(upbeat music) >> Hi everyone. Welcome back to this Cube conversation here in Palo Alto, California. I'm John Furrier, host of "theCUBE." Got a great conversation around Cloud Native, Cloud Native Journey, how enterprises are looking at Cloud Native and putting it all together. And it comes down to operations, developer productivity, and security. It's the hottest topic in technology. We got Chris Jones here in the studio, director of Product Management for Platform9. Chris, thanks for coming in. >> Hey, thanks. >> So when we always chat about, when we're at KubeCon. KubeConEU is coming up and in a few, in a few months, the number one conversation is developer productivity. And the developers are driving all the standards. It's interesting to see how they just throw everything out there and whatever gets adopted ends up becoming the standard, not the old school way of kind of getting stuff done. So that's cool. Security Kubernetes and Containers are all kind of now that next level. So you're starting to see the early adopters moving to the mainstream. Enterprises, a variety of different approaches. You guys are at the center of this. We've had a couple conversations with your CEO and your tech team over there. What are you seeing? You're building the products. What's the core product focus right now for Platform9? What are you guys aiming for? >> The core is that blend of enabling your infrastructure and PlatformOps or DevOps teams to be able to go fast and run in a stable environment, but at the same time enable developers. We don't want people going back to what I've been calling Shadow IT 2.0. It's, hey, I've been told to do something. I kicked off this Container initiative. I need to run my software somewhere. I'm just going to go figure it out. We want to keep those people productive. At the same time we want to enable velocity for our operations teams, be it PlatformOps or DevOps. >> Take us through in your mind and how you see the industry rolling out this Cloud Native journey. Where do you see customers out there? Because DevOps have been around, DevSecOps is rocking, you're seeing AI, hot trend now. Developers are still in charge. Is there a change to the infrastructure of how developers get their coding done and the infrastructure, setting up the DevOps is key, but when you add the Cloud Native journey for an enterprise, what changes? What is the, what is the, I guess what is the Cloud Native journey for an enterprise these days? >> The Cloud Native journey or the change? When- >> Let's start with the, let's start with what they want to do. What's the goal and then how does that happen? >> I think the goal is that promise land. Increased resiliency, better scalability, and overall reduced costs. I've gone from physical to virtual that gave me a higher level of density, packing of resources. I'm moving to Containers. I'm removing that OS layer again. I'm getting a better density again, but all of a sudden I'm running Kubernetes. What does that, what does that fundamentally do to my operations? Does it magically give me scalability and resiliency? Or do I need to change what I'm running and how it's running so it fits that infrastructure? And that's the reality, is you can't just take a Container and drop it into Kubernetes and say, hey, I'm now Cloud Native. I've got reduced cost, or I've got better resiliency. There's things that your engineering teams need to do to make sure that application is a Cloud Native. And then there's what I think is one of the largest shifts of virtual machines to containers. When I was in the world of application performance monitoring, we would see customers saying, well, my engineering team have this Java app, and they said it needs a VM with 12 gig of RAM and eight cores, and that's what we gave it. But it's running slow. I'm working with the application team and you can see it's running slow. And they're like, well, it's got all of its resources. One of those nice features of virtualization is over provisioning. So the infrastructure team would say, well, we gave it, we gave it all a RAM it needed. And what's wrong with that being over provisioned? It's like, well, Java expects that RAM to be there. Now all of a sudden, when you move to the world of containers, what we've got is that's not a set resource limit, really is like it used to be in a VM, right? When you set it for a container, your application teams really need to be paying attention to your resource limits and constraints within the world of Kubernetes. So instead of just being able to say, hey, I'm throwing over the fence and now it's just going to run on a VM, and that VMs got everything it needs. It's now really running on more, much more of a shared infrastructure where limits and constraints are going to impact the neighbors. They are going to impact who's making that decision around resourcing. Because that Kubernetes concept of over provisioning and the virtualization concept of over provisioning are not the same. So when I look at this problem, it's like, well, what changed? Well, I'll do my scale tests as an application developer and tester, and I'd see what resources it needs. I asked for that in the VM, that sets the high watermark, job's done. Well, Kubernetes, it's no longer a VM, it's a Kubernetes manifest. And well, who owns that? Who's writing it? Who's setting those limits? To me, that should be the application team. But then when it goes into operations world, they're like, well, that's now us. Can we change those? So it's that amalgamation of the two that is saying, I'm a developer. I used to pay attention, but now I need to pay attention. And an infrastructure person saying, I used to just give 'em what they wanted, but now I really need to know what they've wanted, because it's going to potentially have a catastrophic impact on what I'm running. >> So what's the impact for the developer? Because, infrastructure's code is what everybody wants. The developer just wants to get the code going and they got to pay attention to all these things, or don't they? Is that where you guys come in? How do you guys see the problem? Actually scope the problem that you guys solve? 'Cause I think you're getting at I think the core issue here, which is, I've got Kubernetes, I've got containers, I've got developer productivity that I want to focus on. What's the problem that you guys solve? >> Platform operation teams that are adopting Cloud Native in their environment, they've got that steep learning curve of Kubernetes plus this fundamental change of how an app runs. What we're doing is taking away the burden of needing to operate and run Kubernetes and giving them the choice of the flexibility of infrastructure and location. Be that an air gap environment like a, let's say a telco provider that needs to run a containerized network function and containerized workloads for 5G. That's one thing that we can deploy and achieve in a completely inaccessible environment all the way through to Platform9 running traditionally as SaaS, as we were born, that's remotely managing and controlling your Kubernetes environments on-premise AWS. That hybrid cloud experience that could be also Bare Metal, but it's our platform running your environments with our support there, 24 by seven, that's proactively reaching out. So it's removing a lot of that burden and the complications that come along with operating the environment and standing it up, which means all of a sudden your DevOps and platform operations teams can go and work with your engineers and application developers and say, hey, let's get, let's focus on the stuff that, that we need to be focused on, which is running our business and providing a service to our customers. Not figuring out how to upgrade a Kubernetes cluster, add new nodes, and configure all of the low level. >> I mean there are, that's operations that just needs to work. And sounds like as they get into the Cloud Native kind of ops, there's a lot of stuff that kind of goes wrong. Or you go, oops, what do we buy into? Because the CIOs, let's go, let's go Cloud Native. We want to, we got to get set up for the future. We're going to be Cloud Native, not just lift and shift and we're going to actually build it out right. Okay, that sounds good. And when we have to actually get done. >> Chris: Yeah. >> You got to spin things up and stand up the infrastructure. What specifically use case do you guys see that emerges for Platform9 when people call you up and you go talk to customers and prospects? What's the one thing or use case or cases that you guys see that you guys solve the best? >> So I think one of the, one of the, I guess new use cases that are coming up now, everyone's talking about economic pressures. I think the, the tap blows open, just get it done. CIO is saying let's modernize, let's use the cloud. Now all of a sudden they're recognizing, well wait, we're spending a lot of money now. We've opened that tap all the way, what do we do? So now they're looking at ways to control that spend. So we're seeing that as a big emerging trend. What we're also sort of seeing is people looking at their data centers and saying, well, I've got this huge legacy environment that's running a hypervisor. It's running VMs. Can we still actually do what we need to do? Can we modernize? Can we start this Cloud Native journey without leaving our data centers, our co-locations? Or if I do want to reduce costs, is that that thing that says maybe I'm repatriating or doing a reverse migration? Do I have to go back to my data center or are there other alternatives? And we're seeing that trend a lot. And our roadmap and what we have in the product today was specifically built to handle those, those occurrences. So we brought in KubeVirt in terms of virtualization. We have a long legacy doing OpenStack and private clouds. And we've worked with a lot of those users and customers that we have and asked the questions, what's important? And today, when we look at the world of Cloud Native, you can run virtualization within Kubernetes. So you can, instead of running two separate platforms, you can have one. So all of a sudden, if you're looking to modernize, you can start on that new infrastructure stack that can run anywhere, Kubernetes, and you can start bringing VMs over there as you are containerizing at the same time. So now you can keep your application operations in one environment. And this also helps if you're trying to reduce costs. If you really are saying, we put that Dev environment in AWS, we've got a huge amount of velocity out of it now, can we do that elsewhere? Is there a co-location we can go to? Is there a provider that we can go to where we can run that infrastructure or run the Kubernetes, but not have to run the infrastructure? >> It's going to be interesting too, when you see the Edge come online, you start, we've got Mobile World Congress coming up, KubeCon events we're going to be at, the conversation is not just about public cloud. And you guys obviously solve a lot of do-it-yourself implementation hassles that emerge when people try to kind of stand up their own environment. And we hear from developers consistency between code, managing new updates, making sure everything is all solid so they can go fast. That's the goal. And that, and then people can get standardized on that. But as you get public cloud and do it yourself, kind of brings up like, okay, there's some gaps there as the architecture changes to be more distributed computing, Edge, on-premises cloud, it's cloud operations. So that's cool for DevOps and Cloud Native. How do you guys differentiate from say, some the public cloud opportunities and the folks who are doing it themselves? How do you guys fit in that world and what's the pitch or what's the story? >> The fit that we look at is that third alternative. Let's get your team focused on what's high value to your business and let us deliver that public cloud experience on your infrastructure or in the public cloud, which gives you that ability to still be flexible if you want to make choices to run consistently for your developers in two different locations. So as I touched on earlier, instead of saying go figure out Kubernetes, how do you upgrade a hundred worker nodes in place upgrade. We've solved that problem. That's what we do every single day of the week. Don't go and try to figure out how to upgrade a cluster and then upgrade all of the, what I call Kubernetes friends, your core DNSs, your metrics server, your Kubernetes dashboard. These are all things that we package, we test, we version. So when you click upgrade, we've already handled that entire process. So it's saying don't have your team focused on that lower level piece of work. Get them focused on what is important, which is your business services. >> Yeah, the infrastructure and getting that stood up. I mean, I think the thing that's interesting, if you look at the market right now, you mentioned cost savings and recovery, obviously kind of a recession. I mean, people are tightening their belts for sure. I don't think the digital transformation and Cloud Native spend is going to plummet. It's going to probably be on hold and be squeezed a little bit. But to your point, people are refactoring looking at how to get the best out of what they got. It's not just open the tap of spend the cash like it used to be. Yeah, a couple months, even a couple years ago. So okay, I get that. But then you look at the what's coming, AI. You're seeing all the new data infrastructure that's coming. The containers, Kubernetes stuff, got to get stood up pretty quickly and it's got to be reliable. So to your point, the teams need to get done with this and move on to the next thing. >> Chris: Yeah, yeah, yeah. >> 'Cause there's more coming. I mean, there's a lot coming for the apps that are building in Data Native, AI-Native, Cloud Native. So it seems that this Kubernetes thing needs to get solved. Is that kind of what you guys are focused on right now? >> So, I mean to use a customer, we have a customer that's in AI/ML and they run their platform at customer sites and that's hardware bound. You can't run AI machine learning on anything anywhere. Well, with Platform9 they can. So we're enabling them to deliver services into their customers that's running their AI/ML platform in their customer's data centers anywhere in the world on hardware that is purpose-built for running that workload. They're not Kubernetes experts. That's what we are. We're bringing them that ability to focus on what's important and just delivering their business services whilst they're enabling our team. And our 24 by seven proactive management are always on assurance to keep that up and running for them. So when something goes bump at the night at 2:00am, our guys get woken up. They're the ones that are reaching out to the customer saying, your environments have a problem, we're taking these actions to fix it. Obviously sometimes, especially if it is running on Bare Metal, there's things you can't do remotely. So you might need someone to go and do that. But even when that happens, you're not by yourself. You're not sitting there like I did when I worked for a bank in one of my first jobs, three o'clock in the morning saying, wow, our end of day processing is stuck. Who else am I waking up? Right? >> Exactly, yeah. Got to get that cash going. But this is a great use case. I want to get to the customer. What do some of the successful customers say to you for the folks watching that aren't yet a customer of Platform9, what are some of the accolades and comments or anecdotes that you guys hear from customers that you have? >> It just works, which I think is probably one of the best ones you can get. Customers coming back and being able to show to their business that they've delivered growth, like business growth and productivity growth and keeping their organization size the same. So we started on our containerization journey. We went to Kubernetes. We've deployed all these new workloads and our operations team is still six people. We're doing way more with growth less, and I think that's also talking to the strength that we're bringing, 'cause we're, we're augmenting that team. They're spending less time on the really low level stuff and automating a lot of the growth activity that's involved. So when it comes to being able to grow their business, they can just focus on that, not- >> Well you guys do the heavy lifting, keep on top of the Kubernetes, make sure that all the versions are all done. Everything's stable and consistent so they can go on and do the build out and provide their services. That seems to be what you guys are best at. >> Correct, correct. >> And so what's on the roadmap? You have the product, direct product management, you get the keys to the kingdom. What is, what is the focus? What's your focus right now? Obviously Kubernetes is growing up, Containers. We've been hearing a lot at the last KubeCon about the security containers is getting better. You've seen verification, a lot more standards around some things. What are you focused on right now for at a product over there? >> Edge is a really big focus for us. And I think in Edge you can look at it in two ways. The mantra that I drive is Edge must be remote. If you can't do something remotely at the Edge, you are using a human being, that's not Edge. Our Edge management capabilities and being in the market for over two years are a hundred percent remote. You want to stand up a store, you just ship the server in there, it gets racked, the rest of it's remote. Imagine a store manager in, I don't know, KFC, just plugging in the server, putting in the ethernet cable, pressing the power button. The rest of all that provisioning for that Cloud Native stack, Kubernetes, KubeVirt for virtualization is done remotely. So we're continuing to focus on that. The next piece that is related to that is allowing people to run Platform9 SaaS in their data centers. So we do ag app today and we've had a really strong focus on telecommunications and the containerized network functions that come along with that. So this next piece is saying, we're bringing what we run as SaaS into your data center, so then you can run it. 'Cause there are many people out there that are saying, we want these capabilities and we want everything that the Platform9 control plane brings and simplifies. But unfortunately, regulatory compliance reasons means that we can't leverage SaaS. So they might be using a cloud, but they're saying that's still our infrastructure. We're still closed that network down, or they're still on-prem. So they're two big priorities for us this year. And that on-premise experiences is paramount, even to the point that we will be delivering a way that when you run an on-premise, you can still say, wait a second, well I can send outbound alerts to Platform9. So their support team can still be proactively helping me as much as they could, even though I'm running Platform9s control plane. So it's sort of giving that blend of two experiences. They're big, they're big priorities. And the third pillar is all around virtualization. It's saying if you have economic pressures, then I think it's important to look at what you're spending today and realistically say, can that be reduced? And I think hypervisors and virtualization is something that should be looked at, because if you can actually reduce that spend, you can bring in some modernization at the same time. Let's take some of those nos that exist that are two years into their five year hardware life cycle. Let's turn that into a Cloud Native environment, which is enabling your modernization in place. It's giving your engineers and application developers the new toys, the new experiences, and then you can start running some of those virtualized workloads with KubeVirt, there. So you're reducing cost and you're modernizing at the same time with your existing infrastructure. >> You know Chris, the topic of this content series that we're doing with you guys is finding the right path, trusting the right path to Cloud Native. What does that mean? I mean, if you had to kind of summarize that phrase, trusting the right path to Cloud Native, what does that mean? It mean in terms of architecture, is it deployment? Is it operations? What's the underlying main theme of that quote? What's the, what's? How would you talk to a customer and say, what does that mean if someone said, "Hey, what does that right path mean?" >> I think the right path means focusing on what you should be focusing on. I know I've said it a hundred times, but if your entire operations team is trying to figure out the nuts and bolts of Kubernetes and getting three months into a journey and discovering, ah, I need Metrics Server to make something function. I want to use Horizontal Pod Autoscaler or Vertical Pod Autoscaler and I need this other thing, now I need to manage that. That's not the right path. That's literally learning what other people have been learning for the last five, seven years that have been focused on Kubernetes solely. So the why- >> There's been a lot of grind. People have been grinding it out. I mean, that's what you're talking about here. They've been standing up the, when Kubernetes started, it was all the promise. >> Chris: Yep. >> And essentially manually kind of getting in in the weeds and configuring it. Now it's matured up. They want stability. >> Chris: Yeah. >> Not everyone can get down and dirty with Kubernetes. It's not something that people want to generally do unless you're totally into it, right? Like I mean, I mean ops teams, I mean, yeah. You know what I mean? It's not like it's heavy lifting. Yeah, it's important. Just got to get it going. >> Yeah, I mean if you're deploying with Platform9, your Ops teams can tinker to their hearts content. We're completely compliant upstream Kubernetes. You can go and change an API server flag, let's go and mess with the scheduler, because we want to. You can still do that, but don't, don't have your team investing in all this time to figure it out. It's been figured out. >> John: Got it. >> Get them focused on enabling velocity for your business. >> So it's not build, but run. >> Chris: Correct? >> Or run Kubernetes, not necessarily figure out how to kind of get it all, consume it out. >> You know we've talked to a lot of customers out there that are saying, "I want to be able to deliver a service to my users." Our response is, "Cool, let us run it. You consume it, therefore deliver it." And we're solving that in one hit versus figuring out how to first run it, then operate it, then turn that into a consumable service. >> So the alternative Platform9 is what? They got to do it themselves or use the Cloud or what's the, what's the alternative for the customer for not using Platform9? Hiring more people to kind of work on it? What's the? >> People, building that kind of PaaS experience? Something that I've been very passionate about for the past year is looking at that world of sort of GitOps and what that means. And if you go out there and you sort of start asking the question what's happening? Just generally with Kubernetes as well and GitOps in that scope, then you'll hear some people saying, well, I'm making it PaaS, because Kubernetes is too complicated for my developers and we need to give them something. There's some great material out there from the likes of Intuit and Adobe where for two big contributors to Argo and the Argo projects, they almost have, well they do have, different experiences. One is saying, we went down the PaaS route and it failed. The other one is saying, well we've built a really stable PaaS and it's working. What are they trying to do? They're trying to deliver an outcome to make it easy to use and consume Kubernetes. So you could go out there and say, hey, I'm going to build a Kubernetes cluster. Sounds like Argo CD is a great way to expose that to my developers so they can use Kubernetes without having to use Kubernetes and start automating things. That is an approach, but you're going to be going completely open source and you're going to have to bring in all the individual components, or you could just lay that, lay it down, and consume it as a service and not have to- >> And mentioned to it. They were the ones who kind of brought that into the open. >> They did. Inuit is the primary contributor to the Argo set of products. >> How has that been received in the market? I mean, they had the event at the Computer History Museum last fall. What's the momentum there? What's the big takeaway from that project? >> Growth. To me, growth. I mean go and track the stars on that one. It's just, it's growth. It's unlocking machine learning. Argo workflows can do more than just make things happen. Argo CD I think the approach they're taking is, hey let's make this simple to use, which I think can be lost. And I think credit where credit's due, they're really pushing to bring in a lot of capabilities to make it easier to work with applications and microservices on Kubernetes. It's not just that, hey, here's a GitOps tool. It can take something from a Git repo and deploy it and maybe prioritize it and help you scale your operations from that perspective. It's taking a step back and saying, well how did we get to production in the first place? And what can be done down there to help as well? I think it's growth expansion of features. They had a huge release just come out in, I think it was 2.6, that brought in things that as a product manager that I don't often look at like really deep technical things and say wow, that's powerful. But they have, they've got some great features in that release that really do solve real problems. >> And as the product, as the product person, who's the target buyer for you? Who's the customer? Who's making that? And you got decision maker, influencer, and recommender. Take us through the customer persona for you guys. >> So that Platform Ops, DevOps space, right, the people that need to be delivering Containers as a service out to their organization. But then it's also important to say, well who else are our primary users? And that's developers, engineers, right? They shouldn't have to say, oh well I have access to a Kubernetes cluster. Do I have to use kubectl or do I need to go find some other tool? No, they can just log to Platform9. It's integrated with your enterprise id. >> They're the end customer at the end of the day, they're the user. >> Yeah, yeah. They can log in. And they can see the clusters you've given them access to as a Platform Ops Administrator. >> So job well done for you guys. And your mind is the developers are moving 'em fast, coding and happy. >> Chris: Yeah, yeah. >> And and from a customer standpoint, you reduce the maintenance cost, because you keep the Ops smoother, so you got efficiency and maintenance costs kind of reduced or is that kind of the benefits? >> Yeah, yep, yeah. And at two o'clock in the morning when things go inevitably wrong, they're not there by themselves, and we're proactively working with them. >> And that's the uptime issue. >> That is the uptime issue. And Cloud doesn't solve that, right? Everyone experienced that Clouds can go down, entire regions can go offline. That's happened to all Cloud providers. And what do you do then? Kubernetes isn't your recovery plan. It's part of it, right, but it's that piece. >> You know Chris, to wrap up this interview, I will say that "theCUBE" is 12 years old now. We've been to OpenStack early days. We had you guys on when we were covering OpenStack and now Cloud has just been booming. You got AI around the corner, AI Ops, now you got all this new data infrastructure, it's just amazing Cloud growth, Cloud Native, Security Native, Cloud Native, Data Native, AI Native. It's going to be all, this is the new app environment, but there's also existing infrastructure. So going back to OpenStack, rolling our own cloud, building your own cloud, building infrastructure cloud, in a cloud way, is what the pioneers have done. I mean this is what we're at. Now we're at this scale next level, abstracted away and make it operational. It seems to be the key focus. We look at CNCF at KubeCon and what they're doing with the cloud SecurityCon, it's all about operations. >> Chris: Yep, right. >> Ops and you know, that's going to sound counterintuitive 'cause it's a developer open source environment, but you're starting to see that Ops focus in a good way. >> Chris: Yeah, yeah, yeah. >> Infrastructure as code way. >> Chris: Yep. >> What's your reaction to that? How would you summarize where we are in the industry relative to, am I getting, am I getting it right there? Is that the right view? What am I missing? What's the current state of the next level, NextGen infrastructure? >> It's a good question. When I think back to sort of late 2019, I sort of had this aha moment as I saw what really truly is delivering infrastructure as code happening at Platform9. There's an open source project Ironic, which is now also available within Kubernetes that is Metal Kubed that automates Bare Metal as code, which means you can go from an empty server, lay down your operating system, lay down Kubernetes, and you've just done everything delivered to your customer as code with a Cloud Native platform. That to me was sort of the biggest realization that I had as I was moving into this industry was, wait, it's there. This can be done. And the evolution of tooling and operations is getting to the point where that can be achieved and it's focused on by a number of different open source projects. Not just Ironic and and Metal Kubed, but that's a huge win. That is truly getting your infrastructure. >> John: That's an inflection point, really. >> Yeah. >> If you think about it, 'cause that's one of the problems. We had with the Bare Metal piece was the automation and also making it Cloud Ops, cloud operations. >> Right, yeah. I mean, one of the things that I think Ironic did really well was saying let's just treat that piece of Bare Metal like a Cloud VM or an instance. If you got a problem with it, just give the person using it or whatever's using it, a new one and reimage it. Just tell it to reimage itself and it'll just (snaps fingers) go. You can do self-service with it. In Platform9, if you log in to our SaaS Ironic, you can go and say, I want that physical server to myself, because I've got a giant workload, or let's turn it into a Kubernetes cluster. That whole thing is automated. To me that's infrastructure as code. I think one of the other important things that's happening at the same time is we're seeing GitOps, we're seeing things like Terraform. I think it's important for organizations to look at what they have and ask, am I using tools that are fit for tomorrow or am I using tools that are yesterday's tools to solve tomorrow's problems? And when especially it comes to modernizing infrastructure as code, I think that's a big piece to look at. >> Do you see Terraform as old or new? >> I see Terraform as old. It's a fantastic tool, capable of many great things and it can work with basically every single provider out there on the planet. It is able to do things. Is it best fit to run in a GitOps methodology? I don't think it is quite at that point. In fact, if you went and looked at Flux, Flux has ways that make Terraform GitOps compliant, which is absolutely fantastic. It's using two tools, the best of breeds, which is solving that tomorrow problem with tomorrow solutions. >> Is the new solutions old versus new. I like this old way, new way. I mean, Terraform is not that old and it's been around for about eight years or so, whatever. But HashiCorp is doing a great job with that. I mean, so okay with Terraform, what's the new address? Is it more complex environments? Because Terraform made sense when you had basic DevOps, but now it sounds like there's a whole another level of complexity. >> I got to say. >> New tools. >> That kind of amalgamation of that application into infrastructure. Now my app team is paying way more attention to that manifest file, which is what GitOps is trying to solve. Let's templatize things. Let's version control our manifest, be it helm, customize, or just a straight up Kubernetes manifest file, plain and boring. Let's get that version controlled. Let's make sure that we know what is there, why it was changed. Let's get some auditability and things like that. And then let's get that deployment all automated. So that's predicated on the cluster existing. Well why can't we do the same thing with the cluster, the inception problem. So even if you're in public cloud, the question is like, well what's calling that API to call that thing to happen? Where is that file living? How well can I manage that in a large team? Oh my God, something just changed. Who changed it? Where is that file? And I think that's one of big, the big pieces to be sold. >> Yeah, and you talk about Edge too and on-premises. I think one of the things I'm observing and certainly when DevOps was rocking and rolling and infrastructures code was like the real push, it was pretty much the public cloud, right? >> Chris: Yep. >> And you did Cloud Native and you had stuff on-premises. Yeah you did some lifting and shifting in the cloud, but the cool stuff was going in the public cloud and you ran DevOps. Okay, now you got on-premise cloud operation and Edge. Is that the new DevOps? I mean 'cause what you're kind of getting at with old new, old new Terraform example is an interesting point, because you're pointing out potentially that that was good DevOps back in the day or it still is. >> Chris: It is, I was going to say. >> But depending on how you define what DevOps is. So if you say, I got the new DevOps with public on-premise and Edge, that's just not all public cloud, that's essentially distributed Cloud Native. >> Correct. Is that the new DevOps in your mind or is that? How would you, or is that oversimplifying it? >> Or is that that term where everyone's saying Platform Ops, right? Has it shifted? >> Well you bring up a good point about Terraform. I mean Terraform is well proven. People love it. It's got great use cases and now there seems to be new things happening. We call things like super cloud emerging, which is multicloud and abstraction layers. So you're starting to see stuff being abstracted away for the benefits of moving to the next level, so teams don't get stuck doing the same old thing. They can move on. Like what you guys are doing with Platform9 is providing a service so that teams don't have to do it. >> Correct, yeah. >> That makes a lot of sense, So you just, now it's running and then they move on to the next thing. >> Chris: Yeah, right. >> So what is that next thing? >> I think Edge is a big part of that next thing. The propensity for someone to put up with a delay, I think it's gone. For some reason, we've all become fairly short-tempered, Short fused. You know, I click the button, it should happen now, type people. And for better or worse, hopefully it gets better and we all become a bit more patient. But how do I get more effective and efficient at delivering that to that really demanding- >> I think you bring up a great point. I mean, it's not just people are getting short-tempered. I think it's more of applications are being deployed faster, security is more exposed if they don't see things quicker. You got data now infrastructure scaling up massively. So, there's a double-edged swords to scale. >> Chris: Yeah, yeah. I mean, maintenance, downtime, uptime, security. So yeah, I think there's a tension around, and one hand enthusiasm around pushing a lot of code and new apps. But is the confidence truly there? It's interesting one little, (snaps finger) supply chain software, look at Container Security for instance. >> Yeah, yeah. It's big. I mean it was codified. >> Do you agree that people, that's kind of an issue right now. >> Yeah, and it was, I mean even the supply chain has been codified by the US federal government saying there's things we need to improve. We don't want to see software being a point of vulnerability, and software includes that whole process of getting it to a running point. >> It's funny you mentioned remote and one of the thing things that you're passionate about, certainly Edge has to be remote. You don't want to roll a truck or labor at the Edge. But I was doing a conversation with, at Rebars last year about space. It's hard to do brake fix on space. It's hard to do a, to roll a someone to configure satellite, right? Right? >> Chris: Yeah. >> So Kubernetes is in space. We're seeing a lot of Cloud Native stuff in apps, in space, so just an example. This highlights the fact that it's got to be automated. Is there a machine learning AI angle with all this ChatGPT talk going on? You see all the AI going the next level. Some pretty cool stuff and it's only, I know it's the beginning, but I've heard people using some of the new machine learning, large language models, large foundational models in areas I've never heard of. Machine learning and data centers, machine learning and configuration management, a lot of different ways. How do you see as the product person, you incorporating the AI piece into the products for Platform9? >> I think that's a lot about looking at the telemetry and the information that we get back and to use one of those like old idle terms, that continuous improvement loop to feed it back in. And I think that's really where machine learning to start with comes into effect. As we run across all these customers, our system that helps at two o'clock in the morning has that telemetry, it's got that data. We can see what's changing and what's happening. So it's writing the right algorithms, creating the right machine learning to- >> So training will work for you guys. You have enough data and the telemetry to do get that training data. >> Yeah, obviously there's a lot of investment required to get there, but that is something that ultimately that could be achieved with what we see in operating people's environments. >> Great. Chris, great to have you here in the studio. Going wide ranging conversation on Kubernetes and Platform9. I guess my final question would be how do you look at the next five years out there? Because you got to run the product management, you got to have that 20 mile steer, you got to look at the customers, you got to look at what's going on in the engineering and you got to kind of have that arc. This is the right path kind of view. What's the five year arc look like for you guys? How do you see this playing out? 'Cause KubeCon is coming up and we're you seeing Kubernetes kind of break away with security? They had, they didn't call it KubeCon Security, they call it CloudNativeSecurityCon, they just had in Seattle inaugural events seemed to go well. So security is kind of breaking out and you got Kubernetes. It's getting bigger. Certainly not going away, but what's your five year arc of of how Platform9 and Kubernetes and Ops evolve? >> It's to stay on that theme, it's focusing on what is most important to our users and getting them to a point where they can just consume it, so they're not having to operate it. So it's finding those big items and bringing that into our platform. It's something that's consumable, that's just taken care of, that's tested with each release. So it's simplifying operations more and more. We've always said freedom in cloud computing. Well we started on, we started on OpenStack and made that simple. Stable, easy, you just have it, it works. We're doing that with Kubernetes. We're expanding out that user, right, we're saying bring your developers in, they can download their Kube conflict. They can see those Containers that are running there. They can access the events, the log files. They can log in and build a VM using KubeVirt. They're self servicing. So it's alleviating pressures off of the Ops team, removing the help desk systems that people still seem to rely on. So it's like what comes into that field that is the next biggest issue? Is it things like CI/CD? Is it simplifying GitOps? Is it bringing in security capabilities to talk to that? Or is that a piece that is a best of breed? Is there a reason that it's been spun out to its own conference? Is this something that deserves a focus that should be a specialized capability instead of tooling and vendors that we work with, that we partner with, that could be brought in as a service. I think it's looking at those trends and making sure that what we bring in has the biggest impact to our users. >> That's awesome. Thanks for coming in. I'll give you the last word. Put a plug in for Platform9 for the people who are watching. What should they know about Platform9 that they might not know about it or what should? When should they call you guys and when should they engage? Take a take a minute to give the plug. >> The plug. I think it's, if your operations team is focused on building Kubernetes, stop. That shouldn't be the cloud. That shouldn't be in the Edge, that shouldn't be at the data center. They should be consuming it. If your engineering teams are all trying different ways and doing different things to use and consume Cloud Native services and Kubernetes, they shouldn't be. You want consistency. That's how you get economies of scale. Provide them with a simple platform that's integrated with all of your enterprise identity where they can just start consuming instead of having to solve these problems themselves. It's those, it's those two personas, right? Where the problems manifest. What are my operations teams doing, and are they delivering to my company or are they building infrastructure again? And are my engineers sprinting or crawling? 'Cause if they're not sprinting, you should be asked the question, do I have the right Cloud Native tooling in my environment and how can I get them back? >> I think it's developer productivity, uptime, security are the tell signs. You get that done. That's the goal of what you guys are doing, your mission. >> Chris: Yep. >> Great to have you on, Chris. Thanks for coming on. Appreciate it. >> Chris: Thanks very much. 0 Okay, this is "theCUBE" here, finding the right path to Cloud Native. I'm John Furrier, host of "theCUBE." Thanks for watching. (upbeat music)

