(upbeat music) >> Hello, everyone. Welcome to theCUBE's coverage here at AWS re:Invent 2022. This is the Executive Summit with Accenture. I'm John Furrier, your host of theCUBE with two great guests coming on today, really talking about the future, the role of humans. Radically human is going to be the topic. Paul Daugherty, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, Global Managing Director of Thought Leadership and Technology Research, Accenture. Gentlemen, thank you for coming on theCUBE for this conversation around your new hit book, "Radically Human." >> Thanks, John. It's great to be with you and great to be present at re:Invent. >> We've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're in this, I call it the systems thinking, revolution is going on now where things have consequences and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as as humans. And so I love the book, very, very strong content, really right on point. What was the motivation for the book? And congratulations, but I noticed you got the structure, part one and part two, this book seems to be packing a big punch. What was the motivation, and what was some of the background in putting the book together? >> That's a great question, John. And I'll start, and then, Jim, my co-author and colleague and partner on the book can join in too. If you step back from the book itself, we'd written a first book called "Human + Machine", which focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the human plus machine pairing. And then when we started working on the next book, it was the COVID era. COVID came on line as we were writing the book. And that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing. Once COVID hit, every company became more dependent on technology. Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies, and what was different from the first research we had done around our first book. And what we found, which was super interesting, is that pre-pandemic, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of 2x. And that was before the pandemic. After the pandemic, we redid the research and the gap widened into 5x. And I think that's played a lot into our book. And we talk about that in the opening of our book. And the message there is exactly what you said is technology is not just the lifeline from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around inflation, energy, supply chain crisis because of the war in Ukraine, et cetera. And companies need the technology more than ever. And that's what we're writing about in "Radically Human." And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud, data and AI, and the metaverse that signal out as three trends that are really driving transformative change for companies. In the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are going to set companies apart as they look to implement this technology and transform their companies for the future. >> Jim, weigh in on this flipping the script, flipping the assumptions. >> You used a really important word there and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as a point solution. They don't think about AI in terms of taking a systems approach. So we were trying to address that. All right, if you're going to build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate it using your talent, focusing on trust, experiences and sustainability? >> I like how it reads. It's almost like a masterclass book because you set the table. It's like, 'cause people right now are like in the mode of what's going on around me? I've been living through three years of COVID. We're coming out the other side. The world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where am I today. So I think the first part really to me hits home. Like, here's the current situation and then part two is here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or society. >> Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where "Radically Human", the title came from. And what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot. And the whole hypothesis or premise of the book I should say, is that the more human like the technology is, the more radically human or the more radical the human potential improvement is, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. Just a couple examples from the ideas framework, the I in IDEAS. The ideas framework is the first part of the book. The five areas to flip your assumptions. The I stands for intelligence and we're talking about more human and less artificial in terms of the intelligence techniques. Things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build using the kind of systems thinking that Jim mentioned. And things like emotional AI, common sense AI, new techniques in addition to machine, the big data driven machine learning techniques, which are essential to vision and solving big problems like that. So that's just an example of how you bring it together and enable that human potential. >> I love the idea, go ahead Jim. >> I was going to say we've been used to adapting to technology, and contorting our fingers to keyboards and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus, in fact, the human is in the ascended. That's one of the big ideas that we try to put out there in this book. >> I love the idea of flipping the script, flipping the assumptions, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, S for strategy. Notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution. Really interesting how you guys put that together. It feels like business is becoming agile and iterative and how it's going to be forming. Can you guys, I mean that's my opinion, but I think observing how developers becoming much more part of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation if you take it down to a conclusion and strategy is just what you do after you get the outcomes you need? What's your reaction to that? >> Yeah, I think one of the most lasting elements of the book might be that chapter on strategy in my opinion, because you need to think about it differently. The old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to lay out with the S in IDEAS, the strategy. The subtitle that chapter is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, that's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential role that technology plays and therefore they need to master technology. Well, you need to think about strategy differently then because of the pace of technology innovation. And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really important. It's about continuous strategy in all cases. An example is one of the techniques we talk about, forever beta, which is, think about a Tesla or companies that it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days as Paul was saying. >> It's interesting because that's the trend you're seeing with more data, more automation, but the human plays a much critical role. And just aside on the Tesla example, is well documented. I think I wrote about in a post just this week that during the model three, Elon wanted full automation and had to actually go off scripts and get to humans back in charge 'cause it wasn't working properly. Now they have a balance. But that brings up to part two, which I like, which is this human piece of it. We always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that second half, trust, talent, experiences. That's more of the person's role, either individually as part of a collective group. Is talent the scarce resource now where that's the goal, that's the key 'cause it all could point to that in a way. Skills gap points to, hey, humans are valuable. In fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think that's something that is not, kind of nuanced point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >> Yeah, go ahead Jim. >> I was going to say it, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book, really zooming in on talent. I think you might think that for every hundred dollars that you put into a technology initiative, you might put 50 or 75 into re-skilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw economic analysis recently that pointed out that for every $1 you spend on technology, you are likely going to need to spend about $9 on intangible human capital. That means on talent, on getting the best talent, on re-skilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >> That's a huge point. >> And I think some of the elements of talent that become really critical that we talked about in the book are becoming a talent creator. We believe the successful companies of the future are going to be able not just to post a job opening and hire people in because there's not going to be enough. And a lot of the jobs that companies are creating don't exist 'cause the technology changing so fast. So the companies that succeed are going to know how to create talent, bring in people, apprentices and such, and shape to tale as they go. We're doing a significant amount of that in our own company. They're going to be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what employees want. And then democratizing access to technology. Things like Amazon's Honeycode is an example, low-code/no-code development to spread development to wider pools of people. Those types of things are really critical going forward to really unlock the talent potential. And really what you end up with is, yeah, the human talent's important, but it's magnified and multiplied by the power of people, giving them in essence superpowers in using technology in new ways. >> I think you nailed it, that's super important. That point about the force multiplier when you put things in combination, whether it's group constructs, two pizza teams flexing, leveraging the talent. I mean, this is a new configuration. You guys are nailing it there. I love that piece. And I think groups and collectives you're going to start to see a lot more of that. But again, with talent comes trust when you start to have these ephemeral and or forming groups that are forming production systems or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously metaverse is a pretext to the virtual world where we're going to start to create these group experiences and create new force multipliers. How does the metaverse play into this new radically human world, and what does it mean for the future of business? >> Yeah, I think the metaverse is radically misunderstood to use the word title when we're not with the title of our book. And we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So that's the potential of the metaverse. And it's not just about the consumer things, it's about metaverse and the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I believe that it has tremendous potential. We write about that in the book and it really takes radically human to another level. And one way to think about this is cloud is really becoming the operating system of business. You have to build your enterprise around the cloud as you go forward. That's going to shape the way you do business. AI becomes the insight and intelligence in how you work, infused with the human talent and such as we said. And the metaverse then reshapes the experience layers. So you have cloud, AI building on top of this metaverse providing a new way to generate experiences for employees, citizens, consumers, et cetera. And that's the way it unfolds, but trust becomes more important because just as AI raises new questions around trust, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five-part framework or five essential parts of the framework around how you establish trust as you implement these new technologies. >> Yeah, we're seeing that about three quarters of companies are really trying to figure out trust, certainly with issues like the metaverse more broadly across their IT so they're focusing on security and privacy, transparency, especially when you're talking about AI systems, explainability. One of the more surprising things that we learned when doing the book, when we were doing the research is that we saw that increasingly consumers and employees want systems to be informed by a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, they're actually training the system by emulating human behavior. So turning the cameras on test drivers to see how they learn and then training the AI using that sense of humanity 'cause other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that AI system is learning from. Some really interesting innovations happening in that trust space. John. >> Jim, I think you bring up a great point that's worth talking more about. Because you're talking about