>> Announcer: Live, from Las Vegas. It's theCUBE. Covering Oracle Modern Customer Experience 2017. Brought to you by Oracle. >> Okay. Welcome back. And we're live here in Las Vegas at the Mandalay Bay Convention Center. This is SiliconANGLE's theCUBE. This is our flagship program where we go out to the events and extract the signal from noise. I'm John Furrier, the co-founder of SiliconANGLE, with Peter Burris, head of research at SiliconANGLE's wikibon.com team. Our next guest is Marta Federici, who's with Royal Philips, who, head of CRM. So CRM, Customer Relationship Management. The old way to do things, now transitioning to modern customer experience. Welcome to theCUBE. You look fabulous. >> Thank you. >> John: Thanks for joining us. >> Thank you for inviting me, pleasure to be here. >> Great to have you on. Because you know, one of the things that we're really focused on with our research that Peter's doing, is the practitioners. How they're thinking about executing the customer experience. And on our reporting side, we're seeing huge reports that these platforms are providing great value. But at the edge, the customers' expectations are higher than the value that the platforms are delivering. >> Marta: Yeah. >> We're seeing with fake news, we're seeing it all over the place. People want authentic experiences, relevant to them. This is the whole purpose. >> Marta: Yeah, yeah. Exactly. >> It's the people factor. >> Marta: Yeah. (laughs) >> That's what you're going to be on stage tomorrow morning. >> Tomorrow morning at 9 a.m. Yeah, indeed. So, I would say to be authentic, to be genuine toward your customers, you always need to be relevant to them, you need to listen, you need to learn. You need to know what they need. You need to be ahead of what can they possibly do. You need to start. You need to focus on the insides. You have to really connect all the dots. I think one of the biggest challenges that we have as a company, but I think can be a shared challenge with many other companies across the globe, is that sometimes you not always have the opportunity to break the silence within a large organization. And work really horizontally. And this is something that we really strive to do. Especially when we have specific projects, or innovation-related project, innovation-driven technology project as well. So we try to build a multifunctional team that really can work hand-in-hand, together, to deliver the higher ROI, the better results, the best customer engagement. And be always relevant when it's needed for our customers, for our consumers, and even for our patients, by the way. >> So let's talk about your team then, and how your team fits within Royal Philips. Describe how you've constituted it, how you've put it together, and how it connects into some of the other functions necessary to drive customer experience. >> Yeah, so by the way, I'm very proud of my team, I would say as a start. We, I mean, I build this team in the past three years. And my team is composed in a particular way. I have a portion of the team that is focusing on business-to-consumer CRM, a portion of the team on business-to-business CRM, and then I have, I would say, two layers in between. One is about CRM technology that spans across both domains. And one is about insights. I would say all of them work together. And I really like the fact that, also, the business-to-consumer and the business-to-business team, they can enrich each other. Sharing challenges and really learning from one another. When I think about my, I would say, my product owner, actually we work very, very closely through his team, with the IT department on one end. Because also we own. >> This is the technology person. >> Exactly. The technology side of the story, I would say. Because we own, for example, the market information tooling, Eloqua, that we leverage for any additional campaign management activity on both B2C and B2B. As well as the identity system, et cetera. And, on the other hand, through the insight team, we also work very, very much closely together with enterprise information management teams. So any team who works with databases, with reporting, with advanced analytics, and predictive analytics. So through them and through the more business side of my team, we can build quite nice stories for our experts. >> So you got a B2B practice, a B2C practice, supported by technology and analytics. >> Technology and insights. Exactly, exactly. That's the structure of the team. >> How did you build the team? I mean, talk a little bit about, we talked about the customer journey and CRM and related technologies needing to intercept and serve customers as they seek their solutions and the value propositions that they want to build. How did this play out at Philips? How did it, where did it start, how did it evolve over time to get to where you are? And obviously at some point and time we're going to ask ya, "And where do you think it's going to go?" >> (laughs) Sure. >> But how has it gotten to where it is? >> Sure. I would say, when I started, I had a white, a blank page, a totally blank page. And I started hiring some experts in key areas. Actually, the first expert I hired, where on the technology side. Because we were supposed to, to deploy Eloqua first, for the first time, on a global level. So that was the first piece of the puzzle, together with the insights team, and also with some key expert in terms of B2C and B2B business domains. So then I started realizing, Okay, but this structure needs to make some sense. They need support, they need help. We enable as a, I would say, CRM, a corporate team, any countries across the globe, and any businesses, B2C or B2B. So we deal with a lot of stakeholders. We have multiple stakeholders, and we run and manage multiple projects at the same time. So let's say I started then figure it out, Okay, what are the talents that I need on a business perspective to really make sure that we design the right journeys, that we build the right campaigns, that we can interpret the data properly? So piece by piece I started really filling out all the boxes that I had in my mind. And now, I think this organization is really working. So the team is very motivated, very committed, very passionate. And in the past month, actually also recently, we deliver quite some best practices. So yeah, award-winning best practices. >> Marta, talk about the learnings. You're in a transformation, and CRM certainly is important as you move and transform into the modern era of relationship management with customers. What is the learnings that you have taken away that you can share with folks that are either on a different part of the journey path than you are, or just anything that you would like to share, that would be helpful. >> Yeah, yeah. So when I think about, also what Laura Ipsen, for example, talked about this morning, the marketing heroes. I think, technology is very-- >> Now, Laura Ipsen is the, runs all the modern marketing products that you're holding. >> Yes, exactly. >> She's the head honcho. She's the head honcho, as they say. (laughs) >> SVP of Oracle Marketing Cloud. So when I listen to her, this morning, she was talking about those marketing evils. Also, while talking to Time Warner CMO, and I think in order to start, and to succeed in any transformation, any additional transformation that you want to carry forward with, you really need the right talents, with the right attitudes, with the right skills, with the right mindset, by the way. And I think on one end technology can really help you, can really be a game-changer, a key enabler, but without the right people on your company's side, and also on your vendor's side, that work together with you on a daily basis, you can not achieve great results. >> And what about the partners? You know, Oracle obviously has a good team. We've been following them now for multiple years. It's our eighth year covering Oracle. We've seen the transformation within Oracle. But also they have partners too. I mean, do you interface with them? And what's your advice for folks that are trying to sort their partnership component out with the vendor? >> Yeah, let's say one particularity of my team and what we do everyday, is that we work daily with Oracle and we also like to embrace any other partners that they suggest us to work with. For example, in a recent campaign we beat a huge Black Friday best practice for our North American market and we also scale it globally, achieving great results, and we partnered up on one end with Oracle. Strategic services, expert services, but also with Return Path. Which is one of their, also, I would say, preferred partners. To make of this campaign something really, really good and to ensure a very good broadcasting performance. On the other hand, we also partnered with some of their additional partners that can be related to some apps specifically or some talents that they have internally. And no matter if it's about consultancy, strategy, technical expert. So, yeah, we're pretty much open, very open-minded. And very, I would say we embrace any inputs, any good inputs. Also because, on one end, what is important for us is to share the challenge that we have with our vendors, with our partners, and of course asking for help. But at the same time, we like to onboard them. To make them understood about what's the real challenge. How do we feel about it? We need to have a common sense of purpose. If we really want to, I mean, to take a project to the next level and make it a success. >> So you implement these tools, and put these relationships in place, the productivity and the effectiveness of marketing goes up. >> Marta: Yep. >> How is, therefore, the role of marketing starting to change within Philips as a basis of these new competencies and these new capabilities that, presumably, the rest of the organization finds valuable? >> Let's say, Philips has a great mission. So, we-- >> And one that's transforming, has gone through a lot of change over the last few years. >> Marta: Exactly. >> Pretty successfully, you might add. >> Exactly, exactly. We are a health technology company. We employ 70,000 people across the globe, across a hundred countries. Our mission is to improve people life. Through meaningful innovation that matters to our consumers and to our customers. So I would say this is a huge challenge. We say that we would like to improve three billions people life by 2025. It's a huge mission. And how are we going to do that? Through innovation, through one-on-one customer relationships. So, and this is where, I mean, we also recently, we started focusing more and more on our customer, we started being truly obsessed. No matter if we talk about consumers on B2C domain, or if we talk about customer. So customer obsession is really at the core of any of our marketing activity right now. And it will be even more. By the way, in the past six-to-nine months, we also had the opportunity to have CRM, as well as our, I would say, shop capabilities, becoming core marketing capabilities. Of course this come with a lot of pressure, a lot of, I would say, attention, also-- >> Some sleepless nights. >> Exactly, exactly. But it is quite exciting. And we also would like to continue to invest on our connected proposition. So we also build products, which are connected to apps, and what's the best way to engage? CRM. So what's the best tactics, or strategy, or how can we build a consistent and long-lasting engagement that delivers the higher results and the higher ROI? So that's, I mean, CRM can be really a game-changer there. >> So Philips is quite legendary. And perhaps because of it's Dutch heritage, 'cause the Dutch had to engage a lot of people from a lot of different backgrounds and a lot of places to make their businesses great. And Philips is quite legendary at being responsive to and responsible, responsive to and responsible to a lot of different people on a global basis. How are some of those cultural values being amplified inside Philips as you bring more of this customer obsession to bear? >> Yeah. Yeah. So let's say, Philips is at quarter in the Netherlands. And in the Netherlands, I would say, Dutch people are always ready to listen. You need to always find a sort of consensus before you can move forward with any strategy, or with any project or program. You always listen also to any inputs. Because you want to really make sure that your idea, on one hand, is agreed, on the other hand, is re-analyzed into the least of the details. So what we do is is really try to understand all perspectives, because any point of view can enrich an initial idea that you have. And I would say our business is also so diverse. If you look at all the business units that we have, and sometimes can be difficult to understand Philips as a whole, but in the end every single of our business units really incorporate together to the greater goal of innovation that matters in improving people lives. So you will find this through any of our stories, any of the products that we deliver, that we build, also together with our customers. So I would say, Philips is, has many, but also, can be also be just one at same time. >> It's transforming, as GE says, you know, they went to bed an industrial company one night and woke up a software analytics company. >> Marta: (laughs) Yeah. >> That's really what's happening. >> Exactly. And, you know what, we are also focusing on delivering services and delivering information. Because what we also strive to do, is to work within the health continuum from prevention, to diagnosis, to care, also home care. And this is what we are really aiming to do, at this stage, also, establishing a connection in between a consumer that can also be a patient on the other side, and delivering the right information to the hospital to take care of them. So in this health continuum story it's really a game-changer, I think, within, I would say, a health tech industry. >> And having the data is critical. Marta, final question for you. Take a minute to share what's exciting here at this event. Why is the modern customer experience show this year so important? There's a big buzz around this platform. There's a big buzz about the early days we're in with modern customer experience being thought differently with AI and seeing this beginning trajectory. What should people get excited about? What's the most important thing in your mind? >> I think the first thing I noticed while coming here, okay, first of all, this year the event is a new vibe. I think this event is even more inspiring than the past edition that I have been to. And I think the fact that they renamed also the event into Modern Customer Experience instead of Modern Marketing Event is really a signal that something is changing. Also on Oracle side. And this is what I notice at the first sight and in the end, when yesterday, during Mark Hurd, I would say, keynote, opening keynote, he mentioned the artificial intelligence, I was pretty pleased to see this focus through their, I would say, app environment. Where if you looked at the services that this app is going to be linked to, you won't see the marketing cloud anymore. You see the CX. So it's all about the CX in the end. And this is, in the end, the core. >> They're bringing it together. >> Marta: Yeah, they're bringing it together. >> Well, the technology is the marketing cloud, the outcome is the CX. >> Marta: Yeah. Exactly. So and I think they are going to focus more and more on that. Also, I mean, technology-wise it doesn't make sense to have silos anymore. >> Yeah, what does this mean for you? How does, when you see that, what's the impact to your world? >> I can be only happy. Because we are always challenged to look at the CX, to start with the CX, to produce an even more announced one. So if I look at the opportunity this can bring to us, I can only be very, very positive. Also the focus on AI is truly important. The focus on data, also this morning, Laura Ipsen was talking a lot about the importance of insight and data and how this is going to be a game-changer. And also this morning with Mark Hurd at breakfast, he mentioned data is the new currency. No way. We were also discussing a bit, Okay, third party data, who are the biggest player? And he said, of course, Facebook and Google. (laughs) Of course. But still, the value that every company should build along is owning his own data. Every company should really care to build an extremely good database to start with. Because anyone can have access to third-party data, but this is, can be just an easy escape, easy or fast. >> So you feel-- >> It's first-person data that's going to determine your differentiation. >> Marta: That is the game-changer, for sure. >> And you're excited by the, by Mark Hurd's comments this morning at breakfast. >> Definitely. (laughs) >> He's been on theCUBE, oddly enough. >> Which means he's now excited too. (laughter) >> Mark, if you're watching, we need you back on theCUBE, he's good. He gets the marketplace, he understands the pulse. But he's also a data-driven guy. >> Yeah, pretty much. >> You know, he's old school like us, but Marta, thank you so much for coming on theCUBE. Marta Federici, Head of CRM. Thank you so much, for sharing your perspective and insight and data with us. >> Thank you, thank you. >> This is theCUBE, I'm John with Peter Burris. We'll be back with more from Oracle Modern Customer Experience after this short break. (electronic music)

>>Partnerships in the technology business, they take many forms. For example, technology engineering partnerships, they drive value in terms of things like integration and simplification for customers. There are product partnerships. They fill gaps to create more comprehensive portfolios and more fluid relationships. Partner ecosystems offer high touch services. They offer managed services, specialty services, and other types of value based off of strong customer knowledge and years of built up trust partner. Ecosystems have evolved quite dramatically over the last decade with the explosion of data and the popularity of cloud models. Public, private, hybrid cross clouds. You know, yes it's true. Partnerships are about selling solutions, but they're also about building long term sustainable trust, where a seller learns the ins and outs of a customer's organization and can anticipate needs that are gonna drive bottom line profits for both sides of the equation, the buyer and the seller. >>Hello and welcome to our program. My name is Dave Ante and along with Lisa Martin, we're going to explore how Hitachi Van Tara drives customer success with its partners. First up, Lisa speaks with Kim King. She's the senior vice president of Strategic Partners and Alliances at Hitachi Van. And they'll set the table for us with an overview of how Hitachi is working with partners and where their priorities are focused. Then Russell Kingsley, he's the CTO and global VP of Technical sales at Hitachi Van Tara. He joins Lisa for a discussion of the tech and they're gonna get into cloud generally and hybrid cloud specifically in the role that partners play in the growing as a service movement. Now, after that I'll talk with Tom Christensen, he's the global technology advisor and executive analyst at Hitachi Vitara. And we're gonna talk about a really important topic, sustainability. We're gonna discuss where it came from, why it matters, and how it can drive bottom line profitability for both customers and partners. Let's get right to it. >>Where for the data driven, for those who understand clarity is currency. Believe progress requires precision and no neutral is not an option. We're for the data driven. The ones who can't tolerate failure, who won't put up with downtime or allow access to just anyone. We're for the data driven who act on insight instead of instinct. Bank on privacy instead of probabilities and rely on resilience instead of reaction. We see ourselves in the obsessive, the incessant, progressive, and the meticulously engineered. We enable the incredible identify with the analytical and are synonymous with the mission critical. We know what it means to be data driven because data is in our dna. We were born industrial and and we breathe digital. We speak predictive analytics so you can keep supply chains moving. We bleed in store and online insights so you can accurately predict customer preferences. We sweat security and digital privacy so you can turn complex regulations into competitive advantage. We break down barriers and eliminate silos. So you can go from data rich to data driven because it's clear the future belongs to the data driven. >>Hey everyone, welcome to this conversation. Lisa Martin here with Kim King, the SVP of Strategic Partners and Alliances at Hitachi Ventera. Kim, it's great to have you on the program. Thank you so much for joining me today. >>Thanks Lisa. It's great to be here. >>Let's talk about, so as we know, we talk about cloud all the time, the landscape, the cloud infrastructure landscape increasingly getting more and more complex. What are some of the biggest challenges and pain points that you're hearing from customers today? >>Yeah, so lot. There are lots, but I would say the, the few that we hear consistently are cost the complexity, right? Really the complexity of where do they go, how do they do it, and then availability. They have a lot of available options, but again, going back to complexity and cost, where do they think that they should move and how, how do they make that a successful move to the cloud? >>So talk to me, Hitachi Ventura has a great partner ecosystem. Where do partners play a role in helping customers to address some of the challenges with respect to the cloud landscape? >>Yeah, so part, our partners are really leading the way in the area of cloud in terms of helping customers understand the complexities of the cloud. As we talked about, they're truly the trusted advisor. So when they look at a customer's complete infrastructure, what are the workloads, what are the CRI critical applications that they work with? What's the unique architecture that they have to drive with that customer for a successful outcome and help them architect that? And so partners are truly leading the way across the board, understanding the complexities of each individual customer and then helping them make the right decisions with and for them. And then bringing us along as part of that, >>Talk to me a little bit about the partner landscape, the partner ecosystem at Hitachi Ventura. How does this fit into the overall strategy for the company? >>So we really look at our ecosystem as an extension of our sales organization and and really extension across the board, I would say our goal is to marry the right customer with the right partner and help them achieve their goals, ensure that they keep costs in check, that they ensure they don't have any security concerns, and that they have availability for the solutions and applications that they're trying to move to the cloud, which is most important. So we really, we really look at our ecosystem as a specialty ecosystem that adds high value for the right customers. >>So Kim, talk to me about how partners fit into Hitachi van's overall strategy. >>So I think our biggest differentiators with partners is that they're not just another number. Our partner organization is that valued extension of our overall sales pre-sales services organization. And we treat them like an extension of our organization. It's funny because I was just on a call with an analyst earlier this week and they said that AWS has increased their number of partners to 150,000 partners from, it was just under a hundred thousand. And I'm really not sure how you provide quality engagement to partners, right? And is how is that really a sustainable strategy? So for us, we look at trusted engagement across the ecosystem as a def differentiation. Really our goal is to make their life simple and profitable and really become their primary trusted partner when we go to market with them. And we see that paying dividends with our partners as they engage with us and as they expand and grow across the segments and then grow globally with us as well. >>And that's key, right? That synergistic approach when you're in customer conversations, what do you articulate as the key competitive differentiators where it relates to your partners? >>So really the, that they're the trusted advisor for that partner, right? That they understand our solutions better than any solution out there. And because we're not trying to be all things to our customers and our partners that we being bring best breaths of breed, best of breed solutions to our customers through our partner community, they can truly provide that end user experience and the successful outcome that's needed without, you know, sort of all kinds of, you know, crazy cha challenges, right? When you look at it, they really wanna make sure that they're driving that co-developed solution and the successful outcome for that customer. >>So then how do you feel that Hitachi Ventura helps partners really to grow and expand their own business? >>Wow, so that's, there's tons of ways, but we've, we've created a very simplified, what we call digital selling platform. And in that digital selling platform, we have allowed our partners to choose their own price and pre-approve their pricing and their promotions. They've actually, we've expanded the way we go to market with our partners from a sort of a technical capabilities. We give them online what we call Hitachi online labs that allow them to really leverage all of the solutions and demo systems out there today. And they have complete access to any one of our resources, product management. And so we really have, like I said, we actually provide our partners with better tools and resources sometimes than we do our own sales and pre-sales organization. So we, we look at them as, because they have so many other solutions out there that we have to be one step ahead of everybody else to give them that solution capability and the expertise that they need for their customers. >>So if you dig in, where is it that Hiti is helping partners succeed with your portfolio? >>Wow. So I think just across the board, I think we're really driving that profitable, trusted, and simplified engagement with our partner community because it's a value base and ease of doing business. I say that we allow them to scale and drive that sort of double digit growth through all of the solutions and and offerings that we have today. And because we've taken the approach of a very complex technical sort of infrastructure from a high end perspective and scale it all the way through to our mid-size enterprise, that allows them to really enter any customer at any vertical and provide them a really quality solution with that 100% data availability guarantee that we provide all of our customers. >>So then if we look at the overall sales cycle and the engagement, where is it that you're helping cus your partners rather succeed with the portfolio? >>Say that again? Sorry, my brain broke. No, >>No worries. So if we look at the overall sales cycle, where is it specifically where you're helping customers to succeed with the portfolio? >>So from the sales cycle, I think because we have the, a solution that is simple, easy, and really scaled for the type of customer that we have out there, it allows them to basically right size their infrastructure based on the application, the workload, the quality or the need that application may have and ensure that we provide them with that best solution. >>So then from a partner's perspective, how is it that Hitachi van is helping them to actually close deals faster? >>Yeah, so lots of great ways I think between our pre-sales organization that's on call and available a hundred percent of the time, I think that we've seen, again, the trusted engagement with them from a pricing and packaging perspective. You know, we, you know, two years ago it would take them two to three weeks to get a pre-approved quote where today they preapproved their own quotes in less than an hour and can have that in the hands of a customer. So we've seen that the ability for our partners to create and close orders in very short periods of time and actually get to the customer's needs very quickly, >>So dramatically faster. Yes. Talk about overall, so the partner relationship's quite strong, very synergistic that, that Hitachi Ventura has with its customers. Let's kind of step back out and look at the cloud infrastructure. How do you see it evolving the market evolving overall in say the next six months, 12 months? >>Yeah, so we see it significantly, we've been doing a lot of studies around this specifically. So we have a couple of different teams. We have our sort of our standard partner team that's out there and now we have a specialty cloud service provider team that really focuses on partners that are building and their own infrastructure or leveraging the infrastructure of a large hyperscaler or another GSI and selling that out. And then what we found is when we dig down deeper into our standard sort of partner reseller or value added reseller market, what we're seeing is that they are want to have the capability to resell the solution, but they don't necessarily wanna have to own and manage the infrastructure themselves. So we're helping both of them through that transition. We see that it's gonna, so it's funny cuz you're seeing a combination of many customers move to really the hyperscale or public cloud and many of them want to repatriate their infrastructure back because they see costs and they see challenges around all of that. And so our partners are helping them understand, again, what is the best solution for them as opposed to let's just throw everything in the public cloud and hope that it works. We're we're really helping them make the right choices and decisions and we're putting the right partners together to make that happen. >>And how was that feedback, that data helping you to really grow and expand the partner program as a whole? >>Yeah, so it's been fantastic. We have a whole methodology that we, we created, which is called PDM plan, develop monetize with partners. And so we went specifically to market with cloud service providers that'll, and we really tested this out with them. We didn't just take a solution and say, here, go sell it, good luck and have, you know, have a nice day. Many vendors are doing that to their partners and the partners are struggling to monetize those solutions. So we spend a lot of time upfront planning with them what is not only the storage infrastructure but your potentially your data resiliency and, and everything else that you're looking at your security solutions. How do we package those all together? How do we help you monetize them? And then who do you target from a customer perspective so that they've built up a pipeline of opportunities that they can go and work with us on and we really sit side by side with them in a co-development environment. >>In terms of that side by side relationship, how does the partner ecosystem play a role in Hitachi Venturas as a service business? >>So our primary go to market with our, as a service business is with and through partners. So our goal is to drive all, almost all of of our as a service. Unless it's super highly complex and something that a partner cannot support, we will make sure that they really, we leverage that with them with all of our partners. >>So strong partner relationships, very strong partner ecosystem. What would you say, Kim, are the priorities for the partner ecosystem going forward? The next say year? >>Yeah, so we have tons of priorities, right? I think really it's double digit growth for them and for us and understanding how a simpler approach that's customized for the specific vertical or customer base or go to market that they have that helps them quickly navigate to be successful. Our goal is always to facilitate trusted engagements with our partners, right? And then really, as I said, directionally our goal is to be 95 to a hundred percent of all of our business through partners, which helps customers and then really use that trusted advisor status they have to provide that value base to the customer. And then going back on our core tenants, which are, you know, really a trusted, simplified, profitable engagement with our partner community that allows them to really drive successful outcomes and go to market with us. And the end users >>Trust is such an important word, we can't underutilize it in these conversations. Last question. Sure. From a channel business perspective, what are some of the priorities coming down the pi? >>Oh, again, my biggest priority right, is always to increase the number of partner success stories that we have and increase the value to our partners. So we really dig in, we, we right now sit about number one or number two in, in our space with our partners in ease of doing business and value to our channel community. We wanna be number one across the board, right? Our goal is to make sure that our partner community is successful and that they really have those profitable engagements and that we're globally working with them to drive that engagement and, and help them build more profitable businesses. And so we just take tons of feedback from our partners regularly to help them understand, but we, we act on it very quickly so that we can make sure we incorporate that into our new program and our go to markets as we roll out every year. >>It sounds like a great flywheel of communications from the partners. Kim, thank you so much for joining me today talking about what Hitachi Vanta is doing with its partner ecosystem, the value in IT for customers. We appreciate your insights. >>Thank you very much. >>Up next, Russell Kingsley joins me, TTO and global VP of technical sales at Hitachi van you watch in the cube, the leader in live tech coverage. Hey everyone, welcome back to our conversation with Hitachi van Tara, Lisa Martin here with Russell Skillings Lee, the CTO and global VP of technical sales at Hitachi Van Russell. Welcome to the program. >>Hi Lisa, nice to be here. >>Yeah, great to have you. So here we are, the end of calendar year 2022. What are some of the things that you're hearing out in the field in terms of customers priorities for 2023? >>Yeah, good one. Just to, to set the scene here, we tend to deal with enterprises that have mission critical IT environments and this has been been our heritage and continues to be our major strength. So just to set the scene here, that's the type of customers predominantly I'd be hearing from. And so that's what you're gonna hear about here. Now, in terms of 20 23, 1 of the, the macro concerns that's hitting almost all of our customers right now, as you can probably appreciate is power consumption. And closely related to that is the whole area of ESG and decarbonization and all of that sort of thing. And I'm not gonna spend a lot of time on that one because that would be a whole session in itself really, but sufficient to say it is a priority for us and we, we are very active in, in that area. >>So aside from from that one that that big one, there's also a couple that are pretty much in common for most of our customers and, and we're in areas that we can help. One of those is in an exponential growth of the amount of data. It's, it's predicted that the world's data is going to triple by 2025 as opposed to where it was in 2020. And I think everyone's contributing to that, including a lot of our customers. So just the, the act of managing that amount of data is, is a challenge in itself. And I think closely related to that, a desire to use that data better to be able to gain more business insights and potentially create new business outcomes and business ideas are, is another one of those big challenges in, in that sense, I think a lot of our customers are in what I would kind of call, I affectionately call the, the post Facebook awakening era. >>And that, and what I mean by that is our traditional businesses, you know, when Facebook came along, they kind of illustrated, hey, I can actually make some use out of what is seemingly an enormous amount of useless data, which is exactly what Facebook did. They took a whole lot of people's Yeah. The minutia of people's lives and turned it into, you know, advertising revenue by gaining insights from, from those, you know, sort of seemingly useless bits of data and, you know, right. And I think this actually gave rise to a lot of digital business at that time. You know, the, this whole idea of what all you really need to be successful and disrupt the business is, you know, a great idea, you know, an app and a whole bunch of data to, to power it. And I think that a lot of our traditional customers are looking at this and wondering how do they get into the act? Because they've been collecting data for decades, an enormous amount of data, right? >>Yes. I mean, every company these days has to be a data company, but to your point, they've gotta be able to extract those insights, monetize it, and create real value new opportunities for the business at record speed. >>Yes, that's exactly right. And so being able to, to wield that data somehow turn it, it kind of turns out our customer's attentions to the type of infrastructure they've got as well. I mean, if you think about those, those companies that have been really successful in leveraging that data, a lot of them have, especially in the early days, leverage the cloud to be able to build out their capabilities. And, and the reason why the cloud became such a pivotal part of that is because it offered self-service. IT and, you know, easy development platforms to those people that had these great ideas. All they needed was access to, to, you know, the provider's website and a credit card. And now all of a sudden they could start to build a business from that. And I think a lot of our traditional IT customers are looking at this and thinking, now how do I build a similar sort of infrastructure? How do I, how do I provide that kind of self-service capability to the owners of business inside my company rather than the IT company sort of being a gatekeeper to a selected set of software packages. How now do I provide this development platform for those internal users? And I think this, this is why really hybrid cloud has become the defacto IT sort of architectural standard, even even for quite traditional, you know, IT companies. >>So when it comes to hybrid cloud, what are some of the challenges the customers are facing? And then I know Hitachi has a great partner ecosystem. How are partners helping Hitachi Ventura and its customers to eliminate or solve some of those hybrid cloud challenges? >>Yeah, it's, it, it's a great question and you know, it's, it's not 1975 anymore. It's not, it's not like you're going to get all of your IT needs from, from one, from one vendor hybrid by sort of, it's, you know, by definition is going to involve multiple pieces. And so there basically is no hybrid at all without a partner ecosystem. You really can't get everything at, at a one stop shop like you used to. But even if you think about the biggest public cloud provider on the planet, aws even, it has a marketplace for partner solutions. So, so even they see, even for customers that might consider themselves to be all in on public cloud, they are still going to need other pieces, which is where their marketplace come comes in. Now for, for us, you know, we are, we're a company that, we've been in the IT business for over 60 years, one of one of the few that could claim that sort of heritage. >>And you know, we've seen a lot of this type of change ourselves, this change of attitude from being able to provide everything yourself to being someone who contributes to an overall ecosystem. So partners are absolutely essential. And so now we kind of have a, a partner first philosophy when it comes to our routes to market on, you know, not just our own products in terms of, you know, a resale channel or whatever, but also making sure that we are working with some of the biggest players in hybrid infrastructure and determining where we can add value to that in our, in our own solutions. And so, you know, when it comes to those, those partner ecosystems, we're always looking for the spaces where we can best add our own capability to those prevailing IT architectures that are successful in the marketplace. And, you know, I think that it's probably fair to say, you know, for us, first and foremost, we, we have a reputation for having the biggest, most reliable storage infrastructure available on the planet. >>And, and we make no apologies for the fact that we tout our speeds and feeds and uptime supremacy. You know, a lot of our, a lot of our competitors would suggest that, hey, speeds and feeds don't matter. But you know, that's kind of what you say when, when you're not the fastest or not the most reliable, you know, of course they matter. And for us, what we, the way that we look at this is we say, let's look at who's providing the best possible hybrid solutions and let's partner with them to make those solutions even better. That's the way we look at it. >>Can you peel the, the onion a little bit on the technology underpinning the solutions, give a glimpse into that and then maybe add some color in terms of how partners are enhancing that? >>Yeah, let me, let me do that with a few examples here, and maybe what I can do is I can sort of share some insight about the way we think with partnering with, with particular people and why it's a good blend or why we see that technologically it's a good blend. So for example, the work we do with VMware, which we consider to be one of our most important hybrid cloud partners and in, and in fact it's, it's my belief, they have one of the strongest hybrid cloud stories in the industry. It resonates really strongly with, with our customers as well. But you know, we think it's made so much better with the robust underpinnings that we provide. We're one of the, one of the few storage vendors that provides a 100% data availability guarantee. So we, we take that sort of level of reliability and we add other aspects like life cycle management of the underpinning infrastructure. >>We combine that with what VMware's doing, and then when you look at our converged or hyper-converged solutions with them, it's a better together story where you now have what is one of the best hybrid cloud stories in the industry with VMware. But now for the on premise part, especially, you've now added a hundred percent data, data availability guarantee, and you've made managing the underlying infrastructure so much easier through the tools that we provide that go down to that level A level underneath where VMware are. And so that's, that's VMware. I've got a couple, couple more examples just to sort of fill, fill that out a bit. Sure. Cisco is another part, very strong partner of ours, a key partner. And I mean, you look at Cisco, they're a 50 billion IT provider and they don't have a dedicated storage infrastructure of their own. So they're going to partner with someone. >>From our perspective, we look at Cisco's, Cisco's customers and we look at them and think they're very similar to our own in terms of they're known to appreciate performance and reliability and a bit of premium in quality, and we think we match them them quite well. They're already buying what we believe are the best converge platforms in the industry from Cisco. So it makes sense that those customers would want to compliment that investment with the best array, best storage array they can get. And so we think we are helping Cisco's customers make the most of their decision to be ucs customers. Final one for, for you, Lisa, by way of example, we have a relationship with, with Equinix and you know, Equinix is the world's sort of leading colo provider. And the way I think they like to think of themselves, and I too tend to agree with them, is their, they're one of the most compelling high-speed interconnect networks in the world. >>They're connected to all of the, the, the significant cloud providers in most of the locations around the world. We have a, a relationship with them where we find we have customers in common who really love the idea of compute from the cloud. Compute from the cloud is great because compute is something that you are doing for a set period of time and then it's over you. Like you have a task, you do some compute, it's done. Cloud is beautiful for that. Storage on the other hand is very long lived storage doesn't tend to operate in that same sort of way. It sort of just becomes a bigger and bigger blob over time. And so the cost model around public cloud and storage is not as compelling as it is for compute. And so our, with our relationship with Equinix, we help our customers to be able to create, let's call it a, a data anchor point where they put our arrays into, into an Equinix location, and then they utilize Equinix as high speeding interconnects to the, to the cloud providers, okay. To take the compute from them. So they take the compute from the cloud providers and they own their own storage, and in this way they feel like we've now got the best of all worlds. Right. What I hope that illustrates Lisa is with those three examples is we are always looking for ways to find our key advantages with any given, you know, alliance partners advantages, >>Right? What are, when you're in customer conversations, and our final few minutes here, I wanna get, what are some of the key differentiators that you talk about when you're in customer conversations, and then how does the partner ecosystem fit into Hitachi vans as a service business? We'll start with differentiators and then let's move into the as service business so we can round out with that. >>Okay. Let's start with the differentiators. Yeah. Firstly and I, and hopefully I've kind of, I've hit this point hard, hard enough. We do believe that we have the fastest and most reliable storage infrastructure on the planet. This is kind of what we are known for, and customers that are working with us already sort of have an appreciation for that. And so they're looking for, okay, you've got that now, how can you make my hybrid cloud aspirations better? So we do have that as a fundamental, right? So, but secondly I'd say, I think it's also because we go beyond just storage management and, and into the areas of data management. You know, we've got, we've got solutions that are not just about storing the bits. We do think that we do that very well, but we also have solutions that move into the areas of enrichment, of the data, cataloging of the data, classification of the data, and most importantly, analytics. >>So, you know, we, we think it's, some of our competitors just stop at storing stuff and some of our competitors are in the analytics space, but we feel that we can bridge that. And we think that that's a, that's a competitive advantage for us. One of the other areas that I think is key for us as well is, as I said, we're one of the few vendors who've been in the marketplace for 60 years and we think this, this, this gives us a more nuanced perspective about things. There are many things in the industry, trends that have happened over time where we feel we've seen this kind of thing before and I think we will see it again. But you only really get that perspective if you are, if you are long lived in the industry. And so we believe that our conversations with our customers bear a little bit more sophistication. It's not just, it's not just about what's the latest and greatest trends. >>Right. We've got about one minute left. Can you, can you round us out with how the partner ecosystem is playing a role in the as service business? >>They're absolutely pivotal in that, you know, we, we ourselves don't own data centers, right? So we don't provide our own cloud services out. So we are 100% partner focused when it comes to that aspect. Our formula is to help partners build their cloud services with our solutions and then onsell them to their customers as as as a service. You know, and by what quick way of example, VMware for example, they've got nearly 5,000 partners selling VMware cloud services. 5,000 blows me away. And many of them are our partners too. So we kind of see this as a virtuous cycle. We've got product, we've got an an alliance with VMware and we work together with partners in common for the delivery of an as a service business. >>Got it. So the, as you said, the partner ecosystem is absolutely pivotal. Russell, it's been a pleasure having you on the program talking about all things hybrid cloud challenges, how Hitachi van is working with its partner ecosystems to really help customers across industries solve those big problems. We really appreciate your insights and your time. >>Thank you very much, Lisa. It's been great. >>Yeah, yeah. For Russell Stingley, I'm Lisa Martin. In a moment we're gonna continue our conversation with Tom Christensen. Stay tuned. >>Sulfur Royal has always embraced digital technology. We were amongst the first hospitals in the UK to install a full electronic patient record system. Unfortunately, as a result of being a pioneer, we often find that there's gaps in the digital solutions. My involvement has been from the very start of this program, a group of us got together to discuss what the problems actually were in the hospital and how we could solve this. >>The digital control center is an innovation that's been designed in partnership between ourselves, anti touch, and it's designed to bring all of the information that is really critical for delivering effective and high quality patient care. Together the DCC is designed not only to improve the lives of patients, but also of our staff giving us information that our demand is going to increase in the number of patients needing support. The technology that we're building can be replicated across sulfur, the NCA, and the wider nhs, including social care and community services. Because it brings all of that information that is essential for delivering high quality efficient care. >>The DCC will save time for both staff and more importantly our patients. It will leave clinicians to care for patients rather than administrate systems and it will allow the system that I work with within the patient flow team to effectively and safely place patients in clinically appropriate environments. >>But we chose to partner with Hitachi to deliver the DCC here at Sulfur. They were willing to work with us to co-produce and design a product that really would work within the environment that we find ourselves in a hospital, in a community setting, in a social care setting. >>My hopes for the DCC is that ultimately we will provide more efficient and reliable care for our patients. >>I do believe the digital control center will improve the lives of staff and also the patients so that we can then start to deliver the real change that's needed for patient care. >>Okay, we're back with Tom Christensen, who's the global technology advisor and executive analyst at Hitachi Van Tara. And we're exploring how Hitachi Van Tower drives customer success specifically with partners. You know Tom, it's funny, back in the early part of the last decade, there was this big push around, remember it was called green it and then the oh 7 0 8 financial crisis sort of put that on the back burner. But sustainability is back and it seems to be emerging as a mega trend in in it is, are you seeing this, is it same wine new label? How real is this trend and where's the pressure coming from? >>Well, we clearly see that sustainability is a mega trend in the IT sector. And when we talk to CIOs or senior IT leaders or simply just invite them in for a round table on this topic, they all tell us that they get the pressure from three different angles. The first one is really end consumers and end consumers. Nowaday are beginning to ask questions about the green profile and what are the company doing for the environment. And this one here is both private and public companies as well. The second pressure that we see is coming from the government. The government thinks that companies are not moving fast enough so they want to put laws in that are forcing companies to move faster. And we see that in Germany as an example, where they are giving a law into enterprise companies to following human rights and sustainability tree levels back in the supply chain. >>But we also see that in EU they are talking about a new law that they want to put into action and that one will replicate to 27 countries in Europe. But this one is not only Europe, it's the rest of the world where governments are talking about forcing companies to move faster than we have done in the past. So we see two types of pressure coming in and at the same time, this one here starts off at the CEO at a company because they want to have the competitive edge and be able to be relevant in the market. And for that reason they're beginning to put KPIs on themself as the ceo, but they're also hiring sustainability officers with sustainability KPIs. And when that happens it replicates down in the organization and we can now see that some CIOs, they have a kpi, others are indirectly measured. >>So we see direct and indirect. The same with CFOs and other C levels. They all get measured on it. And for that reason it replicates down to IT people. And that's what they tell us on these round table. I get that pressure every day, every week, every quarter. But where is the pressure coming from? Well the pressure is coming from in consumers and new laws that are put into action that force companies to think differently and have focus on their green profile and doing something good for the environment. So those are the tree pressures that we see. But when we talk to CFOs as an example, we are beginning to see that they have a new store system where they put out request for proposal and this one is in about 58% of all request for proposal that we receive that they are asking for our sustainability take, what are you doing as a vendor? >>And in their score system cost has the highest priority and number two is sustainability. It waits about 15, 20 to 25% when they look at your proposal that you submit to a cfo. But in some cases the CFO say, I don't even know where the pressure is coming from. I'm asked to do it. Or they're asked to do it because end consumers laws and so on are forcing them to do it. But I would answer, yeah, sustainability has become a make trend this year and it's even growing faster and faster every month we move forward. >>Yeah, Tom, it feels like it's here to stay this time. And your point about public policy is right on, we saw the EU leading with privacy and GDPR and it looks like it's gonna lead again here. You know, just shifting gears, I've been to a number of Hitachi facilities in my day. OWA is my favorite because on a clear day you can see Mount Fuji, but other plants I've been to as well. What does Hitachi do in the production facility to reduce CO2 emissions? >>Yeah, I think you're hitting a good point here. So what we have, we have a, a facility in Japan and we have one in Europe and we have one in America as well to keep our production close to our customers and reduced transportation for the factory out to our customers. But you know, in the, in the, in the May region back in 2020 13, we created a new factory. And when we did that we were asked to do it in an energy, energy neutral way, which means that we are moving from being powered by black energy to green energy in that factory. And we build a factory with concrete walls that were extremely thick to make it cold in the summertime and hot in the winter time with minimum energy consumption. But we also put 17,000 square meters of solar panel on the roof to power that factory. >>We were collecting rain waters to flush it in the toilet. We were removing light bulbs with L E D and when we sent out our equipment to our customers, we put it in a, instead of sending out 25 packages to a customer, we want to reduce the waste as much as possible. And you know, this one was pretty new back in 2013. It was actually the biggest project in EA at that time. I will say if you want to build a factory today, that's the way you are going to do it. But it has a huge impact for us when electricity is going up and price and oil and gas prices are coming up. We are running with energy neutral in our facility, which is a big benefit for us going forward. But it is also a competitive advantage to be able to explain what we have been doing the last eight, nine years in that factory. We are actually walking to talk and we make that decision even though it was a really hard decision to do back in 2013, when you do decisions like this one here, the return of investment is not coming the first couple of years. It's something that comes far out in the future. But right now we are beginning to see the benefit of the decision we made back in 2013. >>I wanna come back to the economics, but before I do, I wanna pick up on something you just said because you know, you hear the slogan sustainability by design. A lot of people might think okay, that's just a marketing slogan, slogan to vector in into this mega trend, but it sounds like it's something that you've been working on for quite some time. Based on your last comments, can you add some color to that? >>Yeah, so you know, the factory is just one example of what you need to do to reduce the CO2 emission and that part of the life of a a product. The other one is really innovating new technology to drive down the CO2 emission. And here we are laser focused on what we call decarbonization by design. And this one is something that we have done the last eight years, so this is far from you for us. So between each generation of products that we have put out over the last eight years, we've been able to reduce the CO2 emission by up to 30 to 60% between each generation of products that we have put into the market. So we are laser focused on driving that one down, but we are far from done, we still got eight years before we hit our first target net zero in 2030. So we got a roadmap where we want to achieve even more with new technology. At its core, it is a technology innovator and our answers to reduce the CO2 emission and the decarbonization of a data center is going to be through innovating new technology because it has the speed, the scale, and the impact to make it possible to reach your sustainability objectives going forward. >>How about recycling? You know, where does that fit? I mean, the other day it was, you know, a lot of times at a hotel, you know, you used to get bottled water, now you get, you know, plant based, you know, waters in a box and, and so we are seeing it all around us. But for a manufacturer of your size, recycling and circular economy, how does that fit into your plans? >>Yeah, let me try to explain what we are doing here. Cause one thing is how you produce it. Another thing is how you innovate all that new technology, but you also need to combine that with service and software, otherwise you won't get the full benefit. So what we are doing here, when it comes to exploring circular economics, it's kind of where we have an eternity mindset. We want to see if it is possible to get nothing out to the landfill. This is the aim that we are looking at. So when you buy a product today, you get an option to keep it in your data center for up to 10 years. But what we wanna do when you keep it for 10 years is to upgrade only parts of the system. So let's say that you need more CBU power, use your switch the controller to next generation controller and you get more CPU power in your storage system to keep it those 10 years. >>But you can also expand with new this media flash media, even media that doesn't exist today will be supported over those 10 years. You can change your protocol in the, in the front end of your system to have new protocols and connect to your server environment with the latest and greatest technology. See, the benefit here is that you don't have to put your system into a truck and a recycle process after three years, four years, five years, you can actually postpone that one for 10 years. And this one is reducing the emission again. But once we take it back, you put it on the truck and we take it into our recycling facility. And here we take our own equipment like compute network and switches, but we also take competitor equipment in and we recycle as much as we can. In many cases, it's only 1% that goes to the landfill or 2% that goes to the landfill. >>The remaining material will go into new products either in our cycle or in other parts of the electronic industry. So it will be reused for other products. So when we look at what we've been doing for many years, that has been linear economics where you buy material, you make your product, you put it into production, and it goes into land feed afterwards. The recycling economics, it's really, you buy material, you make your product, you put it into production, and you recycle as much as possible. The remaining part will go into the landfill. But where we are right now is exploring circle economics where you actually buy material, make it, put it into production, and you reuse as much as you can. And only one 2% is going into the landfill right now. So we have come along and we honestly believe that the circular economics is the new economics going forward for many industries in the world. >>Yeah. And that addresses some of the things that we were talking about earlier about sustainability by design, you have to design that so that you can take advantage of that circular economy. I, I do wanna come back to the economics because, you know, in the early days of so-called green, it, there was a lot of talk about, well, I, I, I'll never be able to lower the power bill. And the facilities people don't talk to the IT people. And that's changed. So explain why sustainability is good business, not just an expense item, but can really drive bottom line profitability. I, I understand it's gonna take some time, but, but help us understand your experience there, Tom. >>Yeah, let me try to explain that one. You know, you often get the question about sustainability. Isn't that a cost? I mean, how much does it cost to get that green profile? But you know, in reality when you do a deep dive into the data center, you realize that sustainability is a cost saving activity. And this one is quite interesting. And we have now done more than 1,200 data center assessment around the world where we have looked at data centers. And let me give you just an average number from a global bank that we work with. And this one is, it is not different from all the other cases that we are doing. So when we look at the storage area, what we can do on the electricity by moving an old legacy data center into a new modernized infrastructure is to reduce the electricity by 96%. >>This is a very high number and a lot of money that you save, but the CO2 mission is reduced by 96% as well. The floor space can go up to 35% reduction as well. When we move down to the compute part, we are talking about 61% reduction in electricity on the compute part just by moving from legacy to new modern infrastructure and 61% on the CO2 emission as well. And see this one here is quite interesting because you save electricity and you and you do something really good for the environment. At the same time, in this case I'm talking about here, the customer was paying 2.5 million US dollar annually and by just modernizing that infrastructure, we could bring it down to 1.1 million. This is 1.4 million savings straight into your pocket and you can start the next activity here looking at moving from virtual machine to containers. Containers only use 10% of the CPU resources compared to a virtual machine. Move up to the application layer. If you have that kind of capability in your organization, modernizing your application with sustainability by design and you can reduce the C, the CO2 emission by up to 50%. There's so much we can do in that data center, but we often start at the infrastructure first and then we move up in the chain and we give customers benefit in all these different layers. >>Yeah, A big theme of this program today is what you guys are doing with partners do, are partners aware of this in your view? Are they in tune with it? Are they demanding it? What message would you like to give the channel partners, resellers and, and distributors who may be watching? >>So the way to look at it is that we offer a platform with product, service and software and that platform can elevate the conversation much higher up in the organization. And partners get the opportunity here to go up and talk to sustainability officers about what we are doing. They can even take it up to the CEO and talk about how can you reach your sustainability KPI in the data center. What we've seen this round table when we have sustainability officers in the room is that they're very focused on the green profile and what is going out of the company. They rarely have a deep understanding of what is going on at the data center. Why? Because it's really technical and they don't have that background. So just by elevating the conversation to these sustainability officers, you can tell them what they should measure and how they should measure that. And you can be sure that that will replicate down to the CIO and the CFO and that immediately your request for proposal going forward. So this one here is really a golden opportunity to take that story, go out and talk to different people in the organization to be relevant and have an impact and make it more easy for you to win that proposal when it gets out. >>Well really solid story on a super important topic. Thanks Tom. Really appreciate your time and taking us through your perspectives. >>Thank you Dave, for the invitation. >>Yeah, you bet. Okay, in a moment we'll be back. To summarize our final thoughts, keep it right there. >>Click by click. The world is changing. We make sense of our world by making sense of data. You can draw more meaning from more data than was ever possible before, so that every thought and every action can build your path to intelligent innovation to change the way the world works. Hitachi Van Tara. >>Okay, thanks for watching the program. We hope you gained a better understanding of how Hitachi Ventura drives customer success with its partners. If you wanna learn more about how you can partner for profit, check out the partner togetherPage@hitachiventera.com and there's a link on the webpage here that will take you right to that page. Okay, that's a wrap for Lisa Martin. This is Dave Valante with the Cube. You a leader in enterprise and emerging tech coverage.

(relaxing music) >> Hello everyone and welcome back to theCUBE's continuing coverage of AWS re:Invent. My name is Savannah Peterson and I am absolutely thrilled for this segment. We are joined by leaders at Cisco AppDynamics as well as Royal Caribbean. The two have been working together for over five years, leveraging full stack observability. We're going to dig in, but first of all please welcome Alice from Royal Caribbean and Greg from Cisco AppDynamics to the show. Hey friends. >> Hi. How are you doing? >> I'm excited, clearly. How are you doing, Greg? >> I'm doing fantastic. Thanks for having me on the show today. >> Hey, it's our, it is absolutely our pleasure. Alice, I have to start with you. I don't think there are too many industries that have gotten as much coverage as cruising has over the last couple of years. You've been working with Royal Caribbean for over a decade so you've seen it through the stormy seas of the pandemic, if you will. What has the last few years and the last few months been like for you? >> You know, it's really been a wild ride. To your point, we were sailing high, and then I don't think any other industry experienced what we did in COVID, that you walked in one day and then that day the whole industry shut down. So it was a big challenge for us. And then as soon as we shut down and we weathered the storm with COVID, then we had what we called our healthy return to service. So as quickly as it stopped, we had to start sailing again. So it's really been a challenge but we're happy to be back on our feet and heading in the right direction now. >> I really hope we can continue the sailing metaphors throughout the course of this interview. And you nailed that for a segment, Alice, I'm so here for it. I want to talk about how you've worked together but I want to give Greg a second to chime in here. So, Greg, you're the executive CTO at Cisco AppDynamics. How have you and the team weathered the last two and a half years? >> Well, you know, it's interesting, the pandemic really brought together an interesting conundrum, right? So on one hand, you had, you know, the consumers, the end users that became very reliant on digital services. They had a function in a way that was very performing, right? So, 84% of the respondents that we had come back through a report called the App Attention Index, came back and said that digital services were really instrumental for them to get back to some level of normalcy. But the interesting part that came about that is that out of those respondents, 60% of them blamed the brand if the application did not work the way they expected it. So they didn't really care about the complex- >> Wow. >> In the back end, right? So when you look at- >> Yeah. >> You look at the shift in the IT department, the IT department had to go out and quickly innovate. Quickly start to introduce new services, which ultimately brought together a sprawl in their technology stack. So, when you're adding to it you're not taking things away, you're continuously growing. So finding that the problems or the root cause of an application issue became more difficult. So that's where, you know, from a Cisco AppDynamics perspective, you know we're one of the leading observability and application performance monitoring tools. So, we help customers like Royal Caribbean to be able to zero in on root cause and ensure that their end users have that best experience. >> It's, I'm smiling as someone who was a former waitress and I can remember the amount of times I was scolded for something that happened that was far out of my control in the complex layers of the kitchen. (Greg laughs) And I think that anyone who's had a poor customer experience while interacting with a brand may or may not intentionally, you know, I think it's actually sometimes very unintentional to your point, get frustrated with said brand. I can imagine that is an experience and a priority that you have at Royal Caribbean, Alice. How has full stack observability played a role in your team's ability to serve the customers and keep your community engaged during this very kind of wobbly time? >> Yeah, you know, we have really worked hard to improve and remove friction from our guest vacation. And we want to keep them on vacation and having a great time. You know, we say we don't really sell a cruise. We sell an experience. So we use AppDynamics to monitor those key applications that our guests are interacting with to ensure that they're having that experience that we expect. You know, we've learned that just because a system or a server says, hey I'm up 99% of the time, that doesn't mean that my guests are experiencing that same type of stability, you know? So once again, we really worked well with AppDynamics. They've partnered with us to ensure that, you know, our guests are getting that vacation experience they're looking for. >> Do you think, just a follow up there, do you think that you would have advanced in the ways that you have working with Cisco AppDynamics and across functions over the last few years, without this crunch? Was necessity the mother of invention for you to any degree? >> You know, I don't think that the crunch brought it on 'cause we, like I said, we started this journey back in 2017. And we're not unlike a lot of companies where we're on this maturity ride where we want to go from being reactive, where our guests are telling us something is broken, to being preventive. Definitely, you know, COVID played into this because I think we learned to do less, you know, more with less. So, you know, it's very hard in the cruise industry. We did take a hit but we were able to use the AppDynamics tools to ensure that our systems were running with having less people also watching those systems. So less eyes on glass, more automation. >> And that's more stability, more credibility, and more transparency is definitely something that we're all looking forward. And it's nice to see that implemented, especially at scale when you're dealing with so many customers from all over the world trying to access your service and wanting that personalized experience. Greg, what does it feel like for you as a leader to hear someone like Alice say how powerful your tool has been in ensuring that customer experience? >> Yeah, that's, you know, it's absolutely fantastic. And especially, you know, Alice is absolutely right. You know, the cruise industry was really, had a very unique challenge in front of them. And I really applaud the folks at Royal Caribbean for stepping up to make sure that when the pandemic eased, so to speak, that the experience to the customer was actually even better, right? So when we were able to work and partner together to make sure that, you know, the user experience is topnotch, the availability's there, the resiliency of their platform is there. So, by working with customers like Royal Caribbean is really one of the shining stars that we can talk about that really helped make a big difference in, you know that post pandemic era to be able to really do what's right for the customer. >> How often are you engaging with customers like Alice as a team? How big is that feedback in your product roadmap? >> Oh, personally, I'm engaged with customers on a daily basis. And I see it across the map from many different industries. And, you know, a lot of folks had different challenges, but the ultimate commonality that I've seen across, you know, multiple industries is that, you know, when we're in that pandemic state, digital services were the only way that their customers were interacting with them. So, you know, when you're looking at a bank or you're looking at, you know, different types of travel agencies and organizations that, you know like Royal Caribbean as well, that really had that opportunity to focus on what's the most valuable thing to them which is user experience. It's a very, very common trend that we saw. And, you know, you see an expedited path of digital transformation happen. And really that's where we partner with, you know, customers like Royal Caribbean and many others across different industries to make sure that the business outcomes were being driven towards the proper direction as well as that, you know, the user experience. And I don't think I can emphasize user experience as being so critically important, anymore than I already have. But it's really one of the most valuable currencies most organizations have. >> One of my favorite lines is community is your first defensible asset. And you know, you can talk about user experience as much as you want on here, at the end of the day. If people aren't having a positive interaction with your brand or your product, it's probably not going to last super long unless it's legacy. And we don't have to go down that rabbit hole today. >> Especially if I can add, there's a lot of competition there. >> Of course. >> Right? There's a lot of competition out there. So if your applications do not perform or your digital services do not perform the end user has the quick ability to just quickly delete and move on. And the same thing with what Alice sees in the cruise industry, you know. You have an opportunity to rise to the top and I really applaud them for taking advantage of that opportunity. >> Yeah. Well, I'm here for both of you cheering each other on. Certainly, the water level rises together. >> That's right. >> Alice, what sort of challenges are you taking on currently that you're able to disclose? What sort of leaps do you think or it doesn't have to be leaps, but what kind of experience are you hoping to continue to enhance for Royal Caribbean customers? >> You know, right now, you know with our current connectivity it's all about managing that bandwidth. You know, we're hoping to go to that state where bandwidth isn't at a high cost. So now we're going to be even able to watch our user interaction more from ship to shore. You know, and we're maybe moving to that area where we're thinking cloud first from a shift. If you think about it, we've got 50 plus data centers floating around the world. So that connectivity is key. Now we're opening up that bandwidth. Now I need to see how the transactions are performing as we come off ship. You know, with that, once again, that cloud first mentality. It's a super exciting time for us. And I really see, you know, AppD is going to play a role in that. >> I love that visual just for a second of 50 data centers with also, surrounded by people having a very wonderful time on board. What a nice thought. I can't say that every data center I've ever been to is as glamorous, fun or sexy as being on a Royal Caribbean ship. However, I hope that we move perhaps in that direction. We were just at Super Computing a few weeks ago and it was great to see all the hardware there. So you never know. What role do you see yourself and the team and Cisco AppDynamics playing in that future for companies like Royal Caribbean, Greg? >> You know, it's really, it's really staying right lockstep with our customers as they move through that digital transformation efforts. The key piece is that we look at it from that full stack view. So we offer full stack observability, which, you know, if you look at the challenges that we want to go after. Traditional IT departments were historically siloed pretty significantly between, you know network and infrastructure, security, app dev. So I mean, ensuring that we can get our customers to be able to have that common view that shows what's the real important pieces across all domains. So when they start moving down the path of digital transformation, that's an opportunity to also revamp how their processes are, the people interact and the technology that they use to be able to deliver the proper business outcomes. So we talk a lot with our customers around full stack observability, but the key part is business context. So if you have a big effort for digital transformation, you're starting to add new services to it. How do you know if it's actually impacting the business in a positive or negative way? So by us implementing the business context to ensure that you understand the investments being made, that you can show to your business leaders, is showing an uptake in the business outcomes you're going after. It's really, really about a strong partnership with our customers. But also ensuring that their business is being positively impacted by our technology to be able to help them really align the teams and be able to have the right desired outcomes. >> I love that Greg and I love that customer first, that community first attitude. It's something that you both share. Final question for the two of you. And I'm going to start with you, Alice, since I suspect you've probably been on more cruises than Greg and I combined. Though I could be making a wild assumption. Where are you cruising to next? >> You know, I just got off a cruise. So next stop, I want to revisit the Galapagos. I think the Galapagos is the best place to go. And if you haven't done it that's absolutely where you should go. >> Oh, it's a beautiful trip. Greg, have you ever done the Galapagos? Is that going to be your next Royal Caribbean cruise? >> I have never done the Galapagos, but that may just have made it to my list. >> Fantastic. Well, I second Alice's endorsement on that. I had the pleasure of going about a decade ago. Very magical place that teaches you a lot about nature. Much like the two of you have taught us very extensively about full stack observability, how it applies to user experience, customer experience and the ocean that I am currently staring at here in Pacifica, California. Alice, thank you so much for joining us from Miami. Greg, to you in Colorado. I hope that you both continue to work in harmony together and that we can all see each other on the friendly seas soon. Thank you all for tuning in to our AWS re:Invent coverage. This is theCUBE. My name's Savannah Peterson. And we look forward to seeing you for our next segment. (relaxing music)

>>Hello everyone and welcome back to The Cube's Continuing coverage of AWS Reinvent. My name is Savannah Peterson and I am absolutely thrilled for this segment. We are joined by leaders at Cisco App Dynamics, as well as Royal Caribbean. The two have been working together for over five years, leveraging full stack observability. We're gonna dig in, but first of all, please welcome Alice from Royal Caribbean and Greg from Cisco App, app Dynamics to the show. Hey friends. >>Hi. How are you doing? >>I'm excited, clearly. How are you doing, Greg? >>I'm doing fantastic. Thanks for having me on the show today. >>Hey, it's our, it is absolutely our pleasure. Alice, I have to start with you. I don't think there are too many industries that have gotten as much coverage as cruising has over the last couple of years. You've been working with Royal Caribbean for over a decade, so you've seen it through the stormy seas of the pandemic, if you will. What has the last few years and the last few months been like for you? >>You know, it's, it's really been a wild ride. To your point, we were sailing high and then I don't think any other industry experience what we did in Covid, that you walked in one day and then that day the whole industry shut down. So it was a, it was a big challenge for us. And then as soon as we shut down and we weathered the storm with Covid, then we have what we called our healthy and return to service. So as quickly as it stopped, we had to start sailing again. So it's, it's really been a challenge, but we're happy to be back on our feet and heading in the right direction now. >>I, I really hope we can continue the sailing metaphors throughout the course of this interview. And you, you nailed that for a segment. Alice, I'm, I'm, I'm so, I'm so here for it. I, I, I wanna talk about how you've worked together, but I wanna give Greg a second to chime in here. So Greg, you're the executive CTO at Cisco App Dynamics. How, how have you and the team, whether the last two and a half years? >>Well, you, you know, it's interesting, the, the pandemic really brought together an interesting conundrum, right? So on, on one hand, you had, you know, the, the, the consumers, the end users that became very reliant on digital services. They had a function in a way that was very performing, right? So, 84% of the respondents that we had come back through a report called the App Attention Index, came back and said that digital services were, were really instrumental for them to, to get back to some level of normalcy. But the interesting part that came about that is that out of those respondents, 60% of them blame the brand if the, if the application did not work the way they expected it. So they didn't really care about the, it's in the back end, right? So when you look at, yeah, you look at the shift in the IT department, the IT department had to go out and, and quickly innovate, quickly start to introduce new services, which ultimately brought together a, a sprawl in their technology stack. So when you're adding to it, you're not taking things away, you're continuously growing. So finding that that, that the problems or the, the root cause of an application issue became more difficult. So that's where, you know, from an app, Cisco AppDynamics perspective, you know, we're one of the leading observability and app application performance monitoring tools. So we help customers like Ro Caribbean to be able to zero in on root cause and ensure that their end users have that best experience. It's, >>It's, it's, I I'm smiling as someone who was a, a former waitress and I can remember the amount of times I was scolded for something that happened that was far out of my control and the complex layers of the kitchen. And I think that, that anyone who's, who's had a, a poor customer experience while interacting with a brand may or may not intentional, I think it's actually sometimes very unintentional to your point, get frustrated with said brand. I can imagine that is an experience and a priority that you have at Royal Caribbean. Alice, how, how has Full Stack Observability played a role in your, in your team's ability to, to serve the customers and your, and keep your community engaged during this, this very kind of wobbly time? >>Yeah, you know, we have, have really worked hard to improve and remove friction from our guest vacation. And we wanna keep them on vacation and having a great time. You know, we say we don't really sell a cruise. We sell an experience. So we use App AppDynamics to monitor those key applications that our guests are interacting with to ensure that they're having that experience that we expect, you know, we've learned that just because a system or a server says, Hey, I'm up 99% of the time, that doesn't mean that my guests are experiencing that same type of stability, you know? So once again, we really worked well with App Dynamics. They've partnered with us to ensure that, you know, our guests are getting that vacation experience they're looking for. >>Do you think, just a follow up there, do you think that you would have advanced in the ways that you have working with Cisco App Dynamics and across functions over the last few years without this crunch, was necessity the mother of invention for you to any degree? >>You know, I don't, I don't think that the Crunch brought it on cuz we, like I said, we started this journey back in 2017 and we're not unlike a lot of companies where we're on this maturity ride where we wanna go from being reactive, where our guests are telling us something is broken to being preventive. Definitely, you know, COVID played into this because I think we learned to do less, you know, more with less. So, you know, we, you know, it's very hard in the cruise industry. We did take a hit, but we were able to use the app dynamics tools to ensure that our systems were running with having less people also watching those systems. So less eyes on glass, more automation, >>And that's a more, with more, more stability, more credibility, and more transparency is definitely something that we're all looking forward. And, and it's nice to see that implemented, especially at scale when you're dealing with so many customers from all over the world trying to access your service and, and wanting that personalized experience. Greg, what does it feel like for you as a leader to hear someone like Alice say how powerful your tool has been in ensuring that customer experience? >>Yeah, that's, you know, it's absolutely fantastic and especially, you know, Alice is absolutely right. You know, the, the, the cruise industry was really, had a very unique challenge in front of them, and I, I really applaud the folks at Royal Caribbean for stepping up to make sure that when the pandemic eased, so to speak, that they, that the experience to the customer was actually even better, right? So when we were able to work and partner together to make sure that, you know, the, the, the user experience is topnotch, the availability is there, the, the, the, the resiliency of their platform is there. So by, by working with customers like Royal CRI and is really one of the, the, the shining stars that we can talk about that really help make a big difference in, you know, that post pandemic era to be able to really do what's right for the customer. >>How often are you engaging with customers like Alice as a team? How big is that feedback in your product roadmap? >>Oh, personally, I, I'm, I'm engaged with customers on a daily basis and I see it fr across the map from many different industries. And, you know, a lot of folks had different challenges, but the, the ultimate commonality that I've seen across, you know, multiple industries is that, you know, when you, when we're in that pandemic state, digital services were the only way that they, their customers were interacting with, with them. So, you know, when you, when you're looking at a, at a bank or you're looking at a, you know, different types of travel agencies and organizations that, you know, like rural Caribbean as well, that, that really had that opportunity to, to focus on what's the most valuable thing to them, which is user experience. It's a very, very common common trend that we saw. And, you know, you see an expedited path of, of, of digital transformation happen. And really that's where we partner with, you know, customers like Royal Caribbean and, and many others across different industries to make sure that that, that the, the business outcomes were being driven towards the, the proper direction. As well as that, you know, the, the user experience, and I don't think I can emphasize user experience as being so critically important anymore than I've already have, but it's really the, one of the most valuable currencies most organizations have. >>I, one of my favorite lines is, is community is your first defensible asset. And you know, I, you can, you can talk about user experience as much as you want on here. At the end of the day, if people aren't having a positive interaction with your brand or your product, it's probably not going to last super long unless it's legacy. And we won't have to go down that rabbit hole today, >>Especially if I can add there's a lot of competition there. Course, right? There's a lot of competition out there. So if your applications do not perform, or your digital services do not perform, the end user has the quick ability to just quickly delete and move on. And, and the same thing with, with what Alice sees in the, in the cruise industry, you know, you have an opportunity to rise to the top and I, I really applaud them for taking advantage of that, that opportunity. Community. >>Community. Yeah. Well, I'm, I'm here for both of you cheering each other on certainly the, the water level rises together. That's >>Right. Alice, >>What sort of, what sort of challenges are you taking on currently that you're able to disclose? What, what sort of leaps do you think, or doesn't have to be leaps, but what, what kind of experience are you hoping to continue to enhance for Royal Caribbean customers? >>So I think, you know, one of our big challenges that we've, you know, we've announced that we do have a relationship with starlink, so that's going to improve our satellite connectivity, and it really is a game changer for our industry. It's very exciting and, and, but it puts the, it puts the user back in the forefront once again. You know, right now, you know, with our current connectivity, it's all about managing that bandwidth. You know, we're hoping to go to that state where bandwidth isn't at a high cost, so now we're gonna be even able to watch our user interaction more from ship to shore, you know, and you're, and you're, we're maybe moving to that area where we're thinking cloud first from a shift. If you think about it, we've got 50 plus data centers floating around the world, so that connectivity is key. Now we're opening up that bandwidth now I need to see how that, how the transactions are performing as we come off ship. You know, with that, once again, that cloud first mentality, it's a super exciting time for us. And I really see, you know, AppD is gonna play a role in that. >>I, I I, I love that visual just for a second of 50 data centers with also surrounded by people having a very wonderful time on board. What a, what a nice spot. I, I can't say that every data center I've ever been to is, is glamorous, fun or sexy as being on a Royal Caribbean ship. However, I, I hope that we move perhaps in that direction. We were just at super computing a few weeks ago and it was great to see all the hardware there. So you never know. What role do you see yourself in the team and, and Cisco app Dynamics playing in that future for companies like Royal Caribbean, Greg? >>You know, it's really, it's really staying right lockstep with our customers as they move through that digital transformation efforts. The key piece is that we look at it from that full stack view. So we offer full stack observability, which, you know, if you look at the challenges that we want to go after is traditional IT departments were historically siloed pretty significantly between, you know, network and infrastructure security app dev. So ensuring that we can get our customers to, to be able to have that common view that shows what's the real important pieces across all domains. So when they start moving down the path of digital transformation, that's an opportunity to also revamp how their processes are that people interact and the technology that they use to be able to deliver the proper business outcomes. So we talk a lot with our customers around full stack observability, but the key part is business context. >>So if you have a big effort for digital transformation, you're starting to add new services to it, how do you know if it's actually impacting the business in a positive or negative way? So by us implementing the, the business context to ensure that you understand the investments being made that you can show to your business leaders is showing an uptick and the business outcomes you're, you're going after, it's really, really about a strong partnership with our customers, but also ensuring that their business is being positively impacted by our technology to be able to help them really align the teams and be able to have the right desired outcomes. >>I love that Greg and I love that customer first. That community first attitude, it's something that you both share. Final question for the two of you, and I'm gonna start with you, Alice, since I suspect you've probably been on more cruises than Greg and I combined, though I could be making a wild assumption. Where are you cruising to next? >>You know, I just got off the cruise, so next up I wanna revisit the Galapagos. I think the Galapagos is the best place to go, and if you haven't done it, that's absolutely where you should go. >>Oh, it's a beautiful trip. Greg, have you ever done the Galapagos? Is that gonna be your next Royal Caribbean cruise? >>I have never done the Galapagos, but I may just have made it to my list. >>Fantastic. Well, I second Alice's endorsement on that. I, I had the pleasure of going about a decade ago. Very magical place that teaches you a lot about nature, much like the two of you have taught us very extensively about full stack absorbability, how it applies to user experience, customer experience, and the ocean that I am currently staring at here in Pacifica, California. Alice, thank you so much for joining us from Miami Greg to you in Colorado. I hope that you both continue to work in harmony together and that we can all see each other on the friendly sees soon. Thank you all for tuning in to our AWS reinvent coverage. This is the cube. My name's Savannah Peterson, and we look forward to seeing you for our next segment.

(upbeat music) >> Hey everyone. Welcome to the AWS partner showcase. This is season one, episode three. And I'm your host, Lisa Martin. I've got two great guests here with me to talk about Women in Tech. Hillary Ashton joins us, the chief product officer at Teradata, and Danielle Greshock is back with us, the ISV PSA director at AWS Ladies. It's great to have you on the program talking through such an important topic. Hillary, let's go ahead and start with you. Give us a little bit of an intro into you, your background and a little bit about Teradata. >> Yeah, absolutely. So I'm Hillary Ashton. I head up the products organization. So that's our engineering, product management, officer of the CTO team at Teradata. I've been with Teradata for just about three years and really have spent the last several decades, if I can say that in the data and analytics space. I spent time really focused on the value of analytics at scale, and I'm super excited to be here at Teradata. I'm also a mom of two teenage boys. And so as we talk about women in tech, I think there's lots of different dimensions and angles of that. At Teradata we are partnered very deeply with AWS and happy to talk a little bit more about that throughout this discussion as well. >> Excellent. A busy mom of two teen boys. My goodness. I don't know how you do it. Let's now look at Teradata's views of diversity, equity and inclusion. It's a topic that's important to everyone but give us a snapshot into some of the initiatives that Teradata has there. >> Yeah, I have to say, I am super proud to be working at Teradata. We have gone through a series of transformations but I think it starts with culture and we are deeply committed to diversity, equity and inclusion. It's really more than just a statement here. It's just how we live our lives. And we use data to back that up. In fact, we were named one of the world's most ethical companies for the 13th year in a row. And all of our executive leadership team has taken an oath around DE&I, that's available on LinkedIn as well. So in fact, our leadership team reporting into the CEO is just about 50/50 men and women which is the first time I've worked in a company where that has been the case. And I think as individuals, we can probably appreciate what a huge difference that makes in terms of not just being a representative, but truly being on a diverse and equitable team. And I think it really improves the behaviors that we can bring to our office. >> There's so much value in that. It's I impressive to see about a 50/50 at the leadership level. That's not something that we see very often. Tell me how you, Hillary, how did you get into tech? Were you an engineering person by computer science or did you have more of a zigzaggy path to where you are now? >> I'm going to pick door number two and say more zigzaggy. I started off thinking that, I started off as a political science major or a government major and I was probably destined to go into the law field but actually took a summer course at Harvard, I did not go to Harvard, but I took a summer course there and learned a lot about multimedia and some programming. And that really set me on a trajectory of how data and analytics can truly provide value and outcomes to our customers. And I have been living that life ever since I graduated from college. So I was very excited and privileged in my early career to work in a company where I found after my first year that I was managing kids, people who had graduated from Harvard Business School and from MIT Sloan School. And that was super crazy 'cause I did not go to either of those schools but I sort of have always had a natural knack for how do you take technology and the really cool things that technology can do, but because I'm not a programmer by training, I'm really focused on the value that I'm able to help organizations really extract value from the technology that we can create, which I think is fantastic. >> I think there's so much value in having a zigzag path into tech. You bring... Danielle, you and I have talked about this many times, you bring such breadth and such a wide perspective that really is such a value add to teams. Danielle, talk to us from AWS's perspective about what can be done to encourage more young women to get, and underrepresented groups as well to get into STEM and stay. >> Yeah, and this is definitely a challenge as we're trying to grow our organization and kind of shift the numbers. And the reality is, especially with the more senior folks in our organization, unless you bring folks with a zigzag path, the likelihood is you won't be able to change the numbers that you have. But for me, it's really been about looking at that, the folks who are just graduating college, maybe in other roles where they are adjacent to technology and to try to spark their interest and show that, yes, they can do it because oftentimes it's really about believing in themselves and realizing that we need folks with all sorts of different perspectives to kind of come in to be able to help really provide both products and services and solutions for all types of people inside of technology which requires all sorts of perspectives. >> Yeah, the diverse perspectives. There's so much value and there's a lot of data that demonstrates how much value, revenue impact organizations can make by having diversity especially at the leadership level. Hillary, let's go back to you. We talked about your career path. You talked about some of the importance of the focus on DE&I at Teradata, but what do you think can be done to encourage, sorry, to recruit more young women and under represented groups into tech, any carrots there that you think are really important that we need to be dangling more of? >> Yeah, absolutely. And I'll build on what Danielle just said. I think the bringing in diverse understandings of customer outcomes, I mean, we've really moved from technology for technology's sake. And I know AWS and Entirety have had a lot of conversations on how do we drive customer outcomes that are differentiated in the market and really being customer-centric. And technology is wonderful. You can do wonderful things with it. You can do not so wonderful things with it as well but unless you're really focused on the outcomes and what customers are seeking technology is not hugely valuable. And so I think bringing in people who understand voice of customer, who understand those outcomes and those are not necessarily the folks who are PhD in mathematics or statistics, those can be people who understand a day in the life of a data scientist or a day in the life of a citizen data scientist. And so really working to bridge the high impact technology with the practical kind of usability, usefulness of data and analytics in our cases, I think is something that we need more of in tech and sort of demystifying tech and freeing technology so that everybody can use it and having a really wide range of people who understand not just the bits and bites and and how to program, but also the value and outcomes that technology through data and analytics can drive. >> Yeah. You know, we often talk about the hard skills but the soft skills are equally, if not more important that even just being curious, being willing to ask questions being not afraid to be vulnerable, being able to show those sides of your personality. I think those are important for young women and underrepresented groups to understand that those are just as important as some of the harder technical skills that can be taught. >> That's right. >> What do you think about from a bias perspective, Hillary, what have you seen in the tech industry and how do you think we can leverage culture as you talked about to help dial down some of the biases that are going on? >> Yeah. I mean, I think first of all, and there's some interesting data out there that says that 90% of the population, which includes a lot of women have some inherent bias in their day to day behaviors when it comes to women in particular. But I'm sure that that is true across all kinds of of diverse and underrepresented folks in the world. And so I think acknowledging that we have bias and actually really learning what that can look like, how that can show up, we might be sitting here and thinking, oh, of course I don't have any bias. And then you realize that as you learn more about different types of bias that actually you do need to kind of account for that and change behaviors. And so I think learning is sort of a fundamental grounding for all of us to really know what bias looks like, know how it shows up in each of us, if we're leaders, know how it shows up in our teams and make sure that we are constantly getting better. We're not going to be perfect anytime soon, but I think being on a path to improvement to overcoming bias is really critical. And part of that is really starting the dialogue, having the conversations, holding ourselves and each other accountable when things aren't going in a copesthetic way, and being able to talk openly about that felt like maybe there was some bias in that interaction and how do we make good on that? How do we change our behavior fundamentally. Of course, data and analytics can have some bias in it as well. And so I think as we look at the technology aspect of bias, looking at at ethical AI I think is a really important additional area. And I'm sure we could spend another 20 minutes talking about that, but I would be remiss if I didn't talk more about sort of the bias and the opportunity to overcome bias in data and analytics as well. >> Yeah. The opportunity to overcome it is definitely there, you bring up a couple of really good points, Hillary. It starts with awareness. We need to be aware that there are inherent biases in data in thought. And also to your other point, hold people accountable, ourselves, our teammates that's critical to being able to dial that back down. Danielle, I want to get your perspective on your view of women in leadership roles. Do you think that we have good representation or we still have work to do in there? >> I definitely think in both technical and product roles we definitely have some work to do. And when I think about our partnership with Teradata, part of the reason why it's so important is, Teradata solution is really the brains of a lot of companies, what they differentiate on, how they figure out insights into their business. And it's all about the product itself and the data, and the same is true at AWS. And we really could do some work to have some more women in these technical roles as well as in the product, shaping the products, just for all the reasons that we just kind of talked about over the last 10 minutes in order to move bias out of our solutions and also to just build better products and have better outcomes for customers. So I think there's a bit of work to do still. >> I agree. There's definitely a bit of work to do and it's all about delivering those better outcomes for customers at the end of the day. We need to figure out what the right ways are of doing that and working together in a community. We've had obviously a lot had changed in the last couple of years. Hillary, what have you seen in terms of the impact that the pandemic has had on this status of women in tech? Has it been a pro, is silver lining, the opposite? What are you seeing? >> Yeah, I mean, certainly there's data out there that tells us factually that it has been very difficult for women during COVID-19. Women have dropped out of the workforce for a wide range of reasons. And that I think is going to set us back all of us, the Royal us or the Royal we back years and years. And it's very unfortunate because I think we're at a time when we're making great progress and now to see COVID setting us back in such a powerful way I think there's work to be done to understand how do we bring people back into the workforce? How do we do that understanding work life balance better, understanding virtual and remote working better. I think in the technology sector we've really embraced hybrid virtual work and are empowering people to bring their whole selves to work. And I think if anything, these Zoom calls have, both for the men and the women on my team. In fact, I would say much more so for the men on my team, we're seeing more kids in the background, more kind of split childcare duties, more ability to start talking about other responsibilities that maybe they had, especially in the early days of COVID where maybe day cares were shut down and maybe a parent was sick. And so we saw quite a lot of people bringing their whole selves to the office which I think was really wonderful. Even our CEO saw some of that. And I think that that really changes the dialogue. It changes it to maybe scheduling meetings at a time when people can do it after daycare drop off and really allowing that both for men and for women, makes it better for women overall. So I would like to think that this hybrid working environment and that this whole view into somebody's life that COVID has really provided for, probably for white collar workers, if I'm being honest for people who are at a better point of privilege, they don't necessarily have to go into the office every day. I would like to think that tech can lead the way in coming out of the old COVID, I don't know if we have a new COVID coming, but the old COVID and really leading the way for women and for people to transform how we do work, leveraging data and analytics but also overcoming some of the disparities that exist for women in particular in the workforce. >> Yeah, I think there's, like we say, there's a lot of opportunity there and I like your point of hopefully tech can be that guiding light that shows us this can be done. We're all humans at the end of the day. And ultimately, if we're able to have some sort of work life balance, everything benefits. Our work, we're more productive, higher performing teams impacts customers. There's so much value that can be gleaned from that hybrid model and embracing for humans. We need to be able to work when we can. We've learned that you don't have to be in an office 24/7 commuting crazy hours, flying all around the world. We can get a lot of things done in ways that fit people's lives rather than taking command over it. I want to get your advice, Hillary, if you were to talk to your younger self, what would be some of the key pieces of advice you would say? And Danielle and I have talked about this before, and sometimes we would both agree on like, ask more questions, don't be afraid to raise your hand, but what advice would you give your younger self and that younger generation in terms of being inspired to get into tech? >> Oh, inspired in being in tech. I think looking at technology as, in some ways I feel like we do a disservice to inclusion when we talk about STEM, 'cause I think stem can be kind of daunting, it can be a little scary for people, for younger people. When I go and talk to folks at schools, I think STEM is like, oh, all the super smart kids are over there. They're all, like maybe they're all men. And so it's a little intimidating. And STEM is actually, especially for people joining the workforce today, it's actually how you've been living your life since you were born. I mean, you know STEM inside and out because you walk around with a phone and you know how to get your internet working and like that is technology fundamentally. And so demystifying STEM as something that is around how we actually make our our lives useful and how we can change outcomes through technology, I think is maybe a different lens to put on it. And there's absolutely, for hard scientists, there's absolutely a great place in the world for folks who want to pursue that, and men and women can do that. So I don't want to be setting the wrong expectations but I think STEM is very holistic in the change that's happening globally for us today across economies, across global warming, across all kinds of impactful issues. And so I think everybody who's interested in some of that world change can participate in STEM. It just may be through a different lens than how we classically talk about STEM. So I think there's great opportunity to demystify STEM. I think also what I would tell my younger self is choose your bosses wisely. And that sounds really funny. That sounds like inside out almost but I think choose the person that you're going to work for in your first five to seven years. And it might be more than one person, but be selective. Maybe be a little less selective about the exact company or the exact title. I think picking somebody that, we talk about mentors and we talk about sponsors and those are important, but the person you're going to spend in your early career, a lot of your day with, who's going to influence a lot of the outcomes for you. That is the person that you, I think want to be more selective about because that person can set you up for success and give you opportunities and set you on course to be a standout or that person can hold you back and that person can put you in the corner and not invite you to the meetings and not give you those opportunities. And so we're in an economy today where you actually can be a little bit picky about who you go and work for. And I would encourage my younger self, I just lucked out actually, but I think that my first boss really set me up for success, gave me a lot of feedback and coaching. And some of it was really hard to hear but it really set me up for the path that I've been on ever since. So that would be my advice. >> I love that advice. It's brilliant. And I think it, choose your bosses wisely, isn't something that we primarily think about. I think a lot of people think about the big name companies that they want to go after and put on a resume, but you bring up a great point. And Danielle and I have talked about this with other guests about mentors and sponsors. I think that is brilliant advice, and also more work to do to demystify STEM. But luckily we have great female leaders like the two of you helping us to do that. Ladies, I want to thank you so much for joining me on the program today and talking through what you're seeing in DE&I, what your companies are doing and the opportunities that we have to move the needle. Appreciate your time. >> Thank you so much. Great to see you, Danielle. Thank you, Lisa. >> Nice to see you. >> My pleasure. For my guests, I'm Lisa Martin. You're watching the AWS partner showcase season one, episode three. (upbeat music)

>> Announcer: From around the globe, it's theCUBE! With digital coverage of IBM Think 2021. Brought to you by IBM. >> Well welcome everyone as theCUBE continues our IBM Think series. It's a pleasure to have you with us here on theCUBE. I'm John Walls, and we're joined today by Brian Loveys who is the Director of Offering Management for Customer and Employee Care Applications at IBM in the Data and AI Division. So, Brian, thanks for joining us from Ottawa, Canada. Good to see you today. >> Yeah, great to be here, John. And looking forward to the session today. >> Which, by the way, I've learned Ottawa are the home of the world's largest ice skating rink. I doubt we get into that today, but it is interesting food for thought. So, Brian, first off, let's just talk about the AI landscape right now. I know IBM obviously very heavily invested in that. Just in terms of how you see this currently in terms of enterprise adoption, what people are doing with it, and just how you would talk about the state of the industry right now. >> You know, it's a really interesting one, right? I think if you look at it, you know, different companies, different industries, frankly, are at different stages of their AI journey, right? I think for me personally, what was really interesting was, and we're all going through the pandemic right now, but last year with COVID-19 in the March timeframe, it was really interesting to see the impact, frankly, in the space that I play predominantly in around customer care, right? When the pandemic hit, immediately call centers, contact centers got flooded with calls, right? And so it created a lot of problems for organizations. But what was interesting to me is it accelerated a lot of adoption of AI to organizations that typically lag in technology, right? So if you think about public sector, right, that was one area that got hit very, very hard with questions and those types of things, and trying to, you know, communicate out information. So it was really interesting to see those organizations, frankly, accelerate really, really quickly, right? And if you actually, you know, talk to those organizations now, I think one of the most interesting things to me in thinking about it and talking to them now is like, hey, you know, we can do this, right? AI is really not that complicated. It can be simplified, we can take advantage of it and all of those types of things, right? So I think for me, you know, I kind of see different industries at sort of different levels, but I think with COVID in particularly, you know, and frankly not just COVID, but even digital transformation alongside COVID is really driving a lot of AI in an accelerated manner. The other thing that I'll kind of talk to a little bit here is I still think we're very much in the early innings of this, right? There's a tremendous opportunity to innovate in this space. And I think we all know that, you know, data is continually being created every single day. And as more people become even more digitalized, there's more and more data being created. Like it's how do you start to harness that data more effectively, right, in your business every day. And frankly, I think we're just scratching the surface on it. And I think tremendous amount of opportunity as we move forward. >> Yeah, you really raised an interesting point which I hadn't thought about in terms of, we think about disruptors, we think about technology being a disruptor, right, but in this case it was purely, or really largely environment, you know, that was driving this disruption, right, forcing people to make these adoption moves and transitions maybe a little quicker than they expected. Well, so because of that, because maybe somebody had to speed up their timetable for deployments and what have you, what kind of challenges have they run into then, where, because as you describe it, it's not been the more organic kind of decision-making that might be made sometimes, situation dictated it. So what have you seen in terms of challenges, you know, barriers, or just a little more complexity, perhaps, for some people who're just now getting into the space because of the environment you were talking about? >> I think a lot of this is like, you know, people don't know where to get started, right, a lot of the time, or how AI can be applied. So a lot of this is going to be about education in terms of what it can and cannot do. And then it all depends on the use cases you're talking about, right? So if I think about, you know, building out machine learning models and those types of things, right, you know, the set of challenges that people will typically face in these types of things are, you know, how do I, you know, collect all the data that I need to go build these models, right? How do I organize that data? You know, how do I get the skillsets needed to ultimately, you know, take advantage of all of that data to actually then apply to where I need it in my business, right? So a lot of this is, you know, people need to understand those concepts or those pieces to ultimately be successful with AI. And you know, what IBM is doing right here, and I'll kind of, this will be a key theme throughout this conversation today is, you know, how do you sort of lower the time to value to get there across that spectrum, but also, you know, frankly, the skills required along the way as well? But a lot of it is like, people don't know what they don't know at the end of the day. >> Well, let me ask you about your AI play then. A lot of people involved in this space, as you well know, competition's pretty fierce and pretty widespread. There's a deep bench here. In terms of IBM though, what do you see as kind of your market differentiator then? You know, what do you think sets you apart in terms of what you're offering in terms of AI deployments and solutions? >> No, that's a great question. I think it's a multifaceted answer, frankly. The first thing I'll kind of talk through a little bit, right, is really around our platform and our framework, right? We kind of refer to as our AI ladder, but it's really an integrated, you know, sort of cohesive platform for companies around the journey to AI, right? So kind of what I was mentioning a bit earlier, right? If you think about, you know, AI is really about supplying the right data into AI, and then being able to infuse it to where you need it to go, right? So to do that, you need a lot of the underlying information architecture to do that, right? So you need the ability to collect the data. You need the ability to organize the data. You need the ability to build out these models or analyze the data, right? And then of course you need to be able to infuse that AI wherever you need it to be, right? And so we have a really nice integrated platform that frankly can be deployed on any cloud, right, so we get the flexibility of that deployment model with that integrated platform. And if you think about it, we also have built, right, you know, sort of these industry-leading AI applications that sit on top of that platform and that underlying infrastructure, right? So Watson Assistant, right, our conversational AI which we'll talk probably a little bit more on this conversation, right? Watson Discovery focused on, you know, intelligent document processing, right, AI search type applications. We've got these sort of market-leading applications that sit on top, but there's also other things, right? Like we have a very, very strong research arm, right, that continues to invest and funnel innovations into our product platform and into our product portfolio, right? I think many people are aware of Project Debater we took on some of the top debaters in the world, right? But research ultimately is very much tied, right, and even, you know, some of the teams that I work with on the ground, we've got them tied directly into the squads that build these products, right? So we have this really big strong research arm that continues to bring innovation around AI and around other aspects into that product portfolio. But it's not just- >> I'm sorry go ahead, please. >> Go ahead, sorry. >> No, no, you go, (laughs) I interrupted, you go ahead. >> Don't worry, I was just going to say, the other two things I'll say like, you know, I'm saying this right, but we've got a lot of sort of proof points in around it, right, so if you talk about the scale, right, the number of customers, the number of case studies, the number of references across the board, right, in around AI at IBM it is significant, right? And not only that, but we've got a lot of, sort of I'll say industry and third-party industry recognition, right? So think about most people are aware of sort of Gartner Magic Quadrants, right, and we're the leader almost across the board, right, or a leader across the board. So, you know, cloud AI developer service, insight engines, machine learning, go down the line. So, you know, if you don't trust me, there's certainly a lot of third party validation around that as well, if that makes sense. >> Yeah, sure does. You know, we hear a lot about conversational AI and, you know, with online chat bots and voice assistance, and a myriad applications in that respect. Let's talk about conversational right now. Some people think is a little narrow, but yet there appears to be a pretty broad opportunity at the same time. So let's talk about that conversational AI element to what you're talking about at IBM and how that is coming into play. And perhaps is a pretty big growth sector in this space. >> Yeah, I think, again, I talk about scratching the surface, early innings, you'll see that theme a lot too. And I think this is another area around that, right? So, listen, let's talk about the broader side. Let's first talk about where conversational AI is typically applied, right? So you see it in customer service. That's the obvious place where I've seen the most deployments in. But if you think about, it's not just really around customer service, right? There's use cases around sales and marketing. You can think about, you know, lead qualification for example, right. You know, I'm on a website, how can I get information about a product or service? How can I automate some of that information collection, answering questions, how can I schedule console? All those things can be automated using, right, conversational AI, but organizations don't want these sort of points solutions across the customer journey. What they're ultimately looking for is a single assistant to kind of, you know, front that particular customer. So what if I do come on from a lead qual perspective, but really I'm not there for lead qual, I'm actually a customer, and I want to get a question answered, right? You don't want to have these awkward starts and stops with organizations, right? So on the customer side where we see the conversational AI going is really sort of covering that whole gambit in terms of that customer journey, right? And it's not just the customer journey, but you also want to be across channels, right? So you can imagine not just, you know, the website and the chat on the website, but also, right, across your messaging channels, across your phone, right? And not just that, but you also want to be able to have a really nice experience around, hey maybe I'm on a phone call with some automation, but I need to be able to hand them off to a digital play, right? Maybe that's easier to sign up for a particular offer, or do some authentication, or whatever it might be, right? So to sort of be able to switch between the channels is really, really going to become more important in terms of a seamless experience as you do kind of go through it, right- >> So let's talk about customers- >> Oh, go ahead sir. >> Yeah, you talked about customers a little bit, and you mentioned case studies, but I hope we can get into some specifics, if you can give us some examples about people, companies with whom you've worked and some success that you've had in that respect. And I think maybe the usual suspects come to mind. I think about finance, I think about healthcare, but you said, "Hey buddy, but customer call issues, you know, service centers, that kind of thing would certainly come into play," but can you give us an idea or some examples of deployments and how this is actually working today? >> Oh, absolutely, right? So I think you were kind of mentioning, you were talking about sort of industries that are relevant, right? So, you know, the ones that I think are most relevant that we've seen are the ones with the biggest sort of consumer side of it, right? So clearly in financial services, banks, insurance are clearly obvious ones. Telecommunication, retail, healthcare, these are all sort of big industries with a lot of sort of customers coming in, right? And so you'll see different use cases in those industries as well, right? So the obvious one, we've got a really good client, Royal Bank of Scotland, they've now changed their name to NatWest in Scotland. So they started out with customer service, right? So dealing with personal banking questions through their website. What's interesting, and you'll see this with a lot of these use cases is they will start small, right, with a single use case, but they'll start to expand from there. So for example, NatWest, right, they're starting with personal banking, but they're now expanding to other areas of the business across that customer journey, right? So that's a great example of where we've seen it. Cardinal Health, right, because we're not dealing with customers in terms of external customers, but dealing with internal customers, right, from an IT help desk standpoint. So it's not always external customers. Oftentimes, frankly, it can be employees, right? So they are using it through an IDR system, right? So through over the phone, right, so I can call, instead of getting that 1-800 number, I'm going to get a nice natural language experience over the phone to help employees with common problems that they have with their help desk. So, and they started really, really small, right? They started with, you know, simple things like password resets, but that represented a tremendous amount of volume that ultimately hit at their call centers. So NatWest is a great example. CIBC, another bank in Canada, Toronto, is a great example. And the nice thing about what CIBC is doing and they're a big, you know, we have four big banks here in Canada. What CIBC do is really focusing a lot on the transactional side. So making it really easy to do interact transfers or send money, or all those types of things, or check your balance or whatever it might be. So putting a nice, simple interface on some of those common, transactional things that you would do with a bank as well. >> You know, before I let you go, I'd like to hit just a buzzword we hear a lot of these days, natural language processing, NLP. All right, so NLP, define that in terms of how you see it and how is it being applied today? Why does NLP matter, and what kind of differences is it making? >> Wow, natural language processing is a loaded term as a buzzword, I completely agree. I mean, listen, at the 50,000 foot level, natural language processing is really about understanding language, right? So what do I mean by that? So let's use the simple conversational example we just talked about. If somebody's asking about, you know, "I'd like to reset my password," right? You have to be able to understand, well what is the intent behind what that user is trying to do, right? They're trying to reset a password, right? So being able to understand that inquiry that user has that's coming in and being able to understand what the intent is behind it. That's sort of one key aspect of natural language processing, right? What is the intent or the topic around that paragraph or whatever it might be. The other sort of key thing around natural language processing, the importance of extracting certain things that you need to know. And again, using the conversational AI side, just for a minute, to give a simple example. If I said, "You know what, I need to reset my password." I know what the intent is, I want to reset a password, but, right, I don't know which password I'm trying to reset. Right, and so this is where sort of you have to be able to extract objects, and we call them entities a lot of the time and sort of the (indistinct) or lingo. But you got to be able to extract those elements. So, you know, I want to reset my ATM password. Great, right, so I know what they're trying to do, but I also need to extract that it's the ATM password that I'm trying to do. So that's one sort of key angle, natural language processing, and there's a lot of different AI techniques to be able to do those types of things. I'll also tell you though, there's a lot around the content side of the fence as well. So you can imagine how like a contract, right, and there were thousands of these contracts, and some of your terms may change. You know, how do you know, out of those thousands of contracts where the problems are, where I need to start looking, right? So another sort of key area of natural language processing is looking at the content itself, right? Can I look at these contracts and automatically understand that this is an indemnity clause, right? Or this is an obligation, right? Or those types of things, right, and being able to sort of pick those things out, so that I can help deal with those sort of contract-processing things. So that's sort of a second dimension. The third dimension I'll kind of give around this is really around, you can think about extracting things like sentiment, right? So we talked about, you know, extracting objects and nouns, and those types of things, but maybe I want to know in an analytics use case with customers, you know, what is the sentiment and, you know, analyzing social media posts or whatever it might be, what's the sentiment that people have around my product or service. So natural language process, if you think about it at the real high level is really about how do I understand language, but there's a variety of sort of ways to do that, if that makes sense. >> Yeah, no sure, and I think there are a lot of people out there saying, "Yeah, the sooner we can identify exasperation (laughs) the better off we're going to be, right, in handling the problems." So, it's hard work, but it's to make our lives easier, and congratulations for your fine work in that space. And thanks for joining us here on theCUBE. We appreciate the time today, Brian. >> Thank you very much. >> You bet, Brian Loveys, he's talking to us from IBM, talking about conversational AI and what it can do for you. I'm John Walls, thanks for joining us here on theCUBE. (upbeat music) ♪ Dah, deeah ♪ ♪ Dah, dee ♪ (chimes ringing)

>>from >>Around the globe. It's the cube with digital coverage of IBM think 2021 brought to you by IBM >>Well welcome everyone is the cube continues or IBM Thanks series. It's a pleasure to have you with us here on the cube. I'm john walls and we're joined today by brian loves who is the director of offering management for customer and employee care applications in the at IBM in the data and AI division. So brian, thanks for joining us from Ottawa Canada, good to see you today. >>Yeah, great to be here john I'm looking forward to the session today >>which by the way I've learned Ottawa is the home of the world's largest ice skating rink. I doubt we'll get into that today, but it is interesting food for thought. Uh so brian first off, let's just talk about um the Ai landscape right now. I know IBM obviously very heavily invested in that uh just in terms of how you see this currently as in terms of enterprise adoption, what people are doing with it and and just how you would talk about the state of the industry right now, >>you know, it's a really interesting one, right? I think if you look at it, you know different companies, different industries frankly are at different stages of their Ai journey, right? Um I think for me personally what was really interesting was, and we're all going through the pandemic right now, but last year with covid 19 in the March timeframe, it was really interesting to see the impact, frankly in the space that I played predominantly in around customer care, right? When the pandemic hit immediately call centers, contact centres got flooded with calls, right? And so it created a lot of problems for organizations. But it was interesting to me is it accelerated a lot of adoption of ai to organizations that typically lag and technology. Right? So if you think about public sector, right, that was one area that got hit very, very hard with questions and those types of things and trying to communicate and communicate out information. So it was really interesting to see those organizations frankly accelerate really, really quickly, right? And if you actually talk to those organizations now, I think one of the most interesting things to me and thinking about it and talking to them now is like, hey, you know, we can do this right, AI is really not that complicated, it can be simplified, we can take advantage of it and all of those types of things. Right? So I think for me, you know, I kind of see different industries that sort of different levels, but I think with Covid in particularly, you know, and frankly not just Covid, but even digital transformation alongside Covid is really driving a lot of ai in an accelerated manner. The other thing I'll kind of I'll kind of talk to a little bit here is I still think we're very much in the early innings of this, right, there is a tremendous opportunity innovating in the space and I think we all know that you know data is continually being created every single day and as more people become even more digitalized, there's more and more data being created. Like how do you start to harness that data more effectively, right in your business every day? And frankly I think we're just scratching scratching the surface on it and I think tremendous amount of opportunity as we move forward. >>Yeah, he really is really raised an interesting point which I hadn't thought about in terms of, we think about disruptors, we think about technology being a disrupter, right? But in this case it was purely really, largely environment that was driving this disruption, right, forcing people to to make these adoption moves and transitions maybe a little quicker than they expected. So because of that, because maybe somebody had to speed up their timetable for deployments and what have you what what kind of challenges have they run into them? Where because, as you describe it, it's not been the more organic kind of decision making that might be made, sometimes situation dictated it. So what have you seen in terms of challenges, barriers or just a little more complexity perhaps for some people who are just not getting into the space because of the environment you were talking about? >>I think a lot of this is like people don't know where to get started, right, a lot of the time or how ai can be applied. So a lot of this is going to be a bad education in terms of what it can and cannot do, and then it all depends on the use cases you're talking about, right? So if I think about, you know, building a machine learning models and those types of things right? You know, this set of challenges that people will typically face in these types of things are, you know, how do I collect all the data that I need to go build these models? Right? How do I organize that data? Um you know, how do I get the skill sets needed to ultimately, you know, take advantage of all that data to actually then apply to where I needed in my business? Right, So a lot of this is, you know, people need to understand, you know, those concepts are those pieces um to ultimately be successful with AI and you know what IBM is doing right here and I'll kind of this will be a key theme through this conversation today, is how do you sort of lower the time to value, to get there across that spectrum, but also, you know, frankly the skills >>required along the way as >>well, but a lot of it is like people don't know what they don't know at the end of the day. Mhm. >>Well, let me ask you about about your AI play then, a lot of people involved in this space, as you well know, you know, competitions pretty fierce and pretty widespread, there's a deep bench here um in terms of IBM know, what do you see is kind of your market different differentiator then, you know, what what do you think set you apart in terms of what you're offering in terms of AI deployments and solutions? >>No, that's a great question. I think it's a multifaceted answer, frankly. Um the first thing I'll kind of talk through a little bit right, is really around our platform and our our framework, right? We could refer to as our air ladder, um but it's really an integrated, you know, sort of cohesive platform for companies around the journey to AI, right? So kind of what I was mentioning earlier, right? If you think about, you know, AI is really about supplying the right data into A I. And then being able to infuse it to where you needed to go. Right? So to do that, you need a lot of the underlying information architecture to do that, Right? So you need the ability to collect the data, you need the ability to organize the data, you need the ability to to build out these models, right? Or analyze the data and then of course you need to be able to infuse that ai wherever you need it to be. Right. And so we have a really nice integrated platform that frankly can be deployed on any cloud. Right? So we got the flexibility that deployment model with that in greater platform. And you think about it? We also have built right, you know, sort of these industry leading Ai applications that sit on top of that platform and that underlying infrastructure. Right? So Watson assistant, Right. Our conversational AI, which we'll talk probably a little bit more on this conversation. Right, Watson discovery focus on, you know, intelligent document processing, right. AI search type applications. We've got these sort of market leading applications that sit on top, but there's also other things, right? Like we have a very, very strong research arm right, that continues to invest and funnel innovations into our product platform and into our product portfolio. Right? I think many people are aware of project debater, we took on some of the top debaters in the world, right? But research ultimately is very much tied, right? And even some of the teams that I work with on the ground, we've got them tied directly into the squads that build these products, Right? So we have this really big strong research arm that continues to bring innovation around AI and around other aspects into that product portfolio. But it's not just go ahead, >>Please go ahead. three. No, no. You know, I interrupted you. Go ahead. >>No, I was just gonna say that the other two things, I'll say it like, you know, I'm saying this right, but we've got a lot of sort of proof points and around it. Right? So, if you talk about the scale right? The number of customers, the number of case studies, a number of references across the board, right? In around AI AT IBM It is significant, Right? Um, and not only that, but we've got a lot of sort of, I'll say industry and third party industry recognition. Right? So think about most people are aware of sort of Gartner magic quadrants, right? And we're the leader almost across the board, Right? Or a leader across the board. So cloudy I developer service inside engines, machine learning go down the line. So, you know, if you don't trust me, there's certainly a lot of third party validation around that as well. That makes sense. >>Yeah, it sure does. You know, we're hearing a lot about conversational AI and, you know, with online chat bots and voice assistance and a myriad applications in that respect. Let's talk about conversational right now. Some people think it's little narrow, but, but yet there appears to be a pretty broad opportunity at the same time. So let's talk about that conversational AI um, uh, element um, to what you're talking about at IBM and how that is coming into play and, and perhaps is a pretty big growth sector in this space. >>Yeah, I think again, I talked about scratching the surface early innings. You'll see that theme a lot too. And I think this is another area around that. So listen, let's talk about the broader side. Let's first talk about where conversation always typically applied. Right? So you see it in customer service, that's the obvious place we're seeing the most appointments in. But if you think about, it's not just really around customer service, right? There's use cases around sales and marketing. If you think about, you know, lead qualification, for example, right? How can, you know, I'm on a website, how can I get information about a product or service? How can I automate some of that information collection, answering questions? How can I schedule console? All those things can be automated using great conversationally. I, the organizations don't want these sort of point solutions across the customer journey. What we're ultimately looking for is a single assistant to kind of, you know, front right, that particular customer. So what if I do come on from a legal perspective, but really I'm not here for legal. I'm actually a customer and I want to get a question answered, right? You don't want to have these awkward starts and stops with organizations, Right? So on the customer side where we see the conversation like, hey, I going and it's really kind of covering that full gambit in terms of that customer journey, right? And it's not just the customer journey, but you also want to be across channels, right? So you can imagine right now, not just, you know, the website and the chat on the website, but also right across their messaging channels, right across your phone. Right. And not just that, but you also want to be a really nice experience around, hey, maybe I'm on a phone call with some automation, but I need to be able to hand them off to a digital play. Right? Maybe that's easier to sign up for a particular offer or do some authentication or whatever might be, right. So to sort of be able to sort of switch between the channels, it's really, really going to become more important in this sort of sort of seamless experience as you just kind of go through it. Right? >>So you're coming by customers. Yeah. >>You talked about customers a little bit and you mentioned case studies, but can we get, I hope we can get into some specifics. You can give us some examples about people, companies with whom you've worked and and some success that you've had that respect. And I think maybe the usual suspects come to mind about finance. I might health care, but you said anybody with customer call issues, service centers, that kind of thing would certainly come into play. But can you give us an idea or some examples of deployments and how this is actually working today? >>Oh, absolutely. Right. So I think you kind of mentioned you become sort of industries that are relevant. Right? So, you know, the ones that I think are most relevant that we've seen are the ones with the biggest sort of consumer sort of side to it. Right? So clearly in financial services, banks, insurance, and clearly obvious ones telecommunications, retail, healthcare, these are all sort of big industries with a lot of sort of customers coming in. Right? So you'll see different use cases in those industries as well. Right. So the obvious one, we've got a really good client, Royal Bank of Scotland, they've now changed their name to natwest Open Scotland. Um So they started out with customer service. Right? So dealing with personal banking questions through their website, what's interesting and you'll see this with a lot of these use cases is they will start small, right with a single use case that they'll start to expand from there. So, for example, >>natwest right there, starting with they started with personal banking, but they're not expanding to other areas of the business across that customer journey. Right. So it's a great example of where we've seen it. Cardinal Health Right. We're not dealing with customers in terms of external customers but dealing with internal customers right from the help that standpoint. So it's not always external customers. Oftentimes frankly it can be employees. Right? So they are using it right through an I. V. R. System. Right? So through over the phone. Right. So I can call instead of getting that 1 800 number. I'm going to get a nice natural language experience over the phone to help employees with common problems that they have with their health does so. And they started really, really small, right? They started with simple things like password resets but that represented a tremendous amount of volume but ultimately headed their cost cost centers. So not West is a great example. C I B C. Another bank in Canada Toronto is a great example and the nice thing about what CNBC is doing and there are big, you know, we have four big banks here in Canada, what have you seen do is really focusing a lot on the transactional side. So making it really easy to do interact transfers or send money or over those types of things or check your balance or whatever it might be. So putting a nice simple interface on some of those common transactional things that you >>would do with the bank as well, >>you know, before I let you go, uh I'd like to hit this of buzz where we hear a lot of these days natural language processing. NLP Alright, so, so NLP define that in terms of how you see it and and how is it being applied today? Why why does NLP matter? And what kind of difference is it making? >>Wow, that's a loaded natural language processing. There's a loaded term in a buzzword. I completely agree. I mean listen, at the 50,000 ft level, natural language processing is really about understanding length, Right? So what do I mean by that? So let's use the simple conversational example. We just talked about if somebody is asking about, I'd like to reset my password right? You have to be able to understand what is the intent behind what that user is trying to do right there? Trying to reset a password, right? So being able to understand that inquiry that the user has that's coming in and being able to understand what the intent is behind it. >>That's sort of one, you know, aspect of natural language processing, right? What is the intent or the topic around that paragraph or whatever it might be. The other sort of key thing around natural language processing the importance, extracting certain things that you need to know. And again using the conversational ai side, just for a minute to give a simple example if I said you know what I need to reset my password, I know what the intent is. I want to reset a password but Right I don't know which password I'm trying to reset. Right? So this is where you have to be able to extract objects and we call them entities a lot of time in sort of the ice bake or lingo but you've got to be able to extract those elements. So you know I want to reset my A. T. M. Password. Great. Right so I know what they're trying to do but I also need to extract that it's the A. T. M. Password that I'm trying to do. So that's one sort of key angle of natural language processing and there's a lot of different techniques to be able to do those types of things. I'll also tell you though there's a lot around the content side of the fence as well, right? So you can imagine having a contract, right? And there are thousands of these contracts and some of your terms may change. How do you know, out of those thousands of contracts where the problems are, where I need to start looking, Right? So another sort of keep key area of natural language processing is looking at the content itself. Can I look at these contracts and automatically understand that this is an indemnity clause, Right? And this is an obligation, right? Or those types of things, right? And be able to sort of pick pick those things out so that I can help deal with those sort of contract processing things. That's sort of a second dimension. The third dimensional kind of kind of give around this is really around. You can think about extracting things like sentiment, right? So we talked about, you know, extracting objects and downs and those types of things. But maybe I want to know and analytics use case with customers. Um you know, what is the sentiment and you know, analyzing social media posts or whatever it might be. What's the sentiment that people have around my product or service? So naturally this process, if you think about it, the real high level is really about how do I understand language? But there's a variety of sort of ways to do that if that makes sense? >>Yeah, sure. And I think there's a lot of people out there saying, yeah, the sooner we can identify exasperation, the better off we're going to be right and handling the problems. But it's hard work but it's to make our lives easier and congratulations for your fine work in that space. And thanks for joining us here on the cube. We appreciate the time. Today, brian, >>thank very much. >>You bet BRian Levine is talking to us from IBM talking about conversational Ai and what it can do for you. I'm john Walsh, thanks for joining us here on the cube. Mhm. >>Mhm.

>>from around the globe. It's the Cube presenting Cuban Cloud brought to you by Silicon Angle. >>Welcome back to the Cubes. Special Presentation on the Future of Cloud. Three years ago, Alan Nance said to me that in order to really take advantage of Cloud and Dr Billions of dollars of value, you have to change the operating model. I've never forgotten that statement have explored it from many angles over the last three years. In fact, it was one of the motivations for me actually running this program for our audience. Of course with me is Alan Nance. He's a change agent. He's led transformations that large organizations, including I N G Bank, Royal, Philips, Barclays Bank and many others. He's also a co founder of Citrus Collab. Alan, great to see you. Thanks for coming on the program. >>Thanks for having me again there. >>All right. So when we were preparing for this interview you shared with me the following you said enterprise, I t often hasn't really tapped the true powers that are available to them to make real connections to take advantage of that opportunity. Connections to the business, That is What >>do >>you mean by that. >>Well, I think, you know, we've been saying for quite a long time that enterprise. It is certainly a big part of our past in technology. But you know, just how much is it going to be in the future on, you know, enterprise, I t has had a difficult time under The pressure's off being a centralized organization with large expanse of large Catholics, while at the same time we see obviously the digital operations growing oftentimes in separate reporting structures and closer to the business on. And what I'm thinking right now is enterprise i t. If it has made this transition to cloud operating models, whether they are proprietary or whether they are public cloud, there's a huge opportunity for enterprise. I t. Thio connect the dots in a way that no other part of the organization can do that. And when they connect those dots working closely with the business, they unleash a huge amount of value that is beyond things like efficiency or things like just just just providing cloud computing to be flexible. It has to be much more about value generation. Andi. I think that a lot of leaders of enterprise I t have not really grasped that, Andi. I think that's the opportunity is sitting right in front of them right now. >>You know what I've seen lately? I wonder if you could. Comment is You know, obviously we always talk about the stove pipes, but you've you've seen, you know, the CEO, >>the chief >>data officer that you just mentioned the chief digital officer, the chief information security officer. They've largely been in their own silos. I'm definitely seeing a move to bring those together. I'm seeing a lot of CDOs and CEO roles come together and even the chief information or the head of security reporting up into that where there's there seems to be as your sort of suggesting just a lot more visibility across the entire organization. Is it Is it an organizational issue? Is it? Ah, is it a mindset? But only if you could comment. >>Well, I would say it zits, two or three different things, but certainly it's an organizational issue. But I think it starts off with a cultural issue. Andi, I think what you're seeing, and if you look at the more progressive companies that you see, I think you are also seeing a new emergence off the enlightened technology leader s O. With all respect to me and my generation, our tenure as the owners off the large enterprise, it is coming to an end. And we grew up trying to master the complexity of the off the silos. As you so definitely pointed out, we were battling this falling technology, trying to get it under control, trying to get the costs down, trying to reduce Catholics. And a lot of that was focused on the partnerships that we had with technology suppliers on DSO. That mindset of being engineers struggling for control. Having your most important part of being a technology company itself that now I think is giving way is giving way to a new generation of technology leaders who haven't grown up with that culture. Onda. Oftentimes what I see is that the new enlightened CEOs are female, and they are coming into the role outside of the regular promotion change. So they're coming to these rolls through finance H R marketing on their bringing. A different focus on the focus is much more about how do we work together to create an amazing experience for our employees and for our customers on an experience that drives value. So I think there's a reset in the culture. And clearly, when you start talking about creating a value chain to improve experience, you're also talking about bringing people together from different multidisciplinary backgrounds to make that happen. >>Well, that's kind of, you know, it makes me think about Amazon's mantra of working backwards. You know, start with the experience and and and a lot of a lot of CEOs that I know would love tow beam or involved in the business. But they're just so busy trying to keep the lights on like you said, trying to manage vendors. And like, you know, I had a discussion the other day, Allen with an individual. We were talking about how you know, you got a shift from a product mindset to a platform mindset. But you know, you've said that that platform thinking you're always ahead of the game platform, thinking it needs to make way for ecosystem thinking, you know, unless you're Internet giant scale business like Amazon or Spotify, you said you're gonna be in a niche market if you really don't tap that ecosystem again. If you could explain what you mean by that. >>I think right now if this movement to experience is fundamental, right? So Joe Pine and Gilmore wrote about the experience economy as far back in 1990. But the things that they predicted then are here now. And so what we're now seeing is that consumers have choice. Employees have choice. I think the pandemic has accelerated that. And so what happens when you, when you when you put an enterprise under that type of external pressure, is that it fragments and even fragment into ways it can fragment dysfunctional E so that every silo tries to go into a a defensive mode protective mode? That's obviously the wrong way to go. But the fragmentation that's exciting is when it fragments into ecosystems that are actually working together to solve an experience problem. And those are not platforms. They're too big, you know, When I was Phillips, I was very enthusiastic about working on this connected health care platform, but I think what I started to realize was it takes too much time. It requires too much investment on you are bringing people to you based on your capability. Where is what the market needs is much more agile than that. So if we look in health care, for instance, and you want to connect patients at home with patient with the doctors in the hospital, in the old model you so I'm gonna build a platform for this. I'm gonna have doctors with a certain competence and they're gonna be connecting into this. And so are the patients in some way. And so are the insurers. I think what you're going to see now is different. We're going to say, Let's get together A small team that understands it's called, For instance, let's get a an insurance provider. Let's get a health care operator. Let's get a healthcare tech company on. Let's pull their data in a way that helps us to create solutions now that that can roll out in 30 60 or 90 days. And the thing that that makes that possible is the move to the public crowd because now there are so many specialized supplier, specialized skill sets available that you can connect to through Amazon through Google, through through azure that that these these things that we usedto I think we're very, very difficult are now much easier. I don't want to minimize the effort, but these things are on the table right now. Thio Revalue. >>So you're also a technologist and I wanna ask you and and everybody always says, it's the technology is easy part. It's the people in the process and, you know, way we can all agree on that. However, sometimes technology could be a blocker. And the example that you just mentioned, I have a couple of takeaways from that. First of all, you know the platform thinking it sounds like it's more command and control, and you're advocating for Let's get the ecosystem who are closest to the problem. To solve those problems, however, they decide and leverage the cloud. So my question is from a technology standpoint, does that echo have system have to be on the same cloud with the state of today's technology? Can it be across clouds can be there pieces on Prem? What's your thinking on that? >>I think I think exactly the opposite. It cannot be monolithic and centralized. It's just not practical because that was that was that would cause you too much time on interoperability and who owns what you see The power behind experience is data. And so the most important technical part of this is dealing with data liquidity. So the data that for instance, um, somebody like Kaiser has or the the Harvard Health Care have or the Philips have that's not going to be put into a central place. But for the ecosystem mobilization, there will be subsets of that data flowing between those parties. So the technical, the heart there is how do we manage data liquidity? How do we manage the security around the data liquidity on How do we also understand that what we're building is going to be ever changing and maybe temporary, because on idea may not work, eh? So you've got this idea that the timeliness is very, very important. The duration is very uncertain. The motor the energy for this is data liquidity data transfer, data sharing. But the vehicle is the combination off. Probably crowd in my mind. >>Somebody said to me, Hey, that data is like water. It'll go. It'll go where it wants to go where it needs to go. You can't try to control it. It's let it go. Uh, now, of course, many organizations, particularly large incumbent organizations there. They have many, many data pipelines. They have many processes, many roles, and they're struggling toe actually kind of inject automation into those pipelines. Maybe that's machine intelligence, uh, really doom or data sharing across that pipeline and and ultimately compress the end and cycle. Time to go from raw data insights that are actionable. What are you seeing there and what's your advice? >>Well, I think the the you make some really good points. But what I hear also a little bit in your observation is you're still observing Enterprises on the end of the focus of the enterprise has been on optimizing the processes within the boundaries of its own system. That's why we have s a P. And that's why we have a sales force and, to some degree, even service. Now it's all been about optimizing how we move data, how we create products and services on. That's not the game. Now that's not an important game. Three important game right now is how do I connect to my employees? How do I connect to my customers in a way that provides them a memorable experience? And the realization is we've seen this already a manufacturing for some years. I can't be allowed things to people. So I have to understand where the first part of data comes in. I have to understand who this person is that I am trying to target. Who is the person that needs this memorable experience on what is that memorable experience gonna look like? And I'm going to need my data. But I'm also going to need the data of other actors in that ecosystem. And then I'm gonna have to build that ecosystem really quickly to take advantage off the system. So this throws a monkey wrench in traditional ideas of standardization. It throws a monkey wrench in the idea that enterprise I t is about efficiency on. But if I may, I just want to come back to the day I because I think we're looking in the wrong places. Things like a I let me give you an example. Today there are 2.2 million people working in call centers around the world. If we imagine that they work in three shifts, that means that any one time there are 700,000 people on the phone to a customer on that customer is calling that company because they're vested. They're calling them with advice. They're calling them with a question. They're calling them with a complaint. It is the most important source off valuable data that any company has. And yet what have we done with that? What we've done with that is we have attacked it with efficiency. So instead of saying these are the most valuable sources of information, let's use a I to to tag the sentiment in the recordings that we make with our most valuable stakeholders on this and analyze them for trends, ideas, things that need to change. We don't do that. What we do is we were going to give every call agent two minutes to get them off the phone. For God's sake, don't ask so many import difficult questions. Don't spend money talking to the customer. Try to make them happy so they get a score and say they hire you at the end of the core and then you're done. So so where the AI and automation needs to come in is not in improving efficiency but in mining value. And the real opportunity with a I Is that Joe Pine says this. If you are able to understand the customer rather than interpret them, that is so valuable to the customer that they will pay money for that. I think that's where the whole focus needs to be in this new teaming of enterprise I t. And that's true business. >>It's a great observations. I think we can all relate to that in your call center example, or you've been in a restaurant. You're trying to turn the tables fast and get you out of there. And that's the last time you ever go to that restaurant and you're you're taking that notion of systems thinking and broadening it to ecosystems thinking. And you've said ecosystems have a better chance of success when they're used to stage an experience for whether it's the employees for the brand and of course, the customer and the partners. >>That's it. That's exactly yet. So every technology leader should be asking themselves what contribution can can my and my organization makes of this movement because the business understands the problem, they don't understand how to solve it, and we've chosen a different dialogues. We've been talking a lot about what cloud could do and the functionality that clown has and the potential that clown has on those aerial good things. But it really comes together now when we work together and we, as the technology group brings in, they know how we know how toe connect quickly through the public cloud. We know how to do that in a secure way. We know how to manage data, liquidity at scale, and we can stand these things up through our, you know, our new learning of agile and devils we can stand. These ecosystems are fairly quickly now. There's still a whole bunch of culture between different businesses that have to work together through the idea that I have to protect my data rather than serve the customer. But once you get past that, there's a whole new conversation enterprise. It you can have that, I think, gives them a new lease of life, new value. And I just think it's a really, really exciting time. Yes, >>so you're seeing the intersection of a lot of different things. You talk about cloud as you know, an enabler for sure, and that's great. We could talk about that, but you've got this what you're referring to before is, you know, maybe you're in a niche market, but you have your marketplace and like you're saying, you can actually use that through an ecosystem to really leave her a much, much broader available market and then vector that into the experience economy. You know, we talk about subscriptions, the AP economy. That really is new thinking, >>yes, and I think what you're seeing here is it zits, not radical. Inasmuch as all of these ideas have been around, some of them have been around since the nineties. But what's radical is the way in which we can now mix and match these technologies to make this happen. That's gone so quickly on, I would argue to you, and I've argued this before. Scale scale is a concept within an organization is dead. It doesn't give you enough value. It gives you enough efficiency, and it gives you a cloud. But it doesn't give you three opportunity to target the niche experiences that you need to do. So. If we start to think off an organization as a a combination off known and unknown potential ecosystems, you start to build a different operating model, a different architectural idea you start to look outside more than you start to look insight. Which is why the cultural change that we were talking about just now goes hand in hand with this because people have to be comfortable thinking in ecosystems that may not yet exist on partnering with people where they bring to the table there, you know, 2030 years of experience in a new and different way. >>Let me make sure I understand that. So you're basically if I understand you're saying that if you're sort of end goal is scale and efficiency at scale, you're you're gonna have a vanilla solution for your customers and your ecosystem. Whereas if you will allow this outside in thinking to come in, you're gonna be able to actually customize those experience experiences and get the value of scale and efficiency. >>Right? So, I mean, Rory Sutherland, who is ah, big finger in the in. The marketing world has always said, ultimately, scale standardization and best practice lead to mediocrity because you are not focused on the most important thing for your employees or your brand, or you're you're focused on the efficiency factors on. They create very little value in fact, we know that they subvert value. So, yes, we need to have a very big mindset change. >>Yeah, You're a top line thinker, Allen. And and always at the forefront. I really appreciate you coming on to the to the Cuban. Participate in this program. Give us the last word. So if you're a change agent, I wanna I'm an organization, and I want to inject this type of change. Where do I >>start? Well, I think it starts by identifying. Are we going to? Is it are we gonna work on the employee experience? Do we feel that we have a model where the employees that are on stage with customers are so important that the focus has to be employees? We go down that route and we look at what happened to the pandemic. What type of experiences are we going to bring to those employees around their ability to have flow in their work, to get returned on energy, to excite the customers? Let's do that. Let's figure out what experience are we driving now? What does that experience need to be if we're the customer side? As I said, let's look ALS. The sources of information that we already have. You know, I know companies to spend hundreds of millions a year trying to figure out what consumers what. And yet if we look in their call centers, you will call up and and they will say to Your call may be recorded for quality purposes and training on this is not true. Less than 10% of those calls that ever listened to on if they are listening to its compliance that's driving that, not the burning desire to better understand the consumer. So if we change that, then we say Okay, so what can we change? What is the experience that we are now able to stage with all we know and with all weaken dio on debts? Start there. Let's start with what is the experience you want to stage? What's the experience landscape look like now? And who do we bring together to make that happen? >>Allen. Fantastic. Having you back in the Cube, it's always a pleasure. And, uh, and thanks so much for participating. >>Thank you, Dave. It's always a pleasure to speak with you. >>Thank you. Everybody, this is Dave Volonte. The Cuban cloud will be right back right after this short break. Stay with