(gentle music intro) >> Okay, we're back. We're live here at theCUBE and at VMworld, VMware Explore, formally VMworld. I'm John Furrier with Dave Vellante. Three days of wall to wall coverage, we've got Vittorio Viarengo, the vice president of Cross-Cloud Services at VMware. Vittorio, great to see you, and thanks for coming on theCUBE right after your keynote. I can't get that off my tongue, VMworld. 12 years of CUBE coverage. This is the first year of VMware Explore, formerly VMworld. Raghu said in his keynote, he explained the VMworld community now with multi-clouds that you're in charge of at VMworld, VMware, is now the Explore brand's going to explore the multi-cloud, that's a big part of Raghu's vision and VMware. You're driving it and you are on the stage just now. What's, what's going on? >> Yeah, what I said at my keynote note is that our customers have been the explorer of IT, new IT frontier, always challenging the status quo. And we've been, our legendary engineering team, been behind the scenes, providing them with the tools of the technology to be successful in that journey to the private cloud. And Kelsey said it. What we built was the foundation for the cloud. And now it's time to start a new journey in the multi-cloud. >> Now, one of the things that we heard today clearly was: multi-cloud's a reality. Cloud chaos, Kit Colbert was talking about that and we've been saying, you know, people are chaotic. We believe that. Andy Grove once said, "Reign in the chaos. Let chaos reign, then reign in the chaos." That's the opportunity. The complexity of cross-cloud is being solved. You guys have a vision, take us through how you see that happening. A lot of people want to see this cross-cloud abstraction happen. What's the story from your standpoint, how you see that evolving? >> I think that IT history repeats itself, right? Every starts nice and neat. "Oh, I'm going to buy a bunch of HP servers and my life is going to be good, and oh, this store." >> Spin up an EC2. >> Yeah. Eventually everything goes like this in IT because every vendor do what they do, they innovate. And so that could create complexity. And in the cloud is the complexity on steroid because you have six major cloud, all the local clouds, the cloud pro- local cloud providers, and each of these cloud brings their own way of doing management security. And I think now it's time. Every customer that I talk to, they want more simplicity. You know, how do I go fast but be able to manage the complexity? So that's where cross-cloud services- Last year, we launched a vision, with a sprinkle of software behind it, of building a set of cloud-native services that allow our customers to build, run, manage, secure, and access any application consistently across any cloud. >> Yeah, so you're a year in now, it's not like, I mean, you know, when you come together in a physical event like this, it resonates more, you got the attention. When you're watching the virtual events, you get doing a lot of different things. So it's not like you just stumbled upon this last week. Okay, so what have you learned in the last year in terms of post that launch. >> What we learned is what we have been building for the last five years, right? Because we started, we saw multi-cloud happening before anybody else, I would argue. With our announcement with AWS five, six years ago, right? And then our first journey to multi-cloud was let's bring vSphere on all the clouds. And that's a great purpose to help our customers accelerate their journey of their "legacy" application. Their application actually deliver business to the cloud. But then around two, three years ago, I think Raghu realized that to add value, we needed- customers were already in the cloud, we needed to embrace the native cloud. And that's where Tanzu came in as a way to build application. Tanzu manage, way to secure manage application. And now with Aria, we now have more differentiated software to actually manage this application across- >> Yeah, and Aria is the management plane. That's the rebrand. It's not a new product per se. It's a collection of the VMware stuff, right? Isn't it like- >> No, it's, it's a... >> It's a new product? >> There is a new innovation there because basically they, the engineering team built this graph and Raghu compared it to the graph that Google builds up around about the web. So we go out and crawl all your assets across any cloud and we'll build you this model that now allows you to see what are your assets, how you can manage them, what are the performance and all that, so. No, it's more than a brand. It's, it's a new innovation and integration of a technology that we had. >> And that's a critical component of cross-cloud. So I want to get back to what you said about Raghu and what he's been focused on. You know, I remember interviewing him in 2016 with Andy Jassy at AWS, and that helped clear up the cloud game. But even before that Raghu and I had talked, Dave, on theCUBE, I think it was like 2014? >> Yeah. >> Pat Gelson was just getting on board as the CEO of VMware. Hybrid was very much on the conversation then. Even then it was early. Hybrid was early, you guys are seeing multi-cloud early. >> It was private cloud. >> Totally give you props on that. So VMware gets total props on that, being right on that. Where are we in that journey? 'Cause super cloud, as we're talking about, you were contributing to that initiative in the open with our open source project. What is multi-cloud? Where is it in the status of the customer? I think everyone will agree, multi-cloud is an outcome that's going to happen. It's happening. Everyone has multiple clouds and they configure things differently. Where are we on the progress bar in your mind? >> I think I want to answer that question and go back to your question, which I didn't address, you know, what we are learning from customers. I think that most customers are at the very, very beginning. They're either in the denial stage, like yesterday talked to a customer, I said, "Are you multi-cloud, are you on your multi-cloud journey?" And he said, "Oh we are on-prem and a little bit of Azure." I said, "Oh really? So the bus- "Oh no, well the business unit is using AWS, right? And we are required company that is using-" I said, "Okay, so you are... that customer is in cloud first stage." >> Like you said, we've seen this movie before. It comes around, right? >> Yeah. >> Somebody's going to have to clean that up at some point. >> Yeah, I think a lot, a lot of- the majority customers are either in denial or in the cloud chaos. And some customers are pushing the envelope like SMP. SMP Global, we heard this morning. Somebody has done all the journey in the private cloud with us, and now I said, and I talked to him a few months ago, he told me, "I had to get in front of my developers. Enough of this, you know, wild west. I had to lay down the tracks and galleries for them to build multi-cloud in a way that was, give them choice, but for me, as an operator and a security person, being able to manage it and secure it." And so I think most customers are in that chaos phase right now. Very early. >> So at our Supercloud22 event, we were riffing and I was asking you about, are you going to hide the complexity, yes. But you're also going to give access to the, to the developers if they want access to the primitives. And I said to you, "It sounds like you want to have your cake and eat it too." And you said, "And want to lose weight." And I never followed up with you, so I want to follow up now. By "lose weight," I presume you mean be essentially that platform of choice, right? So you're going to, you're going to simplify, but you're going to give access to the developers for those primitives, if in fact they want one. And you're going to be the super cloud, my word of choice. So my question to you is why, first of all, is that correct, your "lose weight"? And why VMware? >> When I say you, you want a cake, eat it and lose weight, I, and I'm going to sound a little arrogant, it's hard to be humble when you're good. But now I work for a company, I work for a company that does that. Has done it over and over and over again. We have done stuff, I... Sometimes when I go before customers, I say, "And our technology does this." Then the customer gets on stage and I go, "Oh my God, oh my God." And then the customers say, "Yeah, plus I realize that I could also do this." So that's, you know, that's the kind of company that we are. And I think that we were so busy being successful with on-prem and that, you know, that we kind of... the cloud happened. Under our eyes. But now with the multi-cloud, I think there is opportunity for VMware to do it all over again. And we are the right company to do it for two reasons. One, we have the right DNA. We have those engineers that know how to make stuff that was not designed to work together work together and the right partnership because everybody partners with us. >> But, you know, a lot of companies like, oh, they missed cloud, they missed mobile. They missed that, whatever it was. VMware was very much aware of this. You made an effort to do kind of your own cloud initiative, backed off from- and everybody was like, this is a disaster waiting to happen and of course it was. And so then you realize that, you learn from your mistakes, and then you embraced the AWS deal. And that changed everything, it changed... It cleared it up for your customers. I'm not hearing anybody saying that the cross-cloud services strategy, what we call multi, uh, super cloud is wrong. Nobody's saying that's like a failed, you know, strategy. Now the execution obviously is very important. So that's why I'm saying it's different this time around. It's not like you don't have your pulse on it. I mean, you tried before, okay, the strategy wasn't right, it backfired, okay, and then you embraced it. But now people are generally in agreement that there's either a problem or there's going to be a problem. And so you kind of just addressed why VMware, because you've always been in the catbird seat to solve those problems. >> But it is a testament to the pragmatism of the company. Right? You try- In technology, you cannot always get it right, right? When you don't get it right, say, "Okay, that didn't work. What is the next?" And I think now we're onto something. It's a very ambitious vision for sure. But I think if you look at the companies out there that have the muscles and the DNA and the resources to do it, I think VMware is one. >> One of the risks to the success, what's been, you know you watch the Twitter chatter is, "Oh, can VMware actually attract the developers?" John chimed in and said, >> Yeah. >> It's not just the devs. I mean, just devs. But also when you think of DevOps, the ops, right? When you think about securing and having that consistent platform. So when you think about the critical factors for you to execute, you have to have that pass platform, no question. Well, how do you think about, okay, where are the gaps that we really have to get right? >> I think that for us to go and get the developers on board, it's too late. And it's too late for most companies. Developers go with the open source, they go with the path of least resistance. So our way into that, and as Kelsey Hightower said, building new application, more applications, is a team sport. And part of that team is the Ops team. And there we have an entry, I think. Because that's what- >> I think it possible. I think you, I think you're hitting it. And my dev comment, by the way, I've been kind of snarky on Twitter about this, but I say, "Oh, Dev's got it easy. They're sitting in the beach with sunglasses on, you know, having focaccia. >> Doing whatever they want. >> Happy doing whatever they want. No, it's better life for the developer now. Open source is the software industry, that's going great. Shift left in CI/CD pipeline. Developers are faster than ever, they're innovating. It's all self-service, it's all DevOps. It's looking good for the developers right now. And that's why everyone's focused on that. They're driving the change. The Ops team, that was traditional IT Ops, is now DevOps with developers. So the seed change of data and security, which is core, we're hearing a lot of those. And if you look at all the big successes, Snowflake, Databricks, MinIO, who was on earlier with the S3 cloud storage anywhere, this is the new connective tissue that VMware can connect to and extend the operational platform of IT and connect developers. You don't need to win them all over. You just connect to them. >> You just have to embrace the tools that they're using. >> Exactly. >> You just got to connect to them. >> You know, you bring up an interesting point. Snowflake has to win the developers, 'cause they're basically saying, "Hey, we're building an application development platform on top of our proprietary system." You're not saying that. You're saying we're embracing the open source tools that developers are using, so use them. >> Well, we gave it a single pane of glass to manage your application everywhere. And going back to your point about not hiding the underlying primitives, we manage that application, right? That application could be moving around, but nobody prevents that application to use that API underneath. I mean, that's, that can always do that. >> Right, right. >> And, and one of the reason why we had Kelsey Hightower and my keynote and the main keynote was that I think he shows that the template, the blueprint for our customers, our operators, if you want to have- even propel your career forward, look at what he did, right? VI admin, going up the stack storage and everything else, and then eventually embrace Kubernetes, became an expert. Really took the time to understand how modern application were- are built. And now he's a luminary in the industry. So we don't have, all have to become luminary, but you can- our customers right here, doing the labs upstairs, they can propel the career forward in this. >> So summarize what you guys are announcing around cross cloud-services. Obviously Aria, another version, 1.3 of Tanzu. Lay out the sort of news. >> Yeah, so we- With Tanzu, we have one step forward with our developer experience so that, speaking of meeting where they are, with application templates, with ability to plug into their idea of choice. So a lot of innovation there. Then on the IR side, I think that's the name of the game in multi-cloud, is having that object model allows you to manage anything across anything. And then, we talk about cross-cloud services being a vision last year, I, when I launched it, I thought security and networking up there as a cloud, but it was still down here as ploy technology. And now with NSX, the latest version, we brought that control plane in the cloud as a cloud native cross-cloud service. So, lot of meat around the three pillars, development, the management, and security. >> And then the complementary component of vSphere 8 and vSAN 8 and the whole DPU thing, 'cause that's, 'cause that's cloud, right? I mean, we saw what AWS did with Nitro. >> Yeah. >> Five, seven years ago. >> That's the consumption model cloud. >> That's the future of computing architecture. >> And the licensing model underneath. >> Oh yeah, explain that. Right, the universal licensing model. >> Yeah, so basically what we did when we launch cloud universal was, okay, you can buy our software using credit that you have on AWS. And I said, okay, that's kind of hybrid cloud, it's not multi-cloud, right? But then we brought in Google and now the latest was Microsoft. Now you can buy our software for credits and investment that our customers already have with these great partners of ours and use it to consume as a subscription. >> So that kind of changes your go-to-market and you're not just chasing an ELA renewal now. You're sort of thinking, you're probably talking to different people within the organizations as well, right? So if I can use credits for whatever, Google, for Azure, for on-prem, for AWS, right? Those are different factions necessarily in the organization. >> So not just the technology's multi-cloud, but also the consumption model is truly multi-cloud. >> Okay, Vittorio, what's next? What's the game plan? What do you have going on? It's getting good traction here again, like Dave said, no one's poo-pooing cross-cloud services. It is kind of a timing market forces. We were just talking before you came on. Oh, customers don't- may not think they have a problem, whether they're the frog boiling water or not, they will have the problem coming up or they don't think they have a problem, but they have chaos reigning. So what's next? What are you doing? Is it going to be new tech, new market? What is the plan? >> So I think for, if I take my bombastic kind of marketing side of me hat off and I look at the technology, I think the customers in these scales wants to be told what to do. And so I think what we need to do going forward is articulate these cross-cloud services use cases. Like okay, what does mean to have an application that uses a service over here, a service over there, and then show the value of getting this component from one company? Because cross-cloud services at your event, how many vendors were there? 20? 30? >> Yeah. >> So the market is there. I mean, these are all revenue-generating companies, right, but they provide a piece of the puzzle. Our ambition is to provide a platform approach. And so we need to articulate better, what are the advantages of getting these components management, security, from- >> And Kit, Kit was saying, it's a hybrid kind of scenario. I was kind of saying, oh, putting my little business school scenario hat on, oh yeah, you go hardcore competitive, best product wins, kill or be killed, compete and win. Or you go open and you create a keiretsu, create a consortium, and get support, standardize or defacto standardize a bunch of it, and then let everyone monetize or participate. >> Yeah, we cannot do it alone. >> What's the approach? What's the approach you guys want to take? >> So I think whatever possible, first of all, we're not going to do it alone. Right, so the ecosystem is going to play a part and if the ecosystem can come together around the consortium or a standard that makes sense for customers? Absolutely. >> Well, and you say, nobody's poo-pooing it, and I stand by that. But they are saying, and I think it is true, it's hard, right? It's a very challenging, ambitious goal that you have. But yeah, you've got a track record of- >> I mean the old playbook, >> Exactly! >> The old playbooks are out. I mean, I always say, the old kill and be highly competitive strategy. Proprietary is dead. And then if you look at the old way of winning was, okay, you know, we're going to lock customers in- >> What do you mean proprietary is dead? Proprietary's not dead. >> No, I mean like, I'm talking- Okay, I'm talking about how people sell. Enterprise companies love to create, simplify, create value with chaos like okay, complexity with more complexity. So that's over, you think that's how people are marketing? >> No, no, it's true. But I mean, we see a lot of proprietary out there. >> Like what? >> It's still happening. Snowflake. (laughing) >> Tell that to the entire open store software industry. >> Right, well, but that's not your play. I mean, you have to have some kind of proprietary advantage. >> The enterprise playbook used to be solve complexity with complexity, lock the customers in. Cloud changed all that with open. You're a seasoned marketer, you're also an executive. You have an interesting new wave. How do you market to the enterprise in this new open way? How do you win? >> For us, I think we have that relationship with the C-level and we have delivered for them over and over again. So our challenge from a marketing perspective is to educate these executives about all that. And the fact that we didn't have this user conference in person didn't help, right? And then show that value to the operator so that they can help us just like we did in the past. I mean, our sales motion in the past was we made these people- I told them today, you were the heroes. When you virtualized, when you brought down 1000 servers to 80, you were the hero, right? So we need to empower them with the technology and the know-how to be heroes again in multi-cloud. And I think the business will take care of itself. >> Okay final question from me, and Dave might have another one of his, everybody wanted to know this year at VMworld, VMware Explore, which is the new name, what would it look like? What would the vibe be? Would people show up? Would it be vibrant? Would cross-cloud hunt? Would super cloud be relevant? I got to say looking at the floor last night, looking at the keynotes, looking at the perspective, it seems to look like, oh, people are on board. What is your take on this? You've been talking to customers, you're talking to people in the hallways. You've been brief talking to all the analysts. What is the vibe about this year's Explore? >> I think, you've been covering us for a long time, this is a religious following we have. And we don't take it for granted. I told the audience today, this to us is a family reunion and we couldn't be, so we got a sense of like, that's what I feels like the family is back together. >> And there's a wave coming too. It's not like business is dying. It's like a whole 'nother. Another wave is coming. >> It's funny you mention about the heroes. 'Cause I go back, I don't really have my last question, but it's just the last thought is, I remember the first time I saw a demo of VMware and I went, "Holy crap, wow. This is totally game changing." I was blown away. Right, like you said, 80 servers down to just a couple of handfuls. This is going to change everything. And that's where it all started. You know, I mean, I know it started in workstations, but that's when it really became transformational. >> Yeah, so I think we have an opportunity to do it over again with the family that is here today, of which you guys consider family as well. >> All right, favorite part of the keynote and then we'll wrap up. What was your favorite part of the keynote today? >> I think the excitement from the developer people that were up there. Kelsey- >> The guy who came after Kelsey, what was his name? I didn't catch it, but he was really good. >> Yeah, I mean, it's, what it's all about, right? People that are passionate about solving hard problems and then cannot wait to share it with the community, with the family. >> Yeah. I love the one line, "You kids have it easy today. We walk to school barefoot in the snow back in the day." >> Uphill, both ways. >> Broke the ice to wash our face. >> Vittorio, great to see you, great friend of theCUBE, CUBE alumni, vice president of cross-cloud serves at VMware. A critical new area that's harvesting the fruits coming off the tree as VMware invested in cloud native many years ago. It's all coming to the market, let's see how it develops. Congratulations, good luck, and we'll be back with more coverage here at VMware Explore. I'm John Furrier with Dave Vellante. Stay with us after the short break. (gentle music)

(upbeat music) >> Good afternoon and welcome back to Las Vegas. You're watching theCUBE's coverage of AWS 2021. My name is Dave Vellante. theCUBE goes out to the events. We extract the signal from the noise. Very few physical events this year doing a lot of hybrid stuff. It's great to be back in hybrid event... Physical event land, 25,000 people here. Probably a little few more registered than that. And then on the periphery, got to be another at least 10,000 people that came in, flew in and out, see what's happening. A bunch of VCs, checking things out, a few parties last night and so forth. A lot of action here. It's like re:Invent is back. Matt Coulter is here. He's a technical architect at Liberty Mutual. Matt, thanks for flying in from Belfast. Good to see ya. >> Dave, and thanks for having me today. >> Pleasure. So what's your role as a technical architect? Maybe describe that, we'll get into a little bit. >> Yeah so I am here to empower and enable our developers across the globe to rapidly deliver business value and solve problems for our customers in a well-architected way that doesn't introduce problems or risks, you know, later down the line. So instead of thinking of me as someone who directly every day, build software, I try to create the environment where other people can rapidly build software. >> That's, you know, it's interesting. because you're a developer, right? You can use like, "Hey I code." That's what normally you would say but you're actually creating frameworks and business model so that others can learn, teach them how to fish, so we speak. >> Yeah because I can only scale, there's a certain amount. Whereas if I can teach, there's 5,000 people in Liberty Mutual's tech organization. So if I can teach the 5,000 to be 5% better, it's way more than me even if I 10Xed >> When did you first touch the Cloud? >> Personally, it would have been four/five years ago. That's when I started in the Cloud. >> What was that experience like for you? >> Oh, it was hard. It was very different to anything that we'd done in the past. So it's because you... Traditionally, you would have just written your small piece of code. You would have had a big application that was out there, it had been out there maybe 20 years, it was deployed, and you were just adding a couple of lines. Whereas when you start putting stuff into the Cloud, it's out there. It's on the internet for anyone there to try and hack or try to get into. It was a bit overwhelming the amount that you needed to learn. So it was- >> Was it worth it? >> Oh yeah. Completely. (laughing) So that's the thing, that I would never go back to the way we did things before. And that's why I'm so passionate, enthusiastic about the stuff I've been doing. Because to me, the amount of benefits you can get, like now we can deliver thing. We have teams going out there and doing discovery and framing with the business. And they're pushing well-architected products three days later into production. That was unheard of before, you know, this year. >> Yeah. So you were part of Werner's keynote this morning. Of course that's always one of the keynotes that's most anticipated at re:Invent. It's on the sort of last day. He's awesome. This is you know, 10th year of re:Invent. He sort of did a look back. He started out (chuckles) he's just a cool guy and very passionate. But talk about what your role was in the keynote. >> Yeah so I had a section towards the end of the keynote, and I was to talk about Liberty Mutual's serverless first journey. I actually went through from 2014 through to the current day of all the major Cloud milestones that we've hit. And I talked through some of the impact it's had on our business and the impact it's had on our developers. And yeah it's just been this incredible journey where as I said, it was hard at the start. So we had to spark this culture within our company that we were going to empower and enable our developers and we were going to get them excited about doing this. And that's why we needed to make it safe. So there was a lot of work went down at the start to make the Cloud safe for our developers to experiment. And then the past two years have been known that it's safe, okay? Let's see what it can do. Let's go. >> Yeah so Liberty Mutual has been around many many years, Boston-based, you know, East Coast-based, my home city. I don't live in Boston but I consider it my city. And so talk about your business a little bit because you're an established company. I don't know, probably a hundred years old, right? Any all other newbies nipping at your business, right? Coming in with low-cost products. Maybe not bringing as much protection as you dig into it. But regardless, you've got to compete with them technically. So what are some of the drivers in your business and how are you using the Cloud to sort of defend your turf and grow? >> Yeah so first of all, we're 109 years old. (laughing) Yeah. So absolutely, there's an entire insurtech market of people here gunning for the big Liberty Mutual because we've been here for so long. And our whole thing is we're focused on our customers. So we want to be there for people in their time of need. Because at a point in time whenever you need insurance, typically something is going wrong. And that's why we're building innovative solutions like a serverless call center we built, that after natural disaster, it can automatically process claims in less than four minutes. So instead of having to wait on hold for maybe an hour, you can just text or pick up the phone, and four minutes later your claims are through. And that's we're using technology always focused on the customer. >> That's unbelievable. Think about that experience, to me. I mean I've filed claims before and it's, it's kind of time consuming. And you're saying you've compressed that to minutes? Days, weeks, you know, and now you've compressed that to minutes? >> Yeah. >> Tell us more about how you did that. >> And that's because it's a fully serverless solution that was built. So it doesn't require like people to scale. It can scale to whatever number of our customers need to make a claim at that point because that would typically be the bottleneck if there's some kind of natural disaster. So that means that if something happens we can just switch it on. And customers can choose not to use it. You can always choose to say I want to speak to a person. But now with this technology, we can just make it easy and just go. Everything, all the information we know in the back end, we just use it and actually make things better for you. >> You're talking about the impact that it had on your business and developers. So how do you quantify that? Maybe start with the business. Maybe share some ways in which you look at that measure. >> Yeah, so I mean, in terms of how we measure the impact of the Cloud on our business, we're always looking at our profitability and we're always looking, as I say, at our customers. And ideally, I want our Cloud bill to go down as our number of customers goes up because that's why we're using the serverless fast mindset, we call it. We don't want to build anything we don't have to build. We want to take the best that's out there and just piece it together and produce these products for our customers. So yeah, that's having an impact on our business because now developers aren't spending weeks, months, years doing all this configuration. And they can actually sit down with the business and understand how we write insurance. So now we can start being innovative with our products and talking about the real business instead of everything else. >> When you say you want your Cloud bill to go down, you know, it reminds me like in the old days of IT budgeting, right? It was always slash, do more with less cut, cut, cut, right? And it was kind of going in cycles. But with the Cloud a lot of customers that I talk to, they were like, might be going down as a percentage of revenues but actually it might be going up as you launch more projects because they're driving revenue. There's a tighter tie between revenue and Cloud bill. How do you look at that? >> Yeah. So I mean, with every project, you have to look at the worth-based development often and whether or not it's going to hold this away in the market. And the key thing is with the serverless products that are being released now, they cost pennies if they're low scale. So you can actually launch a new product into the market and it maybe only cost you $20 to see if that thing would fit in the market. So by the time you're getting into the big bills you know whether or not you've got a market fit and you can decide whether you want to pivot. >> Oh wow. So you you've compressed, that's another business metric. You've compressed the time to get certainty around product market fit, right? Which is huge because you really can't go to market until you have product market fit (laughing) >> Exactly. You have to be. Thoroughly understand if it's going to work. >> Right because if you go to the market and you've got 50% churn. (laughing) Well, you don't want to be worried about the go-to market. You got to get back to the product so you can test that and you can generate. >> So that's why, yeah, As I said, we have developers who can go out and do discovery and framing on a potential product and deliver it three days later which (chuckles) >> How has the Cloud effected developer satisfaction or passion? I guess it's... I mean we're in AWS Cloud. Our developers, we tell them "Okay, you got to go back on-prem." They would say, "I quit." (laughing) How has it affected their lives? >> Yeah it's completely there for them, it's way better. So now we have way more ownership over any, you know, of everything we ever did. So it feels like you're truly a part of Liberty Mutual and you're solving Liberty's problems now. Because it's not a case of like, "Okay, let's put in a request to stand up a server, it's going to take six months. And then let's do some big long acquisition." It's a case of like, "Let's actually get done into the nitty gritty of what we going to build." And that's- >> How do you use the Cloud developer kit? Maybe you could talk about that. I mean, explain what it is. It's a framework. But explain from your perspective. >> Yeah so the Cloud typically, it started off, and lot of it was done by Cloud infrastructure engineers who created these big YAML files. That's how they defined all the stuff that's going to be deployed. But that's not typically the development language that most developers use. The CDK is in like Java, TypeScript, .NET, Python. The language is developers ready known love. And it means that they can use everything they already know from all of their previous development experience and bring it to the Cloud. And you see some benefits like, you get, I talked about this morning, a 1500 line YAML file was reduced to 14 lines of TypeScript. And that's what we're talking about with the cognitive difference for a developer using CDK versus anything else. >> Cognitive abstraction, >> Right? >> Yeah. And so it just simplifies your living and you spend more time doing cool stuff. >> Yeah we can write an abstraction for our specific needs once. And then everybody can use that abstraction. And if we want to make a change and make it better, everyone benefits instead of everybody doing the same thing all the time. >> So for people who are unfamiliar, what do you need? You need an AWS account, obviously. You got to get a command-line interface, I would imagine. maybe some Node.js often running, or is it- >> Yeah. So that's it. You need an AWS account, and then you need to install CDK, which is from Node Package Manager. And then from there, it depends on which way you want to start. You could use my project CDK patterns, has a whole ray of working patterns that you can clone among commands. You just have to type, like one command you've got a pattern, and then CDK deploy. And you'll have something working. >> Okay so what do you do day-to-day? You sort of, you evangelize folks to come in and get trained? Is there just like a backlog of people that want your time? How do you manage that? >> So I try to be the place that I'm needed the most based on impact of the business. And that's why I try to go in. Liberty split up into different areas and I try to go into those areas, understand where they are versus where they need to be. And then if I can do that across everywhere, you can see the common thesis. And then I can see where I can have the most impact across the board instead of focusing on one micro place. So there's a variety of tools and techniques that I would do, you know, to go through that but that's the crux of it. >> So you look at your business across the portfolio, so you have portfolio view. And then you do a gap analysis essentially, say "Okay, where can I approach this framework and technology from a developer standpoint, add value? >> Yeah like I could go into every single team with every single project, draw it all out and like, what we call Wardley map, and then you can draw a line and then say "Everything blue in this line is undifferentiated, heavy-lifted. I want you to migrate that. And here's how you're going to do it I've already built the tools for that." And that's how we can drive those conversations. >> So, you know, it's funny, I spent a lot of time in the insurance business not in the business but consulting with heads of application development and looking at portfolios. And you know, they did their thing. But you know, a lot of people sort of question, "Can developers in an insurance company actually become cool Cloud native developers?" You're doing it, right? So that's going to be an amazing transformation for your colleagues and your industry. And it's happening as we look around here (indistinct) >> And that's the thing, in Liberty I'm not the only one. So there's Tommy Gloklin, he's an AWS hero, and there's Diali Mikan, who's an AWS hero. And Diali is in Workgrid but we're still all the same family. >> So what does it mean to be an AWS hero? >> Yeah so this is something that AWS has to offer you to join. So basically, it's about impacting the community. It's not... There's not like a checklist of items you can go through and you're hero. It's you have to be nominated internally through AWS, and then you have to have the right intentions. And yeah, just follow through. >> Dave: That's awesome. Yeah so our producer, Lynette, is looking for an Irish limerick. You know, every, say I'm half Irish is through my marriage. Dad, you didn't know that, did you? And every year we have a St Patrick's Day party and my daughter comes up with limericks. So I don't know, if you have one that you want to share. If you don't, that's fine. >> I have no limericks for now. I'm so sorry. (laughing) >> There once was a producer from, where are you from? (laughing) So where do you want to take this, Matt? What's your future look like with this program? >> So right now, today, I actually launched a book called the CDK book. >> Dave: Really? Awesome. >> Yeah So me and three other heroes got together and put everything we know about CDK and distilled it into one book. But the... I mean there's two sides, there's inside Liberty. The goal as I've mentioned is to get our developers to the point that they're talking about real insurance problems rather than tech. And then outside Liberty in the community the goal is things like CDK Day, which is a global conference that I created and run. And I want to just grow those farther and farther throughout the world so that eventually we can start learning you know, cross business, cross market, cross the main instead of just internally one company. >> It's impressive how tuned in you are to the business. Do you feel like the Cloud almost forces that alignment? >> It does. It definitely does. Because when you move quickly, you need to understand what you're doing. You can't bluff almost, you know. Like everything you're building you're demonstrating that every two weeks or faster. So you need to know the business to do it. >> Well, Matt, congratulations on all the great work that you've done and the keynote this morning. You know, true tech hero. We really appreciate your time coming in theCUBE. >> Thank you, Dave, for having me. >> Our pleasure. And thank you for watching. This is Dave Vellante for theCUBE at AWS re:Invent. We are the leader global tech coverage. We'll be right back. (light upbeat music)

(bright upbeat music) >> Welcome to The Cube. We're here for the AWS Executive Summit part of Reinvent 2021. I'm John Farrow, your host of the Cube. We've got a great segment focus here, Art of the Possible is the segment. Jas Bains, Chief Executive at Hafod and Jamie Smith, director of research and innovation and Laetitia Cailleteau who's the global lead of conversational AI at Accenture. Thanks for joining me today for this Art of the Possible segment. >> Thank you. >> So tell us a little bit about Hafod and what you guys are doing to the community 'cause this is a really compelling story of how technology in home care is kind of changing the game and putting a stake in the ground. >> Yeah, so Hafod is one of the largest not for profits in Wales. We employ about 1400 colleagues. We have three strands a service, which practices on key demographics. So people who are vulnerable and socioeconomically disadvantaged. Our three core strands of service are affordable housing, we provide several thousand homes to people in housing need across Wales. We also are an extensive provider of social provision, both residential and in the community. And then we have a third tier, which is a hybrid in between. So that supports people who are not quite ready for independent living but neither are they ready for residential care. So that's a supportive provision. I suppose what one of the things that marks Hafod out and why we're here in this conversation is that we're uniquely placed as one of the organizations that actually has a research and innovation capacity. And it's the work of the research and innovation capacity led by Jamie that brought about this collaboration with Accenture which is great in great meaning and benefits. So thousands of our customers and hopefully universal application as it develops. >> You know this is a really an interesting discussion because multiple levels, one, the pandemic accelerated this needs so, I want to get comments on that. But two, if you look at the future of work and work and home life, you seeing the convergence of where people live. And I think this idea of having this independent home and the ecosystem around it, there's a societal impact as well. So what brought this opportunity together? How did this come together with Accenture and AWS? >> We're going for Jamie and Laetitia. >> Yeah, I can start. Well, we were trying to apply for the LC Aging Grand Challenge in the U.K., so the United Kingdom recognized the need for change around independent living and run a grand challenge. And then we got together as part of this grand challenge. You know, we had some technology, we had trialed with AGK before and Hanover Housing Association. Hafod was really keen to actually start trying some of that technology with some of the resident. And we also worked with Swansea University, was doing a lot of work around social isolation and loneliness. And we came together to kind of pitch for the grand challenge. And we went quite far actually, unfortunately we didn't win but we have built such a great collaboration that we couldn't really let it be, you know, not going any further. And we decided to continue to invest in this idea. And now we here, probably 18 months on with a number of people, Hafod using the technology and a number of feedbacks and returns coming back and us having a grand ambitions to actually go much broader and scale this solution. >> Jas and Jamie, I'd love to get your reaction and commentary on this trend of tech for good because I mean, I'm sure you didn't wake up, oh, just want to do some tech for good. You guys have an environment, you have an opportunity, you have challenges you're going to turn into opportunities. But if you look at the global landscape right now, things that are jumping out at us are looking at the impact of social media on people. You got the pandemic with isolation, this is a first order problem in this new world of how do we get technology to change how people feel and make them better in their lives. >> Yeah, I think for us, the first has to be a problem to solve. There's got to be a question to be answered. And for us, that was in this instance, how do we mitigate loneliness and how do we take services that rely on person to person contact and not particularly scalable and replicate those through technology somehow. And even if we can do 10% of the job of that in-person service then for us, it's worth it because that is scalable. And there are lots of small interventions we can make using technology which is really efficient way for us to support people in the community when we just can't be everywhere at once. >> So, John, just to add, I think that we have about 1500 people living in households that are living alone and isolated. And I think the issue for us was more than just about technology because a lot of these people don't have access to basic technology features that most of us would take for granted. So far this is a two-prong journey. One is about increasing the accessibility to tech and familiarizing people so that they're comfortable with these devices technology and two importantly, make sure that we have the right means to help people reduce their loneliness and isolation. So the opportunity to try out something over the last 12 months, something that's bespoke, that's customized that will undoubtedly be tweaked as we go forward has been an absolutely marvelous opportunity. And for us, the collaboration with Accenture has been absolutely key. I think what we've seen during COVID is cross-fertilization. We've seen multi-disciplinary teams, we've got engineers, architects, manufacturers, and clinicians, and scientists, all trying to develop new solutions around COVID. And I think this probably just exemplary bias, especially as a post COVID where industry and in our case for example public sector and academia working together. >> Yeah, that's a great example and props to everyone there. And congratulations on this really, really important initiative. Let's talk about the home care solution. What does it do? How does it work? Take us through what's happening? >> Okay, so Home Care is actually a platform which is obviously running on AWS technology and this particular platform is the service offered accessible via voice through the Alexa device. We use the Echo Show to be able to use voice but also visuals to kind of make the technology more accessible for end user. On the platform itself, we have a series of services available out there. We connecting in the background a number of services from the community. So in the particular case of Hafod, we had something around shopping during the pandemic where we had people wanting to have access to their food bank. Or we also had during the pandemic, there was some need for having access to financial coaching and things like that. So we actually brought all of the service on the platform and the skills and this skill was really learning how to interact with the end user. And it was all customized for them to be able to access those things in a very easy way. It did work almost too well because some of our end users have been a kind of you know, have not been digital literate before and it was working so well, they were like, "But why can't it do pretty much anything on the planet? "Why can't it do this or that?" So the expectations were really, really high but we did manage to bring comfort to Hafod residents in a number of their daily kind of a need, some of the things during COVID 'cause people couldn't meet face to face. There was some challenge around understanding what events are running. So the coaches would publish events, you know, through the skills and people would be able to subscribe and go to the event and meet together virtually instead of physically. The number of things that really kind of brought a voice enabled experience for those end users. >> You know, you mentioned the people like the solution just before we, I'm going to get the Jamie in a second, but I want to just bring up something that you brought up. This is a digital divide evolution because digital divide, as Josh was saying, is that none about technology,, first, you have to access, you need access, right? First, then you have to bring broadband and internet access. And then you have to get the technology in the home. But then here it seems to be a whole nother level of digital divide bridging to the new heights. >> Yeah, completely, completely. And I think that's where COVID has really accelerated the digital divide before the solution was put in place for Hafod in the sense that people couldn't move and if they were not digitally literate, it was very hard to have access to services. And now we brought this solution in the comfort of their own home and they have the access to the services that they wouldn't have had otherwise on their own. So it's definitely helping, yeah. >> It's just another example of people refactoring their lives or businesses with technology. Jamie, what's your take on the innovation here and the technical aspects of the home care solutions? >> I think the fact that it's so easy to use, it's personalized, it's a digital companion for the home. It overcomes that digital divide that we talked about, which is really important. If you've got a voice you can use home care and you can interact with it in this really simple way. And what I love about it is the fact that it was based on what our customers told us they were finding difficult during this time, during the early lockdowns of the pandemic. There was 1500 so people Jas talked about who were living alone and at risk of loneliness. Now we spoke to a good number of those through a series of welfare calls and we found out exactly what it is they found challenging. >> What were some of the things that they were finding challenging? >> So tracking how they feel on a day-to-day basis. What's my mood like, what's my wellbeing like, and knowing how that changes over time. Just keeping the fridge in the pantry stocked up. What can I cook with these basic ingredients that I've got in my home? You could be signposted to basic resources to help you with that. Staying connected to the people who are really important to you but the bit that shines out for me is the interface with our services, with our neighborhood coaching service, where we can just give these little nudges, these little interventions just to mitigate and take the edge of that loneliness for people. We can see the potential of that coming up to the pandemic, where you can really encourage people to interact with one another, to be physically active and do all of those things that sort of mitigate against loneliness. >> Let me ask you a question 'cause I think a very important point. The timing of the signaling of data is super important. Could you comment on the relevance of having access to data? If you're getting something connected, when you're connected like this, I can only imagine the benefits. It's all about timing, right? Knowing that someone might be thinking some way or whether it's a tactical, in any scenario, timing of data, the right place at the right time, as they say. What's your take on that 'cause it sounds like what you're saying is that you can see things early when people are in the moment. >> Yeah, exactly. So if there's a trend beginning to emerge, for example, around some of these wellbeing, which has been on a low trajectory for a number of days, that can raise a red flag in our system and it alerts one of our neighborhood coaches just to reach out to that person and say, "Well, John, what's going on? "You haven't been out for a walk for a few days. "We know you like to walk, what's happening?" And these early warning signs are really important when we think of the long-term effects of loneliness and how getting upstream of those, preventing it reaching a point where it moves from being a problem into being a crisis. And the earlier we can detect that the more chance we've got of these negative long-term outcomes being mitigated. >> You know, one of the things we see in the cloud business is kind of separate track but it kind of relates to the real world here that you're doing, is automation and AI and machine learning bringing in a lot of value if applied properly. So how are you guys seeing, I can almost imagine that patterns are coming in, right? Do you see patterns in the data? How does AI and analytics technology improve this process especially with the wellbeing and emotional wellbeing of the elderly? >> I think one of the things we've learned through the pilot study we've done is there's not one size fits all. You know, all those people are very different individuals. They have very different habits. You know, there's some people not sleeping over the night. There's some people wanting to be out early, wanting to be social. Some people you have to put in much more. So it's definitely not one size fits all. And automation and digitalization of those kinds of services is really challenging because if they're not personalized, it doesn't really catch the interest or the need of the individuals. So for me as an IT professional being in the industry for like a 20 plus years, I think this is the time where personalization has really a true meaning. Personalization at scale for those people that are not digitally literate. But also in more vulnerable settings 'cause there's just so many different angles that can make them vulnerable. Maybe it's the body, maybe it's the economy position, their social condition, there's so many variation of all of that. So I think this is one of the use case that has to be powered by technology to complement the human side of it. If we really want to start scaling the services we provide to people in general, meaning obviously, in all the Western country now we all growing old, it's no secret. So in 20 years time the majority of everybody will be old and we obviously need people to take care of us. And at the moment we don't have that population to take care of us coming up. So really to crack on those kinds of challenges, we really need to have technology powering and just helping the human side to make it more efficient, connected than human. >> It's interesting. I just did a story where you have these bots that look at the facial recognition via cameras and can detect either in hospitals and or in care patients, how they feel. So you see where this is going. Jas I got to ask you how all this changes, the home care model and how Hafod works. Your workforce, the career's culture, the consortium you guys are bringing to the table, partners, you know this is an ecosystem now, it's a system. >> Yes John, I think that probably, it's also worth talking a little bit about the pressures on state governments around public health issues which are coming to the fore. And clearly we need to develop alternative ways that we engage with mass audiences and technology is going to be absolutely key. One of the challenges I still think that we've not resolved in the U.K. level, this is probably a global issue, is about data protection. When we're talking to cross governmental agencies, it's about sharing data and establishing protocols and we've enjoyed a few challenging conversations with colleagues around data protection. So I think those need to be set out in the context of the journey of this particular project. I think that what's interesting around COVID is that, hasn't materially changed the nature in which we do things, probably not in our focus and our work remains the same. But what we're seeing is very clear evidence of the ways, I mean, who would have thought that 12 months ago, the majority of our workforce would be working from home? So rapid mobilization to ensure that people can use, set IT home effectively. And then how does that relationship impact with people in the communities we're serving? Some of whom have got access to technology, others who haven't. So that's been, I think the biggest change, and that is a fundamental change in the design and delivery of future services that organizations like us will be providing. So I would say that overall, some things remain the same by and large but technology is having an absolutely profound change in the way that our engagement with customers will go forward. >> Well, you guys are in the front end of some massive innovation here with this, are they possible and that, you're really delivering impact. And I think this is an example of that. And you brought up the data challenges, this is something that you guys call privacy by design. This is a cutting edge issue here because there are benefits around managing privacy properly. And I think here, your solution clearly has value, right? And no one can debate that, but as these little blockers get in the way, what's your reaction to that? 