how human behaviors are being put into the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and we've been calling it supercloud, some call it multi-cloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's going to happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with chat and some video. It's group behavior, it's groups convening, talking, getting things done, debating, doing things differently. And so this idea of humans informing design decisions or software with low-code/no-code, this completely changes strategy. I mean this is a big point of the book. >> Yeah, no, I go back to one of the, the E in the IDEAS framework is expertise. And we talk about from machine learning to machine teaching, which is exactly that. Machine learning is maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with AI. One of the examples we give is one of the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to encode in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >> Well, yeah, it's interesting. I want to to get your thoughts as we get wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in the enterprise of their businesses, as they look at the horizon, they see the the future. They got to start thinking about things like generative AI and how they can bring some of these technologies to the table. We were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are new things you guys are hitting in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge certainly that is an opportunity. How do you apply all this stuff for business? >> I'll go first then Jim can add in. But the first thing I think starts with recognizing the role that technology does play and investing accordingly in it. So the right technology talent, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why the fact you're at re:Invent is so important because companies are, again, rebuilding that operating system of their business in the cloud. And you need that as the foundation to go forward, to do, to build the other types of capabilities. And then I think it's developing those talent systems as well. Do you have the right talent brand? Are you attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward? And then you marry the two together and that's what gives you the radically human formula. >> Yeah. When we were developing that first part of the book, Paul and I did quite a bit of research, and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. One statistic is that 70% of companies that had never tried AI before went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies were not trying to do it themselves and to necessarily build an AI department. They were partnering and it's really important to find a partner, often a cloud partner as a way to get started, start small scale, and then scale up doing experiments. So that was one of the key insights that we had. You don't need to do it all yourself. >> If you see the transformation of just AWS, we're here at re:Invent, since we've been covering the events since 2013, every year there's been a thematic thing. It was startups, enterprise, now builders, and now change your company. This year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and running a SaaS application on the cloud. People are are changing and refactoring and replatforming categorical applications in for this new era. And we're calling it supercloud, superservices, superapps, 'cause they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools, or talent pools in certain ways. So this is real, something's happening here and we've been talking about it a lot lately. So I have to ask you guys, how does a company know if they're radical enough? Like what is radical? How can I put a pin in that? It's like take a temperature or we like radical enough, what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening? How do you know if you're you're pushing the envelope radical enough to take advantage? >> Yeah, I think one. >> You can go ahead, Paul. >> Yeah, I was going to say one of the tests is the impact on your business. You have to start by looking at all this in the context of your business, and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. That's still something you need to do. But now our focus with a lot of our customers is on how do you innovate and grow your business in the cloud? What's the platform that you're using for your new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test whether you're being radical enough is on the one hand, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping people, your human talent with the capabilities they need to perform in very different ways? And those are the two tests that I would give. >> Totally agree. >> Interesting enough, we love this topic and you guys, again, the book is spot on. Very packs of big punch on content, but very relevant in today. And I think one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like IDEAS, your framework, and understand where they are and what's available and what's coming around the corner. They stand out in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean you're building clouds on top of clouds or something's happening. I think you see it, look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >> Yeah and that's a good example. And it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows and the portability of being able to connect and use data across cloud environments and such is tremendously powerful. And I think that's why, you talk about companies doing things differently, that's why it's great, again, that you're at re:Invent. If you look at the index of our book, you'll see AWS mentioned a number of times 'cause we tell a lot of customer company stories about how they're leveraging AWS capabilities in cloud and AI to really do transformative things in their business. And I think that's what it's all about. >> Yeah, and one of the things too in the book, it's great 'cause it has the systems thinking, it's got really relevant information, but you guys have seen the movie before. I think one of the wild cards in this era is global. We're global economy, you've got regions, you've got data sovereignty, you're seeing all kinds of new things emerging. Thoughts on the global impact 'cause you take your book and you overlay that to business, like you got to operate all over the world as a human issue, as a geography issue. What's your guys take on the global impact? >> Well that's why you got to think about cloud as one technology. We talked about in the book and cloud is, I think a lot of people think, well, clouds, it's almost old news. Maybe it's been around for a while. As you said, you've been going to re:Invent since 2013. Cloud is really just getting started. And it's 'cause the reasons you said, when you look at what you need to do around sovereign cloud capability if you're in Europe. For many companies it's about multi-cloud capabilities that you need to deploy differently in different regions. And they need to, in some cases for good reason, they have hybrid cloud capability that they match on their own. And then there's the edge capability which comes into play in different ways. And so the architecture becomes very complex and we talk the A in IDEAS is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and just modularity was the key thing you thought about. It's more the idea of a living system, of living architecture that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the pace of technology advancement. >> Yeah, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is going to be a big discussion as these new flipped assumptions start to generate more activity. It's going to be very interesting to watch. Gentlemen, thank you so much for spending the time here on theCUBE as we break down your new book, "Radically Human" and how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at re:Invent. Thanks so much for sharing and congratulations on a great book. >> Thanks, John. And just one point I'd add is that one of the things we do talk about in talent is the need to reskill talent. People who need to be relevant in the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those that need to reskilling. And the final point I mentioned is that we've mentioned at the end of the book that all proceeds from the book are being donated to NGOs and nonprofits that are focused on reskilling those who need a skill refresh in light of the radically human change in technology that's happening. >> Great. Buy the book. Proceeds go to a great cause and it's a very relevant book. If you're in the middle of this big wave that's coming. this is a great book. There's a guidepost and also give you some great ideas to reset, reflip the scripts, refactor, replatform. Guys, thanks for coming on and sharing. I really appreciate it. Again, congratulations. >> Thanks, John. >> Thanks, John. Great discussion. >> You're watching theCUBE here covering the executive forum here at AWS re:Invent '22. I'm John Furrier, you're host with Accenture. Thanks for watching. (gentle music)

(soft music) >> We're in Las Vegas at The Venetian for our continued coverage here of re:Invent '22, AWS's big show going on. Great success off to a wonderful start. We're in the Executive Summit sponsored by Accenture. And we're going to talk about public health and the cloud, how those have come together in the great state of North Carolina. Charles Carter is going to help us do that. He's assistant secretary for technology services with the state of North Carolina's Department of Health and Human Services. Charles, good to see you. Thanks for joining us here on "theCUBE". >> Thank you very much for having me. >> Yeah, thanks for making the time. So first off, let's talk about what you do on the homefront before what you're doing here and where you're going. But in terms of kind of what your plan has been, what your journey has been from a cloud perspective and how you've implemented that and where you are right now in your journey. >> Sure, so we started. When I got there, we didn't have a cloud footprint at all. There was a- >> Host: Which was how long ago? >> I got there in 2016, so about six years. >> Host: Six, seven years, yeah. >> Yeah, five, six years. So anyways, we started off with our first module within our Medicaid expansion. And that was the first time that we went into the cloud. We worked with AWS to do our encounter processing system. And it was an incredible success. I think the ease of use was really kind of something that people weren't quite ready for. But it was really exciting to see that. And the scalability, to be able to turn that on and cover the entirety of North Carolina was awesome. So once we saw that and get a little taste of it, then we really wanted to start implementing it throughout DHHS. And we marshaled in a cloud-only cloud-first strategy where you had to actually get an exemption not to go to the cloud. And that was a first for our state. So that was really kind of the what launched us. But then COVID hit. And once COVID came in, that took us to a new level. COVID forced us to build technologies that enabled a better treatment, a better care, a better response from our team. And so we were able to stand up platforms in 48 hours. We were able to stand up COVID vaccine management systems in six weeks. And none of that would've been possible without the cloud. >> So forced your hand in a way because all of a sudden you've got this extraordinarily remote workforce, right, and people trying to- And you're doing different tasks that were totally unexpected, right, prior to that. What kind of a shock to the system was that from I get from an IT perspective? >> Yeah, so from a state government perspective, for example, you never hear you have all the money you need and you have to do it quickly. It just doesn't work like that. But this was a rare moment in time where you had this critical need. The entire country and our state population was kind of on edge. How do we move through this? How do we factor our lives into this new integration? What is this virus? Is it spreading in my county, in my city, my zip code? Where is it? And that kind of desperation really kind of focused everybody in on build me technologies that can get me the data that I need to make good healthcare decisions, good clinical decisions. And so that was our challenge. Cloud enabled it because it can scale so quickly. We can set up things, we can exchange data. We can move data around a lot easier. And the security is better from our perspective. So that COVID experience really kind of pushed us, you know, if you will, out the door. And we're never going back because it's just too good. >> Yeah, was that the aha moment then in a way because you had to do so much so fast and before capabilities that maybe you didn't have or maybe hadn't tapped? >> Yeah, yeah. >> I mean what was the accelerant there? Was COVID that big, or was it somebody who had to make a decision to say, this is where we're going with this, somebody in your shoes or somebody with whom you work? >> Yeah, no, I mean cloud at the end of the day, we knew that in order to do what we needed to do we couldn't do it on-prem. It wasn't an option. So if we wanted to build these capabilities, if we wanted to bring in technologies that really brought data to our key, our governor, our secretary, to make good decisions on behalf of our residents in North Carolina, then we were going to have to build things quickly. And the only way you can do that is in the cloud. So it was when they came back and said, "We need these things," there's only one answer. That's a good thing about technology. It's pretty binary, so it was either go with what we had, which wasn't adequate, or build to what we knew we could do and pretty short order. And because of that, we were able to actually usher in a huge expansion of cloud footprint within DHHS. And now we've actually been able to implement it in other departments simply because of our expertise. And that's been a huge asset for the state of North Carolina as a whole. >> So what's your measuring stick then for value in terms of identifying benefit? 