Yeah. It's like the first World Series in I think 56 years or something where you have two 100 win teams facing one another. There have been a lot of parity in baseball for a lot of years. Not that many offensive overall juggernauts. But this year, and last year with the Cubs and the Indians too really. But this year, you have really spectacular teams in the World Series. It kind of is a showcase of modern baseball. Lots of home runs. Lots of strikeouts. >> [Katie] Lots of extra innings. >> Lots of extra innings. Good defense. Lots of pitching changes. So if you love the modern baseball game, it's been about the best example that you've had. If you like a little bit more contact, and fewer strikeouts, maybe not so much. But it's been a spectacular and very exciting World Series. It's amazing to talk. MLB is huge with analysis. I mean, hands down. But across the board, if you can provide a few examples. Because there's so many teams in front offices putting such an, just a heavy intensity on the analysis side. And where the teams are going. And if you could provide any specific examples of teams that have really blown your mind. Especially over the last year or two. Because every year it gets more exciting if you will. I mean, so a big thing in baseball is defensive shifts. So if you watch tonight, you'll probably see a couple of plays where if you're used to watching baseball, a guy makes really solid contact. And there's a fielder there that you don't think should be there. But that's really very data driven where you analyze where's this guy hit the ball. That part's not so hard. But also there's game theory involved. Because you have to adjust for the fact that he knows where you're positioning the defenders. He's trying therefore to make adjustments to his own swing and so that's been a major innovation in how baseball is played. You know, how bullpens are used too. Where teams have realized that actually having a guy, across all sports pretty much, realizing the importance of rest. And of fatigue. And that you can be the best pitcher in the world, but guess what? After four or five innings, you're probably not as good as a guy who has a fresh arm necessarily. So I mean, it really is like, these are not subtle things anymore. It's not just oh, on base percentage is valuable. It really effects kind of every strategic decision in baseball. The NBA, if you watch an NBA game tonight, see how many three point shots are taken. That's in part because of data. And teams realizing hey, three points is worth more than two, once you're more than about five feet from the basket, the shooting percentage gets really flat. And so it's revolutionary, right? Like teams that will shoot almost half their shots from the three point range nowadays. Larry Bird, who wound up being one of the greatest three point shooters of all time, took only eight three pointers his first year in the NBA. It's quite noticeable if you watch baseball or basketball in particular. >> Not to focus too much on sports. One final question. In terms of Major League Soccer, and now in NFL, we're having the analysis and having wearables where it can now showcase if they wanted to on screen, heart rate and breathing and how much exertion. How much data is too much data? And when does it ruin the sport? >> So, I don't think, I mean, again, it goes sport by sport a little bit. I think in basketball you actually have a more exciting game. I think the game is more open now. You have more three pointers. You have guys getting higher assist totals. But you know, I don't know. I'm not one of those people who thinks look, if you love baseball or basketball, and you go in to work for the Astros, the Yankees or the Knicks, they probably need some help, right? You really have to be passionate about that sport. Because it's all based on what questions am I asking? As I'm a fan or I guess an employee of the team. Or a player watching the game. And there isn't really any substitute I don't think for the insight and intuition that a curious human has to kind of ask the right questions. So we can talk at great length about what tools do you then apply when you have those questions, but that still comes from people. I don't think machine learning could help with what questions do I want to ask of the data. It might help you get the answers. >> If you have a mid-fielder in a soccer game though, not exerting, only 80%, and you're seeing that on a screen as a fan, and you're saying could that person get fired at the end of the day? One day, with the data? >> So we found that actually some in soccer in particular, some of the better players are actually more still. So Leo Messi, maybe the best player in the world, doesn't move as much as other soccer players do. And the reason being that A) he kind of knows how to position himself in the first place. B) he realizes that you make a run, and you're out of position. That's quite fatiguing. And particularly soccer, like basketball, is a sport where it's incredibly fatiguing. And so, sometimes the guys who conserve their energy, that kind of old school mentality, you have to hustle at every moment. That is not helpful to the team if you're hustling on an irrelevant play. And therefore, on a critical play, can't get back on defense, for example. >> Sports, but also data is moving exponentially as we're just speaking about today. Tech, healthcare, every different industry. Is there any particular that's a favorite of yours to cover? And I imagine they're all different as well. >> I mean, I do like sports. We cover a lot of politics too. Which is different. I mean in politics I think people aren't intuitively as data driven as they might be in sports for example. It's impressive to follow the breakthroughs in artificial intelligence. It started out just as kind of playing games and playing chess and poker and Go and things like that. But you really have seen a lot of breakthroughs in the last couple of years. But yeah, it's kind of infused into everything really. >> You're known for your work in politics