'Cause this certainly is something that has to be solved. I mean, it's a problem. >> Yeah, so we designed a solution, I think we had, when we design, I co-designed with your end-users actually. We had up to 14 lawyers working with us at one point in time looking at different kinds of angles. So definitely really tackle the solution with privacy by design in mind and with end users but obviously you can't co-design with thousands of people, you have to co-design with a representative subset of a cohort. And some of the challenge we find is obviously, the media have done a lot of scaremongering around technology, AI and all of that kind of things, especially for people that are not necessarily digitally literate, people that are just not in it. And when we go and deploy the solution, people are a little bit worried. When we make them, we obviously explain to them what's going to happen if they're happy, if they want to consent and all that kind of things. But the people are scared, they're just jumping on a technology on top of it we're asking them some questions around consent. So I think it's just that the solution is super secured and we've gone over millions of hoops within Accenture but also with Hafod itself. You know, it's more that like the type of user we deploying the solution to are just not in that world and then they are little bit worried about sharing. Not only they're worried about sharing with us but you know, in home care, there there's an option as well to share some of that data with your family. And there we also see people are kind of okay to share with us but they don't want to share with their family 'cause they don't want to have too much information kind of going potentially worrying or bothering some of their family member. So there is definitely a huge education kind of angle to embracing the technology. Not only when you create the solution but when you actually deploy it with users. >> It's a fabulous project, I am so excited by this story. It's a great story, has all the elements; technology, innovation, cidal impact, data privacy, social interactions, whether it's with family members and others, internal, external. In teams themselves. You guys doing some amazing work, thank you for sharing. It's a great project, we'll keep track of it. My final question for you guys is what comes next for the home care after the trial? What are Hafod's plans and hopes for the future? >> Maybe if I just give an overview and then invite Jamie and Laetitia. So for us, without conversations, you don't create possibilities and this really is a reflection of the culture that we try to engender. So my ask of my team is to remain curious, is to continue to explore opportunities because it's home care up to today, it could be something else tomorrow. We also recognize that we live in a world of collaboration. We need more cross industrial partnerships. We love to explore more things that Accenture, Amazon, others as well. So that's principally what I will be doing is ensuring that the culture invites us and then I hand over to the clever people like Jamie and Laetitia to get on with the technology. I think for me we've already learned an awful lot about home care and there's clearly a lot more we can learn. We'd love to build on this initial small-scale trial and see how home care could work at a bigger scale. So how would it work with thousands of users? How do we scale it up from a cohort of 50 to a cohort of 5,000? How does it work when we bring different kinds of organizations into that mix? So what if, for example, we could integrate it into health care? So a variety of services can have a holistic view of an individual and interact with one another, to put that person on the right pathway and maybe keep them out of the health and care system for longer, actually reducing the costs to the system in the long run and improving that person's outcomes. That kind of evidence speaks to decision-makers and political partners and I think that's the kind of evidence we need to build. >> Yeah, financial impact is there, it's brutal. It's a great financial impact for the system. Efficiency, better care, everything. >> Yeah and we are 100% on board for whatever comes next. >> Laetitia-- >> What about you Laetitia? >> Great program you got there. A amazing story, thank you for sharing. Congratulations on this awesome project. So much to unpack here. I think this is the future. I mean, I think this is a case study of represents all the moving parts that need to be worked on, so congratulations. >> Thank you. >> Thank you. >> We are the Art of the Possible here inside the Cube, part of AWS Reinvent Executive Summit, I'm John Furrier, your host, thanks for watching. (bright upbeat music)

(bright upbeat music) >> Welcome to The Cube. We're here for the AWS Executive Summit part of Reinvent 2021. I'm John Farrow, your host of the Cube. We've got a great segment focus here, Art of the Possible is the segment. Jas Bains, Chief Executive at Hafod and Jamie Smith, director of research and innovation and Laetitia Cailleteau who's the global lead of conversational AI at Accenture. Thanks for joining me today for this Art of the Possible segment. >> Thank you. >> So tell us a little bit about Hafod and what you guys are doing to the community 'cause this is a really compelling story of how technology in home care is kind of changing the game and putting a stake in the ground. >> Yeah, so Hafod is one of the largest not for profits in Wales. We employ about 1400 colleagues. We have three strands a service, which practices on key demographics. So people who are vulnerable and socioeconomically disadvantaged. Our three core strands of service are affordable housing, we provide several thousand homes to people in housing need across Wales. We also are an extensive provider of social provision, both residential and in the community. And then we have a third tier, which is a hybrid in between. So that supports people who are not quite ready for independent living but neither are they ready for residential care. So that's a supportive provision. I suppose what one of the things that marks Hafod out and why we're here in this conversation is that we're uniquely placed as one of the organizations that actually has a research and innovation capacity. And it's the work of the research and innovation capacity led by Jamie that brought about this collaboration with Accenture which is great in great meaning and benefits. So thousands of our customers and hopefully universal application as it develops. >> You know this is a really an interesting discussion because multiple levels, one, the pandemic accelerated this needs so, I want to get comments on that. But two, if you look at the future of work and work and home life, you seeing the convergence of where people live. And I think this idea of having this independent home and the ecosystem around it, there's a societal impact as well. So what brought this opportunity together? How did this come together with Accenture and AWS? >> We're going for Jamie and Laetitia. >> Yeah, I can start. Well, we were trying to apply for the LC Aging Grand Challenge in the U.K., so the United Kingdom recognized the need for change around independent living and run a grand challenge. And then we got together as part of this grand challenge. You know, we had some technology, we had trialed with AGK before and Hanover Housing Association. Hafod was really keen to actually start trying some of that technology with some of the resident. And we also worked with Swansea University, was doing a lot of work around social isolation and loneliness. And we came together to kind of pitch for the grand challenge. And we went quite far actually, unfortunately we didn't win but we have built such a great collaboration that we couldn't really let it be, you know, not going any further. And we decided to continue to invest in this idea. And now we here, probably 18 months on with a number of people, Hafod using the technology and a number of feedbacks and returns coming back and us having a grand ambitions to actually go much broader and scale this solution. >> Jas and Jamie, I'd love to get your reaction and commentary on this trend of tech for good because I mean, I'm sure you didn't wake up, oh, just want to do some tech for good. You guys have an environment, you have an opportunity, you have challenges you're going to turn into opportunities. But if you look at the global landscape right now, things that are jumping out at us are looking at the impact of social media on people. You got the pandemic with isolation, this is a first order problem in this new world of how do we get technology to change how people feel and make them better in their lives. >> Yeah, I think for us, the first has to be a problem to solve. There's got to be a question to be answered. And for us, that was in this instance, how do we mitigate loneliness and how do we take services that rely on person to person contact and not particularly scalable and replicate those through technology somehow. And even if we can do 10% of the job of that in-person service then for us, it's worth it because that is scalable. And there are lots of small interventions we can make using technology which is really efficient way for us to support people in the community when we just can't be everywhere at once. >> So, John, just to add, I think that we have about 1500 people living in households that are living alone and isolated. And I think the issue for us was more than just about technology because a lot of these people don't have access to basic technology features that most of us would take for granted. So far this is a two-prong journey. One is about increasing the accessibility to tech and familiarizing people so that they're comfortable with these devices technology and two importantly, make sure that we have the right means to help people reduce their loneliness and isolation. So the opportunity to try out something over the last 12 months, something that's bespoke, that's customized that will undoubtedly be tweaked as we go forward has been an absolutely marvelous opportunity. And for us, the collaboration with Accenture has been absolutely key. I think what we've seen during COVID is cross-fertilization. We've seen multi-disciplinary teams, we've got engineers, architects, manufacturers, and clinicians, and scientists, all trying to develop new solutions around COVID. And I think this probably just exemplary bias, especially as a post COVID where industry and in our case for example public sector and academia working together. >> Yeah, that's a great example and props to everyone there. And congratulations on this really, really important initiative. Let's talk about the home care solution. What does it do? How does it work? Take us through what's happening? >> Okay, so Home Care is actually a platform which is obviously running on AWS technology and this particular platform is the service offered accessible via voice through the Alexa device. We use the Echo Show to be able to use voice but also visuals to kind of make the technology more accessible for end user. On the platform itself, we have a series of services available out there. We connecting in the background a number of services from the community. So in the particular case of Hafod, we had something around shopping during the pandemic where we had people wanting to have access to their food bank. Or we also had during the pandemic, there was some need for having access to financial coaching and things like that. So we actually brought all of the service on the platform and the skills and this skill was really learning how to interact with the end user. And it was all customized for them to be able to access those things in a very easy way. It did work almost too well because some of our end users have been a kind of you know, have not been digital literate before and it was working so well, they were like, "But why can't it do pretty much anything on the planet? "Why can't it do this or that?" So the expectations were really, really high but we did manage to bring comfort to Hafod residents in a number of their daily kind of a need, some of the things during COVID 'cause people couldn't meet face to face. There was some challenge around understanding what events are running. So the coaches would publish events, you know, through the skills and people would be able to subscribe and go to the event and meet together virtually instead of physically. The number of things that really kind of brought a voice enabled experience for those end users. >> You know, you mentioned the people like the solution just before we, I'm going to get the Jamie in a second, but I want to just bring up something that you brought up. This is a digital divide evolution because digital divide, as Josh was saying, is that none about technology,, first, you have to access, you need access, right? First, then you have to bring broadband and internet access. And then you have to get the technology in the home. But then here it seems to be a whole nother level of digital divide bridging to the new heights. >> Yeah, completely, completely. And I think that's where COVID has really accelerated the digital divide before the solution was put in place for Hafod in the sense that people couldn't move and if they were not digitally literate, it was very hard to have access to services. And now we brought this solution in the comfort of their own home and they have the access to the services that they wouldn't have had otherwise on their own. So it's definitely helping, yeah. >> It's just another example of people refactoring their lives or businesses with technology. Jamie, what's your take on the innovation here and the technical aspects of the home care solutions? >> I think the fact that it's so easy to use, it's personalized, it's a digital companion for the home. It overcomes that digital divide that we talked about, which is really important. If you've got a voice you can use home care and you can interact with it in this really simple way. And what I love about it is the fact that it was based on what our customers told us they were finding difficult during this time, during the early lockdowns of the pandemic. There was 1500 so people Jas talked about who were living alone and at risk of loneliness. Now we spoke to a good number of those through a series of welfare calls and we found out exactly what it is they found challenging. >> What were some of the things that they were finding challenging? >> So tracking how they feel on a day-to-day basis. What's my mood like, what's my wellbeing like, and knowing how that changes over time. Just keeping the fridge in the pantry stocked up. What can I cook with these basic ingredients that I've got in my home? You could be signposted to basic resources to help you with that. Staying connected to the people who are really important to you but the bit that shines out for me is the interface with our services, with our neighborhood coaching service, where we can just give these little nudges, these little interventions just to mitigate and take the edge of that loneliness for people. We can see the potential of that coming up to the pandemic, where you can really encourage people to interact with one another, to be physically active and do all of those things that sort of mitigate against loneliness. >> Let me ask you a question 'cause I think a very important point. The timing of the signaling of data is super important. Could you comment on the relevance of having access to data? If you're getting something connected, when you're connected like this, I can only imagine the benefits. It's all about timing, right? Knowing that someone might be thinking some way or whether it's a tactical, in any scenario, timing of data, the right place at the right time, as they say. What's your take on that 'cause it sounds like what you're saying is that you can see things early when people are in the moment. >> Yeah, exactly. So if there's a trend beginning to emerge, for example, around some of these wellbeing, which has been on a low trajectory for a number of days, that can raise a red flag in our system and it alerts one of our neighborhood coaches just to reach out to that person and say, "Well, John, what's going on? "You haven't been out for a walk for a few days. "We know you like to walk, what's happening?" And these early warning signs are really important when we think of the long-term effects of loneliness and how getting upstream of those, preventing it reaching a point where it moves from being a problem into being a crisis. And the earlier we can detect that the more chance we've got of these negative long-term outcomes being mitigated. >> You know, one of the things we see in the cloud business is kind of separate track but it kind of relates to the real world here that you're doing, is automation and AI and machine learning bringing in a lot of value if applied properly. So how are you guys seeing, I can almost imagine that patterns are coming in, right? Do you see patterns in the data? How does AI and analytics technology improve this process especially with the wellbeing and emotional wellbeing of the elderly? >> I think one of the things we've learned through the pilot study we've done is there's not one size fits all. You know, all those people are very different individuals. They have very different habits. You know, there's some people not sleeping over the night. There's some people wanting to be out early, wanting to be social. Some people you have to put in much more. So it's definitely not one size fits all. And automation and digitalization of those kinds of services is really challenging because if they're not personalized, it doesn't really catch the interest or the need of the individuals. So for me as an IT professional being in the industry for like a 20 plus years, I think this is the time where personalization has really a true meaning. Personalization at scale for those people that are not digitally literate. But also in more vulnerable settings 'cause there's just so many different angles that can make them vulnerable. Maybe it's the body, maybe it's the economy position, their social condition, there's so many variation of all of that. So I think this is one of the use case that has to be powered by technology to complement the human side of it. If we really want to start scaling the services we provide to people in general, meaning obviously, in all the Western country now we all growing old, it's no secret. So in 20 years time the majority of everybody will be old and we obviously need people to take care of us. And at the moment we don't have that population to take care of us coming up. So really to crack on those kinds of challenges, we really need to have technology powering and just helping the human side to make it more efficient, connected than human. >> It's interesting. I just did a story where you have these bots that look at the facial recognition via cameras and can detect either in hospitals and or in care patients, how they feel. So you see where this is going. Jas I got to ask you how all this changes, the home care model and how Hafod works. Your workforce, the career's culture, the consortium you guys are bringing to the table, partners, you know this is an ecosystem now, it's a system. >> Yes John, I think that probably, it's also worth talking a little bit about the pressures on state governments around public health issues which are coming to the fore. And clearly we need to develop alternative ways that we engage with mass audiences and technology is going to be absolutely key. One of the challenges I still think that we've not resolved in the U.K. level, this is probably a global issue, is about data protection. When we're talking to cross governmental agencies, it's about sharing data and establishing protocols and we've enjoyed a few challenging conversations with colleagues around data protection. So I think those need to be set out in the context of the journey of this particular project. I think that what's interesting around COVID is that, hasn't materially changed the nature in which we do things, probably not in our focus and our work remains the same. But what we're seeing is very clear evidence of the ways, I mean, who would have thought that 12 months ago, the majority of our workforce would be working from home? So rapid mobilization to ensure that people can use, set IT home effectively. And then how does that relationship impact with people in the communities we're serving? Some of whom have got access to technology, others who haven't. So that's been, I think the biggest change, and that is a fundamental change in the design and delivery of future services that organizations like us will be providing. So I would say that overall, some things remain the same by and large but technology is having an absolutely profound change in the way that our engagement with customers will go forward. >> Well, you guys are in the front end of some massive innovation here with this, are they possible and that, you're really delivering impact. And I think this is an example of that. And you brought up the data challenges, this is something that you guys call privacy by design. This is a cutting edge issue here because there are benefits around managing privacy properly. And I think here, your solution clearly has value, right? And no one can debate that, but as these little blockers get in the way, what's your reaction to that? 'Cause this certainly is something that has to be solved. I mean, it's a problem. >> Yeah, so we designed a solution, I think we had, when we design, I co-designed with your end-users actually. We had up to 14 lawyers working with us at one point in time looking at different kinds of angles. So definitely really tackle the solution with privacy by design in mind and with end users but obviously you can't co-design with thousands of people, you have to co-design with a representative subset of a cohort. And some of the challenge we find is obviously, the media have done a lot of scaremongering around technology, AI and all of that kind of things, especially for people that are not necessarily digitally literate, people that are just not in it. And when we go and deploy the solution, people are a little bit worried. When we make them, we obviously explain to them what's going to happen if they're happy, if they want to consent and all that kind of things. But the people are scared, they're just jumping on a technology on top of it we're asking them some questions around consent. So I think it's just that the solution is super secured and we've gone over millions of hoops within Accenture but also with Hafod itself. You know, it's more that like the type of user we deploying the solution to are just not in that world and then they are little bit worried about sharing. Not only they're worried about sharing with us but you know, in home care, there there's an option as well to share some of that data with your family. And there we also see people are kind of okay to share with us but they don't want to share with their family 'cause they don't want to have too much information kind of going potentially worrying or bothering some of their family member. So there is definitely a huge education kind of angle to embracing the technology. Not only when you create the solution but when you actually deploy it with users. >> It's a fabulous project, I am so excited by this story. It's a great story, has all the elements; technology, innovation, cidal impact, data privacy, social interactions, whether it's with family members and others, internal, external. In teams themselves. You guys doing some amazing work, thank you for sharing. It's a great project, we'll keep track of it. My final question for you guys is what comes next for the home care after the trial? What are Hafod's plans and hopes for the future? >> Maybe if I just give an overview and then invite Jamie and Laetitia. So for us, without conversations, you don't create possibilities and this really is a reflection of the culture that we try to engender. So my ask of my team is to remain curious, is to continue to explore opportunities because it's home care up to today, it could be something else tomorrow. We also recognize that we live in a world of collaboration. We need more cross industrial partnerships. We love to explore more things that Accenture, Amazon, others as well. So that's principally what I will be doing is ensuring that the culture invites us and then I hand over to the clever people like Jamie and Laetitia to get on with the technology. I think for me we've already learned an awful lot about home care and there's clearly a lot more we can learn. We'd love to build on this initial small-scale trial and see how home care could work at a bigger scale. So how would it work with thousands of users? How do we scale it up from a cohort of 50 to a cohort of 5,000? How does it work when we bring different kinds of organizations into that mix? So what if, for example, we could integrate it into health care? So a variety of services can have a holistic view of an individual and interact with one another, to put that person on the right pathway and maybe keep them out of the health and care system for longer, actually reducing the costs to the system in the long run and improving that person's outcomes. That kind of evidence speaks to decision-makers and political partners and I think that's the kind of evidence we need to build. >> Yeah, financial impact is there, it's brutal. It's a great financial impact for the system. Efficiency, better care, everything. >> Yeah and we are 100% on board for whatever comes next. >> Laetitia-- >> What about you Laetitia? >> Great program you got there. A amazing story, thank you for sharing. Congratulations on this awesome project. So much to unpack here. I think this is the future. I mean, I think this is a case study of represents all the moving parts that need to be worked on, so congratulations. >> Thank you. >> Thank you. >> We are the Art of the Possible here inside the Cube, part of AWS Reinvent Executive Summit, I'm John Furrier, your host, thanks for watching. (bright upbeat music)

>>Hello. And we're here at the cube startup showcase made possible by a Ws. Thanks so much for joining us today. You know when Jim McDaid Ghani was formulating her ideas around data mesh, She wasn't the only one thinking about decentralized data architecture. Hello, Fresh was going into hyper growth mode and realized that in order to support its scale, it needed to rethink how it thought about data. Like many companies that started in the early part of last decade, Hello Fresh relied on a monolithic data architecture and the internal team. It had concerns about its ability to support continued innovation at high velocity. The company's data team began to think about the future and work backwards from a target architecture which possessed many principles of so called data mesh even though they didn't use that term. Specifically, the company is a strong example of an early but practical pioneer of data mission. Now there are many practitioners and stakeholders involved in evolving the company's data architecture, many of whom are listed here on this on the slide to are highlighted in red are joining us today, we're really excited to welcome into the cube Clements cheese, the Global Senior Director for Data at Hello Fresh and christoph Nevada who's the Global Senior Director of data also, of course. Hello Fresh folks. Welcome. Thanks so much for making some time today and sharing your story. >>Thank you very much. Hey >>steve. All right, let's start with Hello Fresh. You guys are number one in the world in your field, you deliver hundreds of millions of meals each year to many, many millions of people around the globe. You're scaling christoph. Tell us a little bit more about your company and its vision. >>Yeah. Should I start or Clements maybe maybe take over the first piece because Clements has actually been a longer trajectory yet have a fresh. >>Yeah go ahead. Climate change. I mean yes about approximately six years ago I joined handle fresh and I didn't think about the startup I was joining would eventually I. P. O. And just two years later and the freshman public and approximately three years and 10 months after. Hello fresh was listed on the German stock exchange which was just last week. Hello Fresh was included in the Ducks Germany's leading stock market index and debt to mind a great great milestone and I'm really looking forward and I'm very excited for the future for the future for head of fashion. All our data. Um the vision that we have is to become the world's leading food solution group and there's a lot of attractive opportunities. So recently we did lounge and expand Norway. This was in july and earlier this year we launched the U. S. Brand green >>chef in the U. K. As >>well. We're committed to launch continuously different geographies in the next coming years and have a strong pipe ahead of us with the acquisition of ready to eat companies like factor in the U. S. And the planned acquisition of you foods in Australia. We're diversifying our offer now reaching even more and more untapped customer segments and increase our total addressable market. So by offering customers and growing range of different alternatives to shop food and consumer meals. We are charging towards this vision and the school to become the world's leading integrated food solutions group. >>Love it. You guys are on a rocket ship, you're really transforming the industry and as you expand your tam it brings us to sort of the data as a as a core part of that strategy. So maybe you guys could talk a little bit about your journey as a company specifically as it relates to your data journey. You began as a start up. You had a basic architecture like everyone. You made extensive use of spreadsheets. You built a Hadoop based system that started to grow and when the company I. P. O. You really started to explode. So maybe describe that journey from a data perspective. >>Yes they saw Hello fresh by 2015 approximately had evolved what amount of classical centralized management set up. So we grew very organically over the years and there were a lot of very smart people around the globe. Really building the company and building our infrastructure. Um This also means that there were a small number of internal and external sources. Data sources and a centralized the I team with a number of people producing different reports, different dashboards and products for our executives for example of our different operations teams, christian company's performance and knowledge was transferred um just via talking to each other face to face conversations and the people in the data where's team were considered as the data wizard or as the E. T. L. Wizard. Very classical challenges. And those et al. Reserves indicated the kind of like a silent knowledge of data management. Right? Um so a central data whereas team then was responsible for different type of verticals and different domains, different geographies and all this setup gave us to the beginning the flexibility to grow fast as a company in 2015 >>christoph anything that might add to that. >>Yes. Um Not expected to that one but as as clement says it right, this was kind of set up that actually work for us quite a while. And then in 2017 when L. A. Freshman public, the company also grew rapidly and just to give you an idea how that looked like. As was that the tech department self actually increased from about 40 people to almost 300 engineers And the same way as a business units as Clemens has described, also grew sustainable, sustainably. So we continue to launch hello fresh and new countries launching brands like every plate and also acquired other brands like much of a factor and with that grows also from a data perspective the number of data requests that centrally we're getting become more and more and more and also more and more complex. So that for the team meant that they had a fairly high mental load. So they had to achieve a very or basically get a very deep understanding about the business. And also suffered a lot from this context switching back and forth, essentially there to prioritize across our product request from our physical product, digital product from the physical from sorry, from the marketing perspective and also from the central reporting uh teams. And in a nutshell this was very hard for these people. And this that also to a situation that, let's say the solution that we have became not really optimal. So in a nutshell, the central function became a bottleneck and slowdown of all the innovation of the company. >>It's a classic case, isn't it? I mean Clements, you see you see the central team becomes a bottleneck and so the lines of business, the marketing team salesman's okay, we're going to take things into our own hands. And then of course I I. T. And the technical team is called in later to clean up the mess. Uh maybe, I mean was that maybe I'm overstating it, but that's a common situation, isn't it? >>Yeah. Uh This is what exactly happened. Right. So um we had a bottleneck, we have the central teams, there was always a little of tension um analytics teams then started in this business domains like marketing, trade chain, finance, HR and so on. Started really to build their own data solutions at some point you have to get the ball rolling right and then continue the trajectory um which means then that the data pipelines didn't meet the engineering standards. And um there was an increased need for maintenance and support from central teams. Hence over time the knowledge about those pipelines and how to maintain a particular uh infrastructure for example left the company such that most of those data assets and data sets are turned into a huge step with decreasing data quality um also decrease the lack of trust, decreasing transparency. And this was increasing challenge where majority of time was spent in meeting rooms to align on on data quality for example. >>Yeah. And and the point you were making christoph about context switching and this is this is a point that Jemaah makes quite often is we've we've we've contextualized are operational systems like our sales systems, our marketing system but not our our data system. So you're asking the data team, Okay. Be an expert in sales, be an expert in marketing, be an expert in logistics, be an expert in supply chain and it start stop, start, stop, it's a paper cut environment and it's just not as productive. But but on the flip side of that is when you think about a centralized organization you think, hey this is going to be a very efficient way, a cross functional team to support the organization but it's not necessarily the highest velocity, most effective organizational structure. >>Yeah, so so I agree with that. Is that up to a certain scale, a centralized function has a lot of advantages, right? That's clear for everyone which would go to some kind of expert team. However, if you see that you actually would like to accelerate that and specific and this hyper growth, right, you wanna actually have autonomy and certain teams and move the teams or let's say the data to the experts in these teams and this, as you have mentioned, right, that increases mental load and you can either internally start splitting your team into a different kind of sub teams focusing on different areas. However, that is then again, just adding another peace where actually collaboration needs to happen busy external sees, so why not bridging that gap immediately and actually move these teams and to end into into the function themselves. So maybe just to continue what, what was Clements was saying and this is actually where over. So Clements, my journey started to become one joint journey. So Clements was coming actually from one of these teams to build their own solutions. I was basically having the platform team called database housed in these days and in 2019 where basically the situation become more and more serious, I would say so more and more people have recognized that this model doesn't really scale In 2019, basically the leadership of the company came together and I identified data as a key strategic asset and what we mean by that, that if we leverage data in a proper way, it gives us a unique competitive advantage which could help us to, to support and actually fully automated our decision making process across the entire value chain. So what we're, what we're trying to do now or what we should be aiming for is that Hello, Fresh is able to build data products that have a purpose. We're moving away from the idea. Data is just a by problem products, we have a purpose why we would like to collect this data. There's a clear business need behind that. And because it's so important to for the company as a business, we also want to provide them as a trust versi asset to the rest of the organization. We say there's the best customer experience, but at least in a way that users can easily discover, understand and security access high quality data. >>Yeah, so and and and Clements, when you c J Maxx writing, you see, you know, she has the four pillars and and the principles as practitioners you look at that say, okay, hey, that's pretty good thinking and then now we have to apply it and that's and that's where the devil meets the details. So it's the four, you know, the decentralized data ownership data as a product, which we'll talk about a little bit self serve, which you guys have spent a lot of time on inclement your wheelhouse which is which is governance and a Federated governance model. And it's almost like if you if you achieve the first two then you have to solve for the second to it almost creates a new challenges but maybe you could talk about that a little bit as to how it relates to Hello fresh. >>Yes. So christophe mentioned that we identified economic challenge beforehand and for how can we actually decentralized and actually empower the different colleagues of ours. This was more a we realized that it was more an organizational or a cultural change and this is something that somebody also mentioned I think thought words mentioned one of the white papers, it's more of a organizational or cultural impact and we kicked off a um faced reorganization or different phases we're currently and um in the middle of still but we kicked off different phases of organizational reconstruct oring reorganization, try unlock this data at scale. And the idea was really moving away from um ever growing complex matrix organizations or matrix setups and split between two different things. One is the value creation. So basically when people ask the question, what can we actually do, what shall we do? This is value creation and how, which is capability building and both are equal in authority. This actually then creates a high urge and collaboration and this collaboration breaks up the different silos that were built and of course this also includes different needs of stuffing forward teams stuffing with more, let's say data scientists or data engineers, data professionals into those business domains and hence also more capability building. Um Okay, >>go ahead. Sorry. >>So back to Tzemach did johnny. So we the idea also Then crossed over when she published her papers in May 2019 and we thought well The four colors that she described um we're around decentralized data ownership, product data as a product mindset, we have a self service infrastructure and as you mentioned, Federated confidential governance. And this suited very much with our thinking at that point of time to reorganize the different teams and this then leads to a not only organisational restructure but also in completely new approach of how we need to manage data, show data. >>Got it. Okay, so your business is is exploding. Your data team will have to become domain experts in too many areas, constantly contact switching as we said, people started to take things into their own hands. So again we said classic story but but you didn't let it get out of control and that's important. So we actually have a picture of kind of where you're going today and it's evolved into this Pat, if you could bring up the picture with the the elephant here we go. So I would talk a little bit about the architecture, doesn't show it here, the spreadsheet era but christoph maybe you can talk about that. It does show the Hadoop monolith which exists today. I think that's in a managed managed hosting service, but but you you preserve that piece of it, but if I understand it correctly, everything is evolving to the cloud, I think you're running a lot of this or all of it in A W. S. Uh you've got everybody's got their own data sources, uh you've got a data hub which I think is enabled by a master catalog for discovery and all this underlying technical infrastructure. That is really not the focus of this conversation today. But the key here, if I understand it correctly is these domains are autonomous and not only that this required technical thinking, but really supportive organizational mindset, which we're gonna talk about today. But christoph maybe you could address, you know, at a high level some of the architectural evolution that you guys went through. >>Yeah, sure. Yeah, maybe it's also a good summary about the entire history. So as you have mentioned, right, we started in the very beginning with the model is on the operation of playing right? Actually, it wasn't just one model is both to one for the back end and one for the for the front and and or analytical plane was essentially a couple of spreadsheets and I think there's nothing wrong with spreadsheets, right, allows you to store information, it allows you to transform data allows you to share this information. It allows you to visualize this data, but all the kind of that's not actually separating concern right? Everything in one tool. And this means that obviously not scalable, right? You reach the point where this kind of management set up in or data management of isn't one tool reached elements. So what we have started is we've created our data lake as we have seen here on Youtube. And this at the very beginning actually reflected very much our operational populace on top of that. We used impala is a data warehouse, but there was not really a distinction between borders, our data warehouse and borders our data like the impala was used as a kind of those as the kind of engine to create a warehouse and data like construct itself and this organic growth actually led to a situation as I think it's it's clear now that we had to centralized model is for all the domains that will really lose kimball modeling standards. There was no uniformity used actually build in house uh ways of building materialized use abuse that we have used for the presentation layer, there was a lot of duplication of effort and in the end essentially they were missing feedbacks, food, which helped us to to improve of what we are filled. So in the end, in the natural, as we have said, the lack of trust and that's basically what the starting point for us to understand. Okay, how can we move away and there are a lot of different things that you can discuss of apart from this organizational structure that we have said, okay, we have these three or four pillars from from Denmark. However, there's also the next extra question around how do we implement our talking about actual right, what are the implications on that level? And I think that is there's something that we are that we are currently still in progress. >>Got it. Okay, so I wonder if we could talk about switch gears a little bit and talk about the organizational and cultural challenges that you faced. What were those conversations like? Uh let's dig into that a little bit. I want to get into governance as well. >>The conversations on the cultural change. I mean yes, we went through a hyper growth for the last year since obviously there were a lot of new joiners, a lot of different, very, very smart people joining the company which then results that collaboration uh >>got a bit more difficult. Of course >>there are times and changes, you have different different artifacts that you were created um and documentation that were flying around. Um so we were we had to build the company from scratch right? Um Of course this then resulted always this tension which I described before, but the most important part here is that data has always been a very important factor at l a fresh and we collected >>more of this >>data and continued to improve use data to improve the different key areas of our business. >>Um even >>when organizational struggles, the central organizational struggles data somehow always helped us to go through this this kind of change. Right? Um in the end those decentralized teams in our local geography ease started with solutions that serve the business which was very very important otherwise wouldn't be at the place where we are today but they did by all late best practices and standards and I always used sport analogy Dave So like any sport, there are different rules and regulations that need to be followed. These rules are defined by calling the sports association and this is what you can think about data governance and compliance team. Now we add the players to it who need to follow those rules and bite by them. This is what we then called data management. Now we have the different players and professionals, they need to be trained and understand the strategy and it rules before they can play. And this is what I then called data literacy. So we realized that we need to focus on helping our teams to develop those capabilities and teach the standards for how work is being done to truly drive functional excellence in a different domains. And one of our mission of our data literacy program for example is to really empower >>every employee at hello >>fresh everyone to make the right data informs decisions by providing data education that scaled by royal Entry team. Then this can be different things, different things like including data capabilities, um, with the learning paths for example. Right? So help them to create and deploy data products connecting data producers and data consumers and create a common sense and more understanding of each other's dependencies, which is important, for example, S. S. L. O. State of contracts and etcetera. Um, people getting more of a sense of ownership and responsibility. Of course, we have to define what it means, what does ownership means? But the responsibility means. But we're teaching this to our colleagues via individual learning patterns and help them up skill to use. Also, there's shared infrastructure and those self self service applications and overall to summarize, we're still in this progress of of, of learning, we are still learning as well. So learning never stops the tele fish, but we are really trying this um, to make it as much fun as possible. And in the end we all know user behavior has changed through positive experience. Uh, so instead of having massive training programs over endless courses of workshops, um, leaving our new journalists and colleagues confused and overwhelmed. >>We're applying um, >>game ification, right? So split different levels of certification where our colleagues can access, have had access points, they can earn badges along the way, which then simplifies the process of learning and engagement of the users and this is what we see in surveys, for example, where our employees that your justification approach a lot and are even competing to collect Those learning path batteries to become the # one on the leader board. >>I love the game ification, we've seen it work so well and so many different industries, not the least of which is crypto so you've identified some of the process gaps uh that you, you saw it is gloss over them. Sometimes I say paved the cow path. You didn't try to force, in other words, a new architecture into the legacy processes. You really have to rethink your approach to data management. So what what did that entail? >>Um, to rethink the way of data management. 