'Cause it's not really about cost. This is about service, I assume, right? >> Right. >> So, you know, how do you quantify the values and the benefits that you're deriving from this migration over to the cloud? >> So from our perspective, it hits several different areas. I mean, you can start in security. We know that if we're in the cloud the tools that can manage and give us visibility in the cloud are 10 times better than an on-prem environment. And so if we can take a lot of these legacy systems and move them to the cloud, we'll be in a better security posture. So we have that piece of it. The other part of it is the data aspect of it, being able to- We're 33 divisions strong, right? We have a large footprint. We have a lot of siloed data elements. And cloud allows us to start integrating those data sets in a much more usable fashion so that we can see that if Charles Carter's in one area in division, a specific division with DHHS, is he somewhere else? And if he is somewhere else, then how do we provide a better clinical care for that individual? And those are conversations that we can't really have if we don't move to the cloud. So those types of- And of course there's always the OKRs, the actual measurements that you apply to things that we're doing. But at the end of the day, can we get the requirements from our business partners, bring those requirements to bear in technology, and really enable the indoctrination of these requirements throughout our clinical and healthcare kills? >> What about they're always pillars here, right? Governance, huge pillar, security, huge pillar, especially in your world, right? >> Yeah. >> So making that move over to the cloud and still recognizing that these are essentials that you have to have in place, I wouldn't say adjustments, but what kind of, I guess, recognition have you had toward that and making sure that you're still very true to those principles that are vital in the terms of public health? >> It is a great question because our secretary at the time and our governor, Roy Cooper, were very focused on enabling transparency. We had to be very transparent with what we were doing because the residents in North Carolina were just really kind of, "What's going on?" It was a scary time for a lot of us. So transparency was a key element towards our success. And in order to do that, you've got to have proper security. You got to have proper governance. You've got to have proper builds within technology that really enable that kind of visibility. One of the things that we did very early on was we set up a governance structure for our cloud environments so that as we wanted to and stand up an easy-to environment or we wanted to do some sort of work within a cloud or stand up in a different environment, we were able actually to set up a framework for how do you introduce that. Are you doing it correctly? Do you have the proper security on it? Do you have the funding for it? Like all the steps that you need to really kind of build into the scaffolding around a lot of these efforts we had to put in place and pretty quickly to get them going. But once we did that, the acceptance and the adoption of it was just tremendous. I mean, it was a light on for all of our business partners 'cause they understood I can either build on-prem, in which case I won't be able to get what I want in any kind of reasonable time period. Or I can build on cloud. And I can have it in some cases in 48 hours. >> Right, tomorrow. >> Yeah, exactly. >> You know, it was a huge difference. >> So where are you there? I mean, this is just not like a really big old lift and shift and we're all done and this is great. Cloud's taken care of all of our needs. Where are you in terms of the journey that you're undertaking? And then ultimately where do you want to go, like how far? What kind of goals have you set for yourself for the next two, three years down the road? >> Yeah, so this is an exciting part because we have actually- Like I mentioned earlier, we are a cloud-first cloud-only strategy, right? There's no reasons for us to be on-prem. It's just a matter of us kind of sunsetting legacy systems and bringing on cloud performance. We hope to be a 60% of our applications, which we have over 400 applications. So it's pretty large footprint. But we're wanting to migrate all of that to the cloud by 2025. So if we can achieve that, I think we'll be well on our way. And the momentum will carry forward for us to do that. We've actually had to do a reorganization of our whole IT structure. I think this is an important part to maintain that momentum because we've reorganized our staff, reorganized ourselves so that we can focus more on how do you adopt cloud, how do you bring in platforms which are all cloud-based, how do you use data within those systems? And that has allowed us to kind of think differently about our responsibilities, who's accountable for what, and to kind of keep those, that momentum going. So we've got some big projects that are on right now. Some of them are lift and shift, like you mentioned. We have a project with kind of a clumsy, monolithic system. It's called (indistinct). We're trying to migrate that to the cloud. We're in the process of doing that. And it's an excellent demonstration of capability once we pull that off. And then of course any new procurement that we put out there no one's making anything for on-prem anymore. Everyone's making their SaaS products for cloud-based experiences. Or if we're going to build or just use integrators then we'll build that in house. But all of it's based on cloud. >> And you mentioned SaaS. How much of this stuff are you doing on your own? And how much are you doing through managed services? >> Yeah, so like I mentioned, we have over 400 applications. So we had a pretty large footprint, right? >> Big, it's huge, right. >> So we're only who we are, and we can only build so much. So we're kind of taking- We did a application rationalization effort, which kind of identified some threats to our systems. Like maybe they're older things, FoxPro, kind of older languages that we're using. And in some cases we got people who are retiring. And there's not many people who can support that anymore. So how do we take those and migrate them to the cloud, either put them on a Salesforce or ServiceNow or Microsoft Dynamics platform and really kind of upgrade those systems? So we're in the process of kind of analyzing those elements. But yeah, that's kind of the exciting launch, if you will, of kind of taking the existing visibility of our applications and then applying it to what we're capable of with the cloud. >> And if you had advice that you could give to your colleagues who are in public health or just in public, the public sector- And your resources, they're finite. This is kind of what you have to deal with. And yet you have needs, and you're trying to stay current. You've got talent challenges, right? You've got rev or spending challenges. So if you could sit down your colleagues in a room and say, "Okay, this has been our experience. Here's what I would keep an eye out for," what kind of headlights would you beat for them? >> Yeah, so I think the biggest aha that I'd like to share with my contemporaries out there is that you've got a great ability to lower your costs, to excite your own personnel because they want to work on the new stuff. We've actually set up a whole professional development pathway within our organization to start getting people certified on AWS, certified on other platforms, to get them ready to start working in those environments. And so all of that work that we're been doing is coming together and allowing us to maintain the momentum. So what I'd recommend to people is, A, look at your own individual staff. I don't think you need to go outside to find the talent. I think you can train the talent that you have interior. I think you've got to aggressively pursue modernization because modernization enables a lot more. It's less expensive. It enables quicker adoption of business requirements and modern business requirements. And then lastly, focus on your data sharing because what you're going to find in the platforms and in the clouds is that there is a lot more opportunities for data integrations and conjoining disparate data sources. So if you can do those elements, you'll find that your capabilities on the business side are much more, much greater on the other end. >> Don't be scared, right, jump in? (laughing) >> Definitely don't be scared. Don't be, the water's warm. (host laughing) Come on in, you're fine, you're fine. (laughing) >> No little toe dipping in there. You're going to dive into the deep end, let her rip. >> Exactly, just go right in, just go right in. >> Well, it sounds like you've done that with great success. >> I'm very happy with it. >> Congratulations on that. And wish you success down the road. >> Thank you very much, I appreciate it. >> Yeah, thank you, Charles. All right, back with more. You are watching theCUBE here in Las Vegas. theCUBE of course the leader, as you know, in tech coverage. (soft music)

(upbeat music) >> Welcome back to Las Vegas, guys and girls. We're so happy that you're with us. This is our first full day of coverage live on theCube at AWS re:Invent '22. We're in Vegas, as I said at the Venetian Expo one of the biggest places to host, and there's probably about 50,000 people here or so. Lisa Martin and Dave Vellante Dave, we've had such great conversations. We talked about data, data, data. Every company is a data company. The most important thing is to make sure that data is accessible, that there's insights gained from it, but that it's protected and recoverable should anything happen. >> Yeah, security is the most important topic right now. We all know that it's the number one priority. The Cloud has changed the security model. the shared responsibility model is great, but at the same time, now you got shared responsibilities across multiple clouds, your developers are being asked to do more, right? It kind of the audit is like the last line of defense. So what the ecosystem does with AWS is really make the CISO's job easier. As opposed to, I mean AWS is a friendly place for security companies and I'm excited to talk about that. >> Yeah, we're going to be unpacking that. Rick Holtman is here, the VP of Advertising and Media Security at Human Security. Rick, welcome to theCUBE. >> Oh, thank you so much. Thanks for having me on. >> Pleasure to have you on here. So talk to us about Human Security. What do you do, what are the differentiators and what's in the name? >> Sure. Human is a cybersecurity company. It's been around for about 12 years right now, and our mission is truly to disrupt the economics of cyber crime. And right now, businesses are under attack like they have not been before. There's been a proliferation of bots on site that are truly hitting people's businesses. And what everyone will understand is that when bots hit your site and permeate your business, you'll never end up with a positive business outcome. >> Let's just say. What are in terms of competitive differentiators, when you're in customer conversations, what are those top three things that you say, this is