though. Especially presidential campaigns. >> Yeah. >> This year, in particular. Was it insanely challenging? What was the most notable thing that came out of any of your predictions? >> I mean, in some ways, looking at the polling was the easiest lens to look at it. So I think there's kind of a myth that last year's result was a big shock and it wasn't really. If you did the modeling in the right way, then you realized that number one, polls have a margin of error. And so when a candidate has a three point lead, that's not particularly safe. Number two, the outcome between different states is correlated. Meaning that it's not that much of a surprise that Clinton lost Wisconsin and Michigan and Pennsylvania and Ohio. You know I'm from Michigan. Have friends from all those states. Kind of the same types of people in those states. Those outcomes are all correlated. So what people thought was a big upset for the polls I think was an example of how data science done carefully and correctly where you understand probabilities, understand correlations. Our model gave Trump a 30% chance of winning. Others models gave him a 1% chance. And so that was interesting in that it showed that number one, that modeling strategies and skill do matter quite a lot. When you have someone saying 30% versus 1%. I mean, that's a very very big spread. And number two, that these aren't like solved problems necessarily. Although again, the problem with elections is that you only have one election every four years. So I can be very confident that I have a better model. Even one year of data doesn't really prove very much. Even five or 10 years doesn't really prove very much. And so, being aware of the limitations to some extent intrinsically in elections when you only get one kind of new training example every four years, there's not really any way around that. There are ways to be more robust to sparce data environments. But if you're identifying different types of business problems to solve, figuring out what's a solvable problem where I can add value with data science is a really key part of what you're doing. >> You're such a leader in this space. In data and analysis. It would be interesting to kind of peek back the curtain, understand how you operate but also how large is your team? How you're putting together information. How quickly you're putting it out. Cause I think in this right now world where everybody wants things instantly-- >> Yeah. >> There's also, you want to be first too in the world of journalism. But you don't want to be inaccurate because that's your credibility. >> We talked about this before, right? I think on average, speed is a little bit overrated in journalism. >> [Katie] I think it's a big problem in journalism. >> Yeah. >> Especially in the tech world. You have to be first. You have to be first. And it's just pumping out, pumping out. And there's got to be more time spent on stories if I can speak subjectively. >> Yeah, for sure. But at the same time, we are reacting to the news. And so we have people that come in, we hire most of our people actually from journalism. >> [Katie] How many people do you have on your team? >> About 35. But, if you get someone who comes in from an academic track for example, they might be surprised at how fast journalism is. That even though we might be slower than the average website, the fact that there's a tragic event in New York, are there things we have to say about that? A candidate drops out of the presidential race, are things we have to say about that. In periods ranging from minutes to days as opposed to kind of weeks to months to years in the academic world. The corporate world moves faster. What is a little different about journalism is that you are expected to have more precision where people notice when you make a mistake. In corporations, you have maybe less transparency. If you make 10 investments and seven of them turn out well, then you'll get a lot of profit from that, right? In journalism, it's a little different. If you make kind of seven predictions or say seven things, and seven of them are very accurate and three of them aren't, you'll still get criticized a lot for the three. Just because that's kind of the way that journalism is. And so the kind of combination of needing, not having that much tolerance for mistakes, but also needing to be fast. That is tricky. And I criticize other journalists sometimes including for not being data driven enough, but the best excuse any journalist has, this is happening really fast and it's my job to kind of figure out in real time what's going on and provide useful information to the readers. And that's really difficult. Especially in a world where literally, I'll probably get off the stage and check my phone and who knows what President Trump will have tweeted or what things will have happened. But it really is a kind of 24/7. >> Well because it's 24/7 with FiveThirtyEight, one of the most well known sites for data, are you feeling micromanagey on your people? Because you do have to hit this balance. You can't have something come out four or five days later. >> Yeah, I'm not -- >> Are you overseeing everything? >> I'm not by nature a micromanager. And so you try to hire well. You try and let people make mistakes. And the flip side of this is that if a news organization that never had any mistakes, never had any corrections, that's raw, right? You have to have some tolerance for error because you are trying to decide things in real time. And figure things out. I think transparency's a big part of that. Say here's what we think, and here's why we think it. If we have a model to say it's not just the final number, here's a lot of detail about how that's calculated. In some case we release the code and the raw data. Sometimes we don't because there's a proprietary advantage. But quite often we're saying we want you to trust us and it's so important that you trust us, here's the model. Go play around with it yourself. Here's the data. And that's also I think an important value. >> That speaks to open source. And