100%. So if I take the example of Revolution, Industrial Revolution or classical supply chain revolution, but just imagine that you have been riding a horse, for example, your whole life and suddenly you can operate a car or you suddenly receive just a complete new way of transporting assets from A to B. Um, so we needed to establish a new set of cross functional business processes to run faster, dry faster, um, more robustly and deliver data products which can be trusted and used by downstream processes and systems. Hence we had a subset of new standards and new procedures that would fall into the internal data governance and compliance sector with internal, I'm always referring to the data operations around new things like data catalog, how to identify >>ownership, >>how to change ownership, how to certify data assets, everything around classical software development, which we know apply to data. This this is similar to a new thinking, right? Um deployment, versioning, QA all the different things, ingestion policies, policing procedures, all the things that suffer. Development has been doing. We do it now with data as well. And in simple terms, it's a whole redesign of the supply chain of our data with new procedures and new processes and as a creation as management and as a consumption. >>So data has become kind of the new development kit. If you will um I want to shift gears and talk about the notion of data product and, and we have a slide uh that we pulled from your deck and I'd like to unpack it a little bit. Uh I'll just, if you can bring that up, I'll read it. A data product is a product whose primary objective is to leverage on data to solve customer problems where customers, both internal and external. So pretty straightforward. I know you've gone much deeper and you're thinking and into your organization, but how do you think about that And how do you determine for instance who owns what? How did you get everybody to agree? >>I can take that one. Um, maybe let me start with the data product. So I think um that's an ongoing debate. Right? And I think the debate itself is an important piece here, right? That visit the debate, you clarify what we actually mean by that product and what is actually the mindset. So I think just from a definition perspective, right? I think we find the common denominator that we say okay that our product is something which is important for the company has come to its value what you mean by that. Okay, it's it's a solution to a customer problem that delivers ideally maximum value to the business. And yes, it leverages the power of data and we have a couple of examples but it had a fresh year, the historical and classical ones around dashboards for example, to monitor or error rates but also more sophisticated ways for example to incorporate machine learning algorithms in our recipe recommendations. However, I think the important aspects of the data product is a there is an owner, right? There's someone accountable for making sure that the product that we are providing is actually served and is maintained and there are, there is someone who is making sure that this actually keeps the value of that problem thing combined with the idea of the proper documentation, like a product description, right that people understand how to use their bodies is about and related to that peace is the idea of it is a purpose. Right? You need to understand or ask ourselves, Okay, why does this thing exist does it provide the value that you think it does. That leads into a good understanding about the life cycle of the data product and life cycle what we mean? Okay from the beginning from the creation you need to have a good understanding, we need to collect feedback, we need to learn about that. We need to rework and actually finally also to think about okay benefits time to decommission piece. So overall, I think the core of the data product is product thinking 11 right that we start the point is the starting point needs to be the problem and not the solution and this is essentially what we have seen what was missing but brought us to this kind of data spaghetti that we have built there in in Russia, essentially we built at certain data assets, develop in isolation and continuously patch the solution just to fulfill these articles that we got and actually these aren't really understanding of the stakeholder needs and the interesting piece as a result in duplication of work and this is not just frustrating and probably not the most efficient way how the company should work. But also if I build the same that assets but slightly different assumption across the company and multiple teams that leads to data inconsistency and imagine the following too narrow you as a management for management perspective, you're asking basically a specific question and you get essentially from a couple of different teams, different kind of grass, different kind of data and numbers and in the end you do not know which ones to trust. So there's actually much more ambiguity and you do not know actually is a noise for times of observing or is it just actually is there actually a signal that I'm looking for? And the same is if I'm running in a B test right, I have a new future, I would like to understand what has it been the business impact of this feature. I run that specific source in an unfortunate scenario. Your production system is actually running on a different source. You see different numbers. What you've seen in a B test is actually not what you see then in production typical thing then is you're asking some analytics tend to actually do a deep dive to understand where the discrepancies are coming from. The worst case scenario. Again, there's a different kind of source. So in the end it's a pretty frustrating scenario and that's actually based of time of people that have to identify the root cause of this divergence. So in a nutshell, the highest degree of consistency is actually achieved that people are just reusing Dallas assets and also in the media talk that we have given right, we we start trying to establish this approach for a B testing. So we have a team but just providing or is kind of owning their target metric associated business teams and they're providing that as a product also to other services including the A B testing team, they'll be testing team can use this information defines an interface is okay I'm joining this information that the metadata of an experiment and in the end after the assignment after this data collection face, they can easily add a graph to the dashboard. Just group by the >>Beatles Hungarian. >>And we have seen that also in other companies. So it's not just a nice dream that we have right. I have actually worked in other companies where we worked on search and we established a complete KPI pipeline that was computing all this information. And this information was hosted by the team and it was used for everything A B test and deep dives and and regular reporting. So uh just one of the second the important piece now, why I'm coming back to that is that requires that we are treating this data as a product right? If you want to have multiple people using the things that I am owning and building, we have to provide this as a trust mercy asset and in a way that it's easy for people to discover and actually work with. >>Yeah. And coming back to that. So this is to me this is why I get so excited about data mesh because I really do think it's the right direction for organizations. When people hear data product they say well, what does that mean? Uh but then when you start to sort of define it as you did, it's it's using data to add value, that could be cutting costs, that could be generating revenue, it could be actually directly you're creating a product that you monetize, So it's sort of in the eyes of the beholder. But I think the other point that we've made is you made it earlier on to and again, context. So when you have a centralized data team and you have all these P NL managers a lot of times they'll question the data because they don't own it. They're like wait a minute. If they don't, if it doesn't agree with their agenda, they'll attack the data. But if they own the data then they're responsible for defending that and that is a mindset change, that's really important. Um And I'm curious uh is how you got to, you know, that ownership? Was it a was it a top down with somebody providing leadership? Was it more organic bottom up? Was it a sort of a combination? How do you decide who owned what in other words, you know, did you get, how did you get the business to take ownership of the data and what is owning? You know, the data actually mean? >>That's a very good question. Dave I think this is one of the pieces where I think we have a lot of learnings and basically if you ask me how we could start the feeling. I think that would be the first piece. Maybe we need to start to really think about how that should be approached if it stopped his ownership. Right? It means somehow that the team has a responsibility to host and self the data efforts to minimum acceptable standards. This minimum dependencies up and down string. The interesting piece has been looking backwards. What what's happening is that under that definition has actually process that we have to go through is not actually transferring ownership from the central team to the distributor teams. But actually most cases to establish ownership, I make this difference because saying we have to transfer ownership actually would erroneously suggests that the data set was owned before. But this platform team, yes, they had the capability to make the changes on data pipelines, but actually the analytics team, they're always the ones who had the business understands, you use cases and but no one actually, but it's actually expensive expected. So we had to go through this very lengthy process and establishing ownership. We have done that, as in the beginning, very naively. They have started, here's a document here, all the data assets, what is probably the nearest neighbor who can actually take care of that and then we we moved it over. But the problem here is that all these things is kind of technical debt, right? It's not really properly documented, pretty unstable. It was built in a very inconsistent over years and these people who have built this thing have already left the company. So there's actually not a nice thing that is that you want to see and people build up a certain resistance, e even if they have actually bought into this idea of domain ownership. So if you ask me these learnings, but what needs to happen as first, the company needs to really understand what our core business concept that they have, they need to have this mapping from. These are the core business concept that we have. These are the domain teams who are owning this concept and then actually link that to the to the assets and integrated better with both understanding how we can evolve actually, the data assets and new data build things new in the in this piece in the domain. But also how can we address reduction of technical death and stabilizing what we have already. >>Thank you for that christoph. So I want to turn a direction here and talk about governance and I know that's an area that's passionate, you're passionate about. Uh I pulled this slide from your deck, which I kind of messed up a little bit sorry for that, but but by the way, we're going to publish a link to the full video that you guys did. So we'll share that with folks. But it's one of the most challenging aspects of data mesh, if you're going to decentralize you, you quickly realize this could be the Wild West as we talked about all over again. So how are you approaching governance? There's a lot of items on this slide that are, you know, underscore the complexity, whether it's privacy, compliance etcetera. So, so how did you approach this? >>It's yeah, it's about connecting those dots. Right. So the aim of the data governance program is about the autonomy of every team was still ensuring that everybody has the right interoperability. So when we want to move from the Wild West riding horses to a civilised way of transport, um you can take the example of modern street traffic, like when all participants can manoeuvre independently and as long as they follow the same rules and standards, everybody can remain compatible with each other and understand and learn from each other so we can avoid car crashes. So when I go from country to country, I do understand what the street infrastructure means. How do I drive my car? I can also read the traffic lights in the different signals. Um, so likewise as a business and Hello Fresh, we do operate autonomously and consequently need to follow those external and internal rules and standards to set forth by the redistribution in which we operate so in order to prevent a car crash, we need to at least ensure compliance with regulations to account for society's and our customers increasing concern with data protection and privacy. So teaching and advocating this advantage, realizing this to everyone in the company um was a key community communication strategy and of course, I mean I mentioned data privacy external factors, the same goes for internal regulations and processes to help our colleagues to adapt to this very new environment. So when I mentioned before the new way of thinking the new way of um dealing and managing data, this of course implies that we need new processes and regulations for our colleagues as well. Um in a nutshell then this means the data governance provides a framework for managing our people the processes and technology and culture around our data traffic. And those components must come together in order to have this effective program providing at least a common denominator, especially critical for shared dataset, which we have across our different geographies managed and shared applications on shared infrastructure and applications and is then consumed by centralized processes um for example, master data, everything and all the metrics and KPI s which are also used for a central steering. Um it's a big change day. Right. And our ultimate goal is to have this noninvasive, Federated um ultimatum and computational governance and for that we can't just talk about it. We actually have to go deep and use case by use case and Qc buy PVC and generate learnings and learnings with the different teams. And this would be a classical approach of identifying the target structure, the target status, match it with the current status by identifying together with the business teams with the different domains have a risk assessment for example, to increase transparency because a lot of teams, they might not even know what kind of situation they might be. And this is where this training and this piece of illiteracy comes into place where we go in and trade based on the findings based on the most valuable use case um and based on that help our teams to do this change to increase um their capability just a little bit more and once they hand holding. But a lot of guidance >>can I kind of kind of trying to quickly David will allow me I mean there's there's a lot of governance piece but I think um that is important. And if you're talking about documentation for example, yes, we can go from team to team and tell these people how you have to document your data and data catalog or you have to establish data contracts and so on the force. But if you would like to build data products at scale following actual governance, we need to think about automation right. We need to think about a lot of things that we can learn from engineering before. And that starts with simple things like if we would like to build up trust in our data products, right, and actually want to apply the same rigor and the best practices that we know from engineering. There are things that we can do and we should probably think about what we can copy and one example might be. So the level of service level agreements, service level objectives. So that level indicators right, that represent on on an engineering level, right? If we're providing services there representing the promises we made to our customers or consumers, these are the internal objectives that help us to keep those promises. And actually these are the way of how we are tracking ourselves, how we are doing. And this is just one example of that thing. The Federated Governor governance comes into play right. In an ideal world, we should not just talk about data as a product but also data product. That's code that we say, okay, as most as much as possible. Right? Give the engineers the tool that they are familiar basis and actually not ask the product managers for example to document their data assets in the data catalog but make it part of the configuration. Have this as a, as a C D C I, a continuous delivery pipeline as we typically see another engineering task through and services we say, okay, there is configuration, we can think about pr I can think about data quality monitoring, we can think about um the ingestion data catalog and so on and forest, I think ideally in the data product will become of a certain templates that can be deployed and are actually rejected or verified at build time before we actually make them deploy them to production. >>Yeah, So it's like devoPS for data product um so I'm envisioning almost a three phase approach to governance and you kind of, it sounds like you're in early phases called phase zero where there's there's learning, there's literacy, there's training, education, there's kind of self governance and then there's some kind of oversight, some a lot of manual stuff going on and then you you're trying to process builders at this phase and then you codify it and then you can automate it. Is that fair? >>Yeah, I would rather think think about automation as early as possible in the way and yes, there needs to be certain rules but then actually start actually use case by use case. Is there anything that small piece that we can already automate? It's as possible. Roll that out and then actually extended step by step, >>is there a role though that adjudicates that? Is there a central Chief state officer who is responsible for making sure people are complying or is it how do you handle that? >>I mean from a from a from a platform perspective, yes, we have a centralized team to uh implement certain pieces they'll be saying are important and actually would like to implement. However, that is actually working very closely with the governance department. So it's Clements piece to understand and defy the policies that needs to be implemented. >>So Clements essentially it's it's your responsibility to make sure that the policy is being followed. And then as you were saying, christoph trying to compress the time to automation as fast as possible percent. >>So >>it's really it's uh >>what needs to be really clear that it's always a split effort, Right? So you can't just do one thing or the other thing, but everything really goes hand in hand because for the right automation for the right engineering tooling, we need to have the transparency first. Uh I mean code needs to be coded so we kind of need to operate on the same level with the right understanding. So there's actually two things that are important which is one its policies and guidelines, but not only that because more importantly or even well equally important to align with the end user and tech teams and engineering and really bridge between business value business teams and the engineering teams. >>Got it. So just a couple more questions because we gotta wrap I want to talk a little bit about the business outcome. I know it's hard to quantify and I'll talk about that in a moment but but major learnings, we've got some of the challenges that you cited. I'll just put them up here. We don't have to go detailed into this, but I just wanted to share with some folks. But my question, I mean this is the advice for your peers question if you had to do it differently if you had a do over or a Mulligan as we like to say for you golfers, what would you do differently? Yeah, >>I mean can we start with from a from the transformational challenge that understanding that it's also high load of cultural change. I think this is this is important that a particular communication strategy needs to be put into place and people really need to be um supported. Right? So it's not that we go in and say well we have to change towards data mesh but naturally it's in human nature, you know, we're kind of resistance to to change right? Her speech uncomfortable. So we need to take that away by training and by communicating um chris we're gonna add something to that >>and definitely I think the point that I have also made before right we need to acknowledge that data mesh is an architecture of scale, right? You're looking for something which is necessary by huge companies who are vulnerable, data productive scale. I mean Dave you mentioned it right, there are a lot of advantages to have a centralized team but at some point it may make sense to actually decentralized here and at this point right? If you think about data Mash, you have to recognize that you're not building something on a green field. And I think there's a big learning which is also reflected here on the slide is don't underestimate your baggage. It's typically you come to a point where the old model doesn't doesn't broke anymore and has had a fresh right? We lost our trust in our data and actually we have seen certain risks that we're slowing down our innovation so we triggered that this was triggering the need to actually change something. So this transition implies that you typically have a lot of technical debt accumulated over years and I think what we have learned is that potentially we have decentralized some assets to earlier, this is not actually taking into account the maturity of the team where we are actually distributed to and now we actually in the face of correcting pieces of that one. Right? But I think if you if you if you start from scratch you have to understand, okay, is are my team is actually ready for taking on this new uh, this news capabilities and you have to make sure that business decentralization, you build up these >>capabilities and the >>teams and as Clements has mentioned, right, make sure that you take the people on your journey. I think these are the pieces that also here, it comes with this knowledge gap, right? That we need to think about hiring and literacy the technical depth I just talked about and I think the last piece that I would add now which is not here on the flight deck is also from our perspective, we started on the analytical layer because that's kind of where things are exploding, right, this is the thing that people feel the pain but I think a lot of the efforts that we have started to actually modernize the current state uh, towards data product towards data Mash. We've understood that it always comes down basically to a proper shape of our operational plane and I think what needs to happen is is I think we got through a lot of pains but the learning here is this need to really be a commitment from the company that needs to happen and to act. >>I think that point that last point you made it so critical because I I hear a lot from the vendor community about how they're gonna make analytics better and that's that's not unimportant, but but through data product thinking and decentralized data organizations really have to operationalize in order to scale. So these decisions around data architecture an organization, their fundamental and lasting, it's not necessarily about an individual project are why they're gonna be project sub projects within this architecture. But the architectural decision itself is an organizational, its cultural and what's the best approach to support your business at scale. It really speaks to to to what you are, who you are as a company, how you operate and getting that right, as we've seen in the success of data driven driven companies is yields tremendous results. So I'll ask each of you to give give us your final thoughts and then we'll wrap maybe >>maybe it quickly, please. Yeah, maybe just just jumping on this piece that you have mentioned, right, the target architecture. If we talk about these pieces right, people often have this picture of mind like OK, there are different kind of stages, we have sources, we have actually ingestion layer, we have historical transformation presentation layer and then we're basically putting a lot of technology on top of that kind of our target architecture. However, I think what we really need to make sure is that we have these different kind of viewers, right? We need to understand what are actually the capabilities that we need in our new goals. How does it look and feel from the different kind of personas and experience view? And then finally, that should actually go to the to the target architecture from a technical perspective um maybe just to give an outlook but what we're what we're planning to do, how we want to move that forward. We have actually based on our strategy in the in the sense of we would like to increase that to maturity as a whole across the entire company and this is kind of a framework around the business strategy and it's breaking down into four pillars as well. People meaning the data, cultural, data literacy, data organizational structure and so on that. We're talking about governance as Clements has actually mentioned that, right, compliance, governance, data management and so on. You talk about technology and I think we could talk for hours for that one. It's around data platform, better science platform and then finally also about enablement through data, meaning we need to understand that a quality data accessibility and the science and data monetization. >>Great, thank you christophe clement. Once you bring us home give us your final thoughts. >>Can't can just agree with christoph that uh important is to understand what kind of maturity people have to understand what the maturity level, where the company where where people organization is and really understand what does kind of some kind of a change replies to that those four pillars for example, um what needs to be taken first and this is not very clear from the very first beginning of course them it's kind of like Greenfield you come up with must wins to come up with things that we really want to do out of theory and out of different white papers. Um only if you really start conducting the first initiatives you do understand. Okay, where we have to put the starts together and where do I missed out on one of those four different pillars? People, process technology and governance. Right? And then that kind of an integration. Doing step by step, small steps by small steps not boiling the ocean where you're capable ready to identify the gaps and see where either you can fill um the gaps are where you have to increase maturity first and train people or increase your text text, >>you know Hello Fresh is an excellent example of a company that is innovating. It was not born in Silicon Valley which I love. It's a global company. Uh and I gotta ask you guys, it seems like this is an amazing place to work you guys hiring? >>Yes, >>definitely. We do >>uh as many rights as was one of these aspects distributing. And actually we are hiring as an entire company specifically for data. I think there are a lot of open roles serious. Please visit or our page from better engineering, data, product management and Clemens has a lot of rules that you can speak about. But yes >>guys, thanks so much for sharing with the cube audience, your, your pioneers and we look forward to collaborations in the future to track progress and really want to thank you for your time. >>Thank you very much. Thank you very much. Dave >>thank you for watching the cubes startup showcase made possible by A W. S. This is Dave Volonte. We'll see you next time. >>Yeah.

>>Okay. Now we're going to dig into the data landscape and cloud of course. And talk a little bit more about that with drew Allen. He's a managing director at Accenture drew. Welcome. Great to see you. Thank you. So let's talk a little bit about, you know, you've been in this game for a number of years. Uh, you've got a particular expertise in, in, in data and finance and insurance. I mean, you think about it within the data and analytics world, even our language is changing. You know, we don't say talk about big data so much anymore. We, we talk more about digital, you know, or, or, or data-driven when you think about sort of where we've come from and where we're going, what are the puts and takes that you have with regard to what's going on in the business today? >>Well, thanks for having me. Um, you know, I think some of the trends we're seeing in terms of challenges and puts some takes are that a lot of companies are already on this digital transformation journey. Um, they focused on customer experience is kind of table stakes. Everyone wants to focus on that and kind of digitizing their channels. But a lot of them are seeing that, you know, a lot of them don't even own their, their channels necessarily. So like we're working with a big cruise line, right. And yes, they've invested in digitizing what they own, but a lot of the channels that they sell through, they don't even own, right. It's the travel agencies or third-party real sellers. So having the data to know where, you know, where those agencies are, that that's something that they've discovered. And so there's a lot of big focus on not just digitizing, but also really understanding your customers and going across products because a lot of the data has built, been built up in individual channels and in digital products. >>And so bringing that data together is something that customers that have really figured out in the last few years is a big differentiator. And what we're seeing too, is that a big trend that the data rich are getting richer. So companies that have really invested in data, um, are having, uh, an outside market share and outside earnings per share and outside revenue growth. And it's really being a big differentiator. And I think for companies just getting started in this, the thing to think about is one of the missteps is to not try to capture all the data at once. The average company has, you know, 10,000, 20,000 data elements individually, when you want to start out, you know, 500, 300 critical data elements, about 5% of the data of a company drives 90% of the business value. So focusing on, on those key critical data elements is really what you need to govern first and really invest in first. And so that's something we tell companies at the beginning of their data strategy is first focus on those critical data elements, really get a handle on governing that data, organizing that data and building data products around >>That data. You can't boil the ocean. Right. And so, and I, I feel like pre pandemic, there was a lot of complacency. Oh yeah, we'll get to that. You know, not on my watch, I'll be retired before that, you know, it becomes a minute. And then of course the pandemic was, I call it sometimes a forced March to digital. So in many respects, it wasn't planned. It just ha you know, you had to do it. And so now I feel like people are stepping back and saying, okay, let's now really rethink this and do it right. But is there, is there a sense of urgency, do you think? >>Absolutely. I think with COVID, you know, we were working with, um, a retailer where they had 12,000 stores across the U S and they had didn't have the insights where they could drill down and understand, you know, with the riots and with COVID was the store operational, you know, with the supply chain of they having multiple, uh, distributors, what did they have in stock? So there are millions of data points that you need to drill down, down at the cell level, at the store level to really understand how's my business performing. And we like to think about it for like a CEO and his leadership team of like, think of it as a digital cockpit, right? You think about a pilot, they have a cockpit with all these dials and, um, dashboards, essentially understanding the performance of their business. And they should be able to drill down and understand for each individual, you know, unit of their work, how are they performing? That's really what we want to see for businesses. Can they get down to that individual performance to really understand how their businesses and >>The ability to connect those dots and traverse those data points and not have to go in and come back out and go into a new system and come back out. And that's really been a lot of the frustration where does machine intelligence and AI fit in? Is that sort of a dot connector, if you will, and an enabler, I mean, we saw, you know, decades of the, the AI winter, and then, you know, there's been a lot of talk about it, but it feels like with the amount of data that we've collected over the last decade and the, the, the low costs of processing that data now, it feels like it's, it's real. Where do you see AI fitting in? Yeah, >>I mean, I think there's been a lot of innovation in the last 10 years with, um, the low cost of storage and computing and these algorithms in non-linear, um, you know, knowledge graphs, and, um, um, a whole bunch of opportunities in cloud where what I think the, the big opportunity is, you know, you can apply AI in areas where a human just couldn't have the scale to do that alone. So back to the example of a cruise lines, you know, you may have a ship being built that has 4,000 cabins on the single cruise line, and it's going to multiple deaths that destinations over its 30 year life cycle. Each one of those cabins is being priced individually for each individual destination. It's physically impossible for a human to calculate the dynamic pricing across all those destinations. You need a machine to actually do that pricing. And so really what a machine is leveraging is all that data to really calculate and assist the human, essentially with all these opportunities where you wouldn't have a human being able to scale up to that amount of data >>Alone. You know, it's interesting. One of the things we talked to Mick Halston about earlier was just the everybody's algorithms are out of whack. You know, you look at the airline pricing, you look at hotels it's as a consumer, you would be able to kind of game the system and predict a, they can't even predict these days. And I feel as though that the data and AI are actually going to bring us back into some kind of normalcy and predictability, uh, w what do you see in that regard? >>Yeah, I think it's, I mean, we're definitely not at a point where when I talk to, you know, the top AI engineers and data scientists, we're not at a point where we have what they call broad AI, right? Where you can get machines to solve general knowledge problems, where they can solve one problem, and then a distinctly different problem, right? That's still many years away, but narrow AI, there's still tons of use cases out there that can really drive tons of business performance challenges, tons of accuracy challenges. So, for example, in the insurance industry, commercial lines, where I work a lot of the time, the biggest leakage of loss experience and pricing for commercial insurers is, um, people will go in as an agent and they'll select an industry to say, you know what, I'm a restaurant business. Um, I'll select this industry code to quote out a policy, but there's, let's say, you know, 12 dozen permutations, you could be an outdoor restaurant. >>You could be a bar, you could be a caterer, and all of that leads to different loss experience. So what this does is they built a machine learning algorithm. We've helped them do this, that actually at the time that they're putting in their name and address, it's crawling across the web and predicting in real time, you know, is this address actually, you know, a business that's a restaurant with indoor dining, does it have a bar is an outdoor dining, and it's that that's able to accurately more price the policy and reduce the loss experience. So there's a lot of that you can do, even with narrow AI that can really drive top line of business results. >>Yeah. I like that term narrow AI because getting things done is important. Let's talk about cloud a little bit because people talk about cloud first public cloud first doesn't necessarily mean public cloud only, of course. So where do you see things like what's the right operating model, the right regime hybrid cloud. We talked earlier about hybrid data help us squint through the cloud landscape. Yeah. >>I mean, I think for most right, most fortune 500 companies, they can't just their fingers and say, let's move all of our data centers to the cloud. They've got to move, you know, gradually. And it's usually a journey that's taking more than two to three plus years, even more than that in some cases. So they're half they have to move their data, uh, incrementally to the cloud. And what that means is that, that they have to move to a hybrid perspective where some of their data is on premise and some of it is publicly on the cloud. And so that's the term hybrid cloud essentially. And so what they've had to think about is from an intelligence perspective, the privacy of that data, where is it being moved? Can they reduce the replication of that data? Because ultimately you like, uh, replicating the data from on-premise to, to the cloud that introduces, you know, errors and data quality issues. So thinking about how do you manage, uh, you know, uh, on-premise and public cloud as a transition is something that Accenture thinks, thinks, and helps our clients do quite a bit. And how do you move them in a manner that's well-organized and well thought about? >>Yeah. So I've been a big proponent of sort of line of business lines of business becoming much more involved in, in the data pipeline, if you will, the data process, if you think about our major operational systems, they all have sort of line of business context in them. Then the salespeople, they know the CRM data and, you know, logistics folks. There they're very much in tune with ERP. I almost feel like for the past decade, the lines of business have been somewhat removed from the, the data team, if you will. And that, that seems to be changing. What are you seeing in terms of the line of line of business being much more involved in sort of end to end ownership if you will, if I can use that term of, uh, of the data and sort of determining things like helping determine anyway, the data quality and things of that nature. Yeah. >>I mean, I think this is where thinking about your data operating model and thinking about ideas of a chief data officer and having data on the CEO agenda, that's really important to get the lines of business, to really think about data sharing and reuse, and really getting them to, you know, kind of unlock the data because they do think about their data as a fiefdom data has value, but you've got to really get organizations in their silos to open it up and bring that data together because that's where the value is. You know, data doesn't operate. When you think about a customer, they don't operate in their journey across the business in silo channels. They don't think about, you know, I use only the web and then I use the call center, right? They think about that as just one experience. And that data is a single journey. >>So we like to think about data as a product. You know, you should think about a data in the same way. You think about your products as, as products, you know, data as a product, you should have the idea of like every two weeks you have releases to it. You have an operational resiliency to it. So thinking about that, where you can have a very product mindset to delivering your data, I think is very important for the success. And that's where kind of, there's not just the things about critical data elements and having the right platform architecture, but there's a soft stuff as well, like a product mindset to data, having the right data, culture, and business adoption and having the right value set mindset for, for data, I think is really, >>I think data as a product is a very powerful concept. And I think it maybe is uncomfortable to some people sometimes. And I think in the early days of big data, if you will, people thought, okay, data is a product going to sell my data, and that's not necessarily what you mean. You mean thinking about products or data that can fuel products that you can then monetize maybe as a product or as a, as, as a service. And I like to think about a new metric in the industry, which is how long does it take me to get from idea of I'm a business person. I have an idea for a data product. How long does it take me to get from idea to monetization? And that's going to be something that ultimately as a business person, I'm going to use to determine the success of my data team and my, my data architecture is, is that kind of thinking starting to really hit the marketplace. >>I mean, I insurers now are working, partnering with, you know, auto manufacturers to monetize, um, driver usage data, you know, on telematics to see, you know, driver behavior on how, you know, how auto manufacturers are using that data. That's very important to insurers, you know, so how an auto manufacturer can monetize that data is very important and also an insurance, you know, cyber insurance, um, are there news new ways we can look at how companies are being attacked with viruses and malware, and is there a way we can somehow monetize that information? So companies that are able to agily, you know, think about how can we, you know, collect this data, bring it together, think about it as a product, and then potentially, you know, sell it as a service is something that, um, company, successful companies are doing >>Great examples of data products, and it might be revenue generating, or it might be in the case of, you know, cyber, maybe it reduces my expected loss. Exactly. And it drops right to my bottom line. What's the relationship between Accenture and cloud era? Do you, I presume you guys meet at the customer, but maybe you could give us some insight as to yeah. So, >>Um, I I'm in the executive sponsor for, um, the Accenture cloud era partnership on the Accenture side. Uh, we do quite a lot of business together and, um, you know, Cloudera has been a great partner for us. Um, and they've got a great product in terms of the Cloudera data platform where, you know, what we do is as a big systems integrator for them, we help, um, you know, configure and we have a number of engineers across the world that come in and help in terms of, um, engineer architects and install, uh, cloud errors, data platform, and think about what are some of those, you know, value cases where you can really think about organizing data and bringing it together for all these different types of use cases. And really just as the examples we thought about. So the telematics, you know, um, in order to realize something like that, you're bringing in petabytes and huge scales of data that, you know, you just couldn't bring on a normal, uh, platform. You need to think about cloud. You need to think about speed of, of data and real-time insights and cloud errors, the right data platform for that. So, um, >>That'd be Cloudera ushered in the modern big data era. We, we kind of all know that, and it was, which of course early on, it was very services intensive. You guys were right there helping people think through there weren't enough data scientists. We've sort of all, all been through that. And of course in your wheelhouse industries, you know, financial services and insurance, they were some of the early adopters, weren't they? Yeah, >>Absolutely. Um, so, you know, an insurance, you've got huge amounts of data with loss history and, um, a lot with IOT. So in insurance, there's a whole thing of like sensorized thing in, uh, you know, taking the physical world and digitizing it. So, um, there's a big thing in insurance where, um, it's not just about, um, pricing out the risk of a loss experience, but actual reducing the loss before it even happens. So it's called risk control or loss control, you know, can we actually put sensors on oil pipelines or on elevators and, you know, reduce, um, you know, accidents before they happen. So we're, you know, working with an insurer to actually, um, listen to elevators as they move up and down and are there signals in just listening to the audio of an elevator over time that says, you know what, this elevator is going to need maintenance, you know, before a critical accident could happen. So there's huge applications, not just in structured data, but in unstructured data like voice and audio and video where a partner like Cloudera has a huge role apply. >>Great example of it. So again, narrow sort of use case for machine intelligence, but, but real value. True. We'll leave it like that. Thanks so much for taking some time. Thank you.