why you go Human. >> Yeah, and that's great. This is why you go Human. We have a tremendous sensor network and what that gives us is observability. Because of our clients and partners, we're actually able to see 20 trillion transactions a week that we filter. And what that does is enables us to look across a broad spectrum of industry. Because of our partner networks, we're able to see all the media transacted across this ecosystem. And what we're working to do is preserve and protect that. So when we work with an SSP, DSP, ad servers and truly the pillars of technology across media, those are our core clients. And we very quickly, in under 10 milliseconds, let them know is this a bot or a human being you're about to serve an ad to, which is paramount to saving them money and not wasting their precious ad dollars. >> So what am I buying from you? Is it a subscription? Explain that. >> Sure. You're buying a subscription to the Human Defense Platform, and across that platform we've got multiple cyber tools. And what we do is we'll take different combinations of those tools and create a specific solution to address a use case. Each one of these businesses is very unique, so we had to be very flexible and malleable with the tools that we use and be able to create custom solutions, which is really what sets us apart in market. >> What are some of the key use cases that you're helping customers to address? >> Sure. It can be anything from simply guarding a website, and actually providing insights and the ability to mitigate bots, it can be guarding against account takeover, form fills. There are so many ways and attack vectors right now for people to get us at that we've got multiple disciplinary ways of looking at how to deploy solutions. It is going to continue to grow because we're seeing more and more new platforms and new types of innovation. A great example is in-game advertising. It is very new, but the industry is starting to look at it and say, hey, we know as growth comes, we're going to see fraud. How do we get out in front of that? How do we make sure that we don't have the same issue we had with CTV? Explosive growth happen before standards were in place, and now we're playing catch up and it's a huge issue. >> How are you doing that as the fraudsters are just getting more and more sophisticated? >> And that's really the problem. I think you hit it on the head. They'll continually change how they attack. They'll continually put resources behind it. And that's why I talk about disrupting the economics of cyber crime because the more we're able to mitigate and stop this, we actually make the cost of attack more and more expensive. Eventually, they're going to move on to a softer target and we want to harden up all of our clients so they're not that soft target. >> I always say, you're in the denominator business You get the bigger denominator, less value so they'll move on to somewhere else. What is your secret sauce? Is it your data? Is it your humans? >> You know, it's actually really three pillars. Part of what we talked about, which is observability. How much we're able to see because of the vast view through our partner network. And that's the other piece is this partner network. So we have what we'll call collective protection because we have so many different data inputs and understanding or what we'll call signal that we're able to interpret. And that is really one of our large differentiators. The last piece is disruption. So we'll use both the signal, our network, and truly go after these fraudsters and actually penalize 'em. And we are responsible for partly one of the largest ad fraud take downs, and someone is sitting in jail today because of it. >> Can you explain the anatomy of an ad hack? Like, what's that look like? I mean, I'm sure there's a lot of different profiles, but what's a common thing? >> And there's a few different profiles, right? One could simply be bots hitting your site, your homepage, right? That could skew data that will be used by a marketing team to make strategic decisions for a business. Form fills, account takeovers, there's all these different types of attack vectors. And then what we also specialize in across the programmatic industry is really reading what we'll call a bid stream. All these pieces of data that are going to come in, and that's how we can actually take a look at the device, the IP, and some of these signals when you put them all together, they give us a true picture of is this a human being or an automated bot swarm trying to permeate a business? >> Okay, and the automated bot swarm. So take it from the hacker's point of view. What's their objective of, you know, hitting you with those bots? What happens after they flood the zone? >> It really depends what they want. In certain cases it could be to actually take over someone's account and buy things. It can be, again, hitting the marketing component and actually driving differentiation on someone's site with form fills and surveys. So there's lots of different ways that they come to us. Inside the bid streams we're able to stop quickly because we're really high up in the actual food chain of that technology. So before some of these ad servers make a single decision, they'll make a call to Human and we'll quickly tell them serve this ad or do not. >> And the profile is largely criminals, not so much nation-state attack, or is it? >> Well, it really could be a little bit of everybody. That's the toughest part to tell. I would say we deal mostly with criminals more than I think nation-states. And people that are simply going after money, and when they see soft targets and people that don't have either they're site hardened or a true understanding of what they're fighting against, they get taken advantage of very quickly. >> What are some of the positive business outcomes that your customers are achieving? Maybe you have a favorite customer story example that you think really shines light on the value that Human is delivering. >> Sure. There's a huge customer inside the media ecosystem, and they truly serve as the gatekeepers or barriers to a lot of fraud. They look at Human as a strategic partner to make sure that when we bring on customers, they're all above board and we are not actually allowing anyone to permeate this advertising and media ecosystem with fraud. So we work hand in glove with lots of the largest platforms across media to really make sure this ecosystem is protected as it can be. >> So- >> You have the sets... Oh, go ahead please. I'm sorry. >> I was going to say, but you do more than media, is that right? >> Absolutely. We have a tremendous enterprise side of our business as well. And that is looking at financials, hospitality companies, travel companies. We really work across a full ecosystem. Bots aren't siloed. They don't care what industry you're in. So we set up industry expertise and domain expertise both across the media spectrum, as well as other components so that we can go as deep as we need to to really mitigate this. >> So you've got this huge observation space, this kind of sensor network if you will. what's the proportionality between the number of channels that we've seen evolve, and the way that that attackers are approaching the hacks? >> Sure. I think, you know, when we look at channels or platforms, the moment a new platform opens up, it gets attacked and we're continually seeing this. So the minute there is money moving towards any sort of industry, you'll see fraud right behind it. So we very carefully track industries, and we make sure we understand the changes and evolutions that are happening so we can get out in front. And a great example is in-game advertising and audio in-game advertising. They're brand new and we're starting to see money shift there for the first time. So those are the companies that have come to us immediately and said, hey, we know what's coming next. The money's here, fraud's on the way, how can Human help us? >> We haven't talked about 5G. It's rare that we don't talk about 5G, but how is that going to affect your customers? >> 5G is really going to give everybody ubiquity in terms of access, right? The more access we have, it allows your device `to become an attack vector. >> It's going to open up more channels. >> Rick: That's right. That's right. >> And so how are you planning as that becomes more mainstream to help customers combat that? As things just keep changing, there's so much flux going on. >> And that's it. You know, cyber is polymorphic. It will continue to change on us. So we are constantly evolving, and one of the things I always like to talk about with Human is the depth of the talent inside the company. And we source cyber talent globally, truly globally. All over the world, we have humans working with extreme expertise. So we've got this global perspective of what's happening everywhere in the world right now. And we're really leveraging that tremendously to fight the economics of cyber crime. >> How are you helping with your expertise at Human, companies address the massive skills gap in cybersecurity? >> Well, that's exactly it. I think there's a lot of education going on. When we meet customers or prospects, we make sure they understand the gravity of the situation and make sure we can help them see and provide insights so they understand who's attacking them, what they're being attacked with, and how to fight back. >> So what's the next step for your technology approach? How should we think about your roadmap? What are your customers asking you 'cause it's hard, right? Like you said, it's polymorphic. Sometimes it's hard to predict, but at the same time, you know, it's like you defend against yourself. You know, you say, okay let's flip the equation. You know, where are weaknesses? What are you guys thinking about in the future? >> Sure, it's a great question. We've continued to build out the Human defense platform. We merged with another company about six months ago, and we just acquired a company as well. The reason we continue on this growth path is to continue to put products and services in place so that we can continue to grow and really actually mitigate against all the different potential attacks out there. So we'll continue to add products, we'll continue to add services because as we see more and more attacks coming, we've got a greater understanding of the how and the why. So we're actually building out products that specifically hit these new pockets in industry so we can get there first and really create a beachhead. >> And how do you work with AWS? >> Sure, AWS is strategic partner and they've done a great job of helping lean in with us. We're not only working with AWS, but working across their ecosystem and working with some of their partners as well and some of their clients as well. So we're really standing up this Human Defense Platform for our partners and direct clients as well. >> Can you give us any examples of that? >> I'm not really allowed to name names when it comes to that. I apologize, but it's truly across their entire partner network. >> Got it. What are some of the things that you've heard? We're only at day one, obviously of re:Invent '22. Anything that you've heard today, maybe during the keynote or some of the things on the show floor that really excite you about the direction that AWS is moving, and the opportunities that it's going to deliver to Human? >> Sure. Absolutely. I think one of the things that was mentioned today was their clean room initiative, and I think that is an excellent place where Human has a great fit. And I think that our filtering technology and our layer there will really make sure that a clean room stays clean, and that the data that is actually joined and used is pure data and not rife with any bots. >> Got it. Humansecurity.com. Last question, Rick. If you had a bumper sticker to put on a fancy shiny new car and it was about Human, what would it say? >> It would say, know who's real. Keep it human. >> Love it. Know who's real, keep it human. Rick, thank you so much for joining us on the program. >> Thanks so much for having me. >> Introducing Human Security to our audience. We appreciate that. Really exciting stuff and so needed, especially in today's dynamic cyber landscape. We appreciate your insights. >> Rick: My pleasure. Thank you guys. >> All right. For our guest and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE. The leader in live enterprise and emerging tech coverage. (soft bright music)