your perspective on that in general. >> Yeah, I mean, look, I'm a big fan of open source. I worry that I think sometimes the trends are a little bit away from open source. But by the way, one thing that happens when you share your data or you share your thinking at least in lieu of the data, and you can definitely do both is that readers will catch embarrassing mistakes that you made. By the way, even having open sourceness within your team, I mean we have editors and copy editors who often save you from really embarrassing mistakes. And by the way, it's not necessarily people who have a training in data science. I would guess that of our 35 people, maybe only five to 10 have a kind of formal background in what you would call data science. >> [Katie] I think that speaks to the theme here. >> Yeah. >> [Katie] That everybody's kind of got to be data literate. >> But yeah, it is like you have a good intuition. You have a good BS detector basically. And you have a good intuition for hey, this looks a little bit out of line to me. And sometimes that can be based on domain knowledge, right? We have one of our copy editors, she's a big college football fan. And we had an algorithm we released that tries to predict what the human being selection committee will do, and she was like, why is LSU rated so high? Cause I know that LSU sucks this year. And we looked at it, and she was right. There was a bug where it had forgotten to account for their last game where they lost to Troy or something and so -- >> That also speaks to the human element as well. >> It does. In general as a rule, if you're designing a kind of regression based model, it's different in machine learning where you have more, when you kind of build in the tolerance for error. But if you're trying to do something more precise, then so much of it is just debugging. It's saying that looks wrong to me. And I'm going to investigate that. And sometimes it's not wrong. Sometimes your model actually has an insight that you didn't have yourself. But fairly often, it is. And I think kind of what you learn is like, hey if there's something that bothers me, I want to go investigate that now and debug that now. Because the last thing you want is where all of a sudden, the answer you're putting out there in the world hinges on a mistake that you made. Cause you never know if you have so to speak, 1,000 lines of code and they all perform something differently. You never know when you get in a weird edge case where this one decision you made winds up being the difference between your having a good forecast and a bad one. In a defensible position and a indefensible one. So we definitely are quite diligent and careful. But it's also kind of knowing like, hey, where is an approximation good enough and where do I need more precision? Cause you could also drive yourself crazy in the other direction where you know, it doesn't matter if the answer is 91.2 versus 90. And so you can kind of go 91.2, three, four and it's like kind of A) false precision and B) not a good use of your time. So that's where I do still spend a lot of time is thinking about which problems are "solvable" or approachable with data and which ones aren't. And when they're not by the way, you're still allowed to report on them. We are a news organization so we do traditional reporting as well. And then kind of figuring out when do you need precision versus when is being pointed in the right direction good enough? >> I would love to get inside your brain and see how you operate on just like an everyday walking to Walgreens movement. It's like oh, if I cross the street in .2-- >> It's not, I mean-- >> Is it like maddening in there? >> No, not really. I mean, I'm like-- >> This is an honest question. >> If I'm looking for airfares, I'm a little more careful. But no, part of it's like you don't want to waste time on unimportant decisions, right? I will sometimes, if I can't decide what to eat at a restaurant, I'll flip a coin. If the chicken and the pasta both sound really good-- >> That's not high tech Nate. We want better. >> But that's the point, right? It's like both the chicken and the pasta are going to be really darn good, right? So I'm not going to waste my time trying to figure it out. I'm just going to have an arbitrary way to decide. >> Serious and business, how organizations in the last three to five years have just evolved with this data boom. How are you seeing it as from a consultant point of view? Do you think it's an exciting time? Do you think it's a you must act now time? >> I mean, we do know that you definitely see a lot of talent among the younger generation now. That so FiveThirtyEight has been at ESPN for four years now. And man, the quality of the interns we get has improved so much in four years. The quality of the kind of young hires that we make straight out of college has improved so much in four years. So you definitely do see a younger generation for which this is just part of their bloodstream and part of their DNA. And also, particular fields that we're interested in. So we're interested in people who have both a data and a journalism background. We're interested in people who have a visualization and a coding background. A lot of what we do is very much interactive graphics and so forth. And so we do see those skill sets coming into play a lot more. And so the kind of shortage of talent that had I think frankly been a problem for a long time, I'm optimistic based on the young people in our office, it's a little anecdotal but you can tell that there are so many more programs that are kind of teaching students the right set of skills that maybe weren't taught as much a few years ago. >> But when you're seeing these big organizations, ESPN as perfect example, moving more towards data and analytics than ever before. >> Yeah. >> You would say that's obviously true. >> Oh for sure. >> If you're not moving that direction, you're going to fall behind quickly. >> Yeah and the thing is, if you read my book or I guess people have a copy of the book. In some ways