>>Have you ever wondered how we sequence the human genome, how your smartphone is so well smart, how we will ever analyze all the patient data for the new vaccines or even how we plan to send humans to Mars? Well, at Cloudera, we believe that data can make what is impossible today possible tomorrow we are the enterprise data cloud company. In fact, we provide analytics and machine learning technology that does everything from making your smartphone smarter, to helping scientists ensure that new vaccines are both safe and effective, big data, no problem out era, the enterprise data cloud company. >>So I think for a long time in this country, we've known that there's a great disparity between minority populations and the majority of population in terms of disease burden. And depending on where you live, your zip code has more to do with your health than almost anything else. But there are a lot of smaller, um, safety net facilities, as well as small academic medical colleges within the United States. And those in those smaller environments don't have the access, you know, to the technologies that the larger ones have. And, you know, I call that, uh, digital disparity. So I'm, Harry's in academic scientist center and our mission is to train diverse health care providers and researchers, but also provide services to underserved populations. As part of the reason that I think is so important for me hearing medical college, to do data science. One of the things that, you know, both Cloudera and Claire sensor very passionate about is bringing those height in technologies to, um, to the smaller organizations. >>It's very expensive to go to the cloud for these small organizations. So now with the partnership with Cloudera and Claire sets a clear sense, clients now enjoy those same technologies and really honestly have a technological advantage over some of the larger organizations. The reason being is they can move fast. So we were able to do this on our own without having to, um, hire data scientists. Uh, we probably cut three to five years off of our studies. I grew up in a small town in Arkansas and is one of those towns where the railroad tracks divided the blacks and the whites. My father died without getting much healthcare at all. And as an 11 year old, I did not understand why my father could not get medical attention because he was very sick. >>Since we come at my Harry are looking to serve populations that reflect themselves or affect the population. He came from. A lot of the data you find or research you find health is usually based on white men. And obviously not everybody who needs a medical provider is going to be a white male. >>One of the things that we're concerned about in healthcare is that there's bias in treatment already. We want to make sure those same biases do not enter into the algorithms. >>The issue is how do we get ahead of them to try to prevent these disparities? >>One of the great things about our dataset is that it contains a very diverse group of patients. >>Instead of just saying, everyone will have these results. You can break it down by race, class, cholesterol, level, other kinds of factors that play a role. So you can make the treatments in the long run. More specifically, >>Researchers are now able to use these technologies and really take those hypotheses from, from bench to bedside. >>We're able to overall improve the health of not just the person in front of you, but the population that, yeah, >>Well, the future is now. I love a quote by William Gibson who said the future is already here. It's just not evenly distributed. If we think hard enough and we apply things properly, uh, we can again take these technologies to, you know, underserved environments, um, in healthcare. Nobody should be technologically disadvantage. >>When is a car not just a car when it's a connected data driven ecosystem, dozens of sensors and edge devices gathering up data from just about anything road, infrastructure, other vehicles, and even pedestrians to create safer vehicles, smarter logistics, and more actionable insights. All the data from the connected car supports an entire ecosystem from manufacturers, building safer vehicles and fleet managers, tracking assets to insurers monitoring, driving behaviors to make roads safer. Now you can control the data journey from edge to AI. With Cloudera in the connected car, data is captured, consolidated and enriched with Cloudera data flow cloud Dara's data engineering, operational database and data warehouse provide the foundation to develop service center applications, sales reports, and engineering dashboards. With data science workbench data scientists can continuously train AI models and use data flow to push the models back to the edge, to enhance the car's performance as the industry's first enterprise data cloud Cloudera supports on-premise public and multi-cloud deployments delivering multifunction analytics on data anywhere with common security governance and metadata management powered by Cloudera SDX, an open platform built on open source, working with open compute architectures and open data stores all the way from edge to AI powering the connected car. >>The future has arrived. >>The Dawn of a retail Renaissance is here and shopping will never be the same again. Today's connected. Consumers are always on and didn't control. It's the era of smart retail, smart shelves, digital signage, and smart mirrors offer an immersive customer experience while delivering product information, personalized offers and recommendations, video analytics, capture customer emotions and gestures to better understand and respond to in-store shopping experiences. Beacons sensors, and streaming video provide valuable data into in-store traffic patterns, hotspots and dwell times. This helps retailers build visual heat maps to better understand custom journeys, conversion rates, and promotional effectiveness in our robots automate routine tasks like capturing inventory levels, identifying out of stocks and alerting in store personnel to replenish shelves. When it comes to checking out automated e-commerce pickup stations and frictionless checkouts will soon be the norm making standing in line. A thing of the past data and analytics are truly reshaping. >>The everyday shopping experience outside the store, smart trucks connect the supply chain, providing new levels of inventory visibility, not just into the precise location, but also the condition of those goods. All in real time, convenience is key and customers today have the power to get their goods delivered at the curbside to their doorstep, or even to their refrigerators. Smart retail is indeed here. And Cloudera makes all of this possible using Cloudera data can be captured from a variety of sources, then stored, processed, and analyzed to drive insights and action. In real time, data scientists can continuously build and train new machine learning models and put these models back to the edge for delivering those moment of truth customer experiences. This is the enterprise data cloud powered by Cloudera enabling smart retail from the edge to AI. The future has arrived >>For is a global automotive supplier. We have three business groups, automotive seating in studios, and then emission control technologies or biggest automotive customers are Volkswagen for the NPSA. And we have, uh, more than 300 sites. And in 75 countries >>Today, we are generating tons of data, more and more data on the manufacturing intelligence. We are trying to reduce the, the defective parts or anticipate the detection of the, of the defective part. And this is where we can get savings. I would say our goal in manufacturing is zero defects. The cost of downtime in a plant could be around the a hundred thousand euros. So with predictive maintenance, we are identifying correlations and patterns and try to anticipate, and maybe to replace a component before the machine is broken. We are in the range of about 2000 machines and we can have up to 300 different variables from pressure from vibration and temperatures. And the real-time data collection is key, and this is something we cannot achieve in a classical data warehouse approach. So with the be data and with clouded approach, what we are able to use really to put all the data, all the sources together in the classical way of working with that at our house, we need to spend weeks or months to set up the model with the Cloudera data lake. We can start working on from days to weeks. We think that predictive or machine learning could also improve on the estimation or NTC patient forecasting of what we'll need to brilliance with all this knowledge around internet of things and data collection. We are applying into the predictive convene and the cockpit of the future. So we can work in the self driving car and provide a better experience for the driver in the car. >>The Cloudera data platform makes it easy to say yes to any analytic workload from the edge to AI, yes. To enterprise grade security and governance, yes. To the analytics your people want to use yes. To operating on any cloud. Your business requires yes to the future with a cloud native platform that flexes to meet your needs today and tomorrow say yes to CDP and say goodbye to shadow it, take a tour of CDP and see how it's an easier, faster and safer enterprise analytics and data management platform with a new approach to data. Finally, a data platform that lets you say yes, >>Welcome to transforming ideas into insights, presented with the cube and made possible by cloud era. My name is Dave Volante from the cube, and I'll be your host for today. And the next hundred minutes, you're going to hear how to turn your best ideas into action using data. And we're going to share the real world examples and 12 industry use cases that apply modern data techniques to improve customer experience, reduce fraud, drive manufacturing, efficiencies, better forecast, retail demand, transform analytics, improve public sector service, and so much more how we use data is rapidly evolving as is the language that we use to describe data. I mean, for example, we don't really use the term big data as often as we used to rather we use terms like digital transformation and digital business, but you think about it. What is a digital business? How is that different from just a business? >>Well, digital business is a data business and it differentiates itself by the way, it uses data to compete. So whether we call it data, big data or digital, our belief is we're entering the next decade of a world that puts data at the core of our organizations. And as such the way we use insights is also rapidly evolving. You know, of course we get value from enabling humans to act with confidence on let's call it near perfect information or capitalize on non-intuitive findings. But increasingly insights are leading to the development of data, products and services that can be monetized, or as you'll hear in our industry, examples, data is enabling machines to take cognitive actions on our behalf. Examples are everywhere in the forms of apps and products and services, all built on data. Think about a real-time fraud detection, know your customer and finance, personal health apps that monitor our heart rates. >>Self-service investing, filing insurance claims and our smart phones. And so many examples, IOT systems that communicate and act machine and machine real-time pricing actions. These are all examples of products and services that drive revenue cut costs or create other value. And they all rely on data. Now while many business leaders sometimes express frustration that their investments in data, people, and process and technologies haven't delivered the full results they desire. The truth is that the investments that they've made over the past several years should be thought of as a step on the data journey. Key learnings and expertise from these efforts are now part of the organizational DNA that can catapult us into this next era of data, transformation and leadership. One thing is certain the next 10 years of data and digital transformation, won't be like the last 10. So let's get into it. Please join us in the chat. >>You can ask questions. You can share your comments, hit us up on Twitter right now. It's my pleasure to welcome Mick Holliston in he's the president of Cloudera mic. Great to see you. Great to see you as well, Dave, Hey, so I call it the new abnormal, right? The world is kind of out of whack offices are reopening again. We're seeing travel coming back. There's all this pent up demand for cars and vacations line cooks at restaurants. Everything that we consumers have missed, but here's the one thing. It seems like the algorithms are off. Whether it's retail's fulfillment capabilities, airline scheduling their pricing algorithms, you know, commodity prices we don't know is inflation. Transitory. Is it a long-term threat trying to forecast GDP? It's just seems like we have to reset all of our assumptions and make a feel a quality data is going to be a key here. How do you see the current state of the industry and the role data plays to get us into a more predictable and stable future? Well, I >>Can sure tell you this, Dave, uh, out of whack is definitely right. I don't know if you know or not, but I happen to be coming to you live today from Atlanta and, uh, as a native of Atlanta, I can, I can tell you there's a lot to be known about the airport here. It's often said that, uh, whether you're going to heaven or hell, you got to change planes in Atlanta and, uh, after 40 minutes waiting on algorithm to be right for baggage claim when I was not, I finally managed to get some bag and to be able to show up dressed appropriately for you today. Um, here's one thing that I know for sure though, Dave, clean, consistent, and safe data will be essential to getting the world and businesses as we know it back on track again, um, without well-managed data, we're certain to get very inconsistent outcomes, quality data will the normalizing factor because one thing really hasn't changed about computing since the Dawn of time. Back when I was taking computer classes at Georgia tech here in Atlanta, and that's what we used to refer to as garbage in garbage out. In other words, you'll never get quality data-driven insights from a poor data set. This is especially important today for machine learning and AI, you can build the most amazing models and algorithms, but none of it will matter if the underlying data isn't rock solid as AI is increasingly used in every business app, you must build a solid data foundation mic. Let's >>Talk about hybrid. Every CXO that I talked to, they're trying to get hybrid, right? Whether it's hybrid work hybrid events, which is our business hybrid cloud, how are you thinking about the hybrid? Everything, what's your point of view with >>All those descriptions of hybrid? Everything there, one item you might not have quite hit on Dave and that's hybrid data. >>Oh yeah, you're right. Mick. I did miss that. What, what do you mean by hybrid data? Well, >>David in cloud era, we think hybrid data is all about the juxtaposition of two things, freedom and security. Now every business wants to be more agile. They want the freedom to work with their data, wherever it happens to work best for them, whether that's on premises in a private cloud and public cloud, or perhaps even in a new open data exchange. Now this matters to businesses because not all data applications are created equal. Some apps are best suited to be run in the cloud because of their transitory nature. Others may be more economical if they're running a private cloud, but either way security, regulatory compliance and increasingly data sovereignty are playing a bigger and more important role in every industry. If you don't believe me, just watch her read a recent news story. Data breaches are at an all time high. And the ethics of AI applications are being called into question every day and understanding the lineage of machine learning algorithms is now paramount for every business. So how in the heck do you get both the freedom and security that you're looking for? Well, the answer is actually pretty straightforward. The key is developing a hybrid data strategy. And what do you know Dave? That's the business cloud era? Is it on a serious note from cloud era's perspective? Adopting a hybrid data strategy is central to every business's digital transformation. It will enable rapid adoption of new technologies and optimize economic models while ensuring the security and privacy of every bit of data. What can >>Make, I'm glad you brought in that notion of hybrid data, because when you think about things, especially remote work, it really changes a lot of the assumptions. You talked about security, the data flows are going to change. You've got the economics, the physics, the local laws come into play. So what about the rest of hybrid? Yeah, >>It's a great question, Dave and certainly cloud era itself as a business and all of our customers are feeling this in a big way. We now have the overwhelming majority of our workforce working from home. And in other words, we've got a much larger surface area from a security perspective to keep in mind the rate and pace of data, just generating a report that might've happened very quickly and rapidly on the office. Uh, ether net may not be happening quite so fast in somebody's rural home in, uh, in, in the middle of Nebraska somewhere. Right? So it doesn't really matter whether you're talking about the speed of business or securing data, any way you look at it. Uh, hybrid I think is going to play a more important role in how work is conducted and what percentage of people are working in the office and are not, I know our plans, Dave, uh, involve us kind of slowly coming back to work, begin in this fall. And we're looking forward to being able to shake hands and see one another again for the first time in many cases for more than a year and a half, but, uh, yes, hybrid work, uh, and hybrid data are playing an increasingly important role for every kind of business. >>Thanks for that. I wonder if we could talk about industry transformation for a moment because it's a major theme of course, of this event. So, and the case. Here's how I think about it. It makes, I mean, some industries have transformed. You think about retail, for example, it's pretty clear, although although every physical retail brand I know has, you know, not only peaked up its online presence, but they also have an Amazon war room strategy because they're trying to take greater advantage of that physical presence, uh, and ended up reverse. We see Amazon building out physical assets so that there's more hybrid going on. But when you look at healthcare, for example, it's just starting, you know, with such highly regulated industry. It seems that there's some hurdles there. Financial services is always been data savvy, but you're seeing the emergence of FinTech and some other challenges there in terms of control, mint control of payment systems in manufacturing, you know, the pandemic highlighted America's reliance on China as a manufacturing partner and, and supply chain. Uh it's so my point is it seems that different industries they're in different stages of transformation, but two things look really clear. One, you've got to put data at the core of the business model that's compulsory. It seems like embedding AI into the applications, the data, the business process that's going to become increasingly important. So how do you see that? >>Wow, there's a lot packed into that question there, Dave, but, uh, yeah, we, we, uh, you know, at Cloudera I happened to be leading our own digital transformation as a technology company and what I would, what I would tell you there that's been arresting for us is the shift from being largely a subscription-based, uh, model to a consumption-based model requires a completely different level of instrumentation and our products and data collection that takes place in real, both for billing, for our, uh, for our customers. And to be able to check on the health and wellness, if you will, of their cloud era implementations. But it's clearly not just impacting the technology industry. You mentioned healthcare and we've been helping a number of different organizations in the life sciences realm, either speed, the rate and pace of getting vaccines, uh, to market, uh, or we've been assisting with testing process. >>That's taken place because you can imagine the quantity of data that's been generated as we've tried to study the efficacy of these vaccines on millions of people and try to ensure that they were going to deliver great outcomes and, and healthy and safe outcomes for everyone. And cloud era has been underneath a great deal of that type of work and the financial services industry you pointed out. Uh, we continue to be central to the large banks, meeting their compliance and regulatory requirements around the globe. And in many parts of the world, those are becoming more stringent than ever. And Cloudera solutions are really helping those kinds of organizations get through those difficult challenges. You, you also happened to mention, uh, you know, public sector and in public sector. We're also playing a key role in working with government entities around the world and applying AI to some of the most challenging missions that those organizations face. >>Um, and while I've made the kind of pivot between the industry conversation and the AI conversation, what I'll share with you about AI, I touched upon a little bit earlier. You can't build great AI, can't grow, build great ML apps, unless you've got a strong data foundation underneath is back to that garbage in garbage out comment that I made previously. And so in order to do that, you've got to have a great hybrid dated management platform at your disposal to ensure that your data is clean and organized and up to date. Uh, just as importantly from that, that's kind of the freedom side of things on the security side of things. You've got to ensure that you can see who just touched, not just the data itself, Dave, but actually the machine learning models and organizations around the globe are now being challenged. It's kind of on the topic of the ethics of AI to produce model lineage. >>In addition to data lineage. In other words, who's had access to the machine learning models when and where, and at what time and what decisions were made perhaps by the humans, perhaps by the machines that may have led to a particular outcome. So every kind of business that is deploying AI applications should be thinking long and hard about whether or not they can track the full lineage of those machine learning models just as they can track the lineage of data. So lots going on there across industries, lots going on as those various industries think about how AI can be applied to their businesses. Pretty >>Interesting concepts. You bring it into the discussion, the hybrid data, uh, sort of new, I think, new to a lot of people. And th this idea of model lineage is a great point because people want to talk about AI, ethics, transparency of AI. When you start putting those models into, into machines to do real time inferencing at the edge, it starts to get really complicated. I wonder if we could talk about you still on that theme of industry transformation? I felt like coming into the pandemic pre pandemic, there was just a lot of complacency. Yeah. Digital transformation and a lot of buzz words. And then we had this forced March to digital, um, and it's, but, but people are now being more planful, but there's still a lot of sort of POC limbo going on. How do you see that? Can you help accelerate that and get people out of that state? It definitely >>Is a lot of a POC limbo or a, I think some of us internally have referred to as POC purgatory, just getting stuck in that phase, not being able to get from point a to point B in digital transformation and, um, you know, for every industry transformation, uh, change in general is difficult and it takes time and money and thoughtfulness, but like with all things, what we found is small wins work best and done quickly. So trying to get to quick, easy successes where you can identify a clear goal and a clear objective and then accomplish it in rapid fashion is sort of the way to build your way towards those larger transformative efforts set. Another way, Dave, it's not wise to try to boil the ocean with your digital transformation efforts as it relates to the underlying technology here. And to bring it home a little bit more practically, I guess I would say at cloud era, we tend to recommend that companies begin to adopt cloud infrastructure, for example, containerization. >>And they begin to deploy that on-prem and then they start to look at how they may move those containerized workloads into the public cloud. That'll give them an opportunity to work with the data and the underlying applications themselves, uh, right close to home in place. They can kind of experiment a little bit more safely and economically, and then determine which workloads are best suited for the public cloud and which ones should remain on prem. That's a way in which a hybrid data strategy can help get a digital transformation accomplish, but kind of starting small and then drawing fast from there on customer's journey to the we'll make we've >>Covered a lot of ground. Uh, last question. Uh, w what, what do you want people to leave this event, the session with, and thinking about sort of the next era of data that we're entering? >>Well, it's a great question, but, uh, you know, I think it could be summed up in, uh, in two words. I want them to think about a hybrid data, uh, strategy. So, uh, you know, really hybrid data is a concept that we're bringing forward on this show really for the, for the first time, arguably, and we really do think that it enables customers to experience what we refer to Dave as the power of, and that is freedom, uh, and security, and in a world where we're all still trying to decide whether each day when we walk out each building, we walk into, uh, whether we're free to come in and out with a mask without a mask, that sort of thing, we all want freedom, but we also also want to be safe and feel safe, uh, for ourselves and for others. And the same is true of organizations. It strategies. They want the freedom to choose, to run workloads and applications and the best and most economical place possible. But they also want to do that with certainty, that they're going to be able to deploy those applications in a safe and secure way that meets the regulatory requirements of their particular industry. So hybrid data we think is key to accomplishing both freedom and security for your data and for your business as a whole, >>Nick, thanks so much great conversation and really appreciate the insights that you're bringing to this event into the industry. Really thank you for your time. >>You bet Dave pleasure being with you. Okay. >>We want to pick up on a couple of themes that Mick discussed, you know, supercharging your business with AI, for example, and this notion of getting hybrid, right? So right now we're going to turn the program over to Rob Bearden, the CEO of Cloudera and Manny veer, DAS. Who's the head of enterprise computing at Nvidia. And before I hand it off to Robin, I just want to say for those of you who follow me at the cube, we've extensively covered the transformation of the semiconductor industry. We are entering an entirely new era of computing in the enterprise, and it's being driven by the emergence of data, intensive applications and workloads no longer will conventional methods of processing data suffice to handle this work. Rather, we need new thinking around architectures and ecosystems. And one of the keys to success in this new era is collaboration between software companies like Cloudera and semiconductor designers like Nvidia. So let's learn more about this collaboration and what it means to your data business. Rob, thanks, >>Mick and Dave, that was a great conversation on how speed and agility is everything in a hyper competitive hybrid world. You touched on AI as essential to a data first strategy and accelerating the path to value and hybrid environments. And I want to drill down on this aspect today. Every business is facing accelerating everything from face-to-face meetings to buying groceries has gone digital. As a result, businesses are generating more data than ever. There are more digital transactions to track and monitor. Now, every engagement with coworkers, customers and partners is virtual from website metrics to customer service records, and even onsite sensors. Enterprises are accumulating tremendous amounts of data and unlocking insights from it is key to our enterprises success. And with data flooding every enterprise, what should the businesses do? A cloud era? We believe this onslaught of data offers an opportunity to make better business decisions faster. >>And we want to make that easier for everyone, whether it's fraud, detection, demand, forecasting, preventative maintenance, or customer churn, whether the goal is to save money or produce income every day that companies don't gain deep insight from their data is money they've lost. And the reason we're talking about speed and why speed is everything in a hybrid world and in a hyper competitive climate, is that the faster we get insights from all of our data, the faster we grow and the more competitive we are. So those faster insights are also combined with the scalability and cost benefit they cloud provides and with security and edge to AI data intimacy. That's why the partnership between cloud air and Nvidia together means so much. And it starts with the shared vision making data-driven, decision-making a reality for every business and our customers will now be able to leverage virtually unlimited quantities of varieties, of data, to power, an order of magnitude faster decision-making and together we turbo charge the enterprise data cloud to enable our customers to work faster and better, and to make integration of AI approaches a reality for companies of all sizes in the cloud. >>We're joined today by NVIDIA's Mandy veer dos, and to talk more about how our technologies will deliver the speed companies need for innovation in our hyper competitive environment. Okay, man, you're veer. Thank you for joining us over the unit. >>Thank you, Rob, for having me. It's a pleasure to be here on behalf of Nvidia. We are so excited about this partnership with Cloudera. Uh, you know, when, when, uh, when Nvidia started many years ago, we started as a chip company focused on graphics, but as you know, over the last decade, we've really become a full stack accelerated computing company where we've been using the power of GPU hardware and software to accelerate a variety of workloads, uh, AI being a prime example. And when we think about Cloudera, uh, and your company, a great company, there's three things we see Rob. Uh, the first one is that for the companies that will already transforming themselves by the use of data, Cloudera has been a trusted partner for them. The second thing seen is that when it comes to using your data, you want to use it in a variety of ways with a powerful platform, which of course you have built over time. >>And finally, as we've heard already, you believe in the power of hybrid, that data exists in different places and the compute needs to follow the data. Now, if you think about in various mission, going forward to democratize accelerated computing for all companies, our mission actually aligns very well with exactly those three things. Firstly, you know, we've really worked with a variety of companies today who have been the early adopters, uh, using the power acceleration by changing the technology in their stacks. But more and more, we see the opportunity of meeting customers, where they are with tools that they're familiar with with partners that they trust. And of course, Cloudera being a great example of that. Uh, the second, uh, part of NVIDIA's mission is we focused a lot in the beginning on deep learning where the power of GPU is really shown through, but as we've gone forward, we found that GPU's can accelerate a variety of different workloads from machine learning to inference. >>And so again, the power of your platform, uh, is very appealing. And finally, we know that AI is all about data, more and more data. We believe very strongly in the idea that customers put their data, where they need to put it. And the compute, the AI compute the machine learning compute needs to meet the customer where their data is. And so that matches really well with your philosophy, right? And Rob, that's why we were so excited to do this partnership with you. It's come to fruition. We have a great combined stack now for the customer and we already see people using it. I think the IRS is a fantastic example where literally they took the workflow. They had, they took the servers, they had, they added GPS into those servers. They did not change anything. And they got an eight times performance improvement for their fraud detection workflows, right? And that's the kind of success we're looking forward to with all customers. So the team has actually put together a great video to show us what the IRS is doing with this technology. Let's take a look. >>My name's Joanne salty. I'm the branch chief of the technical branch and RAs. It's actually the research division research and statistical division of the IRS. Basically the mission that RAs has is we do statistical and research on all things related to taxes, compliance issues, uh, fraud issues, you know, anything that you can think of. Basically we do research on that. We're running into issues now that we have a lot of ideas to actually do data mining on our big troves of data, but we don't necessarily have the infrastructure or horsepower to do it. So it's our biggest challenge is definitely the, the infrastructure to support all the ideas that the subject matter experts are coming up with in terms of all the algorithms they would like to create. And the diving deeper within the algorithm space, the actual training of those Agra algorithms, the of parameters each of those algorithms have. >>So that's, that's really been our challenge. Now the expectation was that with Nvidia in cloud, there is help. And with the cluster, we actually build out the test this on the actual fraud, a fraud detection algorithm on our expectation was we were definitely going to see some speed up in prom, computational processing times. And just to give you context, the size of the data set that we were, uh, the SMI was actually working, um, the algorithm against Liz around four terabytes. If I recall correctly, we'd had a 22 to 48 times speed up after we started tweaking the original algorithm. My expectations, quite honestly, in that sphere, in terms of the timeframe to get results, was it that you guys actually exceeded them? It was really, really quick. Uh, the definite now term short term what's next is going to be the subject matter expert is actually going to take our algorithm run with that. >>So that's definitely the now term thing we want to do going down, go looking forward, maybe out a couple of months, we're also looking at curing some, a 100 cards to actually test those out. As you guys can guess our datasets are just getting bigger and bigger and bigger, and it demands, um, to actually do something when we get more value added out of those data sets is just putting more and more demands on our infrastructure. So, you know, with the pilot, now we have an idea with the infrastructure, the infrastructure we need going forward. And then also just our in terms of thinking of the algorithms and how we can approach these problems to actually code out solutions to them. Now we're kind of like the shackles are off and we can just run them, you know, come onto our art's desire, wherever imagination takes our skis to actually develop solutions, know how the platforms to run them on just kind of the close out. >>I rarely would be very missed. I've worked with a lot of, you know, companies through the year and most of them been spectacular. And, uh, you guys are definitely in that category. The, the whole partnership, as I said, a little bit early, it was really, really well, very responsive. I would be remiss if I didn't. Thank you guys. So thank you for the opportunity to, and fantastic. And I'd have to also, I want to thank my guys. My, uh, my staff, David worked on this Richie worked on this Lex and Tony just, they did a fantastic job and I want to publicly thank him for all the work they did with you guys and Chev, obviously also. Who's fantastic. So thank you everyone. >>Okay. That's a real great example of speed and action. Now let's get into some follow up questions guys, if I may, Rob, can you talk about the specific nature of the relationship between Cloudera and Nvidia? Is it primarily go to market or you do an engineering work? What's the story there? >>It's really both. It's both go to market and engineering and engineering focus is to optimize and take advantage of invidious platform to drive better price performance, lower cost, faster speeds, and better support for today's emerging data intensive applications. So it's really both >>Great. Thank you. Many of Eric, maybe you could talk a little bit more about why can't we just existing general purpose platforms that are, that are running all this ERP and CRM and HCM and you know, all the, all the Microsoft apps that are out there. What, what do Nvidia and cloud era bring to the table that goes beyond the conventional systems that we've known for many years? >>Yeah. I think Dave, as we've talked about the asset that the customer has is really the data, right? And the same data can be utilized in many different ways. Some machine learning, some AI, some traditional data analytics. So the first step here was really to take a general platform for data processing, Cloudera data platform, and integrate with that. Now Nvidia has a software stack called rapids, which has all of the primitives that make different kinds of data processing go fast on GPU's. And so the integration here has really been taking rapids and integrating it into a Cloudera data platform. So that regardless of the technique, the customer's using to get insight from that data, the acceleration will apply in all cases. And that's why it was important to start with a platform like Cloudera rather than a specific application. >>So I think this is really important because if you think about, you know, the software defined data center brought in, you know, some great efficiencies, but at the same time, a lot of the compute power is now going toward doing things like networking and storage and security offloads. So the good news, the reason this is important is because when you think about these data intensive workloads, we can now put more processing power to work for those, you know, AI intensive, uh, things. And so that's what I want to talk about a little bit, maybe a question for both of you, maybe Rob, you could start, you think about the AI that's done today in the enterprise. A lot of it is modeling in the cloud, but when we look at a lot of the exciting use cases, bringing real-time systems together, transaction systems and analytics systems and real time, AI inference, at least even at the edge, huge potential for business value and a consumer, you're seeing a lot of applications with AI biometrics and voice recognition and autonomous vehicles and the like, and so you're putting AI into these data intensive apps within the enterprise. >>The potential there is enormous. So what can we learn from sort of where we've come from, maybe these consumer examples and Rob, how are you thinking about enterprise AI in the coming years? >>Yeah, you're right. The opportunity is huge here, but you know, 90% of the cost of AI applications is the inference. And it's been a blocker in terms of adoption because it's just been too expensive and difficult from a performance standpoint and new platforms like these being developed by cloud air and Nvidia will dramatically lower the cost, uh, of enabling this type of workload to be done. Um, and what we're going to see the most improvements will be in the speed and accuracy for existing enterprise AI apps like fraud detection, recommendation, engine chain management, drug province, and increasingly the consumer led technologies will be bleeding into the enterprise in the form of autonomous factory operations. An example of that would be robots that AR VR and manufacturing. So driving quality, better quality in the power grid management, automated retail IOT, you know, the intelligent call centers, all of these will be powered by AI, but really the list of potential use cases now are going to be virtually endless. >>I mean, this is like your wheelhouse. Maybe you could add something to that. >>Yeah. I mean, I agree with Rob. I mean he listed some really good use cases. You know, the way we see this at Nvidia, this journey is in three phases or three steps, right? The first phase was for the early adopters. You know, the builders who assembled, uh, use cases, particular use cases like a chat bot, uh, uh, from the ground up with the hardware and the software almost like going to your local hardware store and buying piece parts and constructing a table yourself right now. I think we are in the first phase of the democratization, uh, for example, the work we did with Cloudera, which is, uh, for a broader base of customers, still building for a particular use case, but starting from a much higher baseline. So think about, for example, going to Ikea now and buying a table in a box, right. >>And you still come home and assemble it, but all the parts are there. The instructions are there, there's a recipe you just follow and it's easy to do, right? So that's sort of the phase we're in now. And then going forward, the opportunity we really look forward to for the democratization, you talked about applications like CRM, et cetera. I think the next wave of democratization is when customers just adopt and deploy the next version of an application they already have. And what's happening is that under the covers, the application is infused by AI and it's become more intelligent because of AI and the customer just thinks they went to the store and bought, bought a table and it showed up and somebody placed it in the right spot. Right. And they didn't really have to learn, uh, how to do AI. So these are the phases. And I think they're very excited to be going there. Yeah. You know, >>Rob, the great thing about for, for your customers is they don't have to build out the AI. They can, they can buy it. And, and just in thinking about this, it seems like there are a lot of really great and even sometimes narrow use cases. So I want to ask you, you know, staying with AI for a minute, one of the frustrations and Mick and I talked about this, the guy go problem that we've all studied in college, uh, you know, garbage in, garbage out. Uh, but, but the frustrations that users have had is really getting fast access to quality data that they can use to drive business results. So do you see, and how do you see AI maybe changing the game in that regard, Rob over the next several years? >>So yeah, the combination of massive amounts of data that have been gathered across the enterprise in the past 10 years with an open API APIs are dramatically lowering the processing costs that perform at much greater speed and efficiency, you know, and that's allowing us as an industry to democratize the data access while at the same time, delivering the federated governance and security models and hybrid technologies are playing a key role in making this a reality and enabling data access to be hybridized, meaning access and treated in a substantially similar way, your respect to the physical location of where that data actually resides. >>That's great. That is really the value layer that you guys are building out on top of that, all this great infrastructure that the hyperscalers have have given us, I mean, a hundred billion dollars a year that you can build value on top of, for your customers. Last question, and maybe Rob, you could, you can go first and then manufacture. You could bring us home. Where do you guys want to see the relationship go between cloud era and Nvidia? In other words, how should we, as outside observers be, be thinking about and measuring your project specifically and in the industry's progress generally? >>Yeah, I think we're very aligned on this and for cloud era, it's all about helping companies move forward, leverage every bit of their data and all the places that it may, uh, be hosted and partnering with our customers, working closely with our technology ecosystem of partners means innovation in every industry and that's inspiring for us. And that's what keeps us moving forward. >>Yeah. And I agree with Robin and for us at Nvidia, you know, we, this partnership started, uh, with data analytics, um, as you know, a spark is a very powerful technology for data analytics, uh, people who use spark rely on Cloudera for that. And the first thing we did together was to really accelerate spark in a seamless manner, but we're accelerating machine learning. We accelerating artificial intelligence together. And I think for Nvidia it's about democratization. We've seen what machine learning and AI have done for the early adopters and help them make their businesses, their products, their customer experience better. And we'd like every company to have the same opportunity. >>Okay. Now we're going to dig into the data landscape and cloud of course. And talk a little bit more about that with drew Allen. He's a managing director at Accenture drew. Welcome. Great to see you. Thank you. So let's talk a little bit about, you know, you've been in this game for a number of years. Uh, you've got particular expertise in, in data and finance and insurance. I mean, you know, you think about it within the data and analytics world, even our language is changing. You know, we don't say talk about big data so much anymore. We talk more about digital, you know, or, or, or data driven when you think about sort of where we've come from and where we're going. What are the puts and takes that you have with regard to what's going on in the business today? >>Well, thanks for having me. Um, you know, I think some of the trends we're seeing in terms of challenges and puts some takes are that a lot of companies are already on this digital journey. Um, they focused on customer experience is kind of table stakes. Everyone wants to focus on that and kind of digitizing their channels. But a lot of them are seeing that, you know, a lot of them don't even own their, their channels necessarily. So like we're working with a big cruise line, right. And yes, they've invested in digitizing what they own, but a lot of the channels that they sell through, they don't even own, right. It's the travel agencies or third party, real sellers. So having the data to know where, you know, where those agencies are, that that's something that they've discovered. And so there's a lot of big focus on not just digitizing, but also really understanding your customers and going across products because a lot of the data has built, been built up in individual channels and in digital products. >>And so bringing that data together is something that customers that have really figured out in the last few years is a big differentiator. And what we're seeing too, is that a big trend that the data rich are getting richer. So companies that have really invested in data, um, are having, uh, an outside market share and outside earnings per share and outside revenue growth. And it's really being a big differentiator. And I think for companies just getting started in this, the thing to think about is one of the missteps is to not try to capture all the data at once. The average company has, you know, 10,000, 20,000 data elements individually, when you want to start out, you know, 500, 300 critical data elements, about 5% of the data of a company drives 90% of the business value. So focusing on those key critical data elements is really what you need to govern first and really invest in first. And so that's something we, we tell companies at the beginning of their data strategy is first focus on those critical data elements, really get a handle on governing that data, organizing that data and building data products around >>That day. You can't boil the ocean. Right. And so, and I, I feel like pre pandemic, there was a lot of complacency. Oh yeah, we'll get to that. You know, not on my watch, I'll be retired before that, you know, is it becomes a minute. And then of course the pandemic was, I call it sometimes a forced March to digital. So in many respects, it wasn't planned. It just ha you know, you had to do it. And so now I feel like people are stepping back and saying, okay, let's now really rethink this and do it right. But is there, is there a sense of urgency, do you think? Absolutely. >>I think with COVID, you know, we were working with, um, a retailer where they had 12,000 stores across the U S and they had didn't have the insights where they could drill down and understand, you know, with the riots and with COVID was the store operational, you know, with the supply chain of the, having multiple distributors, what did they have in stock? So there are millions of data points that you need to drill down at the cell level, at the store level to really understand how's my business performing. And we like to think about it for like a CEO and his leadership team of it, like, think of it as a digital cockpit, right? You think about a pilot, they have a cockpit with all these dials and, um, dashboards, essentially understanding the performance of their business. And they should be able to drill down and understand for each individual, you know, unit of their work, how are they performing? That's really what we want to see for businesses. Can they get down to that individual performance to really understand how their business >>Is performing good, the ability to connect those dots and traverse those data points and not have to go in and come back out and go into a new system and come back out. And that's really been a lot of the frustration. W where does machine intelligence and AI fit in? Is that sort of a dot connector, if you will, and an enabler, I mean, we saw, you know, decades of the, the AI winter, and then, you know, there's been a lot of talk about it, but it feels like with the amount of data that we've collected over the last decade and the, the, the low costs of processing that data now, it feels like it's, it's real. Where do you see AI fitting? Yeah, >>I mean, I think there's been a lot of innovation in the last 10 years with, um, the low cost of storage and computing and these algorithms in non-linear, um, you know, knowledge graphs, and, um, um, a whole bunch of opportunities in cloud where what I think the, the big opportunity is, you know, you can apply AI in areas where a human just couldn't have the scale to do that alone. So back to the example of a cruise lines, you know, you may have a ship being built that has 4,000 cabins on the single cruise line, and it's going to multiple deaths that destinations over its 30 year life cycle. Each one of those cabins is being priced individually for each individual destination. It's physically impossible for a human to calculate the dynamic pricing across all those destinations. You need a machine to actually do that pricing. And so really what a machine is leveraging is all that data to really calculate and assist the human, essentially with all these opportunities where you wouldn't have a human being able to scale up to that amount of data >>Alone. You know, it's interesting. One of the things we talked to Nicolson about earlier was just the everybody's algorithms are out of whack. You know, you look at the airline pricing, you look at hotels it's as a consumer, you would be able to kind of game the system and predict that they can't even predict these days. And I feel as though that the data and AI are actually going to bring us back into some kind of normalcy and predictability, uh, what do you see in that regard? Yeah, I think it's, >>I mean, we're definitely not at a point where, when I talked to, you know, the top AI engineers and data scientists, we're not at a point where we have what they call broad AI, right? You can get machines to solve general knowledge problems, where they can solve one problem and then a distinctly different problem, right? That's still many years away, but narrow why AI, there's still tons of use cases out there that can really drive tons of business performance challenges, tons of accuracy challenges. So for example, in the insurance industry, commercial lines, where I work a lot of the time, the biggest leakage of loss experience in pricing for commercial insurers is, um, people will go in as an agent and they'll select an industry to say, you know what, I'm a restaurant business. Um, I'll select this industry code to quote out a policy, but there's, let's say, you know, 12 dozen permutations, you could be an outdoor restaurant. >>You could be a bar, you could be a caterer and all of that leads to different loss experience. So what this does is they built a machine learning algorithm. We've helped them do this, that actually at the time that they're putting in their name and address, it's crawling across the web and predicting in real time, you know, is this a address actually, you know, a business that's a restaurant with indoor dining, does it have a bar? Is it outdoor dining? And it's that that's able to accurately more price the policy and reduce the loss experience. So there's a lot of that you can do even with narrow AI that can really drive top line of business results. >>Yeah. I liked that term, narrow AI, because getting things done is important. Let's talk about cloud a little bit because people talk about cloud first public cloud first doesn't necessarily mean public cloud only, of course. So where do you see things like what's the right operating model, the right regime hybrid cloud. We talked earlier about hybrid data help us squint through the cloud landscape. Yeah. I mean, I think for most right, most >>Fortune 500 companies, they can't just snap their fingers and say, let's move all of our data centers to the cloud. They've got to move, you know, gradually. And it's usually a journey that's taking more than two to three plus years, even more than that in some cases. So they're have, they have to move their data, uh, incrementally to the cloud. And what that means is that, that they have to move to a hybrid perspective where some of their data is on premise and some of it is publicly on the cloud. And so that's the term hybrid cloud essentially. And so what they've had to think