(upbeat music) >> Hello, everyone. Welcome to theCUBE's coverage here at AWS re:Invent 2022. This is the Executive Summit with Accenture. I'm John Furrier, your host of theCUBE with two great guests coming on today, really talking about the future, the role of humans. Radically human is going to be the topic. Paul Daugherty, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, Global Managing Director of Thought Leadership and Technology Research, Accenture. Gentlemen, thank you for coming on theCUBE for this conversation around your new hit book, "Radically Human." >> Thanks, John. It's great to be with you and great to be present at re:Invent. >> We've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're in this, I call it the systems thinking, revolution is going on now where things have consequences and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as as humans. And so I love the book, very, very strong content, really right on point. What was the motivation for the book? And congratulations, but I noticed you got the structure, part one and part two, this book seems to be packing a big punch. What was the motivation, and what was some of the background in putting the book together? >> That's a great question, John. And I'll start, and then, Jim, my co-author and colleague and partner on the book can join in too. If you step back from the book itself, we'd written a first book called "Human + Machine", which focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the human plus machine pairing. And then when we started working on the next book, it was the COVID era. COVID came on line as we were writing the book. And that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing. Once COVID hit, every company became more dependent on technology. Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies, and what was different from the first research we had done around our first book. And what we found, which was super interesting, is that pre-pandemic, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of 2x. And that was before the pandemic. After the pandemic, we redid the research and the gap widened into 5x. And I think that's played a lot into our book. And we talk about that in the opening of our book. And the message there is exactly what you said is technology is not just the lifeline from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around inflation, energy, supply chain crisis because of the war in Ukraine, et cetera. And companies need the technology more than ever. And that's what we're writing about in "Radically Human." And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud, data and AI, and the metaverse that signal out as three trends that are really driving transformative change for companies. In the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are going to set companies apart as they look to implement this technology and transform their companies for the future. >> Jim, weigh in on this flipping the script, flipping the assumptions. >> You used a really important word there and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as a point solution. They don't think about AI in terms of taking a systems approach. So we were trying to address that. All right, if you're going to build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate it using your talent, focusing on trust, experiences and sustainability? >> I like how it reads. It's almost like a masterclass book because you set the table. It's like, 'cause people right now are like in the mode of what's going on around me? I've been living through three years of COVID. We're coming out the other side. The world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where am I today. So I think the first part really to me hits home. Like, here's the current situation and then part two is here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or society. >> Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where "Radically Human", the title came from. And what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot. And the whole hypothesis or premise of the book I should say, is that the more human like the technology is, the more radically human or the more radical the human potential improvement is, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. Just a couple examples from the ideas framework, the I in IDEAS. The ideas framework is the first part of the book. The five areas to flip your assumptions. The I stands for intelligence and we're talking about more human and less artificial in terms of the intelligence techniques. Things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build using the kind of systems thinking that Jim mentioned. And things like emotional AI, common sense AI, new techniques in addition to machine, the big data driven machine learning techniques, which are essential to vision and solving big problems like that. So that's just an example of how you bring it together and enable that human potential. >> I love the idea, go ahead Jim. >> I was going to say we've been used to adapting to technology, and contorting our fingers to keyboards and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus, in fact, the human is in the ascended. That's one of the big ideas that we try to put out there in this book. >> I love the idea of flipping the script, flipping the assumptions, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, S for strategy. Notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution. Really interesting how you guys put that together. It feels like business is becoming agile and iterative and how it's going to be forming. Can you guys, I mean that's my opinion, but I think observing how developers becoming much more part of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation if you take it down to a conclusion and strategy is just what you do after you get the outcomes you need? What's your reaction to that? >> Yeah, I think one of the most lasting elements of the book might be that chapter on strategy in my opinion, because you need to think about it differently. The old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to lay out with the S in IDEAS, the strategy. The subtitle that chapter is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, that's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential role that technology plays and therefore they need to master technology. Well, you need to think about strategy differently then because of the pace of technology innovation. And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really important. It's about continuous strategy in all cases. An example is one of the techniques we talk about, forever beta, which is, think about a Tesla or companies that it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days as Paul was saying. >> It's interesting because that's the trend you're seeing with more data, more automation, but the human plays a much critical role. And just aside on the Tesla example, is well documented. I think I wrote about in a post just this week that during the model three, Elon wanted full automation and had to actually go off scripts and get to humans back in charge 'cause it wasn't working properly. Now they have a balance. But that brings up to part two, which I like, which is this human piece of it. We always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that second half, trust, talent, experiences. That's more of the person's role, either individually as part of a collective group. Is talent the scarce resource now where that's the goal, that's the key 'cause it all could point to that in a way. Skills gap points to, hey, humans are valuable. In fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think that's something that is not, kind of nuanced point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >> Yeah, go ahead Jim. >> I was going to say it, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book, really zooming in on talent. I think you might think that for every hundred dollars that you put into a technology initiative, you might put 50 or 75 into re-skilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw economic analysis recently that pointed out that for every $1 you spend on technology, you are likely going to need to spend about $9 on intangible human capital. That means on talent, on getting the best talent, on re-skilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >> That's a huge point. >> And I think some of the elements of talent that become really critical that we talked about in the book are becoming a talent creator. We believe the successful companies of the future are going to be able not just to post a job opening and hire people in because there's not going to be enough. And a lot of the jobs that companies are creating don't exist 'cause the technology changing so fast. So the companies that succeed are going to know how to create talent, bring in people, apprentices and such, and shape to tale as they go. We're doing a significant amount of that in our own company. They're going to be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what employees want. And then democratizing access to technology. Things like Amazon's Honeycode is an example, low-code/no-code development to spread development to wider pools of people. Those types of things are really critical going forward to really unlock the talent potential. And really what you end up with is, yeah, the human talent's important, but it's magnified and multiplied by the power of people, giving them in essence superpowers in using technology in new ways. >> I think you nailed it, that's super important. That point about the force multiplier when you put things in combination, whether it's group constructs, two pizza teams flexing, leveraging the talent. I mean, this is a new configuration. You guys are nailing it there. I love that piece. And I think groups and collectives you're going to start to see a lot more of that. But again, with talent comes trust when you start to have these ephemeral and or forming groups that are forming production systems or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously metaverse is a pretext to the virtual world where we're going to start to create these group experiences and create new force multipliers. How does the metaverse play into this new radically human world, and what does it mean for the future of business? >> Yeah, I think the metaverse is radically misunderstood to use the word title when we're not with the title of our book. And we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So that's the potential of the metaverse. And it's not just about the consumer things, it's about metaverse and the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I believe that it has tremendous potential. We write about that in the book and it really takes radically human to another level. And one way to think about this is cloud is really becoming the operating system of business. You have to build your enterprise around the cloud as you go forward. That's going to shape the way you do business. AI becomes the insight and intelligence in how you work, infused with the human talent and such as we said. And the metaverse then reshapes the experience layers. So you have cloud, AI building on top of this metaverse providing a new way to generate experiences for employees, citizens, consumers, et cetera. And that's the way it unfolds, but trust becomes more important because just as AI raises new questions around trust, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five-part framework or five essential parts of the framework around how you establish trust as you implement these new technologies. >> Yeah, we're seeing that about three quarters of companies are really trying to figure out trust, certainly with issues like the metaverse more broadly across their IT so they're focusing on security and privacy, transparency, especially when you're talking about AI systems, explainability. One of the more surprising things that we learned when doing the book, when we were doing the research is that we saw that increasingly consumers and employees want systems to be informed by a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, they're actually training the system by emulating human behavior. So turning the cameras on test drivers to see how they learn and then training the AI using that sense of humanity 'cause other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that AI system is learning from. Some really interesting innovations happening in that trust space. John. >> Jim, I think you bring up a great point that's worth talking more about. Because you're talking about how human behaviors are being put into the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and we've been calling it supercloud, some call it multi-cloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's