it's saying hey, there are lot of ways to screw up when you're using data. And we've built bad models. We've had models that were bad and got good results. Good models that got bad results and everything else. But the point is that the reason to be out in front of the problem is so you give yourself more runway to make errors and mistakes. And to learn kind of what works and what doesn't and which people to put on the problem. I sometimes do worry that a company says oh we need data. And everyone kind of agrees on that now. We need data science. Then they have some big test case. And they have a failure. And they maybe have a failure because they didn't know really how to use it well enough. But learning from that and iterating on that. And so by the time that you're on the third generation of kind of a problem that you're trying to solve, and you're watching everyone else make the mistake that you made five years ago, I mean, that's really powerful. But that doesn't mean that getting invested in it now, getting invested both in technology and the human capital side is important. >> Final question for you as we run out of time. 2018 beyond, what is your biggest project in terms of data gathering that you're working on? >> There's a midterm election coming up. That's a big thing for us. We're also doing a lot of work with NBA data. So for four years now, the NBA has been collecting player tracking data. So they have 3D cameras in every arena. So they can actually kind of quantify for example how fast a fast break is, for example. Or literally where a player is and where the ball is. For every NBA game now for the past four or five years. And there hasn't really been an overall metric of player value that's taken advantage of that. The teams do it. But in the NBA, the teams are a little bit ahead of journalists and analysts. So we're trying to have a really truly next generation stat. It's a lot of data. Sometimes I now more oversee things than I once did myself. And so you're parsing through many, many, many lines of code. But yeah, so we hope to have that out at some point in the next few months. >> Anything you've personally been passionate about that you've wanted to work on and kind of solve? >> I mean, the NBA thing, I am a pretty big basketball fan. >> You can do better than that. Come on, I want something real personal that you're like I got to crunch the numbers. >> You know, we tried to figure out where the best burrito in America was a few years ago. >> I'm going to end it there. >> Okay. >> Nate, thank you so much for joining us. It's been an absolute pleasure. Thank you. >> Cool, thank you. >> I thought we were going to chat World Series, you know. Burritos, important. I want to thank everybody here in our audience. Let's give him a big round of applause. >> [Nate] Thank you everyone. >> Perfect way to end the day. And for a replay of today's program, just head on over to ibm.com/dsforall. I'm Katie Linendoll. And this has been Data Science for All: It's a Whole New Game. Test one, two. One, two, three. Hi guys, I just want to quickly let you know as you're exiting. A few heads up. Downstairs right now there's going to be a meet and greet with Nate. And we're going to be doing that with clients and customers who are interested. So I would recommend before the game starts, and you lose Nate, head on downstairs. And also the gallery is open until eight p.m. with demos and activations. And tomorrow, make sure to come back too. Because we have exciting stuff. I'll be joining you as your host. And we're kicking off at nine a.m. So bye everybody, thank you so much. >> [Announcer] Ladies and gentlemen, thank you for attending this evening's webcast. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your name badge at the registration desk. Thank you. Also, please note there are two exits on the back of the room on either side of the room. Have a good evening. Ladies and gentlemen, the meet and greet will be on stage. Thank you.

Published Date : Nov 1 2017

SUMMARY :

Today the ability to extract value from data is becoming a shared mission. And for all of you during the program, I want to remind you to join that conversation on And when you and I chatted about it. And the scale and complexity of the data that organizations are having to deal with has It's challenging in the world of unmanageable. And they have to find a way. AI. And it's incredible that this buzz word is happening. And to get to an AI future, you have to lay a data foundation today. And four is you got to expand job roles in the organization. First pillar in this you just discussed. And now you get to where we are today. And if you don't have a strategy for how you acquire that and manage it, you're not going And the way I think about that is it's really about moving from static data repositories And we continue with the architecture. So you need a way to federate data across different environments. So we've laid out what you need for driving automation. And so when you think about the real use cases that are driving return on investment today, Let's go ahead and come back to something that you mentioned earlier because it's fascinating And so the new job roles is about how does everybody have data first in their mind? Everybody in the company has to be data literate. So overall, group effort, has to be a common goal, and we all need to be data literate But at the end of the day, it's kind of not an easy task. It's not easy but it's maybe not as big of a shift as you would think. It's interesting to hear you say essentially you need to train everyone though across the And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. And I've heard that the placement behind those jobs, people graduating with the MS is high. Let me get back to something else you touched on earlier because you mentioned that a number They produce a lot of the shows that I'm sure you watch Katie. And this is a good example. So they have to optimize every aspect of their business from marketing campaigns to promotions And so, as we talk to clients we think about how do you start down this path now, even It's analytics first to the data, not the other way around. We as a practice, we say you want to bring data to where the data sits. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. Female preferred, on the cover of Vogue. And how does it change everything? And while it's important to recognize this critical skill set, you can't just limit it And we call it clickers and coders. [Katie] I like that. And there's not a lot of things available today that do that. Because I hear you talking about the data scientists role and how it's critical to success, And my view is if you have the right platform, it enables the organization to collaborate. And every organization needs to think about what are the skills that are critical? Use this as your chance to reinvent IT. And I can tell you even personally being effected by how important the analysis is in working And think about if you don't do something. And now we're going to get to the fun hands on part of our story. And then how do you move analytics closer to your data? And in here I can see that JP Morgan is calling for a US dollar rebound in the second half But then where it gets interesting is you go to the bottom. data, his stock portfolios, and browsing behavior to build a model which can predict his affinity And so, as a financial adviser, you look at this and you say, all right, we know he loves And I want to do that by picking a auto stock which has got negative correlation with Ferrari. Cause you start clicking that and immediately we're getting instant answers of what's happening. And what I see here instantly is that Honda has got a negative correlation with Ferrari, As a financial adviser, you wouldn't think about federating data, machine learning, pretty And drive the machine learning into the appliance. And even score hundreds of customers for their affinities on a daily basis. And then you see when you deploy analytics next to your data, even a financial adviser, And as a data science leader or data scientist, you have a lot of the same concerns. But you guys each have so many unique roles in your business life. And just by looking at the demand of companies that wants us to help them go through this And I think the whole ROI of data is that you can now understand people's relationships Well you can have all the data in the world, and I think it speaks to, if you're not doing And I think that that's one of the things that customers are coming to us for, right? And Nir, this is something you work with a lot. And the companies that are not like that. Tricia, companies have to deal with data behind the firewall and in the new multi cloud And so that's why I think it's really important to understand that when you implement big And how are the clients, how are the users actually interacting with the system? And right now the way I see teams being set up inside companies is that they're creating But in order to actually see all of the RY behind the data, you also have to have a creative That's one of the things that we see a lot. So a lot of the training we do is sort of data engineers. And I think that's a very strong point when it comes to the data analysis side. And that's where you need the human element to come back in and say okay, look, you're And the people who are really great at providing that human intelligence are social scientists. the talent piece is actually the most important crucial hard to get. It may be to take folks internally who have a lot of that domain knowledge that you have And from data scientist to machine learner. And what I explain to them is look, you're still making decisions in the same way. And I mean, just to give you an example, we are partnering with one of the major cloud And what you're talking about with culture is really where I think we're talking about And I think that communication between the technical stakeholders and management You guys made this way too easy. I want to leave you with an opportunity to, anything you want to add to this conversation? I think one thing to conclude is to say that companies that are not data driven is And thank you guys again for joining us. And we're going to turn our attention to how you can deliver on what they're talking about And finally how you could build models anywhere and employ them close to where your data is. And thanks to Siva for taking us through it. You got to break it down for me cause I think we zoom out and see the big picture. And we saw some new capabilities that help companies avoid lock-in, where you can import And as a data scientist, you stop feeling like you're falling behind. We met backstage. And I go to you to talk about sports because-- And what it brings. And the reason being that sports consists of problems that have rules. And I was going to save the baseball question for later. Probably one of the best of all time. FiveThirtyEight has the Dodgers with a 60% chance of winning. So you have two teams that are about equal. It's like the first World Series in I think 56 years or something where you have two 100 And that you can be the best pitcher in the world, but guess what? And when does it ruin the sport? So we can talk at great length about what tools do you then apply when you have those And the reason being that A) he kind of knows how to position himself in the first place. And I imagine they're all different as well. But you really have seen a lot of breakthroughs in the last couple of years. You're known for your work in politics though. What was the most notable thing that came out of any of your predictions? And so, being aware of the limitations to some extent intrinsically in elections when It would be interesting to kind of peek back the curtain, understand how you operate but But you don't want to be inaccurate because that's your credibility. I think on average, speed is a little bit overrated in journalism. And there's got to be more time spent on stories if I can speak subjectively. And so we have people that come in, we hire most of our people actually