about is from an intelligence perspective, the privacy of that data, where is it being moved? Can they reduce the replication of that data? Because ultimately you like, uh, replicating the data from on-premise to the cloud that introduces, you know, errors and data quality issues. So thinking about how do you manage, uh, you know, uh on-premise and, um, public as a transition is something that Accenture thinks, thinks, and helps our clients do quite a bit. And how do you move them in a manner that's well-organized and well thought of? >>Yeah. So I've been a big proponent of sort of line of business lines of business becoming much more involved in, in the data pipeline, if you will, the data process, if you think about our major operational systems, they all have sort of line of business context in them. And then the salespeople, they know the CRM data and, you know, logistics folks there they're very much in tune with ERP, almost feel like for the past decade, the lines of business have been somewhat removed from the, the data team, if you will. And that, that seems to be changing. What are you seeing in terms of the line of line of business being much more involved in sort of end to end ownership, if you will, if I can use that term of, uh, of the data and sort of determining things like helping determine anyway, the data quality and things of that nature. Yeah. I >>Mean, I think this is where thinking about your data operating model and thinking about ideas of a chief data officer and having data on the CEO agenda, that's really important to get the lines of business, to really think about data sharing and reuse, and really getting them to, you know, kind of unlock the data because they do think about their data as a fiefdom data has value, but you've got to really get organizations in their silos to open it up and bring that data together because that's where the value is. You know, data doesn't operate. When you think about a customer, they don't operate in their journey across the business in silo channels. They don't think about, you know, I use only the web and then I use the call center, right? They think about that as just one experience and that data is a single journey. >>So we like to think about data as a product. You know, you should think about a data in the same way. You think about your products as, as products, you know, data as a product, you should have the idea of like every two weeks you have releases to it. You have an operational resiliency to it. So thinking about that, where you can have a very product mindset to delivering your data, I think is very important for the success. And that's where kind of, there's not just the things about critical data elements and having the right platform architecture, but there's a soft stuff as well, like a, a product mindset to data, having the right data, culture, and business adoption and having the right value set mindset for, for data, I think is really >>Important. I think data as a product is a very powerful concept and I think it maybe is uncomfortable to some people sometimes. And I think in the early days of big data, if you will, people thought, okay, data is a product going to sell my data and that's not necessarily what you mean, thinking about products or data that can fuel products that you can then monetize maybe as a product or as a, as, as a service. And I like to think about a new metric in the industry, which is how long does it take me to get from idea I'm a business person. I have an idea for a data product. How long does it take me to get from idea to monetization? And that's going to be something that ultimately as a business person, I'm going to use to determine the success of my data team and my data architecture. Is that kind of thinking starting to really hit the marketplace? Absolutely. >>I mean, I insurers now are working, partnering with, you know, auto manufacturers to monetize, um, driver usage data, you know, on telematics to see, you know, driver behavior on how, you know, how auto manufacturers are using that data. That's very important to insurers, you know, so how an auto manufacturer can monetize that data is very important and also an insurance, you know, cyber insurance, um, are there news new ways we can look at how companies are being attacked with viruses and malware. And is there a way we can somehow monetize that information? So companies that are able to agily, you know, think about how can we collect this data, bring it together, think about it as a product, and then potentially, you know, sell it as a service is something that, um, company, successful companies, you're doing great examples >>Of data products, and it might be revenue generating, or it might be in the case of, you know, cyber, maybe it reduces my expected loss and exactly. Then it drops right to my bottom line. What's the relationship between Accenture and cloud era? Do you, I presume you guys meet at the customer, but maybe you could give us some insight. >>Yeah. So, um, I, I'm in the executive sponsor for, um, the Accenture Cloudera partnership on the Accenture side. Uh, we do quite a lot of business together and, um, you know, Cloudera has been a great partner for us. Um, and they've got a great product in terms of the Cloudera data platform where, you know, what we do is as a big systems integrator for them, we help, um, you know, configure and we have a number of engineers across the world that come in and help in terms of, um, engineer architects and install, uh, cloud errors, data platform, and think about what are some of those, you know, value cases where you can really think about organizing data and bringing it together for all these different types of use cases. And really just as the examples we thought about. So the telematics, you know, um, in order to realize something like that, you're bringing in petabytes and huge scales of data that, you know, you just couldn't bring on a normal, uh, platform. You need to think about cloud. You need to think about speed of, of data and real-time insights and cloud era is the right data platform for that. So, um, >>Having a cloud Cloudera ushered in the modern big data era, we kind of all know that, and it was, which of course early on, it was very services intensive. You guys were right there helping people think through there weren't enough data scientists. We've sort of all, all been through that. And of course in your wheelhouse industries, you know, financial services and insurance, they were some of the early adopters, weren't they? Yeah, absolutely. >>Um, so, you know, an insurance, you've got huge amounts of data with loss history and, um, a lot with IOT. So in insurance, there's a whole thing of like sensorized thing in, uh, you know, taking the physical world and digitizing it. So, um, there's a big thing in insurance where, um, it's not just about, um, pricing out the risk of a loss experience, but actual reducing the loss before it even happens. So it's called risk control or loss control, you know, can we actually put sensors on oil pipelines or on elevators and, you know, reduce, um, you know, accidents before they happen. So we're, you know, working with an insurer to actually, um, listen to elevators as they move up and down and are there signals in just listening to the audio of an elevator over time that says, you know what, this elevator is going to need maintenance, you know, before a critical accident could happen. So there's huge applications, not just in structured data, but in unstructured data like voice and audio and video where a partner like Cloudera has a huge role to play. >>Great example of it. So again, narrow sort of use case for machine intelligence, but, but real value. True. We'll leave it like that. Thanks so much for taking some time. Yes. Thank you so much. Okay. We continue now with the theme of turning ideas into insights. So ultimately you can take action. We heard earlier that public cloud first doesn't mean public cloud only, and a winning strategy comprises data, irrespective of physical location on prem, across multiple clouds at the edge where real time inference is going to drive a lot of incremental value. Data is going to help the world come back to normal. We heard, or at least semi normal as we begin to better understand and forecast demand and supply and balances and economic forces. AI is becoming embedded into every aspect of our business, our people, our processes, and applications. And now we're going to get into some of the foundational principles that support the data and insights centric processes, which are fundamental to digital transformation initiatives. And it's my pleasure to welcome two great guests, Michelle Goetz. Who's a Kuba woman, VP and principal analyst at Forrester, and doing some groundbreaking work in this area. And Cindy, Mikey, who is the vice president of industry solutions and value management at Cloudera. Welcome to both of >>You. Welcome. Thank you. Thanks Dave. >>All right, Michelle, let's get into it. Maybe you could talk about your foundational core principles. You start with data. What are the important aspects of this first principle that are achievable today? >>It's really about democratization. If you can't make your data accessible, um, it's not usable. Nobody's able to understand what's happening in the business and they don't understand, um, what insights can be gained or what are the signals that are occurring that are going to help them with decisions, create stronger value or create deeper relationships, their customers, um, due to their experiences. So it really begins with how do you make data available and bring it to where the consumer of the data is rather than trying to hunt and Peck around within your ecosystem to find what it is that's important. Great. >>Thank you for that. So, Cindy, I wonder in hearing what Michelle just said, what are your thoughts on this? And when you work with customers at Cloudera, does, are there any that stand out that perhaps embody the fundamentals that Michelle just shared? >>Yeah, there's, there's quite a few. And especially as we look across, um, all the industries that we're actually working with customers in, you know, a few that stand out in top of mind for me is one is IQ via and what they're doing with real-world evidence and bringing together data across the entire, um, healthcare and life sciences ecosystems, bringing it together in different shapes and formats, making the ed accessible by both internally, as well as for their, um, the entire extended ecosystem. And then for SIA, who's working to solve some predictive maintenance issues within, there are a European car manufacturer and how do they make sure that they have, you know, efficient and effective processes when it comes to, uh, fixing equipment and so forth. And then also, um, there's, uh, an Indonesian based, um, uh, telecommunications company tech, the smell, um, who's bringing together, um, over the last five years, all their data about their customers and how do they enhance our customer experience? How do they make information accessible, especially in these pandemic and post pandemic times, um, uh, you know, just getting better insights into what customers need and when do they need it? >>Cindy platform is another core principle. How should we be thinking about data platforms in this day and age? I mean, where does, where do things like hybrid fit in? Um, what's cloud era's point >>Of view platforms are truly an enabler, um, and data needs to be accessible in many different fashions. Um, and also what's right for the business. When, you know, I want it in a cost and efficient and effective manner. So, you know, data needs to be, um, data resides everywhere. Data is developed and it's brought together. So you need to be able to balance both real time, you know, our batch historical information. It all depends upon what your analytical workloads are. Um, and what types of analytical methods you're going to use to drive those business insights. So putting and placing data, um, landing it, making it accessible, analyzing it needs to be done in any accessible platform, whether it be, you know, a public cloud doing it on-prem or a hybrid of the two is typically what we're seeing, being the most successful. >>Great. Thank you, Michelle. Let's move on a little bit and talk about practices and practices and processes as the next core principles. Maybe you could provide some insight as to how you think about balancing practices and processes while at the same time managing agility. >>Yeah, it's a really great question because it's pretty complex. When you have to start to connect your data to your business, the first thing to really gravitate towards is what are you trying to do? And what Cindy was describing with those customer examples is that they're all based off of business goals off of very specific use cases that helps kind of set the agenda about what is the data and what are the data domains that are important to really understanding and recognizing what's happening within that business activity and the way that you can affect that either in, you know, near time or real time, or later on, as you're doing your strategic planning, what that's balancing against is also being able to not only see how that business is evolving, but also be able to go back and say, well, can I also measure the outcomes from those processes and using data and using insight? >>Can I also get intelligence about the data to know that it's actually satisfying my objectives to influence my customers in my market? Or is there some sort of data drift or detraction in my, um, analytic capabilities that are allowing me to be effective in those environments, but everything else revolves around that and really thinking succinctly about a strategy that isn't just data aware, what data do I have and how do I use it, but coming in more from that business perspective to then start to be, data-driven recognizing that every activity you do from a business perspective leads to thinking about information that supports that and supports your decisions, and ultimately getting to the point of being insight driven, where you're able to both, uh, describe what you want your business to be with your data, using analytics, to then execute on that fluidly and in real time. And then ultimately bringing that back with linking to business outcomes and doing that in a continuous cycle where you can test and you can learn, you can improve, you can optimize, and you can innovate because you can see your business as it's happening. And you have the right signals and intelligence that allow you to make great decisions. >>I like how you said near time or real time, because it is a spectrum. And you know, one of the spectrum, autonomous vehicles, you've got to make a decision in real time, but, but, but near real-time, or real-time, it's, it's in the eyes of the holder, if you will, it's it might be before you lose the customer before the market changes. So it's really defined on a case by case basis. Um, I wonder Michelle, if you could talk about in working with a number of organizations, I see folks, they sometimes get twisted up and understanding the dependencies that technology generally, and the technologies around data specifically can have on critical business processes. Can you maybe give some guidance as to where customers should start, where, you know, where can we find some of the quick wins and high return, it >>Comes first down to how does your business operate? So you're going to take a look at the business processes and value stream itself. And if you can understand how people and customers, partners, and automation are driving that step by step approach to your business activities, to realize those business outcomes, it's way easier to start thinking about what is the information necessary to see that particular step in the process, and then take the next step of saying what information is necessary to make a decision at that current point in the process, or are you collecting information asking for information that is going to help satisfy a downstream process step or a downstream decision. So constantly making sure that you are mapping out your business processes and activities, aligning your data process to that helps you now rationalize. Do you need that real time near real time, or do you want to start grading greater consistency by bringing all of those signals together, um, in a centralized area to eventually oversee the entire operations and outcomes as they happen? It's the process and the decision points and acting on those decision points for the best outcome that really determines are you going to move in more of a real-time, uh, streaming capacity, or are you going to push back into more of a batch oriented approach? Because it depends on the amount of information and the aggregate of which provides the best insight from that. >>Got it. Let's, let's bring Cindy back into the conversation in your city. We often talk about people process and technology and the roles they play in creating a data strategy. That's that's logical and sound. Can you speak to the broader ecosystem and the importance of creating both internal and external partners within an organization? Yeah. >>And that's, uh, you know, kind of building upon what Michelle was talking about. If you think about datas and I hate to use the phrase almost, but you know, the fuel behind the process, um, and how do you actually become insight-driven? And, you know, you look at the capabilities that you're needing to enable from that business process, that insight process, um, you're extended ecosystem on, on how do I make that happen? You know, partners, um, and, and picking the right partner is important because a partner is one that actually helps under or helps you implement what your decisions are. Um, so, um, looking for a partner that has the capability that believes in being insight-driven and making sure that when you're leveraging data, um, you know, for within process on that, if you need to do it in a time fashion, that they can actually meet those needs of the business, um, and enabling on those, those process activities. So the ecosystem looking at how you, um, look at, you know, your vendors are, and fundamentally they need to be that trusted partner. Um, do they bring those same principles of value of being insight driven? So they have to have those core values themselves in order to help you as a, um, an end of business person enable those capabilities. So, so yeah, I'm >>Cool with fuel, but it's like super fuel when you talk about data, cause it's not scarce, right? You're never going to run out. So Michelle, let's talk about leadership. W w who leads, what does so-called leadership look like in an organization that's insight driven? >>So I think the really interesting thing that is starting to evolve as late is that organizations enterprises are really recognizing that not just that data is an asset and data has value, but exactly what we're talking about here, data really does drive what your business outcomes are going to be data driving into the insight or the raw data itself has the ability to set in motion. What's going to happen in your business processes and your customer experiences. And so, as you kind of think about that, you're now starting to see your CEO, your CMO, um, your CRO coming back and saying, I need better data. I need information. That's representative of what's happening in my business. I need to be better adaptive to what's going on with my customers. And ultimately that means I need to be smarter and have clearer forecasting into what's about ready to come, not just, you know, one month, two months, three months or a year from now, but in a week or tomorrow. >>And so that's, how is having a trickle down effect to then looking at two other types of roles that are elevating from technical capacity to more business capacity, you have your chief data officer that is shaping the exp the experiences, uh, with data and with insight and reconciling, what type of information is necessary with it within the context of answering these questions and creating a future fit organization that is adaptive and resilient to things that are happening. And you also have a chief digital officer who is participating because they're providing the experience and shaping the information and the way that you're going to interact and execute on those business activities, and either running that autonomously or as part of an assistance for your employees and for your customers. So really to go from not just data aware to data driven, but ultimately to be insight driven, you're seeing way more, um, participation, uh, and leadership at that C-suite level. And just underneath, because that's where the subject matter expertise is coming in to know how to create a data strategy that is tightly connected to your business strategy. >>Right. Thank you. Let's wrap. And I've got a question for both of you, maybe Cindy, you could start and then Michelle bring us home. You know, a lot of customers, they want to understand what's achievable. So it's helpful to paint a picture of a, of a maturity model. Uh, you know, I'd love to go there, but I'm not going to get there anytime soon, but I want to take some baby steps. So when you're performing an analysis on, on insight driven organization, city, what do you see as the major characteristics that define the differences between sort of the, the early, you know, beginners, the sort of fat middle, if you will, and then the more advanced, uh, constituents. >>Yeah, I'm going to build upon, you know, what Michelle was talking about as data as an asset. And I think, you know, also being data where, and, you know, trying to actually become, you know, insight driven, um, companies can also have data and they can have data as a liability. And so when you're data aware, sometimes data can still be a liability to your organization. If you're not making business decisions on the most recent and relevant data, um, you know, you're not going to be insight driven. So you've got to move beyond that, that data awareness, where you're looking at data just from an operational reporting, but data's fundamentally driving the decisions that you make. Um, as a business, you're using data in real time. You're, um, you're, you know, leveraging data to actually help you make and drive those decisions. So when we use the term you're, data-driven, you can't just use the term, you know, tongue in cheek. It actually means that I'm using the recent, the relevant and the accuracy of data to actually make the decisions for me, because we're all advancing upon. We're talking about, you know, artificial intelligence and so forth. Being able to do that, if you're just data where I would not be embracing on leveraging artificial intelligence, because that means I probably haven't embedded data into my processes. It's data could very well still be a liability in your organization. So how do you actually make it an asset? Yeah, I think data >>Where it's like cable ready. So, so Michelle, maybe you could, you could, you could, uh, add to what Cindy just said and maybe add as well, any advice that you have around creating and defining a data strategy. >>So every data strategy has a component of being data aware. This is like building the data museum. How do you capture everything that's available to you? How do you maintain that memory of your business? You know, bringing in data from your applications, your partners, third parties, wherever that information is available, you want to ensure that you're capturing and you're managing and you're maintaining it. And this is really where you're starting to think about the fact that it is an asset. It has value, but you may not necessarily know what that value is. Yet. If you move into a category of data driven, what starts to shift and change there is you're starting to classify label, organize the information in context of how you're making decisions and how you do business. It could start from being more, um, proficient from an analytic purpose. You also might start to introduce some early stages of data science in there. >>So you can do some predictions and some data mining to start to weed out some of those signals. And you might have some simple types of algorithms that you're deploying to do a next next best action for example. And that's what data-driven is really about. You're starting to get value out of it. The data itself is starting to make sense in context of your business, but what you haven't done quite yet, which is what insight driven businesses are, is really starting to take away. Um, the gap between when you see it, know it and then get the most value and really exploit what that insight is at the time when it's right. So in the moment we talk about this in terms of perishable insights, data and insights are ephemeral. And we want to ensure that the way that we're managing that and delivering on that data and insights is in time with our decisions and the highest value outcome we're going to have, that that insight can provide us. >>So are we just introducing it as data-driven organizations where we could see, you know, spreadsheets and PowerPoint presentations and lots of mapping to help make sort of longer strategic decisions, or are those insights coming up and being activated in an automated fashion within our business processes that are either assisting those human decisions at the point when they're needed, or an automated decisions for the types of digital experiences and capabilities that we're driving in our organization. So it's going from, I'm a data hoarder. If I'm data aware to I'm interested in what's happening as a data-driven organization and understanding my data. And then lastly being insight driven is really where light between business, data and insight. There is none it's all coming together for the best outcomes, >>Right? So people are acting on perfect or near perfect information or machines or, or, uh, doing so with a high degree of confidence, great advice and insights. And thank you both for sharing your thoughts with our audience today. It's great to have you. Thank you. Thank you. Okay. Now we're going to go into our industry. Deep dives. There are six industry breakouts, financial services, insurance, manufacturing, retail communications, and public sector. Now each breakout is going to cover two distinct use cases for a total of essentially 12 really detailed segments that each of these is going to be available on demand, but you can scan the calendar on the homepage and navigate to your breakout session for choice of choice or for more information, click on the agenda page and take a look to see which session is the best fit for you. And then dive in, join the chat and feel free to ask questions or contribute your knowledge, opinions, and data. Thanks so much for being part of the community and enjoy the rest of the day.

(Upbeat Music) >> Commvault was an idea that incubated as a project inside of Bell Labs, one of the most prestigious research and development organizations in the world, back in the day. It became an official company in 1996, and Commvault just celebrated its 25th anniversary As such, Commvault has had to reinvent itself many times over the past two and a half decades from riding the waves of the very early PC networking era to supporting a rich set of solutions for the evolving enterprise. This includes things like cloud computing, ransomware, disaster recovery, security compliance, and pretty much all things data protection and data management. And with me to talk about the company, its vision for the future with also a voice of the customer are three great guests. Isabelle Guis is the Chief Marketing Officer of Commvault, Manoj Nair is the GM of Metallic, and Tim Carben is a Principal Systems Engineer with Mitchell International. Folks, welcome to the Commvault power panel. Come inside theCUBE. It's awesome to have you. [Isabelle] Great to be here today. >> All right. First of all, I got to congratulate you celebrating 25 years. That's a long time, not a lot of tech companies make it that far and are still successful and relevant. So Isabelle, maybe you could start off. What do you think has been the driving factor for your ability to kind of lead through the subsequent technological waves that I alluded to upfront? >> So well, 25 years is commendable but we are not counting success in number of years. We're really counting success in how many customers we've helped over those years. And I will say what has been the driving matter for us as who that, has been innovating with our customers. You know, we were there every step of the way when they migrate to hybrid cloud. And now as they go to multi-cloud in a post COVID world where they have to win gold you know, distributed workforce, different types of workloads and devices, we all there too. We assess workload as well. So the innovation keep coming in, thanks to us listening to our customer and then, adding needs that change over the last 25 years and probably for the next 25 as well. You know, we want to be here for customer was thinking that data is an asset, not a liability. And also making sure that we offer them a broad range of use cases to quote why things simple because the world is getting too complex for them. So let's take the complexity on us. >> Thank you for that. So Manoj, you've riffed on the cube before about, you know putting on the binoculars and looking at the future. So, let's talk about that. Where do you see the future for this industry? What are some of the key driving factors that matter? >> It's great to be back on theCUBE. You know, we see our industry no different than lots of other industries. The SaaS Model is rapidly being adopted. And the reason is, you know customers are looking for simplicity, simplicity not just in leveraging, you know the great technology that Commvault has built, but in the business model and the experience. So, you know, that's one of the fastest growing trends that started in consumer apps and other applications, other B to B apps. And now we're seeing it in core infrastructure like data management, data protection. They're also trying to leverage their data better. Make sure it's not fragmented. So how do you deliver more intelligent services? You know, securing the data, insights from the data, transforming the data, and that combination, you know, our ability to do that in a multi-cloud world like Isabelle said, now with increasing edge work loads. Sometimes, you know, our customers say their data centers has a new edge too. So you kind of have this, you know, data everywhere workloads everywhere, yet the desire to deliver that with a holistic experience, we call it the 'power of bank'; the ability to manage your data and leverage the data with the simple lesson without compromise. And that's really what we're seeing as part of the future. >> Okay. I don't know if all want to come back to you and double click on that, but I want to introduce Tim to the conversation here. You bring in the voice of the customer, as they say. Tim, my understanding is Mitchell has been a Commvault customer since the mid-2000s. So, tell us why Commvault, what has kept you with the company for more than 15 years? >> Yeah, we are, it was what, 2006 when we started. And really what it all boils down to it, it's just as Isabel said, innovation. At Mitchell, we're always looking to stay ahead of the trend. And, you know, just to like was mentioned earlier, data is the most important part here. Commvault provides us peace of mind to protect and manage our data. And they do data protection for all of our environments right now. We've been a partner to help in navel our digital transformation including SaaS and cloud adoption. When we start talking about the solutions we have, I mean we of course started in 2006. I mean, this was version version 6 if I remember right. This predates me at the company. Upgraded to seven, eight, nine, we brought in ten, brought in eleven, brought in HyperScale, and then moved on to bring in the Metallic. And Commvault provides the reason for this. I guess I should say is, Commvault provides a reliable backup but most importantly, recovery. Rapid recovery. That's what gives me confidence. That's what helps me sleep better at night. So when I started looking at SaaS as a differentiator to protect our 036 environments or 065 environments, Metallic was a natural choice. And the one thing I wanted to add to that is, it came out cheaper than us building it ourselves. When you take into account resources as well as compute and storage. So again, just a natural choice. >> Yeah. As the saying goes back up as one thing, recovery's everything. Isabelle. Yeah, we've seen the SaaSification of the enterprise. Particularly, you know from the app side. You came from Salesforce. So you, the company that is the poster child for SaaS. But my question is what's catalyzing this shift and why do you think data protection is ready to make the move? >> Well, there's so many good things and that's that. As you know, you remember when people started moving to the cloud and transforming their CAPEX into OPEX. Well SaaS bring yet another level of benefits. IT, we know always has to do more with less. And so SaaS allows you to, once you set up, you've got all the software upgrades automatically without you know, I think it's, why it works. You can better manage your cash flow, because you pay as you grow. And also you have a faster time to value. So all of this at help, the fast adoption and I will tell you today I don't think there is a single customer who doesn't have at least one SaaS application because they have things of value of this. Now, when it comes to backup and recovery everybody's at different stages. You still have On-Premises, you have cloud, there's SaaS, there's Workloads devices. And so what we think was the most important was to offer a broad choice of delivery model being able to support them if they want a software subscription, if they want an integrated appliance, or if they want SaaS as a service model, and also some of our partners actually delivering this in a more custom and managed way as well. So offering choice, because everybody is at a different stage on this journey. When it comes to data management and protection, I actually, you know, I think team is the example of taking full advantage of this bold choice. >> Well, you mentioned Tim that you leaned into Metallic. We have seen the SaaS everywhere. We used to have a email server, right? I mean, you know, On-Prem, that just doesn't happen anymore. But how was Mitchell International thinking about SaaS? Maybe you could share your, from your customer perch, what you're seeing. >> Well, what's interesting about this is, Mitchell is been providing SaaS for a long time. We are a technology company and we do provide solutions, SaaS solutions, to our customers. And this makes it so important to be able to embrace it because we know the value behind it. We're providing that to our customers. And when I look at what Commvault is doing I know that Commvault is doing the same thing. They're providing the SaaS Model as a value to their customers. And it's so important to go with this because we keep our environments cutting edge. As GDPR says, You need to have a cutting edge environment. And if you don't, if you cannot check that box you do not move forward. Commvault has that. And this is one less thing that I have to worry about when choosing Metallic to do my backup of O365. >> So thank you for that, Tim. So Manoj, thinking about what you just heard from Isabelle and Tim, you know, kind of fitting into a company's cloud or hybrid cloud, more importantly, strategy, you were talking before about this. "And", in other words, it's not an either or it's not a zero sum game. It's simpatico, if you will. I wonder if you could elaborate. >> Yeah, no The Power of And, Dave, I'm very proud of that. You know, when I think of The Power of And I think of actually folks like Tim, our customers and Commonwealth first, right. And, and really that, that need for choice. So for example, you know, customers on various different paths to the cloud we kind of homogenize it and say, they're on a cloud journey or they're on a digital transformation journey, but each journey looks different. And so part of that, "And", as Isabella was saying, is really the ability to meet them where they are in that journey. So for example, you know, do you, go in there and say, Hey, you know what, I'm going to be some customers 100% multi-cloud or single cloud even. And that includes SaaS applications and my infrastructure running as a service. So there's a natural fit there saying great all your data protection. You're not going to be running software appliances for that. So you've got to data protection, data management as a service that Metallic is the able to offer across the whole S state. And that's, you know, that's probably a small set of customers, but rapidly growing. Then you see a lot more customers were saying I'm going to do away as you're talking about but the emails are where I'm going to move to office 365, leverage the power of teams. And there's a Shared Responsibility Model there which is different than an On-Prem data protection use case. And so they're, they're able to just add on Metallic to the existing Commonwealth environment, whether it's a Commonwealth software or HyperScale, and connect the two. So it's a single integrated experience. And then you kind of go to the other end of the spectrum and say, great customers all in on a SaaS delivered data protection, as you know, and you hear a lot from a lot of your guests and we hear from our customers, there's still a lot of data sitting out there, you know, 90 plus percent of workloads and data centers increasing edge data workloads. And if you were to back up one of those data workloads and say that the only copy can be in the cloud, then that would take like a 10 day recovery isolation. You know, we have some competitors who say that then that's what they have. Our flexibility, our ability to kind of bring in the Hyper-Scale deployment and just, you know, dock it into Metallic, and have a local copy, instant recovery, SLA, remote, you know, backup copy in the cloud for ransomware, or your worst case scenario. That's the kind of flexibility. So all those are scenarios we're really seeing with our customers. And that's kind of really the power advantage. A very unique part of our portfolio, but, you know, companies can have portfolio products, but to have a single integrated offering with that flexibility, that kind of, depending on the use case, you can start here and grow into a different point. That's really the unique part of the power event. Yeah, 10 day RTO just doesn't cut it, but Timmy, maybe you could weigh in here. Why, What was the catalyst for you adopting Metallic and maybe you could share what was the business impact there? >> Well, the catalyst and impact, obviously two different things. The catalyst, when we look at it, there was a lot of what are we going to do with this? We have an environment, we need to back it up, and how are we going to approach this? So we looked at it from a few different standpoints, and of course, when it boils down to it, one of the major reasons was the financial. But when we started looking at everything else that we have available to us and the flexibility that Commvault has in rolling out new solutions, this really was a no brainer at this point. We are able to essentially back up new features and new products, as soon as they're available. Within our Metallic environment, we are running the activate. We are running the the self-service for the end users to where they can actually recover their own files. We are adding the teams into it to be able to recover and perform these backups for teams. And I want to step aside really quick and mentioned something about this because I'd been with, you know, Metallic for a long time and I'd been waiting for this. We've been waiting for an ability to do these backups and anyone I know Manoj knows that I've been waiting for it. And you know, Commvault came back to me a while back and they said, we just have to wait for the API. We have to wait for Microsoft releases. Well, I follow the news. I saw Microsoft released the API, and I think it may have been two days later. Good. Commvault reached out to me and said, Hey we got it available. Are you ready to do this? And that sort of turned around that sort of flexibility being on top of new applications with that, with Salesforce, that is, you know, just not necessarily the reason why I adopted Metallic but one of those things that puts a smile on my face because I adopted Metallic. >> Well, that's an interesting story. I mean, you get the SDKs and if you're a leader you get them, you know, you can put the resources on it and you're ready when, when the product, you know, comes to GA. Manoj, I wonder if we could talk about just the notion of backing up SaaS, part of the announcements today included within Metallic included backup and offerings for Dynamics 365. But my question is why support Dynamics specifically in SaaS apps generally? I mean, customers might say, doesn't my SaaS provider protect my data? Why do I need a third party? And, and the second part of that question is why Commvault? >> Dave a great question as always. I'll start with the second part of the question. It's really three words the Shared Responsibility Model. And, you know, a lot of times our customers as they go into the cloud model they really start understanding that there is something that you're getting a lot of advantages the certain things you don't have to do, but the Shared Responsibility Model is what every cloud and SaaS provider will indoctrinate in its S&As. And certainly the application data is owned by the customer. And the meaning of that is not something that, you know, some SaaS provider can understand. And so that requires specialized skills. And that's a partnership. We've done this now very successfully with Microsoft and LG 65, we've added support for Salesforce, and we see a rapid customer adoption because of that Shared Responsibility Model. If you have, some kind of, an admin issue as we have seen in the news somebody changed their team setting and then lost all their chat. And then that data is discoverable. And you, the customer is responsible for making sure that data is discoverable or ransomware attacks. Again, recovering that SaaS data is your responsibility because the attack could be coming in from your instance not from the SaaS provider. So those are the reasons. Dynamics is, you know, one of the fastest growing SaaS applications from a business applications perspective out there. And as we looked at our roadmap, and you look at at the right compliment, what is the right adjacency, we're seeing this part of Microsoft's Business Application Suite growing, you know, as millions of users out there and it's rapidly growing. And it's also integrated with the rest of the Microsoft family. So we're now, you know, proud to say that we support all three Microsoft clouds, Microsoft Azure, or 365, Dynamics. Those applications are increasingly integrated so we're seeing commonality in customer base and that's a business critical data. And so customers are looking to manage the data, have solutions that they can be sure they can leverage. It's not just protecting data from worst-case scenarios. In the case of some of the apps like Dynamics, we offer a support, like setting up the staging environment. So it's improving productivity of the application admins, and that's really kind of that the value we're bringing able to bring to the table. >> Yeah. You know, that Shared Responsibility Model. I'm glad you brought that up because I think it's oftentimes misunderstood but when you talk to CSOS, they understand it well. They'll tell you the shared responsibility is my responsibility. You know, maybe the cloud provider will secure the object storage bucket for the physical space, but it's on me. So that's really important. So thank you for that. Isabelle, last question, the roadmap, you know, how do you see Commvault's, Metallic SaaS portfolio evolving? What can you tell us? >> Oh, well, it's, it has a big strategic, you know, impact on Commvault for sure on the first portfolio first because of all of our existing customers as you mentioned earlier, 25 years, it's a lot of customers are somehow some workload as SaaS. And so the ability without, you know, adding more complexity without adding another vendor just to be able to protect them in one take, and as teams they bring a smile to his face is really important for us. The second is also a lot of customers come to Commvault for Metallic. This is the first time enter the Commvault community and Commvault family. And as they start protecting their assessed application they realize that they could leverage the same application to protect their own premised data as well. So back to The Power of And, and without writing off their past investments, you know, going to the cloud at the pace they want. So from that perspective, there is a big impact on our customer community the thing is that Metallic it brings I don't know Manoj is way too humble, but, you know, he don't go to this customer every quarter. And, you know, we have added 24 countries to the portfolio, to the product. So we see a rapid adoption. And so obviously back to your question, we see the impacts of Metallic growing and growing fast because of the market demand, because of the rapid innovation we can take the Commvault technology and put it in the SaaS model and our customers really like it. So I'm very excited. I think it's going to be, you know, a great innovation, a great positive impact for customers, and our new customers we're welcoming, which by the way I think half, Manoj correct me, but I think half of the Metallic customer at Commvault and the other half are new to our family. So, they're very bullish about this. And it's just the beginning, as you know, we are 25 years old, or sorry, 25 years young, and looking forward to the next 25. >> Well, I can confirm, you know, we have a data partner survey, partner ETR, Enterprise Technology Research, and I was looking at the Commvault data and it shows within the cloud segment, when you cut the data by cloud, you're actually accelerating, the spending momentum is accelerating. And I think it's a function of, you know, some of the acquisitions you've made, some of the moves you made in integration. So congratulations on 25 years and you know, you're riding the correct wave, Isabelle, Manoj, Tim, thanks so much for coming in theCUBE. It was great to have you. >> Thank you. >> Thank you Dave. >> I really appreciate it. >> And thank you everybody for watching. This is Dave Vellante for theCUBE. We'll see you next time. (Upbeat Music)