going to happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with chat and some video. It's group behavior, it's groups convening, talking, getting things done, debating, doing things differently. And so this idea of humans informing design decisions or software with low-code/no-code, this completely changes strategy. I mean this is a big point of the book. >> Yeah, no, I go back to one of the, the E in the IDEAS framework is expertise. And we talk about from machine learning to machine teaching, which is exactly that. Machine learning is maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with AI. One of the examples we give is one of the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to encode in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >> Well, yeah, it's interesting. I want to to get your thoughts as we get wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in the enterprise of their businesses, as they look at the horizon, they see the the future. They got to start thinking about things like generative AI and how they can bring some of these technologies to the table. We were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are new things you guys are hitting in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge certainly that is an opportunity. How do you apply all this stuff for business? >> I'll go first then Jim can add in. But the first thing I think starts with recognizing the role that technology does play and investing accordingly in it. So the right technology talent, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why the fact you're at re:Invent is so important because companies are, again, rebuilding that operating system of their business in the cloud. And you need that as the foundation to go forward, to do, to build the other types of capabilities. And then I think it's developing those talent systems as well. Do you have the right talent brand? Are you attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward? And then you marry the two together and that's what gives you the radically human formula. >> Yeah. When we were developing that first part of the book, Paul and I did quite a bit of research, and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. One statistic is that 70% of companies that had never tried AI before went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies were not trying to do it themselves and to necessarily build an AI department. They were partnering and it's really important to find a partner, often a cloud partner as a way to get started, start small scale, and then scale up doing experiments. So that was one of the key insights that we had. You don't need to do it all yourself. >> If you see the transformation of just AWS, we're here at re:Invent, since we've been covering the events since 2013, every year there's been a thematic thing. It was startups, enterprise, now builders, and now change your company. This year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and running a SaaS application on the cloud. People are are changing and refactoring and replatforming categorical applications in for this new era. And we're calling it supercloud, superservices, superapps, 'cause they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools, or talent pools in certain ways. So this is real, something's happening here and we've been talking about it a lot lately. So I have to ask you guys, how does a company know if they're radical enough? Like what is radical? How can I put a pin in that? It's like take a temperature or we like radical enough, what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening? How do you know if you're you're pushing the envelope radical enough to take advantage? >> Yeah, I think one. >> You can go ahead, Paul. >> Yeah, I was going to say one of the tests is the impact on your business. You have to start by looking at all this in the context of your business, and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. That's still something you need to do. But now our focus with a lot of our customers is on how do you innovate and grow your business in the cloud? What's the platform that you're using for your new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test whether you're being radical enough is on the one hand, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping people, your human talent with the capabilities they need to perform in very different ways? And those are the two tests that I would give. >> Totally agree. >> Interesting enough, we love this topic and you guys, again, the book is spot on. Very packs of big punch on content, but very relevant in today. And I think one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like IDEAS, your framework, and understand where they are and what's available and what's coming around the corner. They stand out in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean you're building clouds on top of clouds or something's happening. I think you see it, look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >> Yeah and that's a good example. And it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows and the portability of being able to connect and use data across cloud environments and such is tremendously powerful. And I think that's why, you talk about companies doing things differently, that's why it's great, again, that you're at re:Invent. If you look at the index of our book, you'll see AWS mentioned a number of times 'cause we tell a lot of customer company stories about how they're leveraging AWS capabilities in cloud and AI to really do transformative things in their business. And I think that's what it's all about. >> Yeah, and one of the things too in the book, it's great 'cause it has the systems thinking, it's got really relevant information, but you guys have seen the movie before. I think one of the wild cards in this era is global. We're global economy, you've got regions, you've got data sovereignty, you're seeing all kinds of new things emerging. Thoughts on the global impact 'cause you take your book and you overlay that to business, like you got to operate all over the world as a human issue, as a geography issue. What's your guys take on the global impact? >> Well that's why you got to think about cloud as one technology. We talked about in the book and cloud is, I think a lot of people think, well, clouds, it's almost old news. Maybe it's been around for a while. As you said, you've been going to re:Invent since 2013. Cloud is really just getting started. And it's 'cause the reasons you said, when you look at what you need to do around sovereign cloud capability if you're in Europe. For many companies it's about multi-cloud capabilities that you need to deploy differently in different regions. And they need to, in some cases for good reason, they have hybrid cloud capability that they match on their own. And then there's the edge capability which comes into play in different ways. And so the architecture becomes very complex and we talk the A in IDEAS is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and just modularity was the key thing you thought about. It's more the idea of a living system, of living architecture that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the pace of technology advancement. >> Yeah, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is going to be a big discussion as these new flipped assumptions start to generate more activity. It's going to be very interesting to watch. Gentlemen, thank you so much for spending the time here on theCUBE as we break down your new book, "Radically Human" and how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at re:Invent. Thanks so much for sharing and congratulations on a great book. >> Thanks, John. And just one point I'd add is that one of the things we do talk about in talent is the need to reskill talent. People who need to be relevant in the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those that need to reskilling. And the final point I mentioned is that we've mentioned at the end of the book that all proceeds from the book are being donated to NGOs and nonprofits that are focused on reskilling those who need a skill refresh in light of the radically human change in technology that's happening. >> Great. Buy the book. Proceeds go to a great cause and it's a very relevant book. If you're in the middle of this big wave that's coming. this is a great book. There's a guidepost and also give you some great ideas to reset, reflip the scripts, refactor, replatform. Guys, thanks for coming on and sharing. I really appreciate it. Again, congratulations. >> Thanks, John. >> Thanks, John. Great discussion. >> You're watching theCUBE here covering the executive forum here at AWS re:Invent '22. I'm John Furrier, you're host with Accenture. Thanks for watching. (gentle music)

(upbeat music) >> Hello, everyone. Welcome to theCUBE's coverage here at AWS re:Invent 2022. This is the Executive Summit with Accenture. I'm John Furrier, your host of theCUBE with two great guests coming on today, really talking about the future, the role of humans. Radically human is going to be the topic. Paul Daugherty, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, Global Managing Director of Thought Leadership and Technology Research, Accenture. Gentlemen, thank you for coming on theCUBE for this conversation around your new hit book, "Radically Human." >> Thanks, John. It's great to be with you and great to be present at re:Invent. >> We've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're in this, I call it the systems thinking, revolution is going on now where things have consequences and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as as humans. And so I love the book, very, very strong content, really right on point. What was the motivation for the book? And congratulations, but I noticed you got the structure, part one and part two, this book seems to be packing a big punch. What was the motivation, and what was some of the background in putting the book together? >> That's a great question, John. And I'll start, and then, Jim, my co-author and colleague and partner on the book can join in too. If you step back from the book itself, we'd written a first book called "Human + Machine", which focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the human plus machine pairing. And then when we started working on the next book, it was the COVID era. COVID came on line as we were writing the book. And that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing. Once COVID hit, every company became more dependent on technology. Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies, and what was different from the first research we had done around our first book. And what we found, which was super interesting, is that pre-pandemic, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of 2x. And that was before the pandemic. After the pandemic, we redid the research and the gap widened into 5x. And I think that's played a lot into our book. And we talk about that in the opening of our book. And the message there is exactly what you said is technology is not just the lifeline from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around inflation, energy, supply chain crisis because of the war in Ukraine, et cetera. And companies need the technology more than ever. And that's what we're writing about in "Radically Human." And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud, data and AI, and the metaverse that signal out as three trends that are really driving transformative change for companies. In the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are going to set companies apart as they look to implement this technology and transform their companies for the future. >> Jim, weigh in on this flipping the script, flipping the assumptions. >> You used a really important word there and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as a point solution. They don't think about AI in terms of taking a systems approach. So we were trying to address that. All right, if you're going to build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate it using your talent, focusing on trust, experiences and sustainability? >> I like how it reads. It's almost like a masterclass book because you set the table. It's like, 'cause people right now are like in the mode of what's going on around me? I've been living through three years of COVID. We're coming out the other side. The world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where am I today. So I think the first part really to me hits home. Like, here's the current situation and then part two is