from journalism. And so the kind of combination of needing, not having that much tolerance for mistakes, Because you do have to hit this balance. And so you try to hire well. And your perspective on that in general. But by the way, one thing that happens when you share your data or you share your thinking And you have a good intuition for hey, this looks a little bit out of line to me. And I think kind of what you learn is like, hey if there's something that bothers me, It's like oh, if I cross the street in .2-- I mean, I'm like-- But no, part of it's like you don't want to waste time on unimportant decisions, right? We want better. It's like both the chicken and the pasta are going to be really darn good, right? Serious and business, how organizations in the last three to five years have just And man, the quality of the interns we get has improved so much in four years. But when you're seeing these big organizations, ESPN as perfect example, moving more towards But the point is that the reason to be out in front of the problem is so you give yourself Final question for you as we run out of time. And so you're parsing through many, many, many lines of code. You can do better than that. You know, we tried to figure out where the best burrito in America was a few years Nate, thank you so much for joining us. I thought we were going to chat World Series, you know. And also the gallery is open until eight p.m. with demos and activations. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your

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Nir Kaldero, Galvanize | IBM Data Science For All


 

>> Announcer: Live from New York City, it's The Cube, covering IBM data science for all. Brought to you by IBM. >> Welcome back to data science for all. This is IBM's event here on the west side of Manhattan, here on The Cube. We're live, we'll be here all day, along with Dave Vallente, I'm John Walls Poor Dave had to put up with all that howling music at this hotel last night, kept him up 'til, all hours. >> Lots of fun here in the city. >> Yeah, yeah. >> All the crazies out last night. >> Yeah, but the headphones, they worked for ya. Glad to hear that. >> People are already dressed for Halloween, you know what I mean? >> John: Yes. >> In New York, you know what I mean? >> John: All year. >> All the time. >> John: All year. >> 365. >> Yeah. We have with us now the head of data science, and the VP at Galvanize, Nir Kaldero, and Nir, good to see you, sir. Thanks for being with us. We appreciate the time. >> Well of course, my pleasure. >> Tell us about Galvanize. I know you're heavily involved in education in terms of the tech community, but you've got corporate clients, you've got academic clients. You cover the waterfront, and I know data science is your baby. >> Nir: Right. >> But tell us a little bit about Galvanize and your mission there. >> Sure, so Galvanize is the learning community for technology. We provide the training in data science, data engineering, and also modern software engineering. We recently built a very large, fast growing enterprise corporate training department, where we basically help companies become digital, become nimble, and also very data driven, so they can actually go through this digital transformation, and survive in this fourth industrial revolution. We do it across all layers of the business, from the executives, to managers, to data scientists, and data analysts, and kind of transform and upscale all current skills to be modern, to be digital, so companies can actually go through this transformation. >> Hit on one of those items you talked about, data driven. >> Nir: Right. >> It seems like a no-brainer, right? That the more information you give me, the more analysis I can apply to it, the more I can put it in my business practice, the more money I make, the more my customers are happy. It's a lay up, right? >> Nir: It is. >> What is a data driven organization, then? Do you have to convince people that this is where they need to be today? >> Sometimes I need to convince them, but (laughs) anyway, so let's back up a little bit. We are in the midst of the fourth industrial revolution, and in order to survive in this fourth industrial revolution, companies need to become nimble, as I said, become agile, but most importantly become data driven, so the organization can actually best respond to all the predictions that are coming from this very sophisticated machine intelligence models. If the organization immediately can best respond to all of that, companies will be able to enhance the user experience, get insight about their customers, enhance performances, and et cetera, and we know that the winners in this revolution, in this era, will be companies who are very digital, that master the skills of becoming a data driven organization, and you know, we can talk more about the transformation, and what it consisted of. Do you want me to? >> John: Sure. >> Can I just ask you a question? This fourth wave, this is what, the cognitive machine wave? Or how would you describe it? >> Some people call it artificial intelligence. I think artificial intelligence is like big data, kind of like a buzz word. I think more appropriately, we should call it machine intelligence industrial revolution. >> Okay. I've got a lot of questions, but carry on. >> So hitting on that, so you see that as being a major era. >> Nir: It's a game changer. >> If you will, not just a chapter, but a major game changer. >> Nir: Yup. >> Why so? >> So, okay, I'll jump in again. Machines have always replaced man, people. >> John: The automation, right. >> Nir: To some extent. >> But certain machines have replaced certain human tasks, let's say that. >> Nir: Correct. >> But for the first time in history, this fourth era, machine's are replacing humans with cognitive tasks, and that scares a lot of people, because you look at the United States, the median income of the U.S. worker has dropped since 1999, from $55,000 to $52,000, and a lot of people believe it's sort of the hollowing out of that factor