>> Narrator: From around the globe, it's theCUBE with coverage of KubeCon and CloudNativeCon Europe, 2021 Virtual brought to you by Red Hat, the Cloud Native Computing Foundation and Ecosystem Partners. >> Hello, welcome back to theCUBE'S coverage of KubeCon and CloudNativeCon 2021 Virtual, I'm John Furrier your host of theCUBE. We've got two great guests here, always great to talk to the KubeCon co-chairs and we have Stephen Augustus Head of Open Source at Cisco and also the KubeCon co-chair great to have you back. And Jasmine James Manager and Engineering Effectives at Twitter, the KubeCon co-chair, she's new on the job so we're not going to grill her too hard but she's excited to share her perspective, Jasmine, Stephen great to see you. Thanks for coming on theCUBE. >> Thanks for having us. >> Thank you. >> So obviously the co-chairs you guys see everything upfront Jasmine, you're going to learn that this is a really kind of key fun position because you've got to multiple hats you got to wear, you got to put a great program together, you got to entertain and surprise and delight the attendees and also can get the right trends, pick everything right and then keep that harmonious vibe going at CNCF and KubeCon is hard so it's a hard job. So I got to ask you out of the gate, what are the top trends that you guys have selected and are pushing forward this year that we're seeing evolve and unfold here at KubeCon? >> For sure yeah. So I'm excited to see, and I would say that some of the top trends for Cloud Native right now are just changes in the ecosystem, how we think about different use cases for Cloud Native technology. So you'll see lot's of talk about new architectures being introduced into Cloud Native technologies or things like WebAssembly. WebAssembly Wasm used cases and really starting to and again, I think I mentioned this every time, but like what are the customer used cases actually really thinking about how all of these building blocks connect and create a cohesive story. So I think a lot of it is enduring and will always be a part. My favorite thing to see is pretty much always maintainer and user stories, but yeah, but architecture is Wasm and security. Security is a huge focus and it's nice to see it comes to the forefront as we talked about having these like the security day, as well as all of the talk arounds, supply chain security, it has been a really, really, really big event (laughs) I'll say. >> Yeah. Well, great shot from last year we have been we're virtual again, but we're back in, the real world is coming back in the fall, so we hopefully in North America we'll be in person. Jasmine, you're new to the job. Tell us a little about you introduce yourself to the community and tell more about who you are and why you're so excited to be the co-chair with Stephen. >> Yeah, absolutely. So I'm Jasmine James, I've been in the industry for the past five or six years previous at Delta Airlines, now at Twitter, as a part of my job at Delta we did a huge drive on adopting Kubernetes. So a lot of those experiences, I was very, very blessed to be a part of in making the adoption and really the cultural shift, easy for developers during my time there. I'm really excited to experience like Cloud Native from the co-chair perspective because historically I've been like on the consumer side going to talk, taking all those best practices, stealing everything I could into bring it back into my job. So make everyone's life easier. So it's really, really great to see all of the fantastic ideas that are being presented, all of the growth and maturity within the Cloud Native world. Similar to Stephen, I'm super excited to hear about the security stuff, especially as it relates to making it easy for developers to shift left on security versus it being such an afterthought and making it something that you don't really have to think about. Developer experience is huge for me which is why I took the job at Twitter six months ago, so I'm really excited to see what I can learn from the other co-chairs and to bring it back to my day-to-day. >> Yeah, Twitter's been very active in open source. Everyone knows that and it's a great chance to see you land there. One of the interesting trends is this year I'll see besides security is GitOps but the one that I think is relevant to your background so fresh is the end user contributions and involvement has been really exploding on the scene. It's always been there. We've covered, Envoy with Lyft but now enterprise is now mainstream enterprises have been kind of going to the open source well and bringing those goodies back to their camps and building out and bringing it back. So you starting to see that flywheel developing you've been on that side now here. Talk about that dynamic and how real that is an important and share some perspective of what's really going on around this explosion around more end user contribution, more end user involvement. >> Absolutely. So I really think that a lot of industry like players are starting to see the importance of contributing back to open source because historically we've done a lot of taking, utilizing these different components to drive the business logic and not really making an investment in the product itself. So it's really, really great to see large companies invest in open source, even have whole teams dedicated to open source and how it's consumed internally. So I really think it's going to be a big win for the companies and for the open source community because I really am a big believer in like giving back and making sure that you should give back as much as you're taking and by making it easy for companies to do the right thing and then even highlighting it as a part of CNCF, it'll be really, really great, just a drive for a great environment for everyone. So really excited to see that. >> That's really good. She has been awesome stuff. Great, great insight. Stephen, I just have you piggyback off that and comment on companies enterprises that want to get more involved with the Cloud Native community from their respective experiences, what's the playbook, is there a new on-ramps? Is there new things? Is there a best practice? What's your view? I mean, obviously everyone's growing and changing. You look at IT has changed. I mean, IT is evolving completely to CloudOps, SRE get ops day two operations. It's pretty much standard now but they need to learn and change. What's your take on this? >> Yeah, so I think that to Jasmine's point and I'm not sure how much we've discussed my background in the past, but I actually came from the corporate IT background, did Desktop Sr, Desktop helped us support all of that stuff up into operations, DevOps, SRE, production engineering. I was an SRE at a startup who used core West technologies and started using Kubernetes back when Kubernetes is that one, two, I think. And that was my first journey into Cloud Native. And I became core less is like only customer to employee convert, right? So I'm very much big on that end user story and figuring out how to get people involved because that was my story as well. So I think that, some of the work that we do or a lot of the work that we do in contributor strategy, the SIG CNCF St. Contributor Strategy is all around thinking through how to bring on new contributors to these various Cloud Native projects, Right? So we've had chats with container D and linker D and a bunch of other folks across the ecosystem, as well as the kind of that maintainer circle sessions that we hold which are kind of like a private, not recorded. So maintainers can kind of get raw and talk about what they're feeling, whether it be around bolstering contributions or whether it'd be like managing burnout, right? Or thinking about how you talk through the values and the principles for your projects. So I think that, part of that story is building for multiple use cases, right? You take Kubernetes for example, right? So Ameritas chair for sync PM over in Kubernetes, one of the sub project owners for the enhancements sub project which involves basically like figuring out how we intake new enhancements to the community but as well as like what the end user cases are all of the use cases for that, right? How do we make it easy to use the technology and how we make it more effective for people to have conversations about how they use technology, right? So I think it's kind of a continuing story and it's delightful to see all of the people getting involved in a SIG Contributor Strategy, because it means that they care about all of the folks that are coming into their projects and making it a more welcoming and easier to contribute place so. >> Yeah. That's great stuff. And one of the things you mentioned about IT in your background and the scale change from IT and just the operational change over is interesting. I was just talking with a friend and we were talking about, get Op and, SRAs and how, in colleges is that an engineering track or is it computer science and it's kind of a hybrid, right? So you're seeing essentially this new operational model at scale that's CloudOps. So you've got hybrid, you've got on-premise, you've got Cloud Native and now soon to be multi-cloud so new things come into play architecture, coding, and programmability. All these things are like projects now in CNCF. And that's a lot of vendors and contributors but as a company, the IT functions is changing fast. So that's going to require more training and more involvement and yet open source is filling the void if you look at some of the successes out there, it's interesting. Can you comment on the companies that are out there saying, "Hey, I know my IT department is going to be turning into essentially SRE operations or CloudOps at scale. How do they get there? How could they work with KubeCon and what's the key playbook? How would you answer that? >> Yeah, so I would say, first off the place to go is the one-on-one track. We specifically craft that one-on-one track to make sure that people who are new to Cloud Native get a very cohesive story around what they're trying to get into, right? At any one time. So head to the one-on-one track, please add to the one-on-one track, hang out, definitely check out all of the keynotes that again, the keynotes, we put a lot of work into making sure these keynotes tell a very nice story about all of the technology and the amount of work that our presenters put into it as well is phenomenal. It's top notch. It's top notch every time. So those will always be my suggestions. Actually go to the keynotes and definitely check out the one-on-one track. >> Awesome. Jasmine, I got to get your take on this now that you're on the KubeCon and you're co-chairing with Stephen, what's your story to the folks that are in the end user side out there that were in your old position that you were at Delta doing some great Kubernetes work but now it's going beyond Kubernetes. I was just talking with another participant in the KubeCon ecosystem is saying, "It's not just Kubernetes anymore. There's other systems that we're going to deploy our real-time metrics on and whatnot". So what's the story? What's the update? What do you see on the inside now now that you're on board and you're at a Hyperscale at Twitter, what's your advice? What's your commentary to your old friends and the end user world? >> Yeah. It's not an easy task. I think that was, you had mentioned about starting with the one-on-one is like super key. Like that's where you should start. There's so many great stories out there in previous KubeCon that have been told. I was listening to those stories and the great thing about our community is that it's authentic, right? We're telling like all of the ways we tripped up so we can prevent you from doing this same thing and having an easier path, which is really awesome. Another thing I would say is do not underestimate the cultural shift, right? There are so many tools and technologies out there, but there's also a cultural transformation that has to happen. You're shifting from, traditional IT roles to a really holistic like so many different things are changing about the way infrastructure was interacted with the way developers are developing. So don't underestimate the cultural shift and make sure you're bringing everyone to the party because there's a lot of perspectives from the development side that needs to be considered before you make the shift initially So that way you can make sure you're approaching the problem in the right way. So those would be my recommendation. >> Also, speaking of cultural shifts, Stephen I know this is a big passion of yours is diversity in the ecosystem. I think with COVID we've seen probably in the past two years a major cultural shifts on the personnel involved, the people participating, still a lot more work to get done. Where are we on diversity in the ecosystem? How would you rate the progress and the overall achievements? >> I would say doing better, but never stop what has happened in COVID I think, if you look across companies, if you look across the opportunities that have opened up for people in general, there have been plenty of doors that have shut, right? And doors that have really made the assumption that you need to be physical are in person to do good work. And I think that the Cloud Native ecosystem the work that the LF and CNCF do, and really the way that we interact in projects has kind of pushed towards this async first, this remote first work culture, right? So you see it in these large corporations that have had to change the travel policies because of COVID and really for someone who's coming off being like a field engineer and solutions architect, right? The bread and butter is hopping on and off a plane, shaking hands, going to dinner, doing the song and dance, right? With customers. And for that model to functionally shift, right? Having conversations in different ways, right? And yeah, sometimes it's a lot of Zoom calls, right? Zoom calls, webinars, all of these things but I think some of what has happened is, you take the release team, for example, the Kubernetes release team. This is our first cycle with Dave Vellante who's our 121 released team lead is based in India, right? And that's the first time that we've had APAC region release team lead and what that forced us to do, we were already working on it. But what that forced us to do is really focused on asynchronous communication. How can we get things done without having to have people in the room? And we were like, "With Dave Vellante in here, it either works or it doesn't like, we're either going to prove that what we've put in place works for asynchronous communication or it doesn't." And then, given that a project of this scale can operate just fine, right? Right just fine delivering a release with people all across the globe. It proves that we have a lot of flexibility in the way that we offer opportunities, both on the open source side, as well as on the company side. >> Yeah. And I got to say KubeCon has always been global from day one. I was in Shanghai and I was in hung, Jo, visiting Ali Baba. And who do I see in the lobby? The CNCF crew. And I'm like, "What are you guys doing here?" "Oh, we're here talking to the cloud with Alibaba." So global is huge. You guys have nailed that. So congratulations and keep that going. Jasmine, your perspective is women in tech. I mean, you're seeing more and more focus and some great doors opening. It's still not enough. We've been covering this for a long time. Still the numbers are down, but we had a great conference recently at Stanford Women in Data Science amazing conference, a lot of power players coming in, women in tech is evolving. What's your take on this still a lot more work to done. You're an inspiration. Share your story. >> Yeah. We have a long way to go. There's no question about it. I do think that there's a lot of great organizations CNCF being one of them, really doing a great job at sharing, networking opportunities, encouraging other women to contribute to open source and letting that be sort of the gateway into a tech career. My journey is starting as a systems engineer at Delta, working my way into leadership, somehow I'm not sure I ended up there but really sort of shifting and being able to lift other women up has been like so fortunate to be able to do that. Women who code being a mentor, things of that nature has been a great opportunity, but I do feel like the open source community has a long way go to be a more welcoming place for women contributors, things like code of conduct, that being very prevalent making sure that it's not daunting and scary, going into GitHub and starting to create a PR for out of fear of what someone might say about your contributions instead of it being sort of an educational experience. So I think there's a lot of opportunities but there's a lot of programs, networking opportunities out there, especially everyone being remote now that have presented themselves. So I'm very hopeful. And the CNCF, like I said is doing a great job at highlighting these women contributors that are making changes to CNCF projects in really making it something that is celebrated which is really great. >> Yeah. You know that I love Stephen and we thought this last time and the Clubhouse app has come online since we were last talking and it's all audio. So there's a lot of ideas and it's all open. So with a synchronous first you have more access but still context matters. So the language, so there's still more opportunities potentially to offend or get it right so this is now becoming a new cultural shift. You brought this up last time we chatted around the language, language is important. So I think this is something that we're keeping an eye on and trying to keep open dialogue around, "Hey it matters what you say, asynchronously or in texts." We all know that text moment where someone said, "I didn't really mean that." But it was offensive or- >> It's like you said it. (laughs) >> (murmurs) you passionate about this here. This is super important how we work. >> Yeah. So you mentioned Clubhouse and it's something that I don't like. (laughs) So no offense to anyone who is behind creating new technologies for sure. But I think that Clubhouse from, if you take platforms like that, let's generalize, you take platforms like that and you think about the unintentional exclusion that those platforms involve, right? If you think about folks with disabilities who are not necessarily able to hear a conversation, right? Or you don't provide opportunities to like caption your conversations, right? That either intentionally or unintentionally excludes a group of folks, right? So I've seen Cloud Native, I've seen Cloud Native things happen on a Clubhouse, on a Twitter Spaces. I won't personally be involved in them until I know that it's a platform that is not exclusive. So I think that it's great that we're having new opportunities to engage with folks that are not necessarily, you've got people prefer the Slack and discord vibe, you've got people who prefer the text over phone calls, so to speak thing, right? You've got people who prefer phone calls. So maybe like, maybe Clubhouse, Twitter Spaces, insert new, I guess Disco is doing a thing too- >> They call it stages. Disco has stages, which is- >> Stages. They have stages. Okay. All right. So insert, Clubhouse clone here and- >> Kube House. We've got a Kube House come on in. >> Kube House. Kube House. >> Trivial (murmurs). >> So we've got great ways to engage there for people who prefer that type of engagement and something that is explicitly different from the I'm on a Zoom call all day kind of vibe enjoy yourselves, try to make it as engaging as possible, just realize what you may unintentionally be doing by creating a community that not everyone can be a part of. >> Yeah. Technical consequences. I mean, this is key language matters to how you get involved and how you support it. I mean, the accessibility piece, I never thought about that. If you can't listen, I mean, you can't there's no content there. >> Yeah. Yeah. And that's a huge part of the Cloud Native community, right? Thinking through accessibility, internationalization, localization, to make sure that our contributions are actually accessible, right? To folks who want to get involved and not just prioritizing, let's say the U.S. or our English speaking part of the world so. >> Awesome. Jasmine, what's your take? What can we do better in the world to make the diversity and inclusion not a conversation because when it's not a conversation, then it's solved. I mean, ultimately it's got a lot more work to do but you can't be exclusive. You got to be diverse more and more output happens. What's your take on this? >> Yeah. I feel like they'll always be work to do in this space because there's so many groups of people, right? That we have to take an account for. I think that thinking through inclusion in the onset of whatever you're doing is the best way to get ahead of it. There's so many different components of it and you want to make sure that you're making a space for everyone. I also think that making sure that you have a pipeline of a network of people that represent a good subset of the world is going to be very key for shaping any program or any sort of project that anyone does in the future. But I do think it's something that we have to consistently keep at the forefront of our mind always consider. It's great that it's in so many conversations right now. It really makes me happy especially being a mom with an eight year old girl who's into computer science as well. That there'll be better opportunities and hopefully more prevalent opportunities and representation for her by the time she grows up. So really, really great. >> Get her coding early, as I always say. Jasmine great to have you and Stephen as well. Good to see you. Final question. What do you hope people walk away with this year from KubeCon? What's the final kind of objective? Jasmine, we'll start with you. >> Wow. Final objective. I think that I would want people to walk away with a sense of community. I feel like the KubeCon CNCF world is a great place to get knowledge, but also an established sense of community not stopping at just the conference and taking part of the community, giving back, contributing would be a great thing for people to walk away with. >> Awesome. Stephen? >> I'm all about community as well. So I think that one of the fun things that we've been doing, is just engaging in different ways than we have normally across the kind of the KubeCon boundaries, right? So you take CNCF Twitch, you take some of the things that I can't mention yet, but are coming out you should see around and pose KubeCon week, the way that we're engaging with people is changing and it's needed to change because of how the world is right now. So I hope that to reinforce the community point, my favorite part of any conference is the hallway track. And I think I've mentioned this last time and we're trying our best. We're trying our best to create it. We've had lots of great feedback about, whether it be people playing among us on CNCF Twitch or hanging out on Slack silly early hours, just chatting it up. And are kind of like crafted hallway track. So I think that engage, don't be afraid to say hello. I know that it's new and scary sometimes and trust me, we've literally all been here. It's going to be okay, come in, have some fun, we're all pretty friendly. We're all pretty friendly and we know and understand that the only way to make this community survive and thrive is to bring on new contributors, is to get new perspectives and continue building awesome technology. So don't be afraid. >> I love it. You guys have a global diverse and knowledgeable and open community. Congratulations. Jasmine James, Stephen Augustus, co-chairs for KubeCon here on theCUBE breaking it down, I'm John Furrier for your host, thanks for watching. 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>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020. Special coverage sponsored by A. W s Global Partner Network. Welcome back to the cubes Coverage Cube. Virtual coverage of AWS reinvent 2020. We're not in person this year. We have to do the all the Cube interviews remote. But we've got two great guests from the Amazon Web Services Partner Network A W s a p N. Craig Wicks, senior manager of AWS Satisfactory. Todd Golden, Principal Cloud Architect, Global SAS Tech Lead Gentlemen, Thanks for joining the Cube. Appreciate it. >>Thanks, John. >>Um, first of all, I want to get in Craig with you and just take them in to explain what is the satisfactory. Because this is a unique and growing team within AWS. Um, we've been saying it for years, but the moves to the cloud houses has been obvious is mainstream. But your team, your role is doing some interesting things. Explain. What is the satisfactory? What do you guys do? >>Yeah, Thanks, John. Really delighted to be here today. Yeah, the satisfactory. Maybe for those that may be somewhat disappointing. There's no factory, no sort of easy button for SAS. There's no templates. There's no machinery. We wish we had it. But we're really a global team of subject matter. Experts in SAS that really help AWS partners transform their business right both business and technical to the Saas model and help them do that faster with greater confidence and all the best practices that our team has learned over the years. >>And Todd, your solution architect. So you're the partner. You have to help your customers get their, um, you know, being a solution architect really is like the mechanic of the business. You gotta lay out the engine of innovation and this is what clients are trying to strive for. Can you take him and explain how your role is involved in this? Obviously, SAS is not. It makes sense on paper, but making it happen is not trivial. What do you What do you what? Your role. >>Yeah, so I'm very much, in fact, connected to Craig. We're all part of the same organization, and we're sort of very much deeply involved with these organizations. We get very much, um, embedded with these these partners that we work with and really helped them through sort of the nuts and bolts of what it means to transform an application thio multi tenant sort of SAS models. That means helping them figure out how to map that two different AWS services. It means helping them figure out how to realize the sort of the business objective objectives of transforming to sass. But really, our goal is to sort of just get into the weeds with them, figure out their specific domain because there's no one size fits all. Versace figure out how that really connects toe, where they're at in their trajectory, in terms of where they're trying to get to end of the journey is a business and then find that alignment with a W S services. So there's sort of that trifecta of lining all those bits up and sort of formulating, Ah, technical strategy that really brings all those pieces together for them. >>Craig, I want to get your thoughts on the trends, and Todd, you can weigh in to want to get your reaction. Over the weekend, I was picking some folks on on the Internet, linked in and whatnot from eight years ago when that we did our first cube at reinvent with second year of reinvent, and nobody was there in the industry press, wasn't there were the first I think press to be there. Um and a lot of people have either moved on to big positions or companies have gone public. I bought me. Major things have happened in 2013 clouds certainly rose there. SAS became the business model. Everyone kind of knows that. But the dynamics today are different when you think about the on premises and you got the edge. A big part of the themes this week in the next couple weeks as we unfold here reinvent. This >>is >>different, but the same Can you share? What is the trend that people are riding on? What's the What's the wind of innovation? >>Yeah, and certainly I would say, First of all, just personally, I've been in SAS for some time. It was involved early on, in sort of, ah, model. We called the application service provider model, which was sort of a predecessor assassin, you know, the gray hairs out to remember that one. But, uh, you know, I think first of all, I would say SAS is everywhere and people wanted to be everywhere And so there's just We just see insatiable demand for sass from from customers out there, right? And I think the challenge problem we see is that organizations that we work with just can't transition fast enough, right? The rial technical challenges that air in front of them in terms of how they build an architect, Assaf solution and but most importantly, the business model that sort of underpins. That is a huge transformation for companies that they're going through. And that's one of the things that we just see. You know, Justin, my time in satisfactory native us. The range of organizations we worked with has just changed. So, you know, early on we're working with companies and infrastructure around security and storage and those areas, and the last few years it's just expanded to all sorts of industries, from public sector oil and gas. Um, sort of financial services. You know, everyone really wants to build this model, and that's really, you know, born around the customer demand they're seeing for South. >>That's interesting. You mention challenge. I wanna get your thoughts. You mentioned a SP application service provided you remember those days, you know, vividly, mainly a tech thing, but it's really a consumption model around delivery of software and services. And, you know, Web services came on in 2000. The rest is history. We've got Amazon Web services, but now, as you get more vertically expanded oil and gas and go mainstream. But what >>are some >>of the challenges? Because as people get smarter, it's not just about self service or buy as you go. It's a business model you mentioned. Is it a managed services itself? Services has been embedded into the application. Can you share some of the new things that are emerging on the business model side that people should pay attention to? What, some of those challenges? Yeah, I >>think one of the first things is just a fundamentally are operating service, right? So that changes the dynamics to everything, for in terms of how you engage with customers to how you deliver. You know, the kind of simple thing E I often tell people is you know who's answering the pager now. If someone goes, if something goes wrong, it's not your customer. That's you right, and you have to manage and sustain that service and and really continue Thio provide innovation and value to customers. Right? That's one of the challenges we see is is organizations are now on a treadmill in terms of innovation where customers expect something from South model and you really have to deliver on that. And then one of the final points I would say is it really transforms how you think about going to market right sales and marketing your fundamentally transformed. And, um, you know, traditional ways of really selling software and technology. Um, largely go away and go away and some good ways. And SAS, where you can really put customers in experience right and have them evaluate your technology in a manner where they can have a trial experience, right in a way, toe really introduce them to technology very slowly. And then, um, they grow over time, right? As they see value in that software, which is very aligned, how we think about, you know, a AWS our own technology. >>Okay, Todd, I gotta ask you out. So you want to drive that car? The SAS car, What's under the hood with the right tires? What's the conditions? And it's a technical issues here. If I'm a customer, I'm in a PM, partner. Okay, I'm in there. I got a traditional business pandemic hits or just my business models forcing me. What's your advice? What have I got to do? What's the playbook on the technical side? How doe I go to the next level? >>Well, uh, you know, we're obviously gonna ask a lot of questions and probably the answer to that, sadly, like most technical people will say to you is it depends which is never the answer anybody wants to hear. But so we're definitely gonna ask a lot of questions you about, like where you're at. What are the immediate sort of pressures in your business? This is where the technical team people on our team tended wearing a little bit of a business hat here where we want to know before we sort of guide you down any one particular technical path, like water. Sort of the key sort of dimensions of getting you to a SAS till every model, but but probably as a theme generally were saying to people is, Let's look at how we can get you there incrementally. Let's get you into a SAS model as fast as we possibly can. So we have a lot of different sort of patterns and strategies will use that air about sort of incremental adoption of SAS, which are how can I sort of lift my existing environment, move it into a SAS model, present a SAS offering to the business, Let me operate and run, get the metrics and analytics, get the sort of operational efficiency and the Dev ops goodness of sass, and then sort of move after that into the insides of that sass application. And think about now, how can I begin to move that two more modern constructs? How can I move that into containers? Potentially? Or how can I begin to adopt server list technologies? How can I apply? I am another constructs to achieve Tenet isolation. Eso We're really just trying to put them in a position where they can sort of incrementally modernize their applications while still realizing the benefits of getting to market on a saas model. >>So you're saying that the the playbook is come in low hanging fruit is used existing core building blocks, you see two s three dynamo whatever and then hit the higher level services as you get more experience Or is there a certain recipe that you see working for customers? >>So it's it's probably less about that. It's probably It's not about necessarily where you're out in the service continuum and which services you're using. Um, well, we're gonna move you to a set of services that are probably a good set of services that are that way to move your monolith in most effectively into a saas model as a beginning point that could land you in to that could land you in containers. The more important thing we're going to do here is we're going to surround the that sort of experience with all the other moving parts that you have tow have billing metrics. We're gonna We're gonna build in on boarding so that you could get frictionless on boarding. Those are all gonna be net new things you have to build. We're probably gonna change your identity model and connect that up with cognito or one of our partners solutions eso for us. It's it's sort of grabbing your existing environment. Can we move it over effectively, maybe modernize it a little bit along the way, but more importantly, build all those horizontal concepts in leveraging the right AWS services for you, uh, to bring that to life. >>That's actually smart, aleck. The way you described it that way, it's almost as if it's the core tenant of what Amazon stood for. You standing up fast and you get value, right? So what you're saying is, whatever it takes is a variety of tools to stand it up. I mean, this is interesting, Craig, and talk if you can comment on this because one of the things that we've been reporting on, I've done probably a dozen interviews specifically around companies that have moved to the cloud early, proactively kind of in this way, not in a major radical way. But, you know, operationally they have been transforming, you know, piece by piece. How Todd you laid it out and then pandemic it. And they've had successfully position themselves to take advantage of the forcing function of necessity of dealing with, you know, remote work and all these things that just clobbered him so and again. They were on the wave at the right time. Kind of because they had to because they did the right work. This >>is a >>factor. This is gonna tell sign. Can you guys share your reaction? What you've seen with satisfactory because this >>is the >>benefit of moving to the club. Being positioned needs pandemic today. Tomorrow, its edge. What's after that? Right space. I mean, there's a lot of things. This is kind of the playbook. What's your reaction to that? Correct. >>Yeah. I certainly see, you know, organizations that we work with that have really delivering the SAS model, being more agile, right. The ability to sort of flex resource is and change the way they sell and work with customers and find ways to, um, sort of delivered to them. Um, that don't require, um, some of the things that we're really maybe some of the things that are holding them back from traditional software in terms of how fast they deliver new features and services and, you know, changing to sort of market and world dynamics very quickly. Right is a big part of that. And, you know, one of the things we talked about in the SAS model is really not just getting to sass, but being to deliver in that model, right? And dr Innovations to customers very quickly. Um, s O that you really getting sort of securing, you know, sort of them is the loyal customers and sort of a lifetime customer. Hopefully, um, you know, that's a big part of status. >>Yeah. And there's two types of organizations that you guys have been successful with. The startup, obviously, you know, category creators or disruptors will come in, you know, come in with a nap. Born in the cloud, kick some ass you've seen that movie happens all the time still going on. And then you got the existing organizations that have to stay in that innovation wave and not get crushed by the by the change can you guys share how the factories working? The satisfactory from a mix of of clients is Atmore establishes its startups in between. Give us a taste of What's the makeup? >>Yeah, it's range just to give you a range of some of the companies worked with from kind of legacy technology companies or companies that have been around in some time, like BMC, you know, f five alfresco we've all worked with over the past few years, and they've launched products with our team on a W s. You know, to kind of start ups like Matile. Ian. You know, Cloud zero. Cokie City, which just launched a data management service announced here at Reinvent um, two very kind of specific industry players. I think this is a trend we've seen most recently where, you know, we work with organizations like NASDAQ. I based tea in the aerospace, you know, area Emerson in oil and gas. We've seen in a number of oil and gas companies really come to us based on sort of dynamics, their industry and the constraints the customers are in in terms of how they could deliver the value they provide, >>is there. Is there a key thing that's popping out of all these deals that kind of has a is a tale sign of pattern or, um, a specific thing That's obvious on then, when you look at the data, when you zoom out, >>Yeah, I think one thing I would just say people underestimate the transformation. They have to go through continually. And we still have organizations that come to us, and maybe they come to Todd or others, and they're really they're envisioning This is a technical transformation, right? And they sort of want to talk all about the application and and sort of the new architecture er they they want to move to. But we really see theon pertinent A line business and technology around sass is a model, and that's really fundamental to getting it right. And so, you know, often we see organizations that really have unrealistic launch dates, you know, which is pretty common in software and services these days, but particularly a staff model. We just see that, you know, they underestimate the work in front of them and kind of what they need to bring with that >>Todd real quick for it against the announcements which are cool. Um, technical things that pop out of these organizations is there, Uh, the cream kind of rises to the top. When you look at the value proposition, what do they focused on? Technically, >>um, you know, it's interesting because to me, ah, lot of the focus tends to be more on the things that would surprise you. Like a lot of people are wanna sort of think about how to design the ins Thea click ation on the business logic of their application and take advantage of this scale on the sizing of AWS and those things, they're still all true. But but really an assassin organization with a really successful SAS organizations will see ah, lot more shift to the agility and the operational efficiency, right? So really good organizations will say we're going to invest in all the metrics and all the land analytics, all the tooling that lets us really have our finger on the pulse of what our customers are doing. And then they'll derive all their tech and their business strategy based on this really data driven experience. And I see that as the trend and the thing we certainly advocate a ton inside of the satisfactory is don't under invest in that data because that data is really especially in a multi 10 environment where everybody's running in this sort of shared environment. That data is essential to understanding how to morph your business, how to innovate, understand how your cost profile is really evolving. And so I see the really strong organizations building lots of the sort of foundational bits here, even ahead sometimes of building features and functions into their own products. >>It's not only moving fast and deploying tech is moving fast on the business model innovation as well. You're basically saying, Don't overplay your hand and try toe lock in the business model logic because it's gonna change with the data that what you're saying. >>Yeah, they're playing for for the innovation. They're playing for the agility they're playing for new markets, new segments that may evolve. And so they're really trying to put themselves in the position of being able to pivot and move. And they're really taking pride in the fact that their technology lets them do that. >>You know, that's not that's a business model That's not for the faint of heart. You know, when you have a market that has a lot of competitiveness to it and certainly was seeing the sea change happening over this year in the past few years, with cloud completely changing the playing field, winners and losers air emerging. And that's I think, this key it's you know, as I said in The Godfather, you know, you need a wartime conciliatory for these kind of times, and this is kind of what we're seeing, and I think that's a great point. Todd. Good stuff there. Um Okay. So announcements. You guys had some things on stage. Talked about Craig. You guys launching some new stuff? New programs? >>Yeah, absolutely mhm. Yeah, John, I guess our model is really to learn from a range of partners and experiences we have and then, you know, build tools and approaches to help everyone go faster, right? Because we certainly can't work with thousands organizations. And one of things that our team has had the opportunity over the last few years is published ton of articles, Blog's white papers, you know, very specific approaches to building SAS solutions. If you search Todd Golding out there on YouTube or anything, you'll find a bunch of things. But we wanted to bring on the altogether. And so we've created Central directory called Satisfactory Insights. Hug. And there's a right now over 70 unique pieces of content that our team is produced and curated. Whether you're starting on your staff journey right, you need socks one on one and business planning to level 400 right? 10 10 in isolation from Todd Golding, right. That's all there and available to you on the satisfactory program page. >>What? Some of the interesting things that came out of that that data from the insights you can share. >>Yeah, a couple things that we have we published most recently I would point to are really interesting. We just recently published a five case study where we go deeper in terms of their transformation. To really understand what was, you know, behind the scenes and that, um, we also published a white paper called the SAS Journey Framework, where for the first time, our team really broke down the journey. And what are the steps required? And what are some of the key questions you need to ask Onda Final piece I'd point to for people that Todd talks to is, we have, ah, white paper on SAS tended isolation strategies where we really go deep on on that particular challenge and what's there and that's also published and available on our satisfactory inside sub. Could you >>just define what is that mean tenant isolation strategies? What does that >>go to Todd with that for sure? >>Let's get that on the record. What is the definition of SAS tenant isolation? >>Sure, sure. So, you know, I think I've been in the room and with a lot of people that reinvent and basically have been in Chuck talks and said, You know what's tended isolation to you, and a lot of people will say Oh, that's authentication. Essentially, somebody got into the system. So now I know my system is isolated, but and a multi tenant environment right where we're running all this. These resource is in this data all co mingled from all of these different tenants. Um, it would be a huge blow to the business if one tenant somehow inadvertently exposed the resource or exposed to the resource is of another tenant. And so, fundamentally 10 of isolation is all of these techniques and strategies and architectural patterns that you use to ensure that one tenant can inadvertently get access to the resource is of another tenant s. So it's a sort of a layer of protection and security that goes beyond just the authentication and authorization schemes that you'll typically see in a cess architectures. >>So that's basically like having your own room lock and key doorway not just getting in, but no one can access your your stuff. >>Yeah, so it's a whole set of measures you could imagine. Identity and access management and other policies sort of defining tenant boundaries and saying, as each tenant is trying to access a resource or trying toe, interact with the system in some way, you've put these extra walls up to ensure that you can't cross those boundaries. >>Todd, I want to get your thoughts on this. Well, architected sas lens piece. What is this all about? >>Well, um, a WS has had for a long time the sort of the well architected framework, which has been a really great set of sort of guiding principles and best practices around how to design an architect solutions on top of AWS. And certainly SAS providers have been using that all along the way to sort of ask foundational questions of their architecture. Er But there's always been this layer of additional sort of SAS considerations that have set on top of that are that air SAS specific architectural patterns. And so what we've done is we've used this mechanism called the well architected lens that lets us essentially take our SAS architectural principles and extend the well architected framework and introduce all these concepts into the SAS and to the architecture pillars that really ask the hard SAS architecture questions so security operations reliability all the sort of classic pillars that are part of the well architected framework now have a SAS specific context added to them. Thio to really go after those areas that are unique to sass providers. And this really gives developers, architects, consultants the ability to sit down and look at a SAS application and evaluate its alignment with these best practices. And so far we can really positive response. Thio the content. >>Great job, guys doing great work. Finally, there's something new that you guys are announcing today to make life easier. Preview building SAS on a bus. What's that? What's that about? >>Sure. Eso You know you can imagine. We've been working with thes SAS providers for a number of years now, and as we've worked with them, we've seen a number of different themes emerge on and and we've run into this pattern That's pretty common where we'll see these, uh, these customers that have a classic sort of installed software model. They're installing it on premises or in the cloud, but basically each customer's sort of has their own version of the product. They have one off versions. They have their potentially have customization that are different. And while this works for some time for these businesses, what they find is they sort of run into this operational efficiency and cost wall. Whereas they're trying to grow their businesses, they they just really can't. They can't sort of keep up based on the way that they're running their current systems, and this is sort of a natural draw to move them to sass. But the other pattern that we've seen here is that these organizations are sometimes not in a position where they have the luxury of sort of going away and just saying, Hey, I'll rewrite my system or modernize it and make all of these changes. There could be any number of factors competitive pressures, market realities, cost that just make that too much of, ah, difficult process for them to be able to just take the application and rewrite it. And so what we did is sort of try to acknowledge that and say, What could we do to give you, ah, more prescriptive solution of this, the sort of turn key, easy button, if you will to say, Take my existing monolithic application that I deliver in this classic way and plug it into an existing pre built framework. An environment that is essentially includes all these foundational bits of assassin Vyron mint. And let me just take my monolith, move it into that environment and begin toe offer a SAS product to to the universe. And so what we've done is we've printed something and were introduced. We've introduced this thing called a W s SAS boost So a W s ass boost. It's not on a W s service. It is an open source reference environment. So you essentially download it. You install it into your own A W s account. And then this installs all these building blocks of sass that we've talked about. And it gives you all this sort of prescriptive ability to say, How can I now take my existing monolithic environment lifted into this experience and begin toe offer that to the market as a sash products. So it has, you know, it has billing. It has metrics and analytics. All the things we've been kind of talked about here they're all baked into that from the ground up on. We've also offered this an open source model. So our hope here is that this is really just the starting point of this solution, which, which will solve one business case. But our hope is that essentially the open source community will lean in with us, help us figure out how to evolve and make this into something that addresses a broader set of needs. >>Well, I love the SAS boost. Firstly, I wanna take the energy drink business there. Right there. It sounds like an energy drink. Give me some of that sass boost by that at 7. 11. Craig, I wanna get the final word with you. You've been the SAS business for over 20 years. You've seen this movie before. There are a lot of people who know the SAS business, and some people are learning it. You guys are helping people get there. It's different, though. Now what's different today? Because it's it's It's not just your grandfather's sass. As the expression goes, it's different. It's new dynamics. What is, uh, the most important thing people should pay attention to Whether they have a SAS legacy kind of mindset or they're new to the game. Take us >>home. Yeah, I >>think certainly, you know, getting disaster is not the end of the journey. You know, we see really successful fast provider. Just continue to differentiate, right? And then one of the things that I think we've seen successful SAT providers do is really take advantage of AWS services to go faster. Right? And that's really key, I think in this model is to really find a way to accelerate your business and deliver value faster. Andi just sort of keep that differentiation innovation there. Um, but I would just say now that there's more information out there available than ever, you know, and not only from from our team, but from a host of people that really are our SAS experts and follow the space. And so lots of resources available. Everyone >>All right, gentlemen, Thanks for coming on. Great insight. Great segment on getting to sass, sass boost Just the landscape. You guys are helping customers get there, and that's really the top priority. It's necessity is the mother of all invention during this pandemic. More than ever, uh, keeping business model going and establishing new ones. So thanks for coming on. >>Thanks for having us, John. >>Okay, It's the cubes. Virtual coverage. We are a SAS business. Now we're virtual bringing you remote. Uh, SAS Cube and, uh, more coverage with reinvent next few weeks. Thanks for watching. Okay, yeah.

(upbeat music) >> Narrator: From around the globe, it's theCUBE with digital coverage of AWS reInvent Executive Summit 2020, sponsored by Accenture and AWS. >> Welcome everyone to theCUBE's 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. >> Welcome. >> 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 me. >> 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 West Midlands Police is the second largest police force in the UK, outside of the Metropolitan Police in London. We have an excessive 11,000 people work at West Midlands Police serving communities through and across the Midlands region. So geographically we're quite a big area as well as being population density having that at a high level. So the reason we sort of embarked on the data-driven insights platform and which was a huge change for us was for a number of reasons. Namely we had a lot of disparate data which was spread across a range of legacy systems that were many, many years old with some duplication of what was being captured and no single view for offices or support staff. Some of the access was limited. You have to be in an actual police building on a desktop computer to access it. Other information could only reach offices on the front line through a telephone call back to one of our enabling services where they would do a manual checkup look at the information, then call the offices back and tell them what they needed to know. So it was a very long laborious process not very efficient. And we certainly weren't exploiting the data that we had in a very productive way. >> So it sounds like as you're describing an old clunky system that needed a technological reimagination, so what was the main motivation for making this shift? >> It was really about making us more efficient and more effective in how we do business. So certainly as an IT leader and some of my operational colleagues, we recognize the benefits that data analytics could bring in a policing environment, not something that was really done in the UK at the time. We have a lot of data, so we're very data rich in the information that we have, but we needed to turn it into information that was actionable. So that's where we started looking for technology partners and suppliers to help us and sort of help us really with what's the art of the possible, 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 as with all things, when we're procuring apartment in the public sector, there are many rules and regulations quite rightly because you would expect that to be because we're spending public money so we have to be very, very careful and it's a long process and we have to be open to public scrutiny. So we sort of look to everything, everything that was available as part of that process, but we recognize the benefits that Cloud would provide in this space because we like moving to a Cloud environment. We would literally be replacing something that was legacy with something that was a bit more modern. That's not what we wanted to do. Our ambition was far greater than that. So I think in terms of AWS, really, it was around the scalability, interoperability, just things like the disaster recovery service, the fact that we can scale up and down quickly, we call it dialing up and dialing back. 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 it came out on top for us. So 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 West Midlands Police, sorry, and helping them implement this Cloud-first journey? >> I guess by January the West Midlands Police started paver five years ago now. So we set up a partnership with the force I wanted to operate in a way that was very different to a traditional supplier relationship. Security that the data difference insights program is one of many that we've been working with West Midlands over the last five years. As having said already Cloud gave a number of advantages certainly from big data perspective and the things that that enabled us today from an Accenture to that allowed us to bring in a number of the different teams that we have say Cloud teams, security teams, interacted from a design 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 do you help an entity like West Midlands Police think differently when 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, what is critical is trying to co-create solutions together. Yeah, there's no point just turning up with what we think is the right answer, trying to collectively work through the issues that the force are saying 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 rather than just trying to pick something off the shelf that maybe doesn't fit the full set of requirements in the way that it should do. >> Right, it's not always a one size fits all. >> Absolutely not. What we believe is critical is making sure that we're creating something that met the forces needs in terms of the outcomes they're looking to achieve the financial envelopes that were available and how we can deliver those in a iterative agile way rather than spending years and years working towards an outcome that is going outdate before you even get that. >> So Helen, how are things different? What kinds of business functions and processes have been re-imagined in light of this change and this shift? >> It's actually unrecognizable now in certain areas of the business as it was before. So to give you a little bit of context, when we started working with Accenture and AWS on need data driven insights program, it was very much around providing what was called locally, a wizzy tool for our intelligence analyst to interrogate data, look at data, 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 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. Really it was in line with the mobility strategy that we had where officers were getting new smartphones for the first time to do sort of a lot of things on 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 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 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 an address or check details of an individual 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 while 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 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. So again, it was having the single source of truth 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 get an it back within minutes as opposed to 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 we all should be doing. >> 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 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. But all 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 at police stations as a result and more time out on the 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. >> 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? In 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 West Midlands Police is the buy-in from the top and the chief and his exact team and Helen is the leader from an IT perspective. The entire force is bought in so what is a significant change break ground. And that trickles through everyone in the organization change is difficult and there's a lot of time effort. There's been person to bake the technical delivery and the business change and adoption aspects around each of the projects. But you can see the step change that is making in each aspect to the organization and where that's putting West Midlands Police as a leader in by technology on 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 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. 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 both internally for some of our back office functions, as well as frontline officers. So with DDI in particular, I think that the step change occurred when people could see what it could do for them. We had lots of workshops and seminars where we all talk about big data and it's going to be great and it's data analytics and it's transformational, and quite rightly people that are very busy doing a day job that not necessarily technologists in the main and I'm particularly interested quite rightly so in what we are not dealing with the Cloud, and it was like, yeah, okay it's one more thing. And then when they started to see 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 the stack change, and if we have any issues now it's literally our help desks in meltdown 'cause everyone's like, we can't manage without this anymore. And I think that speaks for itself. So it doesn't happen overnight. It 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? >> We've used a lot of the traditional techniques, things around comms and engagement. We've also used things like 30-day challenge and nudge theory around how can we gradually encourage people to use things. I think there's a point with 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 technology is incredibly complex. The solution itself is extremely large and it's been very difficult to get to live it, 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. I think that's been critical through the whole piece of DDI. >> 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 savings equivalent to 154 full-time officers. What's next? >> I think really it's around exploiting what we've got. And 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 we've been through significant change in the last five years and we are still continuing to batch all of those changes into day operational policing. But what we need to see now 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 all functions. So that we keep getting better and better at this. 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. We're always being expected to, again, look after the public purse and do more for flavs. And I think this is certainly an applied journey and cloud-first by design, which is where we are now 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 Helen and Matthew for joining us. I really appreciate it. >> Thank you. >> And you are watching theCUBE stay tuned for more of theCUBE's coverage of the AWS reInvent Accenture Executive Summit. I'm Rebecca Knight. (upbeat music)

>>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.

>>from around the globe. It's >>the Cube with digital coverage of Dev >>Ops Virtual Forum Brought to You by Broadcom. Welcome to Broadcom, Step Ups, Virtual Forum I and Lisa Martin and I'm joined by another Martin very socially. Distance from me all the way. Coming from Birmingham, England, is Glynn Martin, head of Q. A transformation at BT Glenn. It's great to have you on the program. >>Thank you, Lisa. I'm looking forward, Toa. >>As we said before, we went live to Martin's for the price of one in one segment. So this is gonna be an interesting segment, Guesses. What we're gonna do is Glen's gonna give us a really kind of deep inside out view of Dev ops. From an evolution perspective, Soglo's Let's start transformation is at the heart of what you dio. It's obviously been a very transformative year. How have the events of this year affected the transformation that you are so responsible for driving? >>Yeah. Thank you, Leigh. So I mean, yeah, it has been a difficult year Bond, although working for BT, which is ah, global telecommunications company. Relatively resilient, I suppose, as an industry through covert, it obviously still has been affected and has got its challenges on bond. If anything is actually caused us to accelerate of our transformation journey, you know, we had to do some great things during this time around. You know, in the UK for our emergency and health workers give them unlimited data and for vulnerable people to support them and that spent that we've had to deliver changes quickly. Um, but what? We want to be able to do it, deliver those kind of changes quickly, but sustainably for everything that we do, not just because there's an emergency eso we were already on the kind of journey to by John, but ever so ever more important now that we are what we're able to do, those that kind of work, do it more quickly on. But it works because the implications of it not working is could be terrible in terms of, you know, we've been supporting testing centers, new hospitals to treat covert patients, so we need to get it right and therefore the coverage of what we do, the quality of what we do and how quickly we do. It really has taken on a new scowling what was already a very competitive market within the telco industry within the UK. Um, you know, what I would say is that you know, we are under pressure to deliver more value, but we have small cost challenges. We have to obviously deal with the fact that you know, Cove in 19 has hit most industries kind of revenues and profits. So we've got this kind of paradox between having less cost, but they're having to deliver more value quicker on bond, you know, to higher quality. So, yeah, certainly the finances is on our minds. And that's why we need flexible models, cost models that allow us to kind of do growth. But we get that growth by showing that we're delivering value, especially in, you know, these times when there are financial challenges on companies. >>So one of the things that I want to ask you about again looking at, develops from the inside out on the evolution that you've seen you talked about the speed of things really accelerating in this last nine months or so. When we think Dev ops, we think speed. But one of the things I love to get your perspective on we've talked about in a number of the segments that we've done for this event is cultural change. What are some of the things that scene there as as needing to get, as you said, get things right but done so quickly to support essential businesses, essential workers? How have you seen that cultural shift? >>Yeah, I think you know, before, you know, test test team saw themselves of this part of the software delivery cycle. Andi, actually, now, really, our customers were expecting their quality and to deliver for our customers what they want. Quality has to be ingrained throughout the life cycle. Obviously that you know, there's lots of buzzwords like shift left. How do you do? Shift left testing. But for me, that's really instilling quality and given capabilities shared capabilities throughout the life cycle. That Dr you know, Dr Automation drive improvements. I always say that you know, you're only as good as your lowest common denominator on one thing that we're finding on our Dev Ops Journey Waas that we were you know, we would be trying thio do certain things quicker and had automated build automated tests. But if we were taking weeks to create test scripts or we were taking weeks to manly craft data, and even then when we had taken so long to do it that the coverage was quite poor and that led to lots of defects later in the lifecycle or even in in our production environment, we just couldn't afford to do that. And actually, you know, focusing on continuous testing over the last 9 to 12 months has really given us the ability Thio delivered quickly across the the whole life cycle and therefore actually go from doing a kind of semi agile kind of thing where we did you use the stories we did a few of the kind of, you know, as our ceremonies. But we weren't really deploying any quicker into production because, you know, our stakeholders were scared that we didn't have the same control that we had when we had more water for releases. And, you know, when way didn't think ourselves. So we've done a lot of work on every aspect, especially from a testing point of view, every aspect of every activity, rather than just looking at automated test, you know, whether it is actually creating the test in the first place, Whether it's doing security testing earlier in the light and performance testing. Learn the life cycle, etcetera. So, yeah, it Z It's been a riel key thing that for for C T for us to drive, develops, >>talk to me a little bit about your team. What are some of the shifts in terms of expectations that you're experiencing and how your team interacts with the internal folks from pipeline through life cycle? >>Yeah, we've done a lot of work on this, you know, there's a thing. I think people were pretty quiet. Customer experience. Gap. It reminds me of a cart, a Gilbert cartoon where, you know, we start with the requirements here on Do you know, we almost like a Chinese whisper effects and what we deliver eyes completely, completely different. So we think the testing team or the the delivery team, you know, you know, you think they've done a great job. This is what it said in the acceptance criteria, but then our customers the same Well, actually, that's not working. This isn't working, you know, on there's this kind of gap Way had a great launched this year of actual Requirement Society, one of the board common tools Onda that for the first time in in since I remember actually working within B. T, I had customers saying to may, Wow, you know, we want more of this. We want more projects, um, to have a actual requirements design on it because it allowed us to actually work with the business collaboratively. I mean, we talk about collaboration, but how do you actually, you know, do that have something that both the business on technical people can understand? And we've actually been working with the business using at our requirement. Designer Thio, you know, really look about what the requirements are. Tease out requirements to the hadn't even thought off and making sure that we've got high levels of test coverage. And so what we actually deliver at the end of it, not only have you been able Thio generate test more quickly, but we've got much higher test coverage and also can more smartly, you're using the kind of AI within the tour and with some of the other kind of pipeline tools actually deliver to choose the right tests on the bar, still actually doing a risk based testing approach. So that's been a great launched this year, but just the start of many kind of things that we're >>doing. But what I hear in that Glenn is a lot of positives that have come out of a very challenging situation. Uh, talk to me about it and I like that perspective. This is a very challenging time for everybody in the world, but it sounds like from a collaboration, perspective is you're right. We talk about that a lot critical with Dev Ops. But those challenges there you guys were able to overcome those pretty quickly. What other challenges did you face and figure out quickly enough to be able to pit it so fast? >>I mean, you talked about culture. I mean, you know, Bt is like most come countries companies. So, um, is very siloed. You know, we're still trying to work to become closer as a company. So I think there's a lot of challenges around. How do you integrate with other tools? How do you integrate with you know, the various different technologies and bt we have 58 different whitey stacks? That's not systems that stacks all of those stacks of can have, you know, hundreds of systems on we're trying to. We're gonna drive at the moment a simplified program where we're trying Thio, you know, reduce that number 2 14 stacks. And even then they'll be complexity behind the scenes that that we will be challenged. Maurin Mawr As we go forward, how do you actually hired that to our users on as an I T organization? How do we make ourselves Lena so that even when we you know, we've still got some of that legacy and we'll never fully get rid of it on that's the kind of trade off that we have to make. How do we actually deal with that and and hide that for my users a say and and and drive those programs so we can actually accelerate change. So we take, you know, reduce that kind of waste, and that kind of legacy costs out of our business. You know, the other thing is, well, beating. And I'm sure you know telecoms probably no difference to insurance or finance we've got You know, when you take the number of products that we do and then you combine them, the permutations are tens and hundreds of thousands of products. So we as a business to trying to simplify. We are trying Thio do that in a natural way and haven't trying to do agile in the proper way, you know, and really actually work it paste really deliver value. So I think what we're looking Maura, Maura, at the moment is actually, um is more value focus? Before we used to deliver changes, sometimes into production, someone had a great idea or it was a great idea nine months ago or 12 months ago. But actually, then we end up deploying it. And then we look at the the the users, you know, the usage of that product of that application or whatever it is on. It's not being used for six months, so we're getting much we haven't got, you know, because of the last 12 months, we certainly haven't got room for that kind of waste and you know, the for not really understanding the value of changes that we we are doing. So I think that's the most important thing at the moment is really taken that waste out. You know, there's lots of focus on things like flow management. What bits of the our process are actually taking too long, and we've We've started on that journey, but we've got a hell of a long way to go, you know, But that that involves looking every aspect off the kind of software delivery cycle. >>What are some? Because that that going from, what, 58 i t stocks down to 14 or whatever it's going to be go simplifying is sounds magical. Took everybody. It's a big challenge. What are some of the core technology capabilities that you see really as kind of essential for enabling that with this new way that you're working? >>Yeah. I mean, I think we've started on a continuous testing journey, and I think that's just the start. I mean, that's really, as I say, looking at every aspect off, you know, from a Q, a point of view. It's every aspect of what we dio. But it's also looking at, you know, we're starting to branch into more like a AI ops and, you know, really, the full life cycle on. But, you know, that's just a stepping stone onto, you know, I think oughta Nomics is the way forward, right? You know all of this kind of stuff that happens um, you know, monitoring, you know, monitoring systems, what's happening in production had to be feed that back. How do you get to a point where actually we think about a change on then suddenly it's in production safely. Or if it's not going to safety, it's automatically backing out. So, you know, it's a very, very long journey. But if we want Thio, you know, in a world where the pace is ever increasing the demands of the team and you know, with the pressures on at the moment where with we're being asked to do things, you know more efficiently Ondas leaving as possible. We need to be, you know, thinking about every part of the process. And how do we put the kind of stepping stones in players to lead us to a more automated kind of, you know, their future? >>Do you feel that that plant outcomes are starting to align with what's delivered? Given this massive shift that you're experiencing, >>I think it's starting to, and I think you know, Azzawi. Look at more of a value based approach on. Do you know a Zeiss? A princess was a kind of flight management. I think that's that will become ever evermore important. So I think it's starting to people. Certainly realized that, you know, people teams need to work together. You know, the kind of the cousin between business and ICT, especially as we go Teoh Mawr kind of sad space solutions, low cold solutions. You know there's not such a gap anymore. Actually, some of our business partners expects to be much more tech savvy. Eso I think you know, this is what we have to kind of appreciate. What is I ts role? How do we give the capabilities become more for centers of excellence rather than actually doing Mount amount of work And for May and from a testing point of view, you know, amount, amount of testing, actually, how do we automate that? How do we actually generate that instead of created? I think that's the kind of challenge going forward. >>What are some? As we look forward, what are some of the things that you would like to see implemented or deployed in the next say, 6 to 12 months as we hopefully round a corner with this pandemic? >>Yeah, I think you know, certainly for for where we are as a company from a Q A perspective. We are. Yeah, there's certain bits that we do Well, you know, we've started creating continuous delivery. A day evokes pipelines. Um, there's still manual aspects of that. So, you know, certainly for May I I've challenged my team with saying, How do we do an automated journey? So if I, you know, I put a requirement injera or value whoever it is, that's why. Then click a button on bond, you know, with either zero touch of one touch, then put that into production and have confidence that that has been done safely on that it works. And what happens if it doesn't work? So you know, that's that's the next in the next few months, that's what our concentration is about. But it's also about decision making, you know, how do we actually understand those value judgements? And I think there's lots of the things Dev ops, ai ops, kind of always that aspects of business operations. I think it's about having the information in one place to make those kind of decisions. How does it all tied together, as I say, even still with kind of Dev ops, we've still got elements within my company where we've got lots of different organizations doing some doing similar kind of things but the walking of working in silos Still. So I think, having a eye ops Aziz becomes more and more to the fore as we go to the cloud. And that's what we need to. You know, we're still very early on in our cloud journey, you know. So we need to make sure the technologies work with Cloud as well as you kind of legacy systems. But it's about bringing that all together and having a full visible pipeline. Everybody can see and make decisions against >>you said the word confidence, which jumped out at me right away. Because absolutely, you've gotta have be able to have confidence in what your team is delivering and how it's impacting the business and those customers. Last question for you is how would you advise your peers in a similar situation to leverage technology automation, for example, dev ops to be able to gain the confidence that they're making the right decisions for their business? >>Yeah, I mean, I think the the approach that we've taken actually is not started with technology we've actually taken human centered design a za core principle of what we dio within the i t part of BT. So by using humans tend to design. That means we talked to our customers. We understand their pain points, we map out their current processes on. But when we mapped out, those processes also understand their aspirations as well, you know, Where do they want to be in six months? You know, Do they want to be more agile and you know, or do they want Teoh? Is this apart their business that they want thio run better? We have to Then look at why that's not running well and then see what solutions are out there. We've been lucky that, you know, with our partnership with Broadcom within the P l. A. A lot of the tortures and the P l. A have directly answered some of the businesses problems. But I think by having those conversations and actually engaging with the business, um, you know, especially if the business hold the purse strings, which is you know, in some companies, including as they do there is that kind of, you know, almost by understanding their their pain points and then saying This is how we can solve your problem We've tended to be much more successful than trying Thio impose something and say We're here to technology that they don't quite understand doesn't really understand how it could have resonate with their problems. So I think that's the heart of it is really about, you know, getting looking at the data, looking at the processes, looking at where the kind of waste is on. Then actually then looking at the right solutions. And as I say, continuous testing is a massive for us. We've also got a good relationship with capitals looking at visual ai on. Actually, there's a common theme through that, and I mean, AI is becoming more and more prevalent, and I know yeah, sometimes what is A I and people have kind of the semantics of it. Is it true, ai or not? But yes, certainly, you know, AI and machine learning is becoming more and more prevalent in the way that we work, and it's allowing us to be much more effective, the quicker and what we do on being more accurate. You know, whether it's finding defects, running the right tests or, you know, being able to anticipate problems before they're happening in a production environment. >>Welcome. Thank you so much for giving us this sort of insight. Outlook at Dev Ops, sharing the successes that you're having taking those challenges, converting them toe opportunities and forgiving folks who might be in your shoes or maybe slightly behind advice. I'm sure they appreciate it. We appreciate your time. >>It's been an absolute pleasure, Really. Thank you for inviting me of Extremely enjoyed it. So thank you ever so much. >>Excellent. Me too. I've learned a lot for Glynn Martin and Lisa Martin. You're watching the Cube?

>>Hi, everyone. My name is my uncle. My uncle Poor I worked with Geo reminds you in India. We call ourselves Geo Platforms. Now on. We've been recently in the news. You've raised a lot off funding from one of the largest, most of the largest tech companies in the world. And I'm here to talk about Geos Cloud Journey, Onda Mantis Partnership. I've titled it the story often, Underdog becoming the largest telecom company in India within four years, which is really special. And we're, of course, held by the cloud. So quick disclaimer. Right. The content shared here is only for informational purposes. Um, it's only for this event. And if you want to share it outside, especially on social media platforms, we need permission from Geo Platforms limited. Okay, quick intro about myself. I am a VP of engineering a geo. I lead the Cloud Services and Platforms team with NGO Andi. I mean the geo since the beginning, since it started, and I've seen our cloud footprint grow from a handful of their models to now eight large application data centers across three regions in India. And we'll talk about how we went here. All right, Let's give you an introduction on Geo, right? Giorgio is on how we became the largest telecom campaign, India within four years from 0 to 400 million subscribers. And I think there are There are a lot of events that defined Geo and that will give you an understanding off. How do you things and what you did to overcome massive problems in India. So the slide that I want to talkto is this one and, uh, I The headline I've given is, It's the Geo is the fastest growing tech company in the world, which is not a new understatement. It's eggs, actually, quite literally true, because very few companies in the world have grown from zero to 400 million subscribers within four years paying subscribers. And I consider Geo Geos growth in three phases, which I have shown on top. The first phase we'll talk about is how geo grew in the smartphone market in India, right? And what we did to, um to really disrupt the telecom space in India in that market. Then we'll talk about the feature phone phase in India and how Geo grew there in the future for market in India. and then we'll talk about what we're doing now, which we call the Geo Platforms phase. Right. So Geo is a default four g lt. Network. Right. So there's no to geo three g networks that Joe has, Um it's a state of the art four g lt voiceover lt Network and because it was designed fresh right without any two D and three G um, legacy technologies, there were also a lot of challenges Lawn geo when we were starting up. One of the main challenges waas that all the smart phones being sold in India NGOs launching right in 2000 and 16. They did not have the voice or lt chip set embedded in the smartphone because the chips it's far costlier to embed in smartphones and India is a very price and central market. So none of the manufacturers were embedding the four g will teach upset in the smartphones. But geos are on Lee a volte in network, right for the all the network. So we faced a massive problem where we said, Look there no smartphones that can support geo. So how will we grow Geo? So in order to solve that problem, we launched our own brand of smartphones called the Life um, smartphones. And those phones were really high value devices. So there were $50 and for $50 you get you You At that time, you got a four g B storage space. A nice big display for inch display. Dual cameras, Andi. Most importantly, they had volte chip sets embedded in them. Right? And that got us our initial customers the initial for the launch customers when we launched. But more importantly, what that enabled other oh, EMS. What that forced the audience to do is that they also had to launch similar smartphones competing smartphones with voltage upset embedded in the same price range. Right. So within a few months, 3 to 4 months, um, all the other way EMS, all the other smartphone manufacturers, the Samsung's the Micromax is Micromax in India, they all had volte smartphones out in the market, right? And I think that was one key step We took off, launching our own brand of smartphone life that helped us to overcome this problem that no smartphone had. We'll teach upsets in India and then in order. So when when we were launching there were about 13 telecom companies in India. It was a very crowded space on demand. In order to gain a foothold in that market, we really made a few decisions. Ah, phew. Key product announcement that really disrupted this entire industry. Right? So, um, Geo is a default for GLT network itself. All I p network Internet protocol in everything. All data. It's an all data network and everything from voice to data to Internet traffic. Everything goes over this. I'll goes over Internet protocol, and the cost to carry voice on our smartphone network is very low, right? The bandwidth voice consumes is very low in the entire Lt band. Right? So what we did Waas In order to gain a foothold in the market, we made voice completely free, right? He said you will not pay anything for boys and across India, we will not charge any roaming charges across India. Right? So we made voice free completely and we offer the lowest data rates in the world. We could do that because we had the largest capacity or to carry data in India off all the other telecom operators. And these data rates were unheard off in the world, right? So when we launched, we offered a $2 per month or $3 per month plan with unlimited data, you could consume 10 gigabytes of data all day if you wanted to, and some of our subscriber day. Right? So that's the first phase off the overgrowth and smartphones and that really disorders. We hit 100 million subscribers in 170 days, which was very, very fast. And then after the smartphone faith, we found that India still has 500 million feature phones. And in order to grow in that market, we launched our own phone, the geo phone, and we made it free. Right? So if you take if you took a geo subscription and you carried you stayed with us for three years, we would make this phone tree for your refund. The initial deposit that you paid for this phone and this phone had also had quite a few innovations tailored for the Indian market. It had all of our digital services for free, which I will talk about soon. And for example, you could plug in. You could use a cable right on RCR HDMI cable plug into the geo phone and you could watch TV on your big screen TV from the geophones. You didn't need a separate cable subscription toe watch TV, right? So that really helped us grow. And Geo Phone is now the largest selling feature phone in India on it. 100 million feature phones in India now. So now now we're in what I call the geo platforms phase. We're growing of a geo fiber fiber to the home fiber toe the office, um, space. And we've also launched our new commerce initiatives over e commerce initiatives and were steadily building platforms that other companies can leverage other companies can use in the Jeon o'clock. Right? So this is how a small startup not a small start, but a start of nonetheless least 400 million subscribers within four years the fastest growing tech company in the world. Next, Geo also helped a systemic change in India, and this is massive. A lot of startups are building on this India stack, as people call it, and I consider this India stack has made up off three things, and the acronym I use is jam. Trinity, right. So, um, in India, systemic change happened recently because the Indian government made bank accounts free for all one billion Indians. There were no service charges to store money in bank accounts. This is called the Jonathan. The J. GenDyn Bank accounts. The J out off the jam, then India is one of the few countries in the world toe have a digital biometric identity, which can be used to verify anyone online, which is huge. So you can simply go online and say, I am my ankle poor on duh. I verify that this is indeed me who's doing this transaction. This is the A in the jam and the last M stands for Mobil's, which which were held by Geo Mobile Internet in a plus. It is also it is. It also stands for something called the U. P I. The United Unified Payments Interface. This was launched by the Indian government, where you can carry digital transactions for free. You can transfer money from one person to the to another, essentially for free for no fee, right so I can transfer one group, even Indian rupee to my friend without paying any charges. That is huge, right? So you have a country now, which, with a with a billion people who are bank accounts, money in the bank, who you can verify online, right and who can pay online without any problems through their mobile connections held by G right. So suddenly our market, our Internet market, exploded from a few million users to now 506 106 100 million mobile Internet users. So that that I think, was a massive such a systemic change that happened in India. There are some really large hail, um, numbers for this India stack, right? In one month. There were 1.6 billion nuclear transactions in the last month, which is phenomenal. So next What is the impact of geo in India before you started, we were 155th in the world in terms off mobile in terms of broadband data consumption. Right. But after geo, India went from one 55th to the first in the world in terms of broadband data, largely consumed on mobile devices were a mobile first country, right? We have a habit off skipping technology generation, so we skip fixed line broadband and basically consuming Internet on our mobile phones. On average, Geo subscribers consumed 12 gigabytes of data per month, which is one of the highest rates in the world. So Geo has a huge role to play in making India the number one country in terms off broad banded consumption and geo responsible for quite a few industry first in the telecom space and in fact, in the India space, I would say so before Geo. To get a SIM card, you had to fill a form off the physical paper form. It used to go toe Ah, local distributor. And that local distributor is to check the farm that you feel incorrectly for your SIM card and then that used to go to the head office and everything took about 48 hours or so, um, to get your SIM card. And sometimes there were problems there also with a hard biometric authentication. We enable something, uh, India enable something called E K Y C Elektronik. Know your customer? We took a fingerprint scan at our point of Sale Reliance Digital stores, and within 15 minutes we could verify within a few minutes. Within a few seconds we could verify that person is indeed my hunk, right, buying the same car, Elektronik Lee on we activated the SIM card in 15 minutes. That was a massive deal for our growth. Initially right toe onboard 100 million customers. Within our and 70 days. We couldn't have done it without be K. I see that was a massive deal for us and that is huge for any company starting a business or start up in India. We also made voice free, no roaming charges and the lowest data rates in the world. Plus, we gave a full suite of cloud services for free toe all geo customers. For example, we give goTV essentially for free. We give GOTV it'll law for free, which people, when we have a launching, told us that no one would see no one would use because the Indians like watching TV in the living rooms, um, with the family on a big screen television. But when we actually launched, they found that GOTV is one off our most used app. It's like 70,000,080 million monthly active users, and now we've basically been changing culture in India where culture is on demand. You can watch TV on the goal and you can pause it and you can resume whenever you have some free time. So really changed culture in India, India on we help people liver, digital life online. Right, So that was massive. So >>I'm now I'd like to talk about our cloud >>journey on board Animal Minorities Partnership. We've been partners that since 2014 since the beginning. So Geo has been using open stack since 2014 when we started with 14 note luster. I'll be one production environment One right? And that was I call it the first wave off our cloud where we're just understanding open stack, understanding the capabilities, understanding what it could do. Now we're in our second wave. Where were about 4000 bare metal servers in our open stack cloud multiple regions, Um, on that around 100,000 CPU cores, right. So it's a which is one of the bigger clouds in the world, I would say on almost all teams, with Ngor leveraging the cloud and soon I think we're going to hit about 10,000 Bama tools in our cloud, which is massive and just to give you a scale off our network, our in French, our data center footprint. Our network introduction is about 30 network data centers that carry just network traffic across there are there across India and we're about eight application data centers across three regions. Data Center is like a five story building filled with servers. So we're talking really significant scale in India. And we had to do this because when we were launching, there are the government regulation and try it. They've gotten regulatory authority of India, mandates that any telecom company they have to store customer data inside India and none of the other cloud providers were big enough to host our clothes. Right. So we we made all this intellectual for ourselves, and we're still growing next. I love to show you how we grown with together with Moran says we started in 2014 with the fuel deployment pipelines, right? And then we went on to the NK deployment. Pipelines are cloud started growing. We started understanding the clouds and we picked up M C p, which has really been a game changer for us in automation, right on DNA. Now we are in the latest release, ofem CPM CPI $2019 to on open stack queens, which on we've just upgraded all of our clouds or the last few months. Couple of months, 2 to 3 months. So we've done about nine production clouds and there are about 50 internal, um, teams consuming cloud. We call as our tenants, right. We have open stack clouds and we have communities clusters running on top of open stack. There are several production grade will close that run on this cloud. The Geo phone, for example, runs on our cloud private cloud Geo Cloud, which is a backup service like Google Drive and collaboration service. It runs out of a cloud. Geo adds G o g S t, which is a tax filing system for small and medium enterprises, our retail post service. There are all these production services running on our private clouds. We're also empaneled with the government off India to provide cloud services to the government to any State Department that needs cloud services. So we were empaneled by Maiti right in their ego initiative. And our clouds are also Easter. 20,000 certified 20,000 Colin one certified for software processes on 27,001 and said 27,017 slash 18 certified for security processes. Our clouds are also P our data centers Alsop a 942 be certified. So significant effort and investment have gone toe These data centers next. So this is where I think we've really valued the partnership with Morantes. Morantes has has trained us on using the concepts of get offs and in fries cold, right, an automated deployments and the tool change that come with the M C P Morantes product. Right? So, um, one of the key things that has happened from a couple of years ago to today is that the deployment time to deploy a new 100 north production cloud has decreased for us from about 55 days to do it in 2015 to now, we're down to about five days to deploy a cloud after the bear metals a racked and stacked. And the network is also the physical network is also configured, right? So after that, our automated pipelines can deploy 100 0 clock in five days flight, which is a massive deal for someone for a company that there's adding bear metals to their infrastructure so fast, right? It helps us utilize our investment, our assets really well. By the time it takes to deploy a cloud control plane for us is about 19 hours. It takes us two hours to deploy a compu track and it takes us three hours to deploy a storage rack. Right? And we really leverage the re class model off M C. P. We've configured re class model to suit almost every type of cloud that we have, right, and we've kept it fairly generous. It can be, um, Taylor to deploy any type of cloud, any type of story, nor any type of compute north. Andi. It just helps us automate our deployments by putting every configuration everything that we have in to get into using infra introduction at school, right plus M. C. P also comes with pipelines that help us run automated tests, automated validation pipelines on our cloud. We also have tempest pipelines running every few hours every three hours. If I recall correctly which run integration test on our clouds to make sure the clouds are running properly right, that that is also automated. The re class model and the pipelines helpers automate day to operations and changes as well. There are very few seventh now, compared toa a few years ago. It very rare. It's actually the exception and that may be because off mainly some user letter as opposed to a cloud problem. We also have contributed auto healing, Prometheus and Manager, and we integrate parameters and manager with our even driven automation framework. Currently, we're using Stack Storm, but you could use anyone or any event driven automation framework out there so that it indicates really well. So it helps us step away from constantly monitoring our cloud control control planes and clothes. So this has been very fruitful for us and it has actually apps killed our engineers also to use these best in class practices like get off like in France cord. So just to give you a flavor on what stacks our internal teams are running on these clouds, Um, we have a multi data center open stack cloud, and on >>top of that, >>teams use automation tools like terra form to create the environments. They also create their own Cuba these clusters and you'll see you'll see in the next slide also that we have our own community that the service platform that we built on top of open stack to give developers development teams NGO um, easy to create an easy to destroy Cuban. It is environment and sometimes leverage the Murano application catalog to deploy using heats templates to deploy their own stacks. Geo is largely a micro services driven, Um um company. So all of our applications are micro services, multiple micro services talking to each other, and the leverage develops. Two sets, like danceable Prometheus, Stack stone from for Otto Healing and driven, not commission. Big Data's tax are already there Kafka, Patches, Park Cassandra and other other tools as well. We're also now using service meshes. Almost everything now uses service mesh, sometimes use link. Erred sometimes are experimenting. This is Theo. So So this is where we are and we have multiple clients with NGO, so our products and services are available on Android IOS, our own Geo phone, Windows Macs, Web, Mobile Web based off them. So any client you can use our services and there's no lock in. It's always often with geo, so our sources have to be really good to compete in the open Internet. And last but not least, I think I love toe talk to you about our container journey. So a couple of years ago, almost every team started experimenting with containers and communities and they were demand for as a platform team. They were demanding community that the service from us a manage service. Right? So we built for us, it was much more comfortable, much more easier toe build on top of open stack with cloud FBI s as opposed to doing this on bare metal. So we built a fully managed community that a service which was, ah, self service portal, where you could click a button and get a community cluster deployed in your own tenant on Do the >>things that we did are quite interesting. We also handle some geo specific use cases. So we have because it was a >>manage service. We deployed the city notes in our own management tenant, right? We didn't give access to the customer to the city. Notes. We deployed the master control plane notes in the tenant's tenant and our customers tenant, but we didn't give them access to the Masters. We didn't give them the ssh key the workers that the our customers had full access to. And because people in Genova learning and experimenting, we gave them full admin rights to communities customers as well. So that way that really helped on board communities with NGO. And now we have, like 15 different teams running multiple communities clusters on top, off our open stack clouds. We even handle the fact that there are non profiting. I people separate non profiting I peoples and separate production 49 p pools NGO. So you could create these clusters in whatever environment that non prod environment with more open access or a prod environment with more limited access. So we had to handle these geo specific cases as well in this communities as a service. So on the whole, I think open stack because of the isolation it provides. I think it made a lot of sense for us to do communities our service on top off open stack. We even did it on bare metal, but that not many people use the Cuban, indeed a service environmental, because it is just so much easier to work with. Cloud FBI STO provision much of machines and covering these clusters. That's it from me. I think I've said a mouthful, and now I love for you toe. I'd love to have your questions. If you want to reach out to me. My email is mine dot capulet r l dot com. I'm also you can also message me on Twitter at my uncouple. So thank you. And it was a pleasure talking to you, Andre. Let let me hear your questions.

>> Narrator: From theCUBE's studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a CUBE conversation. >> Hey everybody, this is Dave Vellante and welcome to this episode of "CXO Insights." As you know, we've been grabbing the perspectives of leaders throughout this pandemic and assessing their tips for managing in a crisis and of course, managing in good times as well. But now, as we enter the post-isolation economy, we really want to look at not just how you manage through the crisis but how you manage beyond the crisis. And I'm really excited to have Chris Riley here. He's the newly minted Chief Revenue Officer at Automation Anywhere. Chris, my friend, how you doing? I hope you and the family are well. >> Thank you, David. I wish the same for you. I think getting by as most folks are, it's the new normal, we're all getting used to it but I'm happy to be here and happy to be at Automation Anywhere. >> Yeah, I want to talk about that in detail. Eddie Walsh calls it the new abnormal but so congratulations on the new role. I want to start with your career. I met you in 1987, which ironically was the same year I met Dave Donatelli, the same year I met Michigan I. and Saul Koi, talk about great timing. And then, you came into the industry at a time, really different time. It was, the IBM people don't remember this but IBM was the dominant player and you guys unseated them amazing 12-year career at EMC and then you kind of went to the .com boom. That was amazing. You relive that ride, did a stint at HP and really turned that business around and then came back to Dell, top go to market executive. One of the top in the industry that I know and now, of course at Automation Anywhere we're going to talk about. My first question to you is, a lot of changes have occurred since 1987. What has changed the most? Now we're talking diversity, we're talking all kinds of your different sales models. From your career looking back, what's changed the most? >> I think everything has changed and candidly for the better, Dave. You just led with one of the key areas in an area I'm deeply passionate about and that is diversity and inclusion and I think there's no stronger time, at least in our country's history where the inequalities that exist have been so exposed. So I view this as an opportunity, as I did at Dell to make a difference, lead from the front and make this a destination and a company whose culture really supports and drives diversity and inclusion. So I'd say that's one area, and I know it's very passionate for you as well. The others, it was a time before laptops, desktops. I think Ken Olsen once said, who would ever need a laptop in their home and boy, the world has changed. So I think some of the things though that haven't changed and this is why I'm so excited about Automation Anywhere. At the manual processes we have our workers doing and I think there is a real opportunity. I've lived through explosive growth at EMC, top company performing stock during the 90s, I get to see VMware firsthand. I've seen what's happened with ServiceNow and I believe this RPA space, as to you is in its infancy. It's seeing 30% compounded annual growth and we're just at the beginning and I think it's going to change the way people work and really lead to that digital transformation that so many of us have been talking about for the last decade. >> Yeah and you know kind of my position. Quick aside, I don't know if you saw the Netflix announcement this morning and I've been wondering as a small business, what can we do? What more can we do for inclusion and diversity? Netflix announced they're going to take 2% of their cash and put it into banks, financial institutions that support black causes and I just talked to our CFO. I said, look, why don't we take some of our cash, let's take 2% and stick it into banks, community banks. There's 30 million small businesses in the United States. If just 1% puts 10 grand in each, that's $3 billion that go into black community. So I'm going to start a mission and I just thought I'd share that 'cause I know it's a passion of yours. >> Yeah, and we all need to be in a position to provide equal opportunity for employment and that is reaching out into those communities and starting early on in creating the opportunities for advancement professionally, mentorship and just the path forward. And I'm excited to see what Netflix is doing. I'm sure you'll come up with the right answer for your company and I think all of us are searching, what's the right answer for our respective companies? >> Yeah, so now let's get into it. You're a month in and I want to talk about this project. I've learned a lot about not only RPA but about automation. I've just had a deep dive with your team and it really brought some things into focus. Guys, if you bring up the first slide, I want to get some thoughts on the table here. So this is a chart that sort of came into my focus with a friend of mine, Dave Moschello, who really big thinker on this stuff and he pointed out, this is data from the US Bureau of Labor and Statistics and the EU and it shows the lackluster productivity that's going on in the past decade. So you can see, we had the boost in the 80s and the 90s, we had this sort of productivity uptick from laptops but now, look what's happened since 2007. And the point that Moschello made on the right hand side is we have all these huge issues that we face, whether it's climate change, we have this massive debt, healthcare, an aging population, feeding everyone, et cetera, et cetera, et cetera, and his point was, there's no way we're going to be able to solve all these problems by throwing humans at the problem. So I've really begun to sort of think about this just in terms of machines and the roles that machines will play. I think overnight, Chris, we've gone from, wow, I'm afraid that machines are going to take my job to you can't operate if you're not digital. >> Yeah, well digital transformation is not a new term. I think it's meant something different each year for the last 10 years and I look at this as an opportunity. The World Economic Forum projected that IA and RPA will create 58 million new jobs. It's an astounding number. What COVID-19 has exposed is this work from home phenomenon that really exposes the risk of manual processes within the enterprise. So I think those two things combined is almost a perfect storm and I think what it'll do is accelerate the adoption of RPA and IPA. So something that might've taken years or decades to really be adopted in force, in this new normal, I think is going to be accelerated quite dramatically. >> So, the combination of your go to market execution, you managed complex sales motions before. Automation Anywhere obviously has some great product capabilities. Guys, I want to bring up the next slide and Chris, you might have seen this in some of the stuff that I wrote but this is data from ETR Enterprise technology research. They're a data partner of ours. Now it's clear that Automation Anywhere has the right product market fit and you can see on this chart, this is a methodology that we use. ETR goes out and they ask people, are you adopting a platform new? Are you increasing spending relative to last year? Are you flat, decreasing or replacing? And you can see here, there is zero churn in the Automation Anywhere base. And so obviously you got product market fit. Churn is the silent killer, obviously of SAS companies and so, you've picked a winner and I'm learning more about this. At first I thought the team office is quite large, I sized it. I actually think it's bigger than I originally thought. Chris, I thought this was going to be a winner-take-all type of market. I'm really rethinking that after, especially the deep dive I've had with your team in terms of how you guys go to market with an end-to-end sort of life cycle approach as opposed to sort of putting point products in. So I wonder if that narrative that I just laid out, resonates with you, is it sort of consistent with what you're seeing and then maybe some of the reasons why you joined Automation Anywhere? >> Yeah, I would say the most aggressive software growth that I've seen in the last decade or so, and two companies stand out for me. That's VMware and ServiceNow. They don't have a point product, they have a platform and that's what attracted me to Automation Anywhere is this platform approach. And Dave as you know, I've spent most of my career calling on the enterprise' strong relationships with those types of companies and they aren't looking to develop a point product solution and then cobble together lots of disparate islands of solutions. They're looking for a platform that can grow as they grow. They can extend from the back office to the front office but all centered around workforce, transformation, productivity and just as importantly, resiliency. And as we start to develop more and more capabilities that will be delivered through this platform approach, I think we're going to see explosive growth as the industry goes through its explosive growth. >> Well, I know your approach and your approach is to stay very close to customers. So as you were doing your due diligence on Automation Anywhere and as you enter your sort of first part of your 100-day journey here, I'm sure you've talked to a lot of customers. What are they telling you? What are the big takeaways right now that you're hearing? >> Yeah, so I think some of the data you pointed out with 4,000 customers in essence, zero churn, the opportunity to upsell those customers with more products and solutions clearly is there. New account acquisition has been a tremendous source of growth for the company in a strong professional services organization that actually is able to deliver the outcomes that our customers expect. From an enterprise perspective, I couldn't have come into a better situation with 4,000 customers, 50% of the fortune 500, 2 million bots deployed, those types of strategic relationships are going to be more and more critical as this company continues to accelerate its growth. Most of the RPA solutions really got in through the back office and candidly, really weren't even a component of an IT solution. Now, as you go to the front of the house, where you're looking at customer facing applications and worker productivity, these are CEO, CFO, COO and IT initiatives. So I really believe we're coming into our own, at the front of the house with senior executives that really want to create a better working environment for their employees and de-risk a lot of these manual processes that have existed for years. >> So I know why you chose Automation Anywhere. My question is, why did Automation Anywhere choose Chris Riley? I know your capabilities but obviously when somebody hires a executive like yourself, they say, "Hey, Chris, we want you to help us "get to the next level," but what does that mean? Are we talking about changes in the go to market? Are we talking about your ability to recruit and coach, to manage complex of sales motions? What is it that you want to bring to Automation Anywhere? >> I think it's all those, Dave. Having built a reputation throughout my 30 plus year career around a people-centric focus, a customer-centric focus and those two things kind of aren't interchangeable. When you look at customers, they put their faith and confidence in people and they put their faith and confidence in companies. And what I see here at Automation Anywhere is that the ability to kind of expand upon the great culture that the company already has but do it with someone whose role in a company at scale globally and can put a lot of the best practices and disciplines in place to do that 'cause it is difficult but also, how do we start to do larger, more complex deals and build relationships with the CIO, the CFO, the CEO? And I think a big reason why I'm here is, that experience in doing that, doing large complex multi-year opportunities but also being able to deliver upon the outcomes that we told our customers we could achieve and do that together with our customers and again we have a strong professional services organization and an incredible ecosystem of partners that have demonstrated year over year, the company's ability to actually deliver upon its promise. >> That was my next question to you, was the ecosystem. One of the big changes from when you started in this business, was it used to be just belly to belly, hardcore, direct sales, the importance and leverage that you get from a partner ecosystem. You point out VMware. In fact ServiceNow, it's interesting. When we first started covering ServiceNow, one of the things we said is we want to see as an indicator of success, the partner ecosystem evolve and then sure enough, it exploded with the SIs and all the kinds of developers. So maybe talk about AA's ecosystem, The Partner System. You obviously have a lot of experience there in your career, how do you see that as a leverage point? >> Yeah, it's huge. This market is far larger than we can cover with a direct sales organization and requires substantial services engagements that go well beyond the kind of professional services organization we want to build out organically in the company. So when you look at that, the company today has 1,900 partners. The global systems integrators are key, especially those with VPO type practices, the regional SIs and candidly, the regional VARs who've built out a strong service malpractice, a strong VMware practice and have the professional services capabilities to do some of these complex automation or automation type work that have also built the trust and confidence of their customers. So, in partnership with these types of companies, we believe we can expand our reach. We believe we can offer a more comprehensive outcome and solution to our customers and we, what I'm going to be looking at is, how do we enhance our channel programs to be the kind of company that the channel partners want to engage with, built upon the reputation of the company, the leadership position we have in the technology and also our willingness to go after this space together. >> So I got to go but last question is, what can you share with us about your 100-day plan? Where are you going to focus? >> On the people. There is a strong culture here, there's incredible sales talent and there's talent throughout the organization. I think Dave, you've seen for me over the years, a clarity of our mission, keep things simple and try and drive a repetitive process to deliver results. I'm very accountability focused. So I think what I'm going to look to assess is where the organization is today, how to get more out of the great talent we have, build stronger and deeper relationships with our customers and really scale and grow through our ecosystem of channel partners. >> Well, Chris, I'm super excited for you. A great hire by Automation Anywhere obviously got my attention. I think it'll get the industry's as well. Best of luck, and of course we'll be watching. >> Good, always great to see you, Dave, take care. >> Yeah, ditto, thanks so much for coming on and thank you for watching everybody. Keep it here because this month we're going to be really digging into the ETR data we've been reporting on that horse race between Automation Anywhere and UI Path. The ETR data is in the field and we'll be reporting on that. So look for that. This is Dave Vellante for theCUBE and we'll see you next time. (gentle music)