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Welcome to the cubes coverage of AWS reinvent 2020. The digital version I'm Lisa Martin and I have a couple of Cuba alumni joining me from Wien. We've got Danny Allen. It's C T O and S VP of product strategy And Dave Russell, VP of Enterprise Strategy, is here as well. Danny and a Welcome back to the Cube. >>Hi, Lisa. Great to be here. >>Hey, Lisa. Great to be here. Love talking with this audience >>It and thankfully, because of technologies like this in the zoom, were still able to engage with that audience, even though we would all be gearing up to be Go spending five days in Vegas with what 47,000 of our closest friends across, you know, and walking a lot. But I wanted Thio. Danny, start with you and you guys had them on virtually this summer. That's an event known for its energy. Talk to me about some of the things that you guys announced there. And how are your customers doing with this rapid change toe? work from home and this massive amount of uncertainty. >>Well, certainly no one would have predicted this the beginning of the year. There has been such transformation. There was a statement made earlier this year that we've gone through two years of transformation in just two months, and I would say that is definitely true. If you look both internally and bean our workforce, we have 4400 employees all of a sudden, 3000 of them that had been going into the office or working from home. And that is true of our customer base as well. There's a lot of remote, uh, remote employ, mental remote working, and so that has. You would think it would have impact on the digital systems. But what it's done is it's accelerated the transformation that organizations were going through, and that's been good in a number of different aspects. One certainly cloud adoption of clouds picked up things like Microsoft teams and collaboration software is certainly picked up, so it's certainly been a challenging year on many fronts. But on the on the other hand, it's also been very beneficial for us as well. >>Yeah, I've talked to so many folks in the last few months. There's silver linings everywhere. There's opportunity everywhere. But give our audience standing an overview of who them is, what you do and how you help customers secure their data. >>Sure, so VM has been in the backup businesses. What I'll say We started right around when virtualization was taking off a little before AWS and you see two left computing services on DWI would do back up a virtual environments. You know, over the last decade, we have grown into a $1 billion company doing backup solutions that enable cloud data management. What do you mean by that? Is we do backup of all kinds of different infrastructures, from virtual to cloud based Assad's based to physical systems, You name it. And then when we ingest that data, what we do is we begin to manage it. So an example of this is we have 400,000 customers, they're going back up on premises. And one of the things that we've seen this year is this massive push of that backup data into S three into the public cloud and s. So this is something that we help our customers with as they go through this transformation. >>And so you've got a team for a ws Cloud native solution. Talk to me a little bit about that. And how does that allow business is to get that centralized view of virtual physical SAS applications? >>Yeah, I think it all starts with architecture er and fundamentally beams, architectures. ER is based upon having a portable data format that self describing. So what >>does >>that mean? That means it reduces the friction from moving data that might have been born on premises to later being Stan Shih ated in, say, the AWS cloud. Or you can also imagine now new workloads being born in the cloud, especially towards the middle and end of this year. A lot of us we couldn't get into our data center. We had to do everything remotely. So we had to try to keep those lights on operationally. But we also had to begin to lift and shift and accelerate your point about silver linings. You know, if there is a silver lining, the very prepared really benefited. And I think those that were maybe a little more laggards they caught up pretty quickly. >>Well, that's good to hear stick big sticking with you. I'd love to get your perspectives on I t challenges in the last nine months in particular, what things have changed, what remains the same. And where is back up as a priority for the the I T folks and really the business folks, too? >>Yeah, I almost want to start with that last piece. Where? Where's backup? So back up? Obviously well understood as a concept, it's well funded. I mean, almost everybody in their right mind has a backup product, especially for critical data. But yet that all sounds very much the same. What's very, very different, though? Where are those workloads? Where do they need to be going forward? What are the service level agreements? Meaning that access times required for those workloads? And while we're arguably transitioning from certain types of applications to new applications, the vast majority of us are dead in the middle of that. So we've got to be able to embrace the new while also anchoring back to the past. >>Yeah, I'm not so easily sudden, done professionally or personally, Danny, I'd love to get your perspective on how your customer conversations have changed. You know, we're executives like you, both of you are so used to getting on planes and flying around and being able Thio, engage with your customers, especially events like Vermont, and reinvent What's the change been like? And from a business perspective, are you having more conversations at that business? Little as the end of the day. If you can't recover the data, that's the whole point, right? >>Yeah, it is. I would say the conversations really have four sentiments to them. The first is always starts with the pandemic and the impact of the pandemic on the business. The second from there is it talks about resource. We talked about resource management. That's resource management, both from a cost perspective. Customers trying to shift the costs from Capex models typically on premises into Op X cloud consumption models and also resource management as well. There's the shift from customers who are used to doing business one way, and they're trying to shift the resources to make it effective in a new and better way. I'd say the third conversation actually pivots from there to things like security and governance. One of the interesting things this year we've seen a lot of is ransomware and malware and attacks, especially because the attack surface has increased with people working from home. There is more opportunity for organizations to be challenged, and then, lastly, always pivots where it ends up his digital transformation. How do I get from where I used to be to where I want to be? >>Yeah, the ransomware increase has been quite substantial. I've seen a number of big. Of course you never want to be. The brand garment was head Carnival Cruise Line. I think canon cameras as well and you're talking about you know you're right, Danny. The attacks are toe surfaces, expanding. Um, you know, with unprotected cloud databases. I think that was the Facebook Tic Tac Instagram pack. And so it's and also is getting more personal, which we have more people from home, more distractions. And that's a big challenge that organizations need to be prepared for, because, really, it's not a matter of are we going to get a hit? But it's It's when, and we need to make sure that we have that resiliency. They've talked to us about how them enables customers toe have that resiliency. >>Yeah, you know, it's a multilayered approach like you know, any good defensive mechanism. It's not one thing it's trying to do all of the right things in advance, meaning passwords and perimeter security and, ideally, virtual private networks. But to your point, some of those things can fail, especially as we're all working remotely, and there's more dependence on now. Suddenly, perhaps not so. I t sophisticated people, too. Now do the right things on a daily basis and your point about how personal is getting. If we're all getting emails about, click on this for helpful information on the pandemic, you know there's the likelihood of this goes up. So in addition to try and do good things ahead of time, we've got some early warning detection capabilities. We can alert that something looks suspicious or a novelist, and bare bears out better investigation to confirm that. But ultimately, the couple of things that we do, they're very interesting and unique to beam are we can lock down copy of the backup data so that even internal employees, even somewhat at Amazon, can't go. If it's marked immutable and destroy it, remove it, alter it in any way before it's due to be modified or deleted, erased in any way. But one of the ones I'm most excited about is we can actually recover from an old backup and now introduce updated virus signatures to ensure we don't reintroduced Day zero threats into production environment. >>Is it across all workloads, physical virtual things like, you know, Microsoft or 65 slack talked about those collaboration tools that immune ability, >>so immune ability. We're expanding out into multiple platforms today. We've got it on on premises object storage through a variety of different partners. Actually, a couple dozen different partners now, and we have something very unique with AWS s three object lock that we you can really lock down that data and ensure that can't be compromised. >>That's excellent, Danny, over to you in terms of cloud adoption, you both talked about this acceleration of digital business transformation that we've all seen. I think everyone has whiplash from that and that this adoption of cloud has increased. We've seen a lot of that is being a facilitator like, are you working with clients who are sort of, you know, maybe Dave at that point you talked about in the beginning, like kind of on that on that. Bring in the beginning and we've got to transform. We've got to go to the cloud. How do you kind of help? Maybe facilitate their adoption of public health services like AWS with the technologies that the off first? >>Yeah, I'd say it's really two things everyone wants to say, Hey, we're disrupting the market. We're changing everything about the world around us. You should come with us. Being actually is a very different approach to this one is we provide stability through the disruption around you. So as your business is changing and evolving and you're going through digital transformation, we can give you the stability through that and not only the stability through that change, but we can help in that change. And what I mean by that is if you have a customer who's been on premises and running the workloads on premises for a long while, and maybe they've been sending their backups and deaths three and flagging that impute ability. But maybe now they want to actually migrate the workloads into E. C to weaken. Do that. It's a It's a three step three clicks and workflow to hit a button and say send it up into Easy to. And then once it's in AWS, we can protect the workload when it's there. So we don't just give the stability in this changing environment around us. But we actually help customers go through that transformation and help them move the workloads to the most appropriate business location for them. >>And how does that Danny contending with you from a cost optimization perspective? Of course, we always talk about cost as a factor. Um, I'm going to the cloud. How does that a facilitator of, like, being able to move some of those workloads like attitude that you talked about? Is that a facilitator of cost optimization? Lower tco? I would imagine at some point Yes, >>Yes, it is. So I have this saying the cloud is not a charity right there later in margin, and often people don't understand necessarily what it's going to cost them. So one of the fundamental things that we've had in being back up for a W s since the very beginning since version one is we give cost forecasting and it's not just a rudimentary cost forecasting. We look at the storage we looked compute. We looked at the networking. We look at what all of the different factors that go into a policy, and we will tell them in advance what it's going to cost. That way you don't end up in a position where you're paying a lot more than you expected to pay. And so giving that transparency, giving the the visibility into what the costs of the cloud migration and adoption are going to be is a critical motivator for customers actually to use our software. >>Awesome. And Dave, I'm curious if we look at some of the things trends wise that have gone on, what are you seeing? I t folks in terms of work from home, the remote workers, but I am imagine they're getting their hands on this. But do you expect that a good amount of certain types of folks from industries won't go back into the office because I ts realizing, like more cost optimization? Zor Hey, we don't need to be on site because we can leverage cloud capabilities. >>Yeah, I think it works, actually, in both directions least, I think we'll see employees continue to work remotely, so the notion of skyscrapers being filled with tens of thousands of people, you know, knowledge workers, as they were once called back in the day. That may not come to pass at least any time soon. But conversely to your point everybody getting back into the data center, you know, from a business perspective, the vast majorities of CEO so they don't wanna be in the real estate business. They don't wanna be in the brick and mortar and the power cooling the facilities business. So >>that was >>a trend that was already directionally happening. And just as an accelerant, I think 2000 and 20 and probably 2021 at least the first half just continues that trend. >>Yeah, Silicon Valley is a bit lonely. The freeways there certainly emptier, which is one thing. But it is. It's one of those things that you think you could be now granted folks that worked from home regardless of the functions they were in before. It's not the same. I think we all know that it's not the same working from home during a pandemic when there's just so much more going on. But at the same time, I think businesses are realizing where they can actually get more cost optimization. Since you point not wanting to manage real estate, big data centers, things like that, that may be a ah, positive spin on what this situation has demonstrated. Daddy Last question to you. I always loved it to hear about successful customers. Talk to me about one of your favorite reference customers that really just articulates beams value, especially in this time of helping customers with so many pivots. >>Well, the whole concept of digital transformation is clearly coming to the forefront with the pandemic. And so one of my favorite customers, for example, ducks unlimited up in Canada. They have i ot sensors where they're collecting data about about climate information. They put it into a repository and they keep it for 60 years. Why 60 years? Because who knows? Over the next 60 years, when these sensors in the data they're collecting may be able to solve problems like climate change. But if you >>look at it >>a broader sense, take that same concept of collection of data. I think we're in a fantastic period right now where things like Callum medicine. Um, in the past, >>it was >>kind of in a slow roll remote education and training was on kind of a slow roll. Climate change. Slow roll. Um, but now the pandemics accelerating. Ah, lot of that. Another customer, Royal Dutch Shell, for example. Traditionally in the oil and petrochemical industry, their now taking the data that they have, they're going through this transformation faster than ever before and saying, How do I move to sustainable energy? And so a lot of people look at 2020 and say, I want how does this year? Or, you know, this is not the transformation I want. I actually take the reverse of that. The customers that we have right now are taking the data sets that they have, and they're actually optimizing for a more sustainable future, a better future for us and for our Children. And I think that's a fantastic thing, and being obviously helps in that transformation. >>That's excellent. And I agree with you, Danny, you know, the necessity is the mother of invention. And sometimes when all of these challenges air exposed, it's hard right away to see what are the what are the positives right? What are the opportunities? But from a business perspective is you guys were talking about the beginning of our segment, you know, in the beginning was keeping the lights on. Well, now we've got to get from keeping the lights on, too. Surviving to pivoting well to thriving. So that hopefully 2021 this is good as everybody hopes it's going to be. Right, Dave? >>Yeah, absolutely. It's all data driven and you're right. We have to move from keep the lights up on going the operational aspect to growing the business in new ways and ideally transforming the business in new ways. And you can see we hit on digital transformation a number of times. Why? Because its data driven, Why do we intercept that with being well? Because if it's important to you, it's probably backed up and held for long term safekeeping. So we want to be able to better leverage the data like Danny mentioned with Ducks Unlimited. >>And of course, as we know, data volumes are only growing. So next time you're on day, you have to play us out with one of your guitars. Deal >>definitely, definitely will. >>Excellent for Dave Russell and Danny Allen. I'm Lisa Martin. Guys, thank you so much for joining. You're watching the Cube

>> From the cube studios in Palo Alto and Boston, connecting with thought leaders all around the world. This is a cube conversation. >> Hello everyone, welcome back to the cubes. Special presentation on the future of cloud. Three years ago, Alan Nance said to me that in order to really take advantage of cloud and drive billions of dollars of value, you have to change the operating model. I've never forgotten that statement and have explored it from many angles over the last three years. In fact it was one of the motivations for me actually running this program for our audience. Of course with me is Alan Nance. He is a change agent. He's led transformations at large organizations, including ING bank, Royal Phillips, Barclay's bank, and many others. He's also a co-founder of CitrusCollab. Alan, great to see you. Thanks for coming on the program. >> Thanks for having me again, Dave. >> All right, so when we were preparing for this interview, you shared with me the following, you said enterprise IT, often hasn't really tapped the true powers that are available to them to make real connections, to take advantage of that opportunity, connections to the business that is. What do you mean by that? >> Well I think we we've been saying for quite a long time that enterprise IT is certainly a big part of our past in technology. But just how much is it going to be in the future? And enterprise IT has had a difficult time under the cost pressures of being a centralized organization with large, expensive, large topics. While at the same time we see obviously the digital operations for growing oftentimes in separate reporting structures and closest to the business. And what I'm thinking right now is enterprise IT, if it has made this transition to a cloud operating models, whether they are proprietary or whether they are public cloud, there's a huge opportunity for enterprise IT to connect the dots in a way that no other part of the organization can do that. And when they connect those dots, working closely with the business, they unleash a huge amount of value that is beyond things like efficiency or things like just providing cloud computing to be flexible. It has to be much more about value generation. And I think that a lot of leaders of enterprise IT have not really grasped that. And I think that's the opportunity sitting right in front of them right now. >> You know what I've seen lately? I wonder if you could comment, is obviously we always talk about the stove pipes, but you've seen the CIO, the chief data officer that you just mentioned, the chief digital officer, the chief information security officer, they've largely been in their own silos of definitely seeing a move to bring those together. I'm seeing a lot of CDOs and CIO roles come together. And even the chief information or the head of security reporting up into that, where there seems to be as you're sort of suggesting just a lot more visibility across the entire organization. Is it an organizational issue? Is it a mindset? Go on if you could comment. >> Well I would say it's two or three different things. Certainly it's an organizational issue, but I think it starts off with a cultural issue. And I think what you're seeing, and if you look at the more progressive companies that you see, I think you are also seeing a new emergence of the enlightened technology leader. So with all respect to me and my generation our tenure as the owners of the large enterprise IT is coming to an end. And we grew up trying to master the complexity of the silos as you so deftly pointed out. Out we were battling this soaring technology, trying to get it under control, trying to get the costs down, trying to reduce CapEx. And a lot of that was focused on the partnerships that we had with technology suppliers. And so that mindset of being engineers struggling for control, having your most important part of being a technology company itself, I've got now, I think is giving way, giving way to a new generation of technology leaders who haven't grown up with that culture. And oftentimes what I see is that the new enlightened CIOs are female and they are coming into the role outside of the regular promotion chain, so they're coming to these roles through finance, HR, marketing, and they're bringing a different focus. And the focus is much more about how do we work together to create an amazing experience for our employees and for our customers and an experience that drives value. So I think there's a reset in the culture. And clearly when you start talking about creating a value chain to improve experience, you're also talking about bringing people together from different multidisciplinary backgrounds to make that happen. >> Well that's kind of, it makes me think about Amazon's mantra of working backwards, start with the experience. And then a lot of CIOs that I know would love to be more involved in the business, but they're just so busy trying to keep the lights on. Like you said, trying to manage vendors and in the like. I've had a discussion the other day with an individual, we were talking about how, you got to shift from a product mindset to a platform mindset, but you've said that the platform thinking you're always ahead of the game. Platform thinking it needs to make way for ecosystem thinking. Unless you're into that, it'd be giant scale business like Amazon or Spotify you said, you're going to be in a niche market if you really don't tap that ecosystem again . If you could explain what you mean by that? >> Well I think right now, if this movement to experience is fundamental. Right? So Joe Pine and Jim Gilmore wrote about the experience economy as far back in 1990, but the things that they predicted then are here now. And so what we're now seeing is that consumers have choice. Employees have choice. I think the pandemic has accelerated that. And so what happens when you put an enterprise under that type of external pressure, is that it fragments. And if it can fragment in two ways. It can fragment dysfunctionally so that every silo tries to go into a defensive mode, protective mode. That's obviously the wrong way to go. But the fragmentation that's exciting is when it fragments into ecosystems that are actually working together to solve and experience problem. And those are not platforms they're too big. When I was at Phillips, I was very enthusiastic about working on this connected healthcare platform. But I think what I started to realize was it takes too much time. It requires too much investment and you are bringing people who tune you based on your capability, whereas what the market needs is much more agile than that. So if we look in healthcare, for instance and you want to connect patients at home, with patients, with the doctors in the hospital. In the old model when you said, I'm going to build a platform for this, I'm going to have doctors with a certain competence, so they're going to be connecting into this. And so are the patients in some way. And so are the insurers. I think what you're going to see now is different. We're going to say let's get together a small team that understands its competence. So for instance, let's get an insurance provider, let's get a healthcare operator, let's get a healthcare tech company and let's pull their data in a way that helps us to create solutions now that can roll out in 30, 60 or 90 days. And the thing that makes that possible is the move to the public cloud. Because now there are so many specialized suppliers, specialized skillsets available that you can connect to through Amazon, through Google, through Azure, that these things that we used to think were very, very difficult, are now much easier. I don't want to minimize the effort, but these things are on the table right now to read value. >> So you're also technologist. And I want to ask you and everybody always says, technology is easy part of the people and the process. We can all agree on that. However sometimes technology can be a blocker. And the example that you just mentioned, I have a couple of takeaways from that. First of all the platform thinking is somewhat, sounds like it's more command and control and you're advocating for let's get the ecosystem who are closest to the problem to solve those problems. However they decide and they'll leverage the cloud. So my question is from a technology standpoint. Does that ecosystem have to be in the same cloud, with the state of today's technology? can it be across clouds? Can be there pieces on prem? What's your thinking on that? >> I think exactly the opposite. It cannot be monolithic and centralized. It's just not practical because that would cause you too much time on interoperability. And who owns what. You see the power behind experience is data. And so the most important technical part of this is dealing with data liquidity. So the data that, for instance somebody like Kaiser has or the Harvard Mental Healthcare have or the Phillips have, that's not going to be put into a central place for the ecosystem mobilization. There will be subsets of that data flowing between those parties. So the technical, the hardware. Is how do we manage data liquidity? How do we manage the security around data liquidity? And how do we also understand that what we're building is going to be ever changing and maybe temporary, because an idea may not work. And so you've got this idea that the timeliness is very very important. The duration is very uncertain. The mojo energy for this is data liquidity, data transfer, data sharing. But the vehicle is the combination of public cloud, in my mind. >> Somebody said to me, hey that data's like water. It'll go where it wants to go, where it needs to go and you can't try to control it. It's let it go. Now of course many organizations, particularly large incumbent organizations they have many many data pipelines. They have many processes, many roles, and they're struggling to actually kind of inject automation into those pipelines. Maybe that's machine intelligence really do more data sharing across that pipeline and ultimately compress the end and cycle time to go from raw data to insights that are actionable. What are you seeing there? And what's your advice? >> Well I think you make some really good points, but what I hear also a little bit in your observation is you're still observing enterprises. And the focus of the enterprise has been on optimizing the processes within the boundaries of its own system. That's why we have SAP and this why we have Salesforce. And to some degree even service now. It's all been about optimizing how we move data, how we create production services. And that's not the game now. That's not an important game. The important game right now is how do I connect to my employees? How do I connect to my customers in a way that provides them a memorable experience? And the realization is, I'm assuming it's already manufacturing for some years. I can't be all things to all people. So I have to understand this is where the first part of data comes in. I have to understand. Who this person is that I am trying to target? Who is the person that needs this memorable experience? And what is that memorable experience going to look like? And I'm going to need my data, but I'm also going to need the data of other actors in that ecosystem. And then I'm going to have to build that ecosystem really quickly to take advantage of the system. So this throws a monkey rage in traditional ideas of standardization. It throws a monkey rage in the idea that enterprise IT is about efficiency. If I may, I just want to come back to the AI because I think we're looking in the wrong places. Things like AI. And let me give you an example today, there are 2.2 million people working in call centers around the world. If we imagine that they work in three shifts, that means that anyone time there are 700,000 people on the phone to a customer, and that customer is calling that company because they're vested, they're calling them with advice. They're calling them with a question they're calling them with a complaint. It is the most important source of valuable data that any company has. And yet, what have we done with that? What we've done with that is we've attacked it with efficiency. So instead of saying, these are the most valuable sources of information, let's use AI to tag the sentiment in the recordings that we make with our most valuable stakeholders. And let's analyze them for trends, ideas things that needs to change. We don't do that. What we do is we're going to give every cool agent two minutes to get them off the phone. For God's sake, don't answer many important, difficult questions. Don't spend money talking to the customer, try to make them happy. So they get a score and say, they hire you at the end of the call, and then you're done. So where the AI automation needs to come in is not in improving your efficiency, but in mining value. And the real opportunity with AI is that Joe Pine says this. "If you are able to understand the customer, rather than interpret them, that is so valuable to the customer, that they will pay money for that". And I think that's where the whole focus needs to be in this new team in enterprise IT, and they're still in the business. >> That's a great observation. I think we can all relate to that in your call center example, or you've been a restaurant, and you're trying to turn the tables fast and get out of there. And it's the last time you ever go to that restaurant. And you're taking that notion of systems thinking and broadening it to ecosystems thinking. And you've said, ecosystems have a better chance of success when they're used to stage and experience for whether it's the employee for the brand. And of course the customer and the partners. >> That's it that's exactly it. So every technology leader should be asking themselves what contribution can I and my organization make to this movement, because the business understands the problem. They don't understand how to solve it, and we've chosen a different dialogue. So we've been talking a lot about what cloud can do and the functionality that cloud has and the potential that cloud has. And those are all good things, but it really comes together. Now when we work together and we as the technology group brings in the know how we know how to connect quickly through the public cloud, we know how to do that in a secure way. We know how to manage data liquidity at scale, and we can stand these things up through our new learning of agile and DevOps. We can stand these ecosystems up fairly quickly. Now there's still a whole bunch of culture between different businesses that have to work together. The idea that I have to protect my data rather than serve the customer. But once you get past that, there's a whole new conversation enterprise IT can have, that I think gives them a new lease of life, new value. And I just think it's a really really exciting time. >> (inaudible) The intersection of a lot of different things. You talk about cloud as an enabler for sure. And that's great. We can talk about that, but you've got this. What you were referring to before is maybe you're in a niche market, but you have your marketplace. And like you're saying, you can actually use that through an ecosystem to really leave a much, much broader available market. And then vector that into the experience economy. We talk about subscriptions, the API economy, that really is new thinking. >> It is and I think what you're seeing here it's not radical in as much as all of these ideas have been around. Some of them have been around since the nineties, but what's radical is the way in which we can now mix and match these technologies to make this happen. That's growing so quickly. And I would argue to you and I've argued this before. Scale, scale as a concept within an organization is dead. It doesn't give you enough value. It gives you enough efficiency and it gives you a cloud. And it doesn't give you the opportunity to target the niche experiences that you need to do. So if we start to think of an organization as a combination of known and unknown potential ecosystems, you start to build a different operating model, a different architectural idea. You start to look outside more than you start to look inside. Which is why the cultural change that we were talking about just now goes hand in hand with this because people have to be comfortable thinking in ecosystems that may not yet exist and partnering with people where they bring to the table. There 20, 30 years of experience in a new and different way. >> So let me make sure I understand that. So you basically, if I understand it, you're saying that if your sort of end goal is scale and efficiency at scale you're going to have a vanilla solution for your customers in your ecosystem. Whereas if you will allow this outside in thinking to come in, you're going to be able to actually customize those experience, experiences and get the value of scale and efficiency. >> Right, so I mean Rory Sutherland, who is a big thinker in the marketing world has always said, "ultimately scale standardization and best practice lead to mediocrity". Because you are not focused on the most important thing for your employee or your brand. You're focused on the efficiency factors and they create very little value. In fact we know that they subvert value. So yes we need to have a very big mindset change. >> Yeah you're a top line thinker Alan and always at the forefront. I really appreciate you coming on to the cube and participate in this program. Give us a last word. So if you're a change agent, I'm an organization and I want to inject this type of change. Where do I start? >> Well I think it starts by identifying. Are we going to work on the employee experience? Do we feel that we have a model where the employees that are on stage with customers are so important that the focus has to be employees. We go down that route and then we look at what's happened to the pandemic. What type of experiences are we going to bring to those employees around their ability to have flow in their work, to get return on energy, to excite the customers? Let's do that. Let's figure out what experience are we driving now? And what does that experience need to be? If we're the customer side. As I said let's look at all the sources of information that we already have. I know companies that spend hundreds of millions a year trying to figure out what consumers want. And yet if we look in their call sentences, you will call up and they will say to you, your call may be recorded for quality purposes and training. And it's not true, less than 10% of those calls are ever listened to. And if they listened to, it's compliance, that's driving that, not the burning desire to better understand the consumer. So if we change that, then we shall get to. What can we change? What is the experience we are now able to stage with all we know and with all we can do. And let's start there, let's start with, what is the experience you want to stage? What's the experience landscape look like now? And who do we bring together to make that happen? >> Alan fantastic. Having you back in the cube, it's always a pleasure and thanks so much for participating. >> Thank you, Dave. It's always a pleasure to speak with you. >> And thank you everybody. This is Dave Vellante the cube on cloud. We'll be right back right after this short break, stay with us. (soft music)

>>Hello. I'm Professor Toru Suzuki Cherif cardiovascular medicine on associate dean of the College of Life Sciences at the University of Leicester in the United Kingdom, where I'm also director of the Lester Life Sciences accelerator. I'm also honorary consultant cardiologist within our university hospitals. It's part of the national health system NHS Trust. Today, I'd like to talk to you about our Lester Clinical Data Science Initiative. Now brief background on Lester. It's university in hospitals. Lester is in the center of England. The national health system is divided depending on the countries. The United Kingdom, which is comprised of, uh, England, Scotland to the north, whales to the west and Northern Ireland is another part in a different island. But national health system of England is what will be predominantly be discussed. Today has a history of about 70 years now, owing to the fact that we're basically in the center of England. Although this is only about one hour north of London, we have a catchment of about 100 miles, which takes us from the eastern coast of England, bordering with Birmingham to the west north just south of Liverpool, Manchester and just south to the tip of London. We have one of the busiest national health system trust in the United Kingdom, with a catchment about 100 miles and one million patients a year. Our main hospital, the General Hospital, which is actually called the Royal Infirmary, which can has an accident and emergency, which means Emergency Department is that has one of the busiest emergency departments in the nation. I work at Glen Field Hospital, which is one of the main cardiovascular hospitals of the United Kingdom and Europe. Academically, the Medical School of the University of Leicester is ranked 20th in the world on Lee, behind Cambridge, Oxford Imperial College and University College London. For the UK, this is very research. Waited, uh, ranking is Therefore we are very research focused universities as well for the cardiovascular research groups, with it mainly within Glenn Field Hospital, we are ranked as the 29th Independent research institution in the world which places us. A Suffield waited within our group. As you can see those their top ranked this is regardless of cardiology, include institutes like the Broad Institute and Whitehead Institute. Mitt Welcome Trust Sanger, Howard Hughes Medical Institute, Kemble, Cold Spring Harbor and as a hospital we rank within ah in this field in a relatively competitive manner as well. Therefore, we're very research focused. Hospital is well now to give you the unique selling points of Leicester. We're we're the largest and busiest national health system trust in the United Kingdom, but we also have a very large and stable as well as ethnically diverse population. The population ranges often into three generations, which allows us to do a lot of cohort based studies which allows us for the primary and secondary care cohorts, lot of which are well characterized and focused on genomics. In the past. We also have a biomedical research center focusing on chronic diseases, which is funded by the National Institutes of Health Research, which funds clinical research the hospitals of United Kingdom on we also have a very rich regional life science cluster, including med techs and small and medium sized enterprises. Now for this, the bottom line is that I am the director of the letter site left Sciences accelerator, >>which is tasked with industrial engagement in the local national sectors but not excluding the international sectors as well. Broadly, we have academics and clinicians with interest in health care, which includes science and engineering as well as non clinical researchers. And prior to the cove it outbreak, the government announced the £450 million investment into our university hospitals, which I hope will be going forward now to give you a brief background on where the scientific strategy the United Kingdom lies. Three industrial strategy was brought out a za part of the process which involved exiting the European Union, and part of that was the life science sector deal. And among this, as you will see, there were four grand challenges that were put in place a I and data economy, future of mobility, clean growth and aging society and as a medical research institute. A lot of the focus that we have been transitioning with within my group are projects are focused on using data and analytics using artificial intelligence, but also understanding how chronic diseases evolved as part of the aging society, and therefore we will be able to address these grand challenges for the country. Additionally, the national health system also has its long term plans, which we align to. One of those is digitally enabled care and that this hope you're going mainstream over the next 10 years. And to do this, what is envision will be The clinicians will be able to access and interact with patient records and care plants wherever they are with ready access to decision support and artificial intelligence, and that this will enable predictive techniques, which include linking with clinical genomic as well as other data supports, such as image ing a new medical breakthroughs. There has been what's called the Topol Review that discusses the future of health care in the United Kingdom and preparing the health care workforce for the delivery of the digital future, which clearly discusses in the end that we would be using automated image interpretation. Is using artificial intelligence predictive analytics using artificial intelligence as mentioned in the long term plans. That is part of that. We will also be engaging natural language processing speech recognition. I'm reading the genome amusing. Genomic announced this as well. We are in what is called the Midland's. As I mentioned previously, the Midland's comprised the East Midlands, where we are as Lester, other places such as Nottingham. We're here. The West Midland involves Birmingham, and here is ah collective. We are the Midlands. Here we comprise what is called the Midlands engine on the Midland's engine focuses on transport, accelerating innovation, trading with the world as well as the ultra connected region. And therefore our work will also involve connectivity moving forward. And it's part of that. It's part of our health care plans. We hope to also enable total digital connectivity moving forward and that will allow us to embrace digital data as well as collectivity. These three key words will ah Linkous our health care systems for the future. Now, to give you a vision for the future of medicine vision that there will be a very complex data set that we will need to work on, which will involve genomics Phanom ICS image ing which will called, uh oh mix analysis. But this is just meaning that is, uh complex data sets that we need to work on. This will integrate with our clinical data Platforms are bioinformatics, and we'll also get real time information of physiology through interfaces and wearables. Important for this is that we have computing, uh, processes that will now allow this kind of complex data analysis in real time using artificial intelligence and machine learning based applications to allow visualization Analytics, which could be out, put it through various user interfaces to the clinician and others. One of the characteristics of the United Kingdom is that the NHS is that we embrace data and captured data from when most citizens have been born from the cradle toe when they die to the grave. And it's important that we were able to link this data up to understand the journey of that patient. Over time. When they come to hospital, which is secondary care data, we will get disease data when they go to their primary care general practitioner, we will be able to get early check up data is Paula's follow monitoring monitoring, but also social care data. If this could be linked, allow us to understand how aging and deterioration as well as frailty, uh, encompasses thes patients. And to do this, we have many, many numerous data sets available, including clinical letters, blood tests, more advanced tests, which is genetics and imaging, which we can possibly, um, integrate into a patient journey which will allow us to understand the digital journey of that patient. I have called this the digital twin patient cohort to do a digital simulation of patient health journeys using data integration and analytics. This is a technique that has often been used in industrial manufacturing to understand the maintenance and service points for hardware and instruments. But we would be using this to stratify predict diseases. This'll would also be monitored and refined, using wearables and other types of complex data analysis to allow for, in the end, preemptive intervention to allow paradigm shifting. How we undertake medicine at this time, which is more reactive rather than proactive as infrastructure we are presently working on putting together what's it called the Data Safe haven or trusted research environment? One which with in the clinical environment, the university hospitals and curated and data manner, which allows us to enable data mining off the databases or, I should say, the trusted research environment within the clinical environment. Hopefully, we will then be able to anonymous that to allow ah used by academics and possibly also, uh, partnering industry to do further data mining and tool development, which we could then further field test again using our real world data base of patients that will be continually, uh, updating in our system. In the cardiovascular group, we have what's called the bricks cohort, which means biomedical research. Informatics Center for Cardiovascular Science, which was done, started long time even before I joined, uh, in 2010 which has today almost captured about 10,000 patients arm or who come through to Glenn Field Hospital for various treatments or and even those who have not on. We asked for their consent to their blood for genetics, but also for blood tests, uh, genomics testing, but also image ing as well as other consent. Hable medical information s so far there about 10,000 patients and we've been trying to extract and curate their data accordingly. Again, a za reminder of what the strengths of Leicester are. We have one of the largest and busiest trust with the very large, uh, patient cohort Ah, focused dr at the university, which allows for chronic diseases such as heart disease. I just mentioned our efforts on heart disease, uh which are about 10,000 patients ongoing right now. But we would wish thio include further chronic diseases such as diabetes, respiratory diseases, renal disease and further to understand the multi modality between these diseases so that we can understand how they >>interact as well. Finally, I like to talk about the lesser life science accelerator as well. This is a new project that was funded by >>the U started this January for three years. I'm the director for this and all the groups within the College of Life Sciences that are involved with healthcare but also clinical work are involved. And through this we hope to support innovative industrial partnerships and collaborations in the region, a swells nationally and further on into internationally as well. I realized that today is a talked to um, or business and commercial oriented audience. And we would welcome interest from your companies and partners to come to Leicester toe work with us on, uh, clinical health care data and to drive our agenda forward for this so that we can enable innovative research but also product development in partnership with you moving forward. Thank you for your time.

>> Announcer: From around the globe, it's theCUBE with coverage of KubeCon + CloudNativeCon Europe 2020 Virtual brought to you by Red Hat, the Cloud Native Computing Foundation and Ecosystem partners. >> Welcome back I'm Stu Miniman, this is theCUBE's coverage of KubeCon + CloudNativeCon Europe 2020, the virtual event. Of course, when we talk about Cloud Native we talk about Kubernetes there's a lot that's happening to modernize the infrastructure but a very important thing that we're going to talk about today is also what's happening up the stack, what sits on top of it and some of the new use cases and applications that are enabled by all of this modern environment and for that we're going to talk about artificial intelligence and machine learning or AI and ML as we tend to talk in the industry, so happy to welcome to the program. We have two first time guests joining us from Red Hat. First of all, we have Abhinav Joshi and Tushar Katarki they are both senior managers, part of the OpenShift group. Abhinav is in the product marketing and Tushar is in product management. Abhinav and Tushar thank you so much for joining us. >> Thanks a lot, Stu, we're glad to be here. >> Thanks Stu and glad to be here at KubeCon. >> All right, so Abhinav I mentioned in the intro here, modernization of the infrastructure is awesome but really it's an enabler. We know... I'm an infrastructure person the whole reason we have infrastructure is to be able to drive those applications, interact with my data and the like and of course, AI and ML are exciting a lot going on there but can also be challenging. So, Abhinav if I could start with you bring us inside your customers that you're talking to, what are the challenges, the opportunities? What are they seeing in this space? Maybe what's been holding them back from really unlocking the value that is expected? >> Yup, that's a very good question to kick off the conversation. So what we are seeing as an organization they typically face a lot of challenges when they're trying to build an AI/ML environment, right? And the first one is like a talent shortage. There is a limited amount of the AI, ML expertise in the market and especially the data scientists that are responsible for building out the machine learning and the deep learning models. So yeah, it's hard to find them and to be able to retain them and also other talents like a data engineer or app DevOps folks as well and the lack of talent can actually stall the project. And the second key challenge that we see is the lack of the readily usable data. So the businesses collect a lot of data but they must find the right data and make it ready for the data scientists to be able to build out, to be able to test and train the machine learning models. If you don't have the right kind of data to the predictions that your model is going to do in the real world is only going to be so good. So that becomes a challenge as well, to be able to find and be able to wrangle the right kind of data. And the third key challenge that we see is the lack of the rapid availability of the compute infrastructure, the data and machine learning, and the app dev tools for the various personas like a data scientist or data engineer, the software developers and so on that can also slow down the project, right? Because if all your teams are waiting on the infrastructure and the tooling of their choice to be provisioned on a recurring basis and they don't get it in a timely manner, it can stall the projects. And then the next one is the lack of collaboration. So you have all these kinds of teams that are involved in the AI project, and they have to collaborate with each other because the work one of the team does has a dependency on a different team like say for example, the data scientists are responsible for building the machine learning models and then what they have to do is they have to work with the app dev teams to make sure the models get integrated as part of the app dev processes and ultimately rolled out into the production. So if all these teams are operating in say silos and there is lack of collaboration between the teams, so this can stall the projects as well. And finally, what we see is the data scientists they typically start the machine learning modeling on their individual PCs or laptops and they don't focus on the operational aspects of the solution. So what this means is when the IT teams have to roll all this out into a production kind of deployment, so they get challenged to take all the work that has been done by the individuals and then be able to make sense out of it, be able to make sure that it can be seamlessly brought up in a production environment in a consistent way, be it on-premises, be it in the cloud or be it say at the edge. So these are some of the key challenges that we see that the organizations are facing, as they say try to take the AI projects from pilot to production. >> Well, some of those things seem like repetition of what we've had in the past. Obviously silos have been the bane of IT moving forward and of course, for many years we've been talking about that gap between developers and what's happening in the operation side. So Tushar, help us connect the dots, containers, Kubernetes, the whole DevOps movement. How is this setting us up to actually be successful for solutions like AI and ML? >> Sure Stu I mean, in fact you said it right like in the world of software, in the world of microservices, in the world of app modernization, in the world of DevOps in the past 10, 15 years, but we have seen this evolution revolution happen with containers and Kubernetes driving more DevOps behavior, driving more agile behavior so this in fact is what we are trying to say here can ease up the cable to EIML also. So the various containers, Kubernetes, DevOps and OpenShift for software development is directly applicable for AI projects to make them move agile, to get them into production, to make them more valuable to organization so that they can realize the full potential of AI. We already touched upon a few personas so it's useful to think about who the users are, who the personas are. Abhinav I talked about data scientists these are the people who obviously do the machine learning itself, do the modeling. Then there are data engineers who do the plumbing who provide the essential data. Data is so essential to machine learning and deep learning and so there are data engineers that are app developers who in some ways will then use the output of what the data scientists have produced in terms of models and then incorporate them into services and of course, none of these things are purely cast in stone there's a lot of overlap you could find that data scientists are app developers as well, you'll see some of app developers being data scientist later data engineer. So it's a continuum rather than strict boundaries, but regardless what all of these personas groups of people need or experts need is self service to that preferred tools and compute and storage resources to be productive and then let's not forget the IT, engineering and operations teams that need to make all this happen in an easy, reliable, available manner and something that is really safe and secure. So containers help you, they help you quickly and easily deploy a broad set of machine learning tools, data tools across the cloud, the hybrid cloud from data center to public cloud to the edge in a very consistent way. Teams can therefore alternatively modify, change a shared container images, machine learning models with (indistinct) and track changes. And this could be applicable to both containers as well as to the data by the way and be transparent and transparency helps in collaboration but also it could help with the regulatory reasons later on in the process. And then with containers because of the inherent processes solution, resource control and protection from threat they can also be very secure. Now, Kubernetes takes it to the next level first of all, it forms a cluster of all your compute and data resources, and it helps you to run your containerized tools and whatever you develop on them in a consistent way with access to these shared compute and centralized compute and storage and networking resources from the data center, the edge or the public cloud. They provide things like resource management, workload scheduling, multi-tendency controls so that you can be a proper neighbors if you will, and quota enforcement right? Now that's Kubernetes now if you want to up level it further if you want to enhance what Kubernetes offers then you go into how do you write applications? How do you actually make those models into services? And that's where... and how do you lifecycle them? And that's sort of the power of Helm and for the more Kubernetes operators really comes into the picture and while Helm helps in installing some of this for a complete life cycle experience. A kubernetes operator is the way to go and they simplify the acceleration and deployment and life cycle management from end-to-end of your entire AI, ML tool chain. So all in all organizations therefore you'll see that they need to dial up and define models rapidly just like applications that's how they get ready out of it quickly. There is a lack of collaboration across teams as Abhinav pointed out earlier, as you noticed that has happened still in the world of software also. So we're talking about how do you bring those best practices here to AI, ML. DevOps approaches for machine learning operations or many analysts and others have started calling as MLOps. So how do you kind of bring DevOps to machine learning, and fosters better collaboration between teams, application developers and IT operations and create this feedback loop so that the time to production and the ability to take more machine learning into production and ML-powered applications into production increase is significant. So that's kind of the, where I wanted shine the light on what you were referring to earlier, Stu. >> All right, Abhinav of course one of the good things about OpenShift is you have quite a lot of customers that have deployed the solution over the years, bring us inside some of your customers what are they doing for AI, ML and help us understand really what differentiates OpenShift in the marketplace for this solution set. >> Yeah, absolutely that's a very good question as well and we're seeing a lot of traction in terms of all kinds of industries, right? Be it the financial services like healthcare, automotive, insurance, oil and gas, manufacturing and so on. For a wide variety of use cases and what we are seeing is at the end of the day like all these deployments are focused on helping improve the customer experience, be able to automate the business processes and then be able to help them increase the revenue, serve their customers better, and also be able to save costs. If you go to openshift.com/ai-ml it's got like a lot of customer stories in there but today I will not touch on three of the customers we have in terms of the different industries. The first one is like Royal Bank of Canada. So they are a top global financial institution based out of Canada and they have more than 17 million clients globally. So they recently announced that they build out an AI-powered private cloud platform that was based on OpenShift as well as the NVIDIA DGX AI compute system and this whole solution is actually helping them to transform the customer banking experience by being able to deliver an AI-powered intelligent apps and also at the same time being able to improve the operational efficiency of their organization. And now with this kind of a solution, what they're able to do is they're able to run thousands of simulations and be able to analyze millions of data points in a fraction of time as compared to the solution that they had before. Yeah, so like a lot of great work going on there but now the next one is the ETCA healthcare. So like ETCA is one of the leading healthcare providers in the country and they're based out of the Nashville, Tennessee. And they have more than 184 hospitals as well as more than 2,000 sites of care in the U.S. as well as in the UK. So what they did was they developed a very innovative machine learning power data platform on top of our OpenShift to help save lives. The first use case was to help with the early detection of sepsis like it's a life-threatening condition and then more recently they've been able to use OpenShift in the same kind of stack to be able to roll out the new applications that are powered by machine learning and deep learning let say to help them fight COVID-19. And recently they did a webinar as well that had all the details on the challenges they had like how did they go about it? Like the people, process and technology and then what the outcomes are. And we are proud to be a partner in the solution to help with such a noble cause. And the third example I want to share here is the BMW group and our partner DXC Technology what they've done is they've actually developed a very high performing data-driven data platform, a development platform based on OpenShift to be able to analyze the massive amount of data from the test fleet, the data and the speed of the say to help speed up the autonomous driving initiatives. And what they've also done is they've redesigned the connected drive capability that they have on top of OpenShift that's actually helping them provide various use cases to help improve the customer experience. With the customers and all of the customers are able to leverage a lot of different value-add services directly from within the car, their own cars. And then like last year at the Red Hat Summit they had a keynote as well and then this year at Summit, they were one of the Innovation Award winners. And we have a lot more stories but these are the three that I thought are actually compelling that I should talk about here on theCUBE. >> Yeah Abhinav just a quick follow up for you. One of the things of course we're looking at in 2020 is how has the COVID-19 pandemic, people working from home how has that impacted projects? I have to think that AI and ML are one of those projects that take a little bit longer to deploy, is it something that you see are they accelerating it? Are they putting on pause or are new project kicking off? Anything you can share from customers you're hearing right now as to the impact that they're seeing this year? >> Yeah what we are seeing is that the customers are now even more keen to be able to roll out the digital (indistinct) but we see a lot of customers are now on the accelerated timeline to be able to say complete the AI, ML project. So yeah, it's picking up a lot of momentum and we talk to a lot of analyst as well and they are reporting the same thing as well. But there is the interest that is actually like ramping up on the AI, ML projects like across their customer base. So yeah it's the right time to be looking at the innovation services that it can help improve the customer experience in the new virtual world that we live in now about COVID-19. >> All right, Tushar you mentioned that there's a few projects involved and of course we know at this conference there's a very large ecosystem. Red Hat is a strong contributor to many, many open source projects. Give us a little bit of a view as to in the AI, ML space who's involved, which pieces are important and how Red Hat looks at this entire ecosystem? >> Thank you, Stu so as you know technology partnerships and the power of open is really what is driving the technology world these days in any ways and particularly in the AI ecosystem. And that is mainly because one of the machine learning is in a bootstrap in the past 10 years or so and a lot of that emerging technology to take advantage of the emerging data as well as compute power has been built on the kind of the Linux ecosystem with openness and languages like popular languages like Python, et cetera. And so what you... and of course tons of technology based in Java but the point really here is that the ecosystem plays a big role and open plays a big role and that's kind of Red Hat's best cup of tea, if you will. And that really has plays a leadership role in the open ecosystem so if we take your question and kind of put it into two parts, what is the... what we are doing in the community and then what we are doing in terms of partnerships themselves, commercial partnerships, technology partnerships we'll take it one step at a time. In terms of the community itself, if you step back to the three years, we worked with other vendors and users, including Google and NVIDIA and H2O and other Seldon, et cetera, and both startups and big companies to develop this Kubeflow ecosystem. The Kubeflow is upstream community that is focused on developing MLOps as we talked about earlier end-to-end machine learning on top of Kubernetes. So Kubeflow right now is in 1.0 it happened a few months ago now it's actually at 1.1 you'll see that coupon here and then so that's the Kubeflow community in addition to that we are augmenting that with the Open Data Hub community which is something that extends the capabilities of the Kubeflow community to also add some of the data pipelining stuff and some of the data stuff that I talked about and forms a reference architecture on how to run some of this on top of OpenShift. So the Open Data Hub community also has a great way of including partners from a technology partnership perspective and then tie that with something that I mentioned earlier, which is the idea of Kubernetes operators. Now, if you take a step back as I mentioned earlier, Kubernetes operators help manage the life cycle of the entire application or containerized application including not only the configuration on day one but also day two activities like update and backups, restore et cetera whatever the application needs. Afford proper functioning that a "operator" needs for it to make sure so anyways, the Kubernetes operators ecosystem is also flourishing and we haven't faced that with the OperatorHub.io which is a community marketplace if you will, I don't call it marketplace a community hub because it's just comprised of community operators. So the Open Data Hub actually can take community operators and can show you how to run that on top of OpenShift and manage the life cycle. Now that's the reference architecture. Now, the other aspect of it really is as I mentioned earlier is the commercial aspect of it. It is from a customer point of view, how do I get certified, supported software? And to that extent, what we have is at the top of the... from a user experience point of view, we have certified operators and certified applications from the AI, ML, ISV community in the Red Hat marketplace. And from the Red Hat marketplace is where it becomes easy for end users to easily deploy these ISVs and manage the complete life cycle as I said. Some of the examples of these kinds of ISVs include startups like H2O although H2O is kind of well known in certain sectors PerceptiLabs, Cnvrg, Seldon, Starburst et cetera and then on the other side, we do have other big giants also in this which includes partnerships with NVIDIA, Cloudera et cetera that we have announced, including our also SaaS I got to mention. So anyways these provide... create that rich ecosystem for data scientists to take advantage of. A TEDx Summit back in April, we along with Cloudera, SaaS Anaconda showcased a live demo that shows all these things to working together on top of OpenShift with this operator kind of idea that I talked about. So I welcome people to go and take a look the openshift.com/ai-ml that Abhinav already referenced should have a link to that it take a simple Google search might download if you need some of that, but anyways and the other part of it is really our work with the hardware OEMs right? And so obviously NVIDIA GPUs is obviously hardware, and that accelerations is really important in this world but we are also working with other OEM partners like HP and Dell to produce this accelerated AI platform that turnkey solutions to run your data-- to create this open AI platform for "private cloud" or the data center. The other thing obviously is IBM, IBM Cloud Pak for Data is based on OpenShift that has been around for some time and is seeing very good traction, if you think about a very turnkey solution, IBM Cloud Pak is definitely kind of well ahead in that and then finally Red Hat is about driving innovation in the open-source community. So, as I said earlier, we are doing the Open Data Hub which that reference architecture that showcases a combination of upstream open source projects and all these ISV ecosystems coming together. So I welcome you to take a look at that at opendatahub.io So I think that would be kind of the some total of how we are not only doing open and community building but also doing certifications and providing to our customers that assurance that they can run these tools in production with the help of a rich certified ecosystem. >> And customer is always key to us so that's the other thing that the goal here is to provide our customers with a choice, right? They can go with open source or they can go with a commercial solution as well. So you want to make sure that they get the best in cloud experience on top of our OpenShift and our broader portfolio as well. >> All right great, great note to end on, Abhinav thank you so much and Tushar great to see the maturation in this space, such an important use case. Really appreciate you sharing this with theCUBE and Kubecon community. >> Thank you, Stu. >> Thank you, Stu. >> Okay thank you and thanks a lot and have a great rest of the show. Thanks everyone, stay safe. >> Thanks you and stay with us for a lot more coverage from KubeCon + CloudNativeCon Europe 2020, the virtual edition I'm Stu Miniman and thank you as always for watching theCUBE. (soft upbeat music plays)

(upbeat electronic music) >> Narrator: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Okay, hello everyone. I'm John Furrier with theCUBE. We're here with Meet the Analysts segment Sunday morning. We've got everyone around the world here to discuss a bit of the news around the EU killing the privacy deal, striking it down, among other topics around, you know, data privacy and global commerce. We got great guests here, Ray Wang, CEO of Constellation Research. Bill Mew, founder and CEO of Cyber Crisis Management from the Firm Crisis Team. And JD, CEO of Spearhead Management. JD, I can let you say your name because I really can't pronounce it. How do I (laughs) pronounce it, doctor? >> I wouldn't even try it unless you are Dutch, otherwise it will seriously hurt your throat. (Ray laughing) So, JD works perfect for me. >> Doctor Drooghaag. >> And Sarbjeet Johal, who's obviously an influencer, a cloud awesome native expert. Great, guys. Great to have you on, appreciate it, thanks for comin' on. And Bill, thank you for initiating this, I appreciate all your tweets. >> Happy Sunday. (Bill laughing) >> You guys have been really tweeting up a storm, I want to get everyone together, kind of as an analyst, Meet the Analyst segment. Let's go through with it. The news is the EU and U.S. Privacy Shield for data struck down by the court, that's the BBC headline. Variety of news, different perspectives, you've got an American perspective and you've got an international perspective. Bill, we'll start with you. What does this news mean? I mean, basically half the people in the world probably don't know what the Privacy Shield means, so why is this ruling so important, and why should it be discussed? >> Well, thanks to sharing between Europe and America, it's based on a two-way promise that when data goes from Europe to America, the Americans promise to respect our privacy, and when data goes form America to Europe, the Europeans promise to respect the American privacy. Unfortunately, there are big cultural differences between the two blocks. The Europeans have a massive orientation around privacy as a human right. And in the U.S., there's somewhat more of a prioritization on national security, and therefore for some time there's been a mismatch here, and it could be argued that the Americans haven't been living up to their promise because they've had various different laws, and look how much talk about FISA and the Cloud Act that actually contravene European privacy and are incompatible with the promise Americans have given. That promise, first of all, was in the form of a treaty called Safe Harbor. This went to court and was struck down. It was replaced by Privacy Shield, which was pretty much the same thing really, and that has recently been to the court as well, and that has been struck down. There now is no other means of legally sharing data between Europe and America other than what are being called standard contractual clauses. This isn't a broad treaty between two nations, these are drawn by each individual country. But also in the ruling, they said that standard contractual clauses could not be used by any companies that were subject to mass surveillance. And actually in the U.S., the FISA courts enforce a level of mass surveillance through all of the major IT firms, of all major U.S. telcos, cloud firms, or indeed, social media firms. So, this means that for all of the companies out there and their clients, business should be carrying on as usual apart from if you're one of those major U.S. IT firms, or one of their clients. >> So, why did this come about? Was there like a major incident? Why now, was it in the court, stuck in the courts? Were people bitchin' and moanin' about it? Why did this go down, what's the real issue? >> For those of us who have been following this attentively, things have been getting more and more precarious for a number of years now. We've had a situation where there are different measures being taken in the U.S., that have continued to erode the different protections that there were for Europeans. FISA is an example that I've given, and that is the sort of secret courts and secret warrants that are issued to seize data without anyone's knowledge. There's the Cloud Act, which is a sort of extrajudicial law that means that warrants can be served in America to U.S. organizations, and they have to hand over data wherever that data resides, anywhere in the world. So, data could exist on a European server, if it was under the control of an American company, they'd have to hand that over. So, whilst FISA is in direct conflict with the promises that the Americans made, things like the Cloud Act are not only in controversion with the promise they've made, there's conflicting law here, because if you're a U.S. subsidiary of a big U.S. firm, and you're based in Europe, who do you obey, the European law that says you can't hand it over because of GDPR, or the American laws that says they've got extrajudicial control, and that you've got to hand it over. So, it's made things a complete mess. And to say has this stuff, hasn't really happened? No, there's been a gradual erosion, and this has been going through the courts for a number of years. And many of us have seen it coming, and now it just hit us. >> So, if I get you right in what you're saying, it's basically all this mishmash of different laws, and there's no coherency, and consistency, is that the core issue? >> On the European side you could argue there's quite a lot of consistency, because we uphold people's privacy, in theory. But there have been incidents which we could talk about with that, but in theory, we hold your rights dear, and also the rights of Europeans, so everyone's data should be safe here from the sort of mass surveillance we're seeing. In the U.S., there's more of a direct conflict between everything, including there's been a, in his first week in the White House, Donald Trump signed an executive order saying that the Privacy Act in the U.S., which had been the main protection for people in the U.S., no longer applied to non-U.S. citizens. Which was, if you wanted try and cause a storm, and if you wanted to try and undermine the treaty, there's no better way of doing it than that. >> A lot of ways, Ray, I mean simplify this for me, because I'm a startup, I'm hustlin', or I'm a big company, I don't even know who runs the servers anymore, and I've got data stored in multiple clouds, I got in regions, and Oracle just announced more regions, you got Amazon, a gazillion regions, I could be on-premise. I mean bottom line, what is this about? I mean, and -- >> Bill's right, I mean when Max Schrems, the Austrian. Bill's right, when Max Schrems the Austrian activist actually filed his case against Facebook for where data was being stored, data residency wasn't as popular. And you know, what it means for companies that are in the cloud is that you have to make sure your data's being stored in the region, and following those specific region rules, you can't skirt those rules anymore. And I think the cloud companies know that this has been coming for some time, and that's why there's been announced in a lot of regions, a lot of areas that are actually happening, so I think that's the important part. But going back to Bill's earlier point, which is important, is America is basically the Canary Islands of privacy, right? Privacy is there, but it isn't there in a very, very explicit sense, and I think we've been skirting the rules for quite some time, because a lot of our economy depends on that data, and the marketing of the data. And so we often confuse privacy with consent, and also with value exchange, and I think that's part of the problem of what's going on here. Companies that have been building their business models on free data, free private data, free personally identifiable data information are the ones that are at risk! And I think that's what's going on here. >> It's the classic Facebook issue, you're the product, and the data is your product. Well, I want to get into what this means, 'cause my personal take away, not knowing the specifics, and just following say, cyber security for instance, one of the tenets there is that data sharing is an invaluable, important ethos in the community. Now, everyone has their own privacy, or security data, they don't want to let everyone know about their exploits but, but it's well known in the security world that sharing data with each other, different companies and countries is actually a good thing. So, the question that comes in my mind, is this really about data sharing or data privacy, or both? >> I think it's about both. And actually what the ruling is saying here is, all we're asking from the European side is please stop spying on us and please give us a level of equal protection that you give to your own citizens. Because data comes from America to Europe, whatever that data belongs to, a U.S. citizen or a European citizen, it's given equal protection. It is only if data goes in the other direction, where you have secret courts, secret warrants, seizure of data on this massive scale, and also a level of lack of equivalence that has been imposed. And we're just asking that once you've sorted out a few of those things, we'd say everything's back on the table, away we go again! >> Why don't we merge the EU with the United States? Wouldn't that solve the problem? (Bill laughing) >> We just left Europe! (laughs heartily) >> Actually I always -- >> A hostile takeover of the UK maybe, the 52nd state. (Bill laughing loudly) >> I always pick on Bill, like Bill, you got all screaming loud and clear about all these concerns, but UKs trying to get out of that economic union. It is a union at the end of the day, and I think the problem is the institutional mismatch between the EU and U.S., U.S. is old democracy, bigger country, population wise, bigger economy. Whereas Europe is several countries trying to put together, band together as one entity, and the institutions are new, like you know, they're 15 years old, right? They're maturing. I think that's where the big mismatch is and -- >> Well, Ray, I want to get your thoughts on this, Ray wrote a book, I forget what year it was, this digital disruption, basically it was digital transformation before it was actually a trend. I mean to me it's like, do you do the process first and then figure out where the value extraction is, and this may be a Silicon Valley or an American thing, but go create value, then figure out how to create process or understand regulations. So, if data and entrepreneurship is going to be a new modern era of value, why wouldn't we want to create a rule based system that's open and enabling, and not restrictive? >> So, that's a great point, right? And the innovation culture means you go do it first, and you figure out the rules later, and that's been a very American way of getting things done, and very Silicon Valley in our perspective, not everyone, but I think in general that's kind of the trend. I think the challenge here is that we are trading privacy for security, privacy for convenience, privacy for personalization, right? And on the security level, it's a very different conversation than what it is on the consumer end, you know, personalization side. On the security side I think most Americans are okay with a little bit of "spying," at least on your own side, you know, to keep the country safe. We're not okay with a China level type of spying, which we're not sure exactly what that means or what's enforceable in the courts. We look like China to the Europeans in the way we treat privacy, and I think that's the perspective we need to understand because Europeans are very explicit about how privacy is being protected. And so this really comes back to a point where we actually have to get to a consent model on privacy, as to knowing what data is being shared, you have the right to say no, and when you have the right to say no. And then if you have a value exchange on that data, then it's really like sometimes it's monetary, sometimes it's non-monetary, sometimes there's other areas around consensus where you can actually put that into place. And I think that's what's missing at this point, saying, you know, "Do we pay for your data? Do we explicitly get your consent first before we use it?" And we haven't had that in place, and I think that's where we're headed towards. And you know sometimes we actually say privacy should be a human right, it is in the UN Charter, but we haven't figured out how to enforce it or talk about it in the digital age. And so I think that's the challenge. >> Okay, people, until they lose it, they don't really understand what it means. I mean, look at Americans. I have to say that we're idiots on this front, (Bill chuckling) but you know, the thing is most people don't even understand how much value's getting sucked out of their digital exhaust. Like, our kids, TikTok and whatnot. So I mean, I get that, I think there's some, there's going to be blow back for America for sure. I just worry it's going to increase the cost of doing business, and take away from the innovation for citizen value, the people, because at the end of the day, it's for the people right? I mean, at the end of the day it's like, what's my privacy mean if I lose value? >> Even before we start talking about the value of the data and the innovation that we can do through data use, you have to understand the European perspective here. For the European there's a level of double standards and an erosion of trust. There's double standards in the fact that in California you have new privacy regulations that are slightly different to GDPR, but they're very much GDPR like. And if the boot was on the other foot, to say if we were spying on Californians and looking at their personal data, and contravening CCPA, the Californians would be up in arms! Likewise if we having promised to have a level of equality, had enacted a local rule in Europe that said that when data from America's over here, actually the privacy of Americans counts for nothing, we're only going to prioritize the privacy of Europeans. Again, the Americans would be up in arms! And therefore you can see that there are real double standards here that are a massive issue, and until those addressed, we're not going to trust the Americans. And likewise, the very fact that on a number of occasions Americans have signed up to treaties and promised to protect our data as they did with Safe Harbor, as they did with Privacy Shield, and then have blatantly, blatantly failed to do so means that actually to get back to even a level playing field, where we were, you have a great deal of trust to overcome! And the thing from the perspective of the big IT firms, they've seen this coming for a long time, as Ray was saying, and they sought to try and have a presence in Europe and other things. But the way this ruling has gone is that, I'm sorry, that isn't going to be sufficient! These big IT firms based in the U.S. that have been happy to hand over data, well some of them maybe more happy than others, but they all need to hand over data to the NSA or the CIA. They've been doing this for some time now without actually respecting this data privacy agreement that has existed between the two trading blocks. And now they've been called out, and the position now is that the U.S. is no longer trusted, and neither are any of these large American technology firms. And until the snooping stops and equality is introduced, they can now no longer, even from their European operations, they can no longer use standard contractual clauses to transfer data, which is going to be a massive restriction on their business. And if they had any sense, they'd be lobbying very, very hard right now to the Senate, to the House, to try and persuade U.S. lawmakers actually to stick to some these treaties! To stop introducing really mad laws that ride roughshod over other people's privacy, and have a certain amount of respect. >> Let's let JD weigh in, 'cause he just got in, sorry on the video, I made him back on a host 'cause he dropped off. Just, Bill, real quick, I mean I think it's like when, you know, I go to Europe there's the line for Americans, there's the line for EU. Or EU and everybody else. I mean we might be there, but ultimately this has to be solved. So, JD, I want to let you weigh in, Germany has been at the beginning forefront of privacy, and they've been hardcore, and how's this all playing out in your perspective? >> Well, the first thing that we have to understand is that in Germany, there is a very strong law for regulation. Germans panic as soon as they know regulation, so they need to understand what am I allowed to do, and what am I not allowed to do. And they expect the same from the others. For the record I'm not German, but I live in Germany for some 20 years, so I got a bit of a feeling for them. And that sense of need for regulation has spread very fast throughout the European Union, because most of the European member states of the European Union consider this, that it makes sense, and then we found that Britain had already a very good framework for privacy, so GDPR itself is very largely based on what the United Kingdom already had in place with their privacy act. Moving forward, we try to find agreement and consensus with other countries, especially the United States because that's where most of the tech providers are, only to find out, and that is where it started to go really, really bad, 2014, when the mass production by Edward Snowden came out, to find out it's not data from citizens, it's surveillance programs which include companies. I joined a purchasing conference a few weeks ago where the purchase of a large European multinational, where the purchasing director explicitly stated that usage of U.S. based tech providers for sensitive data is prohibited as a result of them finding out that they have been under surveillance. So, it's not just the citizens, there's mass -- >> There you have it, guys! We did trust you! We did have agreements there that you could have abided by, but you chose not to, you chose to abuse our trust! And you're now in a position where you are no longer trusted, and unless you can lobby your own elected representatives to actually recreate a level playing field, we're not going to continue trusting you. >> So, I think really I -- >> Well I mean that, you know, innovation has to come from somewhere, and you know, has to come from America if that's the case, you guys have to get on board, right? Is that what it -- >> Innovation without trust? >> Is that the perspective? >> I don't think it's a country thing, I mean like, it's not you or them, I think everybody -- >> I'm just bustin' Bill's chops there. >> No, but I think everybody, everybody is looking for what the privacy rules are, and that's important. And you can have that innovation with consent, and I think that's really where we're going to get to. And this is why I keep pushing that issue. I mean, privacy should be a fundamental right, and how you get paid for that privacy is interesting, or how you get compensated for that privacy if you know what the explicit value exchange is. What you're talking about here is the surveillance that's going on by companies, which shouldn't be happening, right? That shouldn't be happening at the company level. At the government level I can understand that that is happening, and I think those are treaties that the governments have to agree upon as to how much they're going to impinge on our personal privacy for the trade off for security, and I don't think they've had those discussions either. Or they decided and didn't tell any of their citizens, and I think that's probably more likely the case. >> I mean, I think what's happening here, Bill, you guys were pointing out, and Ray, you articulated there on the other side, and my kind of colorful joke aside, is that we're living a first generation modern sociology problem. I mean, this is a policy challenge that extends across multiple industries, cyber security, citizen's rights, geopolitical. I mean when would look, and even when we were doing CUBE events overseas in Europe, in North American companies we'd call it abroad, we'd just recycle the American program, and we found there's so much localization value. So, Ray, this is the digital disruption, it's the virtualization of physical for digital worlds, and it's a lot of network theory, which is computer science, a lot of sociology. This is a modern challenge, and I don't think it so much has a silver bullet, it's just that we need smart people working on this. That's my take away! >> I think we can describe the ideal endpoint being somewhere we have meaningful protection alongside the maximization of economic and social value through innovation. So, that should be what we would all agree would be the ideal endpoint. But we need both, we need meaningful protection, and we need the maximization of economic and social value through innovation! >> Can I add another axis? Another axis, security as well. >> Well, I could -- >> I put meaningful protection as becoming both security and privacy. >> Well, I'll speak for the American perspective here, and I won't speak, 'cause I'm not the President of the United States, but I will say as someone who's been from Silicon Valley and the east coast as a technical person, not a political person, our lawmakers are idiots when it comes to tech, just generally. (Ray laughing) They're not really -- (Bill laughing loudly) >> They really don't understand. They really don't understand the tech at all! >> So, the problem is -- >> I'm not claiming ours are a great deal better. (laughs) >> Well, this is why I think this is a modern problem. Like, the young people I talk to are like, "Why do we have this rules?" They're all lawyers that got into these positions of Congress on the American side, and so with the American JEDI Contract you guys have been following very closely is, it's been like the old school Oracle, IBM, and then Amazon is leading with an innovative solution, and Microsoft has come in and re-pivoted. And so what you have is a fight for the digital future of citizenship! And I think what's happening is that we're in a massive societal transition, where the people in charge don't know what the hell they're talkin' about, technically. And they don't know who to tap to solve the problems, or even shape or frame the problems. Now, there's pockets of people that are workin' on it, but to me as someone who looks at this saying, it's a pretty simple solution, no one's ever seen this before. So, there's a metaphor you can draw, but it's a completely different problem space because it's, this is all digital, data's involved. >> We've got a lobbyists out there, and we've got some tech firms spending an enormous amount of lobbying. If those lobbyists aren't trying to steer their representatives in the right direction to come up with law that aren't going to massively undermine trade and data sharing between Europe and America, then they're making a big mistake, because we got here through some really dumb lawmaking in the U.S., I mean, there are none of the laws in Europe that are a problem here. 'Cause GDPR isn't a great difference, a great deal different from some of the laws that we have already in California and elsewhere. >> Bill, Bill. >> The laws that are at issue here -- >> Bill, Bill! You have to like, back up a little bit from that rhetoric that EU is perfect and U.S. is not, that's not true actually. >> I'm not saying we're perfect! >> No, no, you say that all the time. >> But I'm saying there's a massive lack of innovation. Yeah, yeah. >> I don't, I've never said it! >> Arm wrestle! >> Yes, yes. >> When I'm being critical of some of the dumb laws in the U.S, (Sarbjeet laughing) I'm not saying Europe is perfect. What we're trying to say is that in this particular instance, I said there was an equal balance here between meaningful protection and the maximization of economic and social value. On the meaningful protection side, America's got it very wrong in terms of the meaningful protection it provides to civil European data. On the maximization of economic and social value, I think Europe's got it wrong. I think there are a lot of things we could do in Europe to actually have far more innovation. >> Yeah. >> It's a cultural issue. The Germans want rules, that's what they crave for. America's the other way, we don't want rules, I mean, pretty much is a rebel society. And that's kind of the ethos of most tech companies. But I think you know, to me the media, there's two things that go on with this tech business. The company's themselves have to be checked by say, government, and I believe in not a lot of regulation, but enough to check the power of bad actors. Media so called "checking power", both of these major roles, they don't really know what they're talking about, and this is back to the education piece. The people who are in the media so called "checking power" and the government checking power assume that the companies are bad. Right, so yeah, because eight out of ten companies like Amazon, actually try to do good things. If you don't know what good is, you don't really, (laughs) you know, you're in the wrong game. So, I think media and government have a huge education opportunity to look at this because they don't even know what they're measuring. >> I support the level of innovation -- >> I think we're unreeling from the globalization. Like, we are undoing the globalization, and that these are the side effects, these conflicts are a side effect of that. >> Yeah, so all I'm saying is I support the focus on innovation in America, and that has driven an enormous amount of wealth and value. What I'm questioning here is do you really need to spy on us, your allies, in order to help that innovation? And I'm starting to, I mean, do you need mass surveillance of your allies? I mean, I can see you may want to have some surveillance of people who are a threat to you, but wait, guys, we're meant to be on your side, and you haven't been treating our privacy with a great deal of respect! >> You know, Saudi Arabia was our ally. You know, 9/11 happened because of them, their people, right? There is no ally here, and there is no enemy, in a way. We don't know where the rogue actors are sitting, like they don't know, they can be within the walls -- >> It's well understood I think, I agree, sorry. it's well understood that nation states are enabling terrorist groups to take out cyber attacks. That's well known, the source enables it. So, I think there's the privacy versus -- >> I'm not sure it's true in your case that it's Europeans that's doing this though. >> No, no, well you know, they share -- >> I'm a former officer in the Royal Navy, I've stood shoulder to shoulder with my U.S. counterparts. I put my life on the line on NATO exercises in real war zones, and I'm now a disabled ex-serviceman as a result of that. I mean, if I put my line on the line shoulder to shoulder with Americans, why is my privacy not respected? >> Hold on -- >> I feel it's, I was going to say actually that it's not that, like even the U.S., right? Part of the spying internally is we have internal actors that are behaving poorly. >> Yeah. >> Right, we have Marxist organizations posing as, you know, whatever it is, I'll leave it at that. But my point being is we've got a lot of that, every country has that, every country has actors and citizens and people in the system that are destined to try to overthrow the system. And I think that's what that surveillance is about. The question is, we don't have treaties, or we didn't have your explicit agreements. And that's why I'm pushing really hard here, like, they're separating privacy versus security, which is the national security, and privacy versus us as citizens in terms of our data being basically taken over for free, being used for free. >> John: I agree with that. >> That I think we have some agreement on. I just think that our governments haven't really had that conversation about what surveillance means. Maybe someone agreed and said, "Okay, that's fine. You guys can go do that, we won't tell anybody." And that's what it feels like. And I don't think we deliberately are saying, "Hey, we wanted to spy on your citizens." I think someone said, "Hey, there's a benefit here too." Otherwise I don't think the EU would have let this happen for that long unless Max had made that case and started this ball rolling, so, and Edward Snowden and other folks. >> Yeah, and I totally support the need for security. >> I want to enter the -- >> I mean we need to, where there are domestic terrorists, we need to stop them, and we need to have local action in UK to stop it happening here, and in America to stop it happening there. But if we're doing that, there is absolutely no need for the Americans to be spying on us. And there's absolutely no need for the Americans to say that privacy applies to U.S. citizens only, and not to Europeans, these are daft, it's just daft! >> That's a fair point. I'm sure GCHQ and everyone else has this covered, I mean I'm sure they do. (laughs) >> Oh, Bill, I know, I've been involved, I've been involved, and I know for a fact the U.S. and the UK are discussing I know a company called IronNet, which is run by General Keith Alexander, funded by C5 Capital. There's a lot of collaboration, because again, they're tryin' to get their arms around how to frame it. And they all agree that sharing data for the security side is super important, right? And I think IronNet has this thing called Iron Dome, which is essentially like they're saying, hey, we'll just consistency around the rules of shared data, and we can both, everyone can have their own little data. So, I think there's recognition at the highest levels of some smart people on both countries. (laughs) "Hey, let's work together!" The issue I have is just policy, and I think there's a lot of clustering going on. Clustered here around just getting out of their own way. That's my take on that. >> Are we a PG show? Wait, are we a PG show? I just got to remember that. (laughs) (Bill laughing) >> It's the internet, there's no regulation, there's no rules! >> There's no regulation! >> The European rules or is it the American rules? (Ray laughing) >> I would like to jump back quickly to the purpose of the surveillance, and especially when mass surveillance is done under the cover of national security and terror prevention. I worked with five clients in the past decade who all have been targeted under mass surveillance, which was revealed by Edward Snowden, and when they did their own investigation, and partially was confirmed by Edward Snowden in person, they found out that their purchasing department, their engineering department, big parts of their pricing data was targeted in mass surveillance. There's no way that anyone can explain me that that has anything to do with preventing terror attacks, or finding the bad guys. That is economical espionage, you cannot call it in any other way. And that was authorized by the same legislation that authorizes the surveillance for the right purposes. I'm all for fighting terror, and anything that can help us prevent terror from happening, I would be the first person to welcome it. But I do not welcome when that regulation is abused for a lot of other things under the cover of national interest. I understand -- >> Back to the lawmakers again. And again, America's been victim to the Chinese some of the individual properties, well documented, well known in tech circles. >> Yeah, but just 'cause the Chinese have targeted you doesn't give you free right to target us. >> I'm not saying that, but its abuse of power -- >> If the U.S. can sort out a little bit of reform, in the Senate and the House, I think that would go a long way to solving the issues that Europeans have right now, and a long way to sort of reaching a far better place from which we can all innovate and cooperate. >> Here's the challenge that I see. If you want to be instrumenting everything, you need a closed society, because if you have a free country like America and the UK, a democracy, you're open. If you're open, you can't stop everything, right? So, there has to be a trust, to your point, Bill. As to me that I'm just, I just can't get my arms around that idea of complete lockdown and data surveillance because I don't think it's gettable in the United States, like it's a free world, it's like, open. It should be open. But here we've got the grids, and we've got the critical infrastructure that should be protected. So, that's one hand. I just can't get around that, 'cause once you start getting to locking down stuff and measuring everything, that's just a series of walled gardens. >> So, to JD's point on the procurement data and pricing data, I have been involved in some of those kind of operations, and I think it's financial espionage that they're looking at, financial security, trying to figure out a way to track down capital flows and what was purchased. I hope that was it in your client's case, but I think it's trying to figure out where the money flow is going, more so than trying to understand the pricing data from competitive purposes. If it is the latter, where they're stealing the competitive information on pricing, and data's getting back to a competitor, that is definitely a no-no! But if it's really to figure out where the money trail went, which is what I think most of those financial analysts are doing, especially in the CIA, or in the FBI, that's really what that probably would have been. >> Yeah, I don't think that the CIA is selling the data to your competitors, as a company, to Microsoft or to Google, they're not selling it to each other, right? They're not giving it to each other, right? So, I think the one big problem I studied with FISA is that they get the data, but how long they can keep the data and how long they can mine the data. So, they should use that data as exhaust. Means like, they use it and just throw it away. But they don't, they keep mining that data at a later date, and FISA is only good for five years. Like, I learned that every five years we revisit that, and that's what happened this time, that we renewed it for six years this time, not five, for some reason one extra year. So, I think we revisit all these laws -- >> Could be an election cycle. >> Huh? >> Could be an election cycle maybe. (laughs) >> Yes, exactly! So, we revisit all these laws with Congress and Senate here periodically just to make sure that they are up to date, and that they're not infringing on human rights, or citizen's rights, or stuff like that. >> When you say you update to check they're not conflicting with anything, did you not support that it was conflicting with Privacy Shield and some of the promises you made to Europeans? At what point did that fail to become obvious? >> It does, because there's heightened urgency. Every big incident happens, 9/11 caused a lot of new sort of like regulations and laws coming into the picture. And then the last time, that the Russian interference in our election, that created some sort of heightened urgency. Like, "We need to do something guys here, like if some country can topple our elections, right, that's not acceptable." So, yeah -- >> And what was it that your allies did that caused you to spy on us and to downgrade our privacy? >> I'm not expert on the political systems here. I think our allies are, okay, loose on their, okay, I call it village politics. Like, world is like a village. Like it's so only few countries, it's not millions of countries, right? That's how I see it, a city versus a village, and that's how I see the countries, like village politics. Like there are two camps, like there's Russia and China camp, and then there's U.S. camp on the other side. Like, we used to have Russia and U.S., two forces, big guys, and they managed the whole world balance somehow, right? Like some people with one camp, the other with the other, right? That's how they used to work. Now that Russia has gone, hold on, let me finish, let me finish. >> Yeah. >> Russia's gone, there's this void, right? And China's trying to fill the void. Chinese are not like, acting diplomatic enough to fill that void, and there's, it's all like we're on this imbalance, I believe. And then Russia becomes a rogue actor kind of in a way, that's how I see it, and then they are funding all these bad people. You see that all along, like what happened in the Middle East and all that stuff. >> You said there are different camps. We thought we were in your camp! We didn't expect to be spied on by you, or to have our rights downgraded by you. >> No, I understand but -- >> We thought we were on your side! >> But, but you have to guys to trust us also, like in a village. Let me tell you, I come from a village, that's why I use the villager as a hashtag in my twitter also. Like in village, there are usually one or two families which keep the village intact, that's our roles. >> Right. >> Like, I don't know if you have lived in a village or not -- >> Well, Bill, you're making some great statements. Where's the evidence on the surveillance, where can people find more information on this? Can you share? >> I think there's plenty of evidence, and I can send some stuff on, and I'm a little bit shocked given the awareness of the FISA Act, the Cloud Act, the fact that these things are in existence and they're not exactly unknown. And many people have been complaining about them for years. I mean, we've had Safe Harbor overturned, we've had Privacy Shield overturned, and these weren't just on a whim! >> Yeah, what does JD have in his hand? I want to know. >> The Edward Snowden book! (laughs) >> By Edward Snowden, which gives you plenty. But it wasn't enough, and it's something that we have to keep in mind, because we can always claim that whatever Edward Snowden wrote, that he made it up. Every publication by Edward Snowden is an avalanche of technical confirmation. One of the things that he described about the Cisco switches, which Bill prefers to quote every time, which is a proven case, there were bundles of researchers saying, "I told you guys!" Nobody paid attention to those researchers, and Edward Snowden was smart enough to get the mass media representation in there. But there's one thing, a question I have for Sabjeet, because in the two parties strategy, it is interesting that you always take out the European Union as part. And the European Union is a big player, and it will continue to grow. It has a growing amount of trade agreements with a growing amount of countries, and I still hope, and I think think Bill -- >> Well, I think the number of countries is reducing, you've just lost one! >> Only one. (Bill laughing loudly) Actually though, those are four countries under one kingdom, but that's another point. (Bill chortling heartily) >> Guys, final topic, 5G impact, 'cause you mentioned Cisco, couldn't help think about -- >> Let me finish please my question, John. >> Okay, go ahead. How would you the United States respond if the European Union would now legalize to spy on everybody and every company, and every governmental institution within the United States and say, "No, no, it's our privilege, we need that." How would the United States respond? >> You can try that and see economically what happens to you, that's how the village politics work, you have to listen to the mightier than you, and we are economically mightier, that's the fact. Actually it's hard to swallow fact for, even for anybody else. >> If you guys built a great app, I would use it, and surveil all you want. >> Yeah, but so this is going to be driven by the economics. (John laughing) But the -- >> That's exactly what John said. >> This is going to be driven by the economics here. The big U.S. cloud firms are got to find this ruling enormously difficult for them, and they are inevitably going to lobby for a level of reform. And I think a level of a reform is needed. Nobody on your side is actually arguing very vociferously that the Cloud Act and the discrimination against Europeans is actually a particularly good idea. The problem is that once you've done the reform, are we going to believe you when you say, "Oh, it's all good now, we've stopped it!" Because with Crypto AG scandal in Switzerland you weren't exactly honest about what you were doing. With the FISA courts, so I mean FISA secret courts, the secret warrants, how do we know and what proof can we have that you've stopped doing all these bad things? And I think one of the challenges, A, going to be the reform, and then B, got to be able to show that you actually got your act together and you're now clean. And until you can solve those two, many of your big tech companies are going to be at a competitive disadvantage, and they're going to be screaming for this reform. >> Well, I think that, you know, General Mattis said in his book about Trump and the United states, is that you need alliances, and I think your point about trust and executing together, without alliances, it really doesn't work. So, unless there's some sort of real alliance, (laughs) like understanding that there's going to be some teamwork here, (Bill laughing) I don't think it's going to go anywhere. So, otherwise it'll continue to be siloed and network based, right? So to the village point, if TikTok can become a massively successful app, and they're surveilling, so and then we have to decide that we're going to put up with that, I mean, that's not my decision, but that's what's goin' on here. It's like, what is TikTok, is it good or bad? Amazon sent out an email, and they've retracted it, that's because it went public. I guarantee you that they're talkin' about that at Amazon, like, "Why would we want infiltration by the Chinese?" And I'm speculating, I have no data, I'm just saying, you know. They email those out, then they pull it back, "Oh, we didn't mean to send that." Really, hmm? (laughs) You know, so this kind of -- >> But the TRA Balin's good, you always want to get TRA Balin out there. >> Yeah, exactly. There's some spying going on! So, this is the reality. >> So, John, you were talking about 5G, and I think you know, the role of 5G, you know, the battle between Cisco and Huawei, you just have to look at it this way, would you rather have the U.S. spy on you, or would you rather have China? And that's really your binary choice at this moment. And you know both is happening, and so the question is which one is better. Like, the one that you're in alliance with? The one that you're not in alliance with, the one that wants to bury you, and decimate your country, and steal all your secrets and then commercialize 'em? Or the one kind of does it, but doesn't really do it explicitly? So, you've got to choose. (laughs) >> It's supposed to be -- >> Or you can say no, we're going to create our own standard for 5G and kick both out, that's an option. >> It's probably not as straightforward a question as, or an answer to that question as you say, because if we were to fast-forward 50 years, I would argue that China is going to be the largest trading nation in the world. I believe that China is going to have the upper hand on many of these technologies, and therefore why would we not want to use some of their innovation, some of their technology, why would we not actually be more orientated around trading with them than we might be with the U.S.? I think the U.S. is throwing its weight around at this moment in time, but if we were to fast-forward I think looking in the longterm, if I had to put my money on Huawei or some of its competitors, I think given its level of investments in research and whatever, I think the better longterm bet is Huawei. >> No, no, actually you guys need to pick a camp. It's a village again. You have to pick a camp, you can't be with both guys. >> Global village. >> Oh, right, so we have to go with the guys that have been spying on us? >> How do you know the Chinese haven't been spying on you? (Ray and John laughing loudly) >> I think I'm very happy, you find a backdoor in the Huawei equipment and you show it to us, we'll take them to task on it. But don't start bullying us into making decisions based on what-ifs. >> I don't think I'm, I'm not qualified to represent the U.S., but what we would want to say is that if you look at the dynamics of what's going on, China, we've been studying that as well in terms of the geopolitical aspects of what happens in technology, they have to do what they're doing right now. Because in 20 years our population dynamics go like this, right? You've got the one child policy, and they won't have the ability to go out and fight for those same resources where they are, so what they're doing makes sense from a country perspective and country policy. But I think they're going to look like Japan in 20 years, right? Because the xenophobia, the lack of immigration, the lack of inside stuff coming in, an aging population. I mean, those are all factors that slow down your economy in the long run. And the lack of bringing new people in for ideas, I mean that's part of it, they're a closed system. And so I think the longterm dynamics of every closed system is that they tend to fail versus open systems. So, I'm not sure, they may have better technology along the way. But I think a lot of us are probably in the camp now thinking that we're not going to aid and abet them, in that sense to get there. >> You're competing a country with a company, I didn't say that China had necessarily everything rosy in its future, it'll be a bigger economy, and it'll be a bigger trading partner, but it's got its problems, the one child policy and the repercussions of that. But that is not one of the things, Huawei, I think Huawei's a massively unlimited company that has got a massive lead, certainly in 5G technology, and may continue to maintain a lead into 6G and beyond. >> Oh yeah, yeah, Huawei's done a great job on the 5G side, and I don't disagree with that. And they're ahead in many aspects compared to the U.S., and they're already working on the 6G technologies as well, and the roll outs have been further ahead. So, that's definitely -- >> And they've got a great backer too, the financer, the country China. Okay guys, (Ray laughing) let's wrap up the segment. Thanks for everyone's time. Final thoughts, just each of you on this core issue of the news that we discussed and the impact that was the conversation. What's the core issue? What should people think about? What's your solution? What's your opinion of how this plays out? Just final statements. We'll start with Bill, Ray, Sarbjeet and JD. >> All I'm going to ask you is stop spying on us, treat us equally, treat us like the allies that we are, and then I think we've got to a bright future together! >> John: Ray? >> I would say that Bill's right in that aspect in terms of how security agreements work, I think that we've needed to be more explicit about those. I can't represent the U.S. government, but I think the larger issue is really how do we view privacy, and how we do trade offs between security and convenience, and you know, what's required for personalization, and companies that are built on data. So, the sooner we get to those kind of rules, an understanding of what's possible, what's a consensus between different countries and companies, I think the better off we will all be a society. >> Yeah, I believe the most important kind of independence is the economic independence. Like, economically sound parties dictate the terms, that's what U.S. is doing. And the smaller countries have to live with it or pick the other bigger player, number two in this case is China. John said earlier, I think, also what JD said is the fine balance between national security and the privacy. You can't have, you have to strike that balance, because the rogue actors are sitting in your country, and across the boundaries of the countries, right? So, it's not that FISA is being fought by Europeans only. Our internal people are fighting that too, like how when you are mining our data, like what are you using it for? Like, I get concerned too, when you can use that data against me, that you have some data against me, right? So, I think it's the fine balance between security and privacy, we have to strike that. Awesome. JD? I'll include a little fake check, fact check, at the moment China is the largest economy, the European Union is the second largest economy, followed directly by the USA, it's a very small difference, and I recommend that these two big parties behind the largest economy start to collaborate and start to do that eye to eye, because if you want to balance the economical and manufacturing power of China, you cannot do that as being number two and number three. You have to join up forces, and that starts with sticking with the treaties that you signed, and that has not happened in the past, almost four years. So, let's go back to the table, let's work on rules where from both sides the rights and the privileges are properly reflected, and then do the most important thing, stick to them! >> Yep, I think that's awesome. I think I would say that these young kids in high school and college, they need to come up and solve the problems, this is going to be a new generational shift where the geopolitical landscape will change radically, you mentioned the top three there. And new alliances, new kinds of re-imagination has to be there, and from America's standpoint I'll just say that I'd like to see lawmakers have, instead of a LinkedIn handle, a GitHub handle. You know, when they all go out on campaign talk about what code they've written. So, I think having a technical background or some sort of knowledge of computer science and how the internet works with sociology and societal impact will be critical for our citizenships to advance. So, you know rather a lawyer, right so? (laughs) Maybe get some law involved in that, I mean the critical lawyers, but today most people are lawyers in American politics, but show me a GitHub handle of that congressman, that senator, I'd be impressed. So, that's what we need. >> Thanks, good night! >> Ray, you want to say something? >> I wanted to say something, because I thought the U.S. economy was 21 trillion, the EU is sittin' at about 16, and China was sitting about 14, but okay, I don't know. >> You need to do math man. >> Hey, we went over our 30 minutes time, we can do an hour with you guys, so you're still good. (laughs) >> Can't take anymore. >> No go on, get in there, go at it when you've got something to say. >> I don't think it's immaterial the exact size of the economy, I think that we're better off collaborating on even and fair terms, we are -- >> We're all better off collaborating. >> Yeah. >> Gentlemen -- >> But the collaboration has to be on equal and fair terms, you know. (laughs) >> How do you define fair, good point. Fair and balanced, you know, we've got the new -- >> We did define fair, we struck a treaty! We absolutely defined it, absolutely! >> Yeah. >> And then one side didn't stick to it. >> We will leave it right there, and we'll follow up (Bill laughing) in a later conversation. Gentlemen, you guys are good. Thank you. (relaxing electronic music)

>> (vocalizing) >> Narrator: From theCube studios in Palo Alto and Boston, it's theCube. Covering IBM Think, brought to you by IBM. >> Hi everybody, this is Dave Vallante and this is our continuing coverage of Think 2020, the digital event experience. This is the post-thing, the sort of halo effect, the afterthoughts, and joining me is Rob Thomas, he's back. The Senior Vice president of Cloud and Data Platform. Rob, thanks for taking some time to debrief on Think. >> Absolutely Dave, great to be here, good to see you again. >> Yeah, so you have a great event, you guys put it together in record time. I want to talk about sort of your innovation agenda. I mean, you are at the heart of innovation. You're talking cloud, data, AI, really the pillars of innovation, I could probably add in edge to extend the cloud. But I wonder if you could talk about your vision for the innovation agenda and how you're bringing that to customers. I mean, we heard from PayPal, you talked about Royal Bank of Scotland, Credit Mutual, a number of customer examples. How are you bringing innovation forward with the customer? >> I wouldn't describe innovation, maybe I'd give it two different categories. One is, I think the classic term would be consumerization, and you're innovating by making interiorized technology really easy to use. That's why we built out a huge design capability, it's why we've been able to get products like Watson Assistant to get companies live in 24 hours. That's the consumerization aspect, just making enterprise products really easy to use. The second aspect is even harder, which is, how do you tap into an institution like IBM Research, where we're doing fundamental invention. So, one of our now strengths in the last couple of months was around taking technology out of IBM Debater, project Debater, the AI system that could debate humans and then putting that into enterprised products. And, you saw companies like PayPal that are using Watson Assistant and now they have access to that kind of language capability. There's only two aspects here, there's the consumerization and then there's about fundamental technology that really changes how businesses can operate. >> I mean, the point you made about speed and implementation in your key note was critical, I mean really, within 24 hours, very important during this pandemic. Talk about automation, you know, you would think by now right, everything's automation. But, now you're seeing a real boom in automation and it really is driven by AI, all this data, so there's seems to be a next wave, almost a renaissance, if you will, in automation. >> There is and I think automation, when people hear first of the term, it's sometimes a scary term. Because people are like hey, is this going to take my job? Gain a lot of momentum for automation is a difficult, repetitive tasks that nobody really wanted to do in the first place. Whether it's things like data matching, containerizing an application. All these are really hard things and the output's great, but nobody really wants to do that work, they just want the outcome. And, as we've started to demonstrate different use cases for automation that are in that realm, a lot of momentum has taken off, that we're seeing. >> I want to come back to this idea of consumerization and simplification. I mean, when you think about what's been happening over the last several years. And, you and I have talked about this a lot, AI for consumer versus AI for business and enterprise. And really, one of the challenges for the encumbrance, if you will, is to really become data driven, put data at the core and apply machine intelligence to that, just to that data. Now the good news is, they don't have to invent all this stuff, because guys like you are doing that and talk about how you're making that simple. I mean, cloud packs is an example of that, simplification, but talk about how customers are going to be able to tap into AI without having to be AI inventors. >> Well, the classic AI problem actually is a data problem, and the classic data problem is data slide over, which is a company has got a lot of data but it's spread across a hundred or a thousand or tens of thousands different repositories or locations. Our strategy when we say a hybrid cloud is about how do we unify those data storage. So, it's called PaaS, on red hat open shift. We do a lot of things like data virtualization, really high performance. So, we take what is thousands of different data sources and we have that packed like a single fluid item. So then, when you're training models, you can train your models in one place and connect to all your data. That is the big change that's happening and that's how you take something like hybrid cloud, and it actually starts to impact your data architecture. And once you're doing that, then AI becomes a lot easier, because the biggest AI challenge that I described is, where's the data? Is the data in a usable form? >> A lot of times in this industry, you know, we go whale hunting, there are a lot of big companies out there, a lot of times they take priority. You know, at the same time though, a lot of the innovations are coming from companies, you know, we've never even heard of that could be multi-billion dollar companies by the end of the decade. So, how can, you know, small companies and mid-sized companies tap into this trend? Is it just for the big whales or could the small guys participate? >> The thing that's pretty amazing about modern cloud and data technology, I'll call it, is it's accessible to companies of any size. When we talked about, you know, the hundred or so clients that have adopted Watson Assistant since COVID-19 started, many of those are very small institutions with no IT staff or very limited IT staff. Though, we're making this technology very accessible. when you look at something like data, now a small company may not have a hundred different repositories, which is fine, but what they do have is they do want to make better predictions, they do want to automate, they do want to optimize the business processes that they're running in their business. And, the way that we've transformed our model consumption base starting small, it's really making technology available to, you know, from anywhere from the local deli to the Fortune 50 Company. >> So, last question is, What are your big takeaways from Think? I would ask that question normally when we're in a live event. It's a little different with the digital event, but there are still takeaways. What was your reaction and what do to leave people with? >> Even as we get back to doing physical events, which I'm positive will happen at some point. What we learned is there is something great about an immersive digital experience. So, I think the future of events is probably higher than this. Meaning, a big digital experience, to complement the physical experience. That's one big takeaway because the reaction was so positive to the content and how people could access it. Second one is the, all the labs that we did. So, for developers, builders, those were at capacity, meaning we didn't even take any more. So, there's definitively a thirst in the market for developing new applications, developing new data products, developing new security products. That's clear just by the attendance that we saw, that's exciting. Now, I'd say third, that is that AI is now moving into the mainstream, that was clear from the customer examples, whether it was with Tansa or UPS or PayPal that I mentioned before, that was talking with me. AI is becoming accessible to every company, that's pretty exciting. >> Well, the world is hybrid, oh you know the lab, the point you're making about labs is really important. I've talked to a number of individuals saying, "Hey I'm using this time to update my skills. I'm working longer hours, maybe different times of the day, but I'm going to skill up." And you know, the point about AI, 37 years ago, when I started in this business AI was all the buzz and it didn't happen. It's real this time and I'm really excited Rob, that you're at the heart of all this innovation, so really, I appreciate you taking the time. And, best of luck, stay safe, and hopefully we'll see you face to face. >> Offscreen Man: Sure. >> Thanks Dave, same to you and the whole team at theCube, take care. >> Thank you Rob, and thank you for watching everybody, this is Dave Vellante for theCube and our coverage of IBM Think 2020, the digital event experience and the post-event. We'll see you next time. (music)

>>live from Miami, Florida. It's the Q covering. IBM is data in a I forum brought to you by IBM. >>Welcome back to the port of Miami, Everybody. You're watching the Cube, the leader in live tech coverage. We're here covering the IBM data and a I form. Rob Thomas is here. He's the general manager for data in A I and I'd be great to see again. >>Right. Great to see you here in Miami. Beautiful week here on the beach area. It's >>nice. Yeah. This is quite an event. I mean, I had thought it was gonna be, like, roughly 1000 people. It's over. Sold or 17. More than 1700 people here. This is a learning event, right? I mean, people here, they're here to absorb best practice, you know, learn technical hands on presentations. Tell us a little bit more about how this event has evolved. >>It started as a really small training event, like you said, which goes back five years. And what we saw those people, they weren't looking for the normal kind of conference. They wanted to be hands on. They want to build something. They want to come here and leave with something they didn't have when they arrived. So started as a little small builder conference and now somehow continues to grow every year, which were very thankful for. And we continue to kind of expand at sessions. We've had to add hotels this year, so it's really taken off >>you and your title has two of the three superpowers data. And of course, Cloud is the third superpower, which is part of IBMs portfolio. But people want to apply those superpowers, and you use that metaphor in your your keynote today to really transform their business. But you pointed out that only about a eyes only 4 to 10% penetrated within organizations, and you talked about some of the barriers that, but this is a real appetite toe. Learn isn't there. >>There is. Let's go talk about the superpower for a bit. A. I does give employees superpowers because they can do things now. They couldn't do before, but you think about superheroes. They all have an origin story. They always have somewhere where they started and applying a I an organization. It's actually not about doing something completely different. It's about extenuating. What you already d'oh doing something massively better. That's kind of in your DNA already. So we're encouraging all of our clients this week like use the time to understand what you're great at, what your value proposition is. And then how do you use a I to accentuate that? Because your superpower is only gonna last if it's starts with who you are as a company or as a >>person who was your favorite superhero is a kid. Let's see. I was >>kind of into the whole Hall of Justice. Super Superman, that kind of thing. That was probably my cartoon. >>I was a Batman guy. And the reason I love that movie because all the combination of tech, it's kind of reminds me, is what's happening here today. In the marketplace, people are taking data. They're taking a I. They're applying machine intelligence to that data to create new insights, which they couldn't have before. But to your point, there's a There's an issue with the quality of data and and there's a there's a skills gap as well. So let's let's start with the data quality problem described that problem and how are you guys attacking it? >>You're a I is only as good as your data. I'd say that's the fundamental problem and organization we worked with. 80% of the projects get slowed down or they get stopped because the company has a date. A problem. That's why we introduce this idea of the A i ladder, which is all of the steps that a company has to think about for how they get to a level of data maturity that supports a I. So how they collect their data, organize their data, analyze their data and ultimately begin to infuse a I into business processes soap. Every organization needs to climb that ladder, and they're all different spots. So for someone might be, we gotta focus on organization a data catalogue. For others, it might be we got do a better job of data collection data management. That's for every organization to figure out. But you need a methodical approach to how you attack the data problem. >>So I wanna ask you about the Aye aye ladder so you could have these verbs, the verbs overlay on building blocks. I went back to some of my notes in the original Ai ai ladder conversation that you introduced a while back. It was data and information architecture at the at the base and then building on that analytics machine learning. Aye, aye, aye. And then now you've added the verbs, collect, organized, analyze and infused. Should we think of this as a maturity model or building blocks and verbs that you can apply depending on where you are in that maturity model, >>I would think of it as building blocks and the methodology, which is you got to decide. Do wish we focus on our data collection and doing that right? Is that our weakness or is a data organization or is it the sexy stuff? The Aye. Aye. The data science stuff. We just This is just a tool to help organizations organize themselves on what's important. I asked every company I visit. Do you have a date? A strategy? You wouldn't believe the looks you get when you ask that question, you get either. Well, she's got one. He's got one. So we got seven or you get No, we've never had one. Or Hey, we just hired a CDO. So we hope to have one. But we use the eye ladder just as a tool to encourage companies to think about your data strategy >>should do you think in the context I want follow up on that data strategy because you see a lot of tactical data strategies? Well, we use Data Thio for this initiative of that initiative. Maybe in sales or marketing, or maybe in R and D. Increasingly, our organization's developing. And should they develop a holistic data strategy, or should they trying to just get kind of quick wins? What are you seeing in the marketplace? >>It depends on where you are in your maturity cycle. I do think it behooves every company to say We understand where we are and we understand where we want to go. That could be the high level data strategy. What are our focus and priorities gonna be? Once you understand focus and priorities, the best way to get things into production is through a bunch of small experiments to your point. So I don't think it's an either or, but I think it's really valuable tohave an overarching data strategy, and I recommended companies think about a hub and spokes model for this. Have a centralized chief date officer, but your business units also need a cheap date officer. So strategy and one place execution in another. There's a best practice to going about this >>the next you ask the question. What is a I? You get that question a lot, and you said it's about predicting, automating and optimizing. Can we unpack that a little bit? What's behind those three items? >>People? People overreact a hype on topics like II. And they think, Well, I'm not ready for robots or I'm not ready for self driving Vehicles like those Mayor may not happen. Don't know. But a eyes. Let's think more basic it's about can we make better predictions of the business? Every company wants to see a future. They want the proverbial crystal ball. A. I helped you make better predictions. If you have the data to do that, it helps you automate tasks, automate the things that you don't want to do. There's a lot of work that has to happen every day that nobody really wants to do you software to automate that there's about optimization. How do you optimize processes to drive greater productivity? So this is not black magic. This is not some far off thing. We're talking about basics better predictions, better automation, better optimization. >>Now interestingly, use the term black magic because because a lot of a I is black box and IBM is always made a point of we're trying to make a I transparent. You talk a lot about taking the bias out, or at least understanding when bias makes sense. When it doesn't make sense, Talk about the black box problem and how you're addressing. >>That starts with one simple idea. A eyes, not magic. I say that over and over again. This is just computer science. Then you have to look at what are the components inside the proverbial black box. With Watson, we have a few things. We've got tools for clients that want to build their own. Aye, aye, to think of it as a tool box you can choose. Do you want a hammer and you want a screwdriver? You wanna nail you go build your own, aye, aye. Using Watson. We also have applications, so it's basically an end user application that puts a I into practice things like Watson assistant to virtually no create a virtual agent for customer service or Watson Discovery or things like open pages with Watson for governance, risk and compliance. So, aye, aye, for Watson is about tools. You want to build your own applications if you want to consume an application, but we've also got in bed today. I capability so you can pick up Watson and put it inside of any software product in the >>world. He also mentioned that Watson was built with a lot of of of, of open source components, which a lot of people might not know. What's behind Watson. >>85% of the work that happens and Watson today is open source. Most people don't know that it's Python. It's our it's deploying into tensorflow. What we've done, where we focused our efforts, is how do you make a I easier to use? So we've introduced Auto Way. I had to watch the studio, So if you're building models and python, you can use auto. I tow automate things like feature engineering algorithm, selection, the kind of thing that's hard for a lot of data scientists. So we're not trying to create our own language. We're using open source, but then we make that better so that a data scientist could do their job better >>so again come back to a adoption. We talked about three things. Quality, trust and skills. We talked about the data quality piece we talked about the black box, you know, challenge. It's not about skills you mention. There's a 250,000 person Gap data science skills. How is IBM approaching how our customers and IBM approaching closing that gap? >>So think of that. But this in basic economic terms. So we have a supply demand mismatch. Massive demand for data scientists, not enough supply. The way that we address that is twofold. One is we've created a team called Data Science Elite. They've done a lot of work for the clients that were on stage with me, who helped a client get to their first big win with a I. It's that simple. We go in for 4 to 6 weeks. It's an elite team. It's not a long project we're gonna get you do for your success. Second piece is the other way to solve demand and supply mismatch is through automation. So I talked about auto. Aye, aye. But we also do things like using a eye for building data catalogs, metadata creation data matching so making that data prep process automated through A. I can also help that supply demand. Miss Max. The way that you solve this is we put skills on the field, help clients, and we do a lot of automation in software. That's how we can help clients navigate this. So the >>data science elite team. I love that concept because way first picked up on a couple of years ago. At least it's one of the best freebies in the business. But of course you're doing it with the customers that you want to have deeper relationships with, and I'm sure it leads toe follow on business. What are some of the things that you're most proud of from the data science elite team that you might be able to share with us? >>The clients stories are amazing. I talked in the keynote about origin stories, Roll Bank of Scotland, automating 40% of their customer service. Now customer SATs going up 20% because they put their customer service reps on those hardest problems. That's data science, a lead helping them get to a first success. Now they scale it out at Wonderman Thompson on stage, part of big W P p big advertising agency. They're using a I to comb through customer records they're using auto Way I. That's the data science elite team that went in for literally four weeks and gave them the confidence that they could then do this on their own. Once we left, we got countless examples where this team has gone in for very short periods of time. And clients don't talk about this because they have to talk about it cause they're like, we can't believe what this team did. So we're really excited by the >>interesting thing about the RVs example to me, Rob was that you basically applied a I to remove a lot of these mundane tasks that weren't really driving value for the organization. And an R B s was able to shift the skill sets. It's a more strategic areas. We always talk about that, but But I love the example C. Can you talk a little bit more about really, where, where that ship was, What what did they will go from and what did they apply to and how it impacted their businesses? A improvement? I think it was 20% improvement in NPS but >>realizes the inquiry's they had coming in were two categories. There were ones that were really easy. There were when they were really hard and they were spreading those equally among their employees. So what you get is a lot of unhappy customers. And then once they said, we can automate all the easy stuff, we can put all of our people in the hardest things customer sat shot through the roof. Now what is a virtual agent do? Let's decompose that a bit. We have a thing called intent classifications as part of Watson assistant, which is, it's a model that understands customer a tent, and it's trained based on the data from Royal Bank of Scotland. So this model, after 30 days is not very good. After 90 days, it's really good. After 180 days, it's excellent, because at the core of this is we understand the intent of customers engaging with them. We use natural language processing. It really becomes a virtual agent that's done all in software, and you can only do that with things like a I. >>And what is the role of the human element in that? How does it interact with that virtual agent. Is it a Is it sort of unattended agent or is it unattended? What is that like? >>So it's two pieces. So for the easiest stuff no humans needed, we just go do that in software for the harder stuff. We've now given the RVs, customer service agents, superpowers because they've got Watson assistant at their fingertips. The hardest thing for a customer service agent is only finding the right data to solve a problem. Watson Discovery is embedded and Watson assistant so they can basically comb through all the data in the bank to answer a question. So we're giving their employees superpowers. So on one hand, it's augmenting the humans. In another case, we're just automating the stuff the humans don't want to do in the first place. >>I'm gonna shift gears a little bit. Talk about, uh, red hat in open shift. Obviously huge acquisition last year. $34 billion Next chapter, kind of in IBM strategy. A couple of things you're doing with open shift. Watson is now available on open shifts. So that means you're bringing Watson to the data. I want to talk about that and then cloudpack for data also on open shifts. So what has that Red had acquisition done for? You obviously know a lot about M and A but now you're in the position of you've got to take advantage of that. And you are taking advantage of this. So give us an update on what you're doing there. >>So look at the cloud market for a moment. You've got around $600 million of opportunity of traditional I t. On premise, you got another 600 billion. That's public clouds, dedicated clouds. And you got about 400 billion. That's private cloud. So the cloud market is fragmented between public, private and traditional. I t. The opportunity we saw was, if we can help clients integrate across all of those clouds, that's a great opportunity for us. What red at open shift is It's a liberator. It says right. Your application once deployed them anywhere because you build them on red hot, open shift. Now we've brought cloudpack for data. Our data platform on the red hot open shift certified on that Watson now runs on red had open shift. What that means is you could have the best data platform. The best Aye, Aye. And you can run it on Google. Eight of us, Azure, Your own private cloud. You get the best, Aye. Aye. With Watson from IBM and run it in any of those places. So the >>reason why that's so powerful because you're able to bring those capabilities to the data without having to move the date around It was Jennifer showed an example or no, maybe was tail >>whenever he was showing Burt analyzing the data. >>And so the beauty of that is I don't have to move any any data, talk about the importance of not having Thio move that data. And I want I want to understand what the client prerequisite is. They really take advantage of that. This one >>of the greatest inventions out of IBM research in the last 10 years, that hasn't gotten a lot attention, which is data virtualization. Data federation. Traditional federation's been around forever. The issue is it doesn't perform our data virtualization performance 500% faster than anything else in the market. So what Jennifer showed that demo was I'm training a model, and I'm gonna virtualized a data set from Red shift on AWS and on premise repositories a my sequel database. We don't have to move the data. We just virtualized those data sets into cloudpack for data and then we can train the model in one place like this is actually breaking down data silos that exist in every organization. And it's really unique. >>It was a very cool demo because what she did is she was pulling data from different data stores doing joins. It was a health care application, really trying to understand where the bias was peeling the onion, right? You know, it is it is bias, sometimes biases. Okay, you just got to know whether or not it's actionable. And so that was that was very cool without having to move any of the data. What is the prerequisite for clients? What do they have to do to take advantage of this? >>Start using cloudpack for data. We've got something on the Web called cloudpack experiences. Anybody can go try this in less than two minutes. I just say go try it. Because cloudpack for data will just insert right onto any public cloud you're running or in your private cloud environment. You just point to the sources and it will instantly begin to start to create what we call scheme a folding. So a skiing version of the schema from your source writing compact for data. This is like instant access to your data. >>It sounds like magic. OK, last question. One of the big takeaways You want people to leave this event with? >>We are trying to inspire clients to give a I shot. Adoption is 4 to 10% for what is the largest economic opportunity we will ever see in our lives. That's not an acceptable rate of adoption. So we're encouraging everybody Go try things. Don't do one, eh? I experiment. Do Ah, 100. Aye, aye. Experiments in the next year. If you do, 150 of them probably won't work. This is where you have to change the cultural idea. Ask that comes into it, be prepared that half of them are gonna work. But then for the 52 that do work, then you double down. Then you triple down. Everybody will be successful. They I if they had this iterative mindset >>and with cloud it's very inexpensive to actually do those experiments. Rob Thomas. Thanks so much for coming on. The Cuban great to see you. Great to see you. All right, Keep right, everybody. We'll be back with our next guest. Right after this short break, we'll hear from Miami at the IBM A I A data form right back.

>>Live from Miami, Florida. It's the cube covering IBM's data and AI forum brought to you by IBM. >>Welcome everybody to the port of Miami. My name is Dave Vellante and you're watching the cube, the leader in live tech coverage. We go out to the events, we extract the signal from the noise and we're here at the IBM data and AI form. The hashtag is data AI forum. This is IBM's. It's formerly known as the, uh, IBM analytics university. It's a combination of learning peer network and really the focus is on AI and data. And there are about 1700 people here up from, Oh, about half of that last year, uh, when it was the IBM, uh, analytics university, about 600 customers, a few hundred partners. There's press here, there's, there's analysts, and of course the cube is covering this event. We'll be here for one day, 128 hands-on sessions or ER or sessions, 35 hands on labs. As I say, a lot of learning, a lot of technical discussions, a lot of best practices. >>What's happening here. For decades, our industry has marched to the cadence of Moore's law. The idea that you could double the processor performance every 18 months, doubling the number of transistors, you know, within, uh, the footprint that's no longer what's driving innovation in the it and technology industry today. It's a combination of data with machine intelligence applied to that data and cloud. So data we've been collecting data, we've always talked about all this data that we've collected and over the past 10 years with the advent of lower costs, warehousing technologies in file stores like Hadoop, um, with activity going on at the edge with new databases and lower cost data stores that can handle unstructured data as well as structured data. We've amassed this huge amount of, of data that's growing at a, at a nonlinear rate. It's, you know, this, the curve is steepening is exponential. >>So there's all this data and then applying machine intelligence or artificial intelligence with machine learning to that data is the sort of blending of a new cocktail. And then the third piece of that third leg of that stool is the cloud. Why is the cloud important? Well, it's important for several reasons. One is that's where a lot of the data lives too. It's where agility lives. So cloud, cloud, native of dev ops, and being able to spin up infrastructure as code really started in the cloud and it's sort of seeping to to on prem, slowly and hybrid and multi-cloud, ACC architectures. But cloud gives you not only that data access, not only the agility, but also scale, global scale. So you can test things out very cheaply. You can experiment very cheaply with cloud and data and AI. And then once your POC is set and you know it's going to give you business value and the business outcomes you want, you can then scale it globally. >>And that's really what what cloud brings. So this forum here today where the big keynotes, uh, Rob Thomas kicked it off. He uh, uh, actually take that back. A gentleman named Ray Zahab, he's an adventure and ultra marathon or kicked it off. This Jude one time ran 4,500 miles in 111 days with two ultra marathon or colleagues. Um, they had no days off. They traveled through six countries, they traversed Africa, the continent, and he took two showers in a 111 days. And his whole mission is really talking about the power of human beings, uh, and, and the will of humans to really rise above any challenge would with no limits. So that was the sort of theme that, that was set for. This, the, the tone that was set for this conference that Rob Thomas came in and invoked the metaphor of superheroes and superpowers of course, AI and data being two of those three superpowers that I talked about in addition to cloud. >>So Rob talked about, uh, eliminating the good to find the great, he talked about some of the experiences with Disney's ward. Uh, ward Kimball and Stanley, uh, ward Kimball went to, uh, uh, Walt Disney with this amazing animation. And Walter said, I love it. It was so funny. It was so beautiful, was so amazing. Your work 283 days on this. I'm cutting it out. So Rob talked about cutting out the good to find, uh, the great, um, also talking about AI is penetrated only about four to 10% within organizations. Why is that? Why is it so low? He said there are three things that are blockers. They're there. One is data and he specifically is referring to data quality. The second is trust and the third is skillsets. So he then talked about, you know, of course dovetailed a bunch of IBM products and capabilities, uh, into, you know, those, those blockers, those challenges. >>He talked about two in particular, IBM cloud pack for data, which is this way to sort of virtualize data across different clouds and on prem and hybrid and and basically being able to pull different data stores in, virtualize it, combine join data and be able to act on it and apply a machine learning and AI to it. And then auto AI a way to basically machine intelligence for artificial intelligence. In other words, AI for AI. What's an example? How do I choose the right algorithm and that's the best fit for the use case that I'm using. Let machines do that. They've got experience and they can have models that are trained to actually get the best fit. So we talked about that, talked about a customer, a panel, a Miami Dade County, a Wunderman Thompson, and the standard bank of South Africa. These are incumbents that are using a machine intelligence and AI to actually try to super supercharge their business. We heard a use case with the Royal bank of Scotland, uh, basically applying AI and driving their net promoter score. So we'll talk some more about that. Um, and we're going to be here all day today, uh, interviewing executives, uh, from, uh, from IBM, talking about, you know, what customers are doing with a, uh, getting the feedback from the analysts. So this is what we do. Keep it right there, buddy. We're in Miami all day long. This is Dave Olanta. You're watching the cube. We'll be right back right after this short break..