that we just mentioned. Education many believe is the answer. You know, Galvanize is an organization that plays a critical role in helping deal with that problem, does it not? >> So, as Mark Zuckerberg says, there is a lot of hate love relationship with A.I. People love it on one side, because they're excited about all the opportunities that can come from this utilization of machine intelligence, but many people actually are afraid from it. I read a survey a few weeks ago that says that 36% of the population thinks that A.I. will destroy humanity, and will conquer the world. That's a fact that's what people think. If I think it's going to happen? I don't think so. I highly believe that education is one of the pillars that can address this fear for machine intelligence, and you spoke a lot about jobs I talk about it forever, but just my belief is that machines can actually replace some of our responsibilities, right? Not necessarily take and replace the entire job. Let's talk about lawyers, right? Lawyers currently spend between 40% to 60% of the time writing contracts, or looking at previous cases. The machine can write a contract in two minutes, or look up millions of data points of previous cases in zero time. Why a lawyer today needs to spend 40% to 60% of the time on that? >> Billable hours, that's why. >> It is, so I don't think the machine will replace the job of the lawyer. I think in the future, the machine replaces some of the responsibilities, like auditing, or writing contracts, or looking at previous cases. >> Menial labor, if you will. >> Yes, but you know, for example, the machine is not that great right now with negotiations skills. So maybe in the future, the job of the lawyer will be mostly around negotiation skills, rather than writing contracts, et cetera, but yeah, you're absolutely right. There is a big fear in the market right now among executives, among people in the public. I think we should educate people about what is the true implications of machine intelligence in this fourth industrial revolution and era, and education is definitely one of those. >> Well, one of my favorite stories, when people bring up this topic, is when Gary Kasparov lost to the IBM super computer, Blue Jean, or whatever it's called. >> Nir: Yup. >> Instead of giving up, what he said is he started a competition, where he proved that humans and machines could beat the IBM super computer. So to this day has a competition where the best chess player in the world is a combination between humans and machines, and so it's that creativity. >> Nir: Imagination. >> Imagination, right, combinatorial effects of different technologies that education, hopefully, can help keep those either way. >> Look, I'm a big fan of neuroscience. I wish I did my PhD in neuroscience, but we are very, very far away from understanding how our brain works. Now to try to imitate the brain when we don't know how the brain works? We are very far away from being in a place where a machine can actually replicate, and really best respond like a human. We don't know how our brain works yet. So we need to do a lot of research on that before we actually really write a very strong, powerful machine intelligence model that can actually replace us as humans, and outbid us. We can speak about Jeopardy, and what's on, and we can speak about AlphaGo, it's a Google company that kind of outperformed the world champion. These are very specific tasks, right? Again, like the lawyer, the machines can write beautiful contracts with NLP, machines can look at millions and trillions of data and figure out what's the conclusion there, right? Or summarize text very fast, but not necessarily good in negotiation yet. >> So when you think about a digital business, to us a digital business is a business that uses data to differentiate, and serve customers, and maintain customers. So when you talk about data driven, it strikes me that when everybody's saying digital business, digital transformation, it's about a data transformation, how well they utilize data, and if you look at the bell curve of organizations, most are not. Everybody wants to be data driven, many say they are data driven. >> Right. >> Dave: Would you agree most are not? >> I will agree that most companies say that they are data driven, but actually they're not. I work with a lot of Fortune 500 companies on a daily basis. I meet their executives and functional leaders, and actually see their data, and business problems that they have. Most of them do tend to say that they are data driven, but truly just ask them if they put data and decisions in the same place, every time they have to make a decision, they don't do it. It's a habit that they don't yet have. Companies need to start investing in building what we say healthy data culture in order to enable and become data driven. Part of it is democratization of data, right? Currently what I see if lots of organizations actually open the data just for the analyst, or the marketers, people who kind of make decisions, that need to make decisions with data, but not throughout the entire organization. I know I always say that everyone in the organization makes decisions on a daily basis, from the barista, to the CEO, right? And the entirety of becoming data driven is that data can actually help us make better decisions on a daily basis, so how about democratizing the data to everyone? So everyone, from the barista, to the CEO, can actually make better decisions on a daily basis, and companies don't excel yet in doing it. Not every company is as digital as Amazon. Amazon, I think, is actually one of the most digital companies in the world, if you look at the digital index. Not everyone is Google or Facebook. Most companies want to be there, most companies understand that they will not be able to survive in this era if they will not become data driven, so it's a big problem. We try at Galvanize to address this problem from executive type of education, where we actually meet with the C-level executives in companies, and actually guide them through how to write their data strategy, how to think about prioritizing data investment, to actual implementation of that, and so far we are highly successful. We were able to make a big transformation in very large, important organizations. So I'm actually very proud of it. >> How long are these eras? Is it a century, or more? >> This fourth industrial? >> Yeah. >> Well it's hard to predict that, and I'm not a machine, or what's on it. (laughs) >> But certainly more than 50 years, would you say? Or maybe not, I don't know. >> I actually don't think so. I think it's going to be fast, and we're going to move to the next one pretty soon that will be even more, with more intelligence, with more data. >> So the reason I ask, is there was an article I saw and linked, and I haven't had time to read it, but it talked about the Four Horsemen, Amazon, Google, Facebook, and Apple, and it said they will all be out of business in 50 years. Now, I don't know, I think Apple probably has 50 years of cash flow in the bank, but then they said, the one, the author said, if I had to predict one that would survive, it would be Amazon, to your point, because they are so data driven. The premise, again I didn't read the whole thing, was that some new data driven, digital upstart will disrupt them. >> Yeah, and you know, companies like Amazon, and Alibaba lately, that try kind of like in a competition with Amazon about who is becoming more data driven, utilizing more machine intelligence, are the ones that invested in these capabilities many, many years ago. It's no that they started investing in it last year, or five years ago. We speak about 15 and 20 years ago. So companies who were really a pioneer, and invested very early on, will predict actually to survive in the future, and you know, very much align. >> Yeah, I'm going to touch on something. It might be a bridge too far, I don't know, but you talk about, Dave brought it up, about replacing human capital, right? Because of artificial intelligence. >> Nir: Yup. >> Is there a reluctance, perhaps, on behalf of executives to embrace that, because they are concerned about their own price? >> Nir: You should be in the room with me. (laughing) >> You provide data, but you also provide that capability to analyze, and make the best informed decision, and therefore, eliminate the human element of a C-suite executive that maybe they're not as necessary today, or tomorrow, as they were two years ago. >> So it is absolutely true, and there is a lot of fear in the room, especially when I show them robots, they freak out typically, (John and Dave laugh) but the fact is well known. Leaders who will not embrace these skills, and understanding, and will help the organization to become agile, nimble, and data driven, will not survive. They will be replaced. So on the one hand, they're afraid from it. On the other side, they see that if they will not actually do something, and take an action today, they might be replaced in the future. >> Where should organizations start? Hey, I want to be data driven. Where do I start? >> That's a good question. So data science, machine learning, is a top down initiative. It requires a lot of funding. It requires a change in culture and habits. So it has to start from the top. The journey has to start from executive, from educating and executive about what is data science, what is machine learning, how to prioritize investments in this field, how to build data driven culture, right? When we spoke about data driven, we mainly speaks about the culture aspect here, not specifically about the technical side of it. So it has to come from the top, leaders have to incorporate it in the organization, the have to give authority and power for people, they have to put the funding at first, and then, this is how it's beautiful, that you actually see it trickles down to the organization when they have a very powerful CEO that makes a decision, and moves the organization quickly to become data driven, make executives look at data every time they make a decision, get them into the habit. When people look up to executives, they try to do the same, and if my boss is an example for me, someone who is looking at data every time he is making a decision, ask the right questions, know how to prioritize, set the right goals for me, this helps me, and helps the organization better perform. >> Follow the leader, right? >> Yup. >> Follow the leader. >> Yup, follow the leader. >> Thanks for being with us. >> Nir: Of course, it's my pleasure. >> Pinned this interesting love hate thing that we have going on. >> We should address that. >> Right, right. That's the next segment, how about that? >> Nir Kaldero from Galvanize joining us here live on The Cube. Back with more from New York in just a bit.

Published Date : Nov 1 2017

SUMMARY :

Brought to you by IBM. the west side of Manhattan, Yeah, but the headphones, and the VP at Galvanize, Nir Kaldero, in terms of the tech community, and your mission there. from the executives, to managers, you talked about, data driven. the more analysis I can apply to it, We are in the midst of the I think artificial but carry on. so you see that as being a major era. If you will, not just a chapter, Machines have always replaced man, people. But certain machines have But for the first time of the pillars that can address of the responsibilities, the job of the lawyer will to the IBM super computer, and so it's that creativity. that education, hopefully, kind of outperformed the world champion. and if you look at the bell from the barista, to the CEO, right? and I'm not a machine, or what's on it. 50 years, would you say? I think it's going to be fast, the author said, if I had to are the ones that invested in Yeah, I'm going to touch on something. Nir: You should be in the room with me. and make the best informed decision, So on the one hand, Hey, I want to be data driven. the have to give authority that we have going on. That's the next segment, how about that? New York in just a bit.

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