here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or society. >> Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where "Radically Human", the title came from. And what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot. And the whole hypothesis or premise of the book I should say, is that the more human like the technology is, the more radically human or the more radical the human potential improvement is, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. Just a couple examples from the ideas framework, the I in IDEAS. The ideas framework is the first part of the book. The five areas to flip your assumptions. The I stands for intelligence and we're talking about more human and less artificial in terms of the intelligence techniques. Things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build using the kind of systems thinking that Jim mentioned. And things like emotional AI, common sense AI, new techniques in addition to machine, the big data driven machine learning techniques, which are essential to vision and solving big problems like that. So that's just an example of how you bring it together and enable that human potential. >> I love the idea, go ahead Jim. >> I was going to say we've been used to adapting to technology, and contorting our fingers to keyboards and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus, in fact, the human is in the ascended. That's one of the big ideas that we try to put out there in this book. >> I love the idea of flipping the script, flipping the assumptions, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, S for strategy. Notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution. Really interesting how you guys put that together. It feels like business is becoming agile and iterative and how it's going to be forming. Can you guys, I mean that's my opinion, but I think observing how developers becoming much more part of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation if you take it down to a conclusion and strategy is just what you do after you get the outcomes you need? What's your reaction to that? >> Yeah, I think one of the most lasting elements of the book might be that chapter on strategy in my opinion, because you need to think about it differently. The old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to lay out with the S in IDEAS, the strategy. The subtitle that chapter is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, that's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential role that technology plays and therefore they need to master technology. Well, you need to think about strategy differently then because of the pace of technology innovation. And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really important. It's about continuous strategy in all cases. An example is one of the techniques we talk about, forever beta, which is, think about a Tesla or companies that it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days as Paul was saying. >> It's interesting because that's the trend you're seeing with more data, more automation, but the human plays a much critical role. And just aside on the Tesla example, is well documented. I think I wrote about in a post just this week that during the model three, Elon wanted full automation and had to actually go off scripts and get to humans back in charge 'cause it wasn't working properly. Now they have a balance. But that brings up to part two, which I like, which is this human piece of it. We always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that second half, trust, talent, experiences. That's more of the person's role, either individually as part of a collective group. Is talent the scarce resource now where that's the goal, that's the key 'cause it all could point to that in a way. Skills gap points to, hey, humans are valuable. In fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think that's something that is not, kind of nuanced point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >> Yeah, go ahead Jim. >> I was going to say it, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book, really zooming in on talent. I think you might think that for every hundred dollars that you put into a technology initiative, you might put 50 or 75 into re-skilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw economic analysis recently that pointed out that for every $1 you spend on technology, you are likely going to need to spend about $9 on intangible human capital. That means on talent, on getting the best talent, on re-skilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >> That's a huge point. >> And I think some of the elements of talent that become really critical that we talked about in the book are becoming a talent creator. We believe the successful companies of the future are going to be able not just to post a job opening and hire people in because there's not going to be enough. And a lot of the jobs that companies are creating don't exist 'cause the technology changing so fast. So the companies that succeed are going to know how to create talent, bring in people, apprentices and such, and shape to tale as they go. We're doing a significant amount of that in our own company. They're going to be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what employees want. And then democratizing access to technology. Things like Amazon's Honeycode is an example, low-code/no-code development to spread development to wider pools of people. Those types of things are really critical going forward to really unlock the talent potential. And really what you end up with is, yeah, the human talent's important, but it's magnified and multiplied by the power of people, giving them in essence superpowers in using technology in new ways. >> I think you nailed it, that's super important. That point about the force multiplier when you put things in combination, whether it's group constructs, two pizza teams flexing, leveraging the talent. I mean, this is a new configuration. You guys are nailing it there. I love that piece. And I think groups and collectives you're going to start to see a lot more of that. But again, with talent comes trust when you start to have these ephemeral and or forming groups that are forming production systems or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously metaverse is a pretext to the virtual world where we're going to start to create these group experiences and create new force multipliers. How does the metaverse play into this new radically human world, and what does it mean for the future of business? >> Yeah, I think the metaverse is radically misunderstood to use the word title when we're not with the title of our book. And we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So that's the potential of the metaverse. And it's not just about the consumer things, it's about metaverse and the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I believe that it has tremendous potential. We write about that in the book and it really takes radically human to another level. And one way to think about this is cloud is really becoming the operating system of business. You have to build your enterprise around the cloud as you go forward. That's going to shape the way you do business. AI becomes the insight and intelligence in how you work, infused with the human talent and such as we said. And the metaverse then reshapes the experience layers. So you have cloud, AI building on top of this metaverse providing a new way to generate experiences for employees, citizens, consumers, et cetera. And that's the way it unfolds, but trust becomes more important because just as AI raises new questions around trust, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five-part framework or five essential parts of the framework around how you establish trust as you implement these new technologies. >> Yeah, we're seeing that about three quarters of companies are really trying to figure out trust, certainly with issues like the metaverse more broadly across their IT so they're focusing on security and privacy, transparency, especially when you're talking about AI systems, explainability. One of the more surprising things that we learned when doing the book, when we were doing the research is that we saw that increasingly consumers and employees want systems to be informed by a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, they're actually training the system by emulating human behavior. So turning the cameras on test drivers to see how they learn and then training the AI using that sense of humanity 'cause other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that AI system is learning from. Some really interesting innovations happening in that trust space. John. >> Jim, I think you bring up a great point that's worth talking more about. Because you're talking about how human behaviors are being put into the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and we've been calling it supercloud, some call it multi-cloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's going to happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with chat and some video. It's group behavior, it's groups convening, talking, getting things done, debating, doing things differently. And so this idea of humans informing design decisions or software with low-code/no-code, this completely changes strategy. I mean this is a big point of the book. >> Yeah, no, I go back to one of the, the E in the IDEAS framework is expertise. And we talk about from machine learning to machine teaching, which is exactly that. Machine learning is maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with AI. One of the examples we give is one of the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to encode in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >> Well, yeah, it's interesting. I want to to get your thoughts as we get wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in the enterprise of their businesses, as they look at the horizon, they see the the future. They got to start thinking about things like generative AI and how they can bring some of these technologies to the table. We were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are new things you guys are hitting in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge certainly that is an opportunity. How do you apply all this stuff for business? >> I'll go first then Jim can add in. But the first thing I think starts with recognizing the role that technology does play and investing accordingly in it. So the right technology talent, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why the fact you're at re:Invent is so important because companies are, again, rebuilding that operating system of their business in the cloud. And you need that as the foundation to go forward, to do, to build the other types of capabilities. And then I think it's developing those talent systems as well. Do you have the right talent brand? Are you attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward? And then you marry the two together and that's what gives you the radically human formula. >> Yeah. When we were developing that first part of the book, Paul and I did quite a bit of research, and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. One statistic is that 70% of companies that had never tried AI before went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies were not trying to do it themselves and to necessarily build an AI department. They were partnering and it's really important to find a partner, often a cloud partner as a way to get started, start small scale, and then scale up doing experiments. So that was one of the key insights that we had. You don't need to do it all yourself. >> If you see the transformation of just AWS, we're here at re:Invent, since we've been covering the events since 2013, every year there's been a thematic thing. It was startups, enterprise, now builders, and now change your company. This year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and running a SaaS application on the cloud. People are are changing and refactoring and replatforming categorical applications in for this new era. And we're calling it supercloud, superservices, superapps, 'cause they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools, or talent pools in certain ways. So this is real, something's happening here and we've been talking about it a lot lately. So I have to ask you guys, how does a company know if they're radical enough? Like what is radical? How can I put a pin in that? It's like take a temperature or we like radical enough, what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening? How do you know if you're you're pushing the envelope radical enough to take advantage? >> Yeah, I think one. >> You can go ahead, Paul. >> Yeah, I was going to say one of the tests is the impact on your business. You have to start by looking at all this in the context of your business, and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. That's still something you need to do. But now our focus with a lot of our customers is on how do you innovate and grow your business in the cloud? What's the platform that you're using for your new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test whether you're being radical enough is on the one hand, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping people, your human talent with the capabilities they need to perform in very different ways? And those are the two tests that I would give. >> Totally agree. >> Interesting enough, we love this topic and you guys, again, the book is spot on. Very packs of big punch on content, but very relevant in today. And I think one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like IDEAS, your framework, and understand where they are and what's available and what's coming around the corner. They stand out in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean you're building clouds on top of clouds or something's happening. I think you see it, look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >> Yeah and that's a good example. And it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows and the portability of being able to connect and use data across cloud environments and such is tremendously powerful. And I think that's why, you talk about companies doing things differently, that's why it's great, again, that you're at re:Invent. If you look at the index of our book, you'll see AWS mentioned a number of times 'cause we tell a lot of customer company stories about how they're leveraging AWS capabilities in cloud and AI to really do transformative things in their business. And I think that's what it's all about. >> Yeah, and one of the things too in the book, it's great 'cause it has the systems thinking, it's got really relevant information, but you guys have seen the movie before. I think one of the wild cards in this era is global. We're global economy, you've got regions, you've got data sovereignty, you're seeing all kinds of new things emerging. Thoughts on the global impact 'cause you take your book and you overlay that to business, like you got to operate all over the world as a human issue, as a geography issue. What's your guys take on the global impact? >> Well that's why you got to think about cloud as one technology. We talked about in the book and cloud is, I think a lot of people think, well, clouds, it's almost old news. Maybe it's been around for a while. As you said, you've been going to re:Invent since 2013. Cloud is really just getting started. And it's 'cause the reasons you said, when you look at what you need to do around sovereign cloud capability if you're in Europe. For many companies it's about multi-cloud capabilities that you need to deploy differently in different regions. And they need to, in some cases for good reason, they have hybrid cloud capability that they match on their own. And then there's the edge capability which comes into play in different ways. And so the architecture becomes very complex and we talk the A in IDEAS is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and just modularity was the key thing you thought about. It's more the idea of a living system, of living architecture that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the pace of technology advancement. >> Yeah, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is going to be a big discussion as these new flipped assumptions start to generate more activity. It's going to be very interesting to watch. Gentlemen, thank you so much for spending the time here on theCUBE as we break down your new book, "Radically Human" and how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at re:Invent. Thanks so much for sharing and congratulations on a great book. >> Thanks, John. And just one point I'd add is that one of the things we do talk about in talent is the need to reskill talent. People who need to be relevant in the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those that need to reskilling. And the final point I mentioned is that we've mentioned at the end of the book that all proceeds from the book are being donated to NGOs and nonprofits that are focused on reskilling those who need a skill refresh in light of the radically human change in technology that's happening. >> Great. Buy the book. Proceeds go to a great cause and it's a very relevant book. If you're in the middle of this big wave that's coming. this is a great book. There's a guidepost and also give you some great ideas to reset, reflip the scripts, refactor, replatform. Guys, thanks for coming on and sharing. I really appreciate it. Again, congratulations. >> Thanks, John. >> Thanks, John. Great discussion. >> You're watching theCUBE here covering the executive forum here at AWS re:Invent '22. I'm John Furrier, you're host with Accenture. Thanks for watching. (gentle music)

>>Hello and welcome to the Cube's coverage here at AWS Reinvent 2022. This is the Executive Summit with Accenture. I'm John Furry, your host of the Cube at two great guests coming on today, really talking about the future, the role of humans. Radically human is gonna be the topic. Paul Dardy, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, global managing director of thought Leadership and Technology research. Accenture. Gentlemen, thank you for coming on the cube for this conversation around your new hit book. Radically human. >>Thanks, John. It's great to, great to be with you and great, great to be present at reinvent. >>You know, we've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're kind of in this, I call it the systems thinking, revolutions going on now where things have consequences and, and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as, as humans. And so I love the book. Very, very strong content, really. Right on point. What was the motivation for the book? And congratulations. But, you know, I noticed you got the, the structure part one and part two, This book seems to be packing a big punch. What's, what was the motivation and, and what was some of the background in, in putting the book together? >>That's a great question, John, and I'll start, and then, you know, Jim, my co-author and, and part colleague and partner on this, on the book and join in too. You know, the, if you step back from the book itself, we'd written a first book called, you know, Human Plus Machine, which talked about the, you know, focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the Human plus machine pairing. And then, you know, when we started, you know, working on the next book, Covid was, you know, it was kinda the Covid era. Covid came online as, as we were writing the book. And, but that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing, you know, once Covid hit, every company became more dependent on technology. >>Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies ba, you know, and what was different from the first, you know, research we had done around our first book. And what we found, which was super interesting, is that, is that, you know, pre pandemic, the, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of two x. And that was before the pandemic. After the pandemic. We redid the research and the gap widen into five x. And I think that's, and, and that's kind of played a lot into our book. And we talk about that in the opening of our book. And the message message there is exactly what you said is technology is not just the lifeline, you know, from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around, you know, inflation energy, supply chain crisis because of the war in Ukraine, et cetera. >>And companies need the technology more than ever. And that's what we're writing about in, in Radically Human. And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud data and ai and the metaverse that signal out is three trends that are really driving transformative change for companies. And the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are gonna set companies apart as they look to, you know, to implement this technology and transform their companies for the future. >>Jim, weigh in on this. Flipping the script, flipping the assumptions. No, >>You, you, you used a really important word there, and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as kind of a point solution. They don't think of about AI in terms of taking a systems approach. So we were trying to address that, all right, if you're gonna build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the, the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate using your talent, focusing on trust, experiences and sustainability. >>You know, I like this, I like how it reads. It's almost like a masterclass book because you kind of set the table. It's like, cuz people right now are like in the mode of, you know, what's going on around me. I'm been living through three years of covid. But coming out the other side, the world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where I am, where am I today. So I think the first part really to me hits home, like, here's the current situation and then part two is, here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or you know, society. >>Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where, you know, radically human, you know, the title came from. And you know, the, what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot and, and that, you know, the whole hypothesis, you know, or premise of the book I should say, is that the more humanlike the technology is, the more radically human or the more radical the, you know, the, the the, the human potential improvement is the more, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I, you know, talk about, you know, talked about, you know, talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. >>Just a couple examples from the ideas framework, the eye and ideas is each of the, the ideas framework is the first part of the book, The five areas to flip your Assumptions, The eye stands for intelligence. And we're talking about more, more human and less artificial in terms of the intelligence techniques, things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build, using the kind of systems thinking that Jim mentioned. And you know, things like emotional ai, common sense ai, new techniques in addition to machine the big data driven machine learning techniques which are essential to vision and solving big problems like that. So that's, that's just an example of, you know, how you bring it together and enable that human potential. >>I love the, we've been, >>We've >>Go ahead Jim. >>I was gonna say we've been used to adapting to technology, you know, and you know, contorting our fingers to keyboards and and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus. In fact, the human is in the ascended. That's one of the, one of the big ideas that we try to put out there in this book. >>You know, I love the idea of flipping the script, flicking assumptions, but, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, s for strategy, notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution really kind of interesting kind of how you guys put that together. It kind of feels like business is becoming agile and iterative and it's how it's gonna be forming. Can you guys, I mean that's my opinion, but I think, you know, observing how developers becoming much more part of, of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is kind of how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation? If you take it down to a conclusion, strategy is just what you do after you get the outcomes you need. Is that, can you, what's your reaction to that? >>Yeah, yeah, I think, I think one of the most lasting elements of the book might be that chapter on strategy in, in my opinion, because you need to think about it differently. The old, old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to, you know, to lay out with the, the essence ideas, you know, the strategy and the, the, the fun. You know, the, the subtitle that chapter is is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, That's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential world that technology plays and therefore they need to, to master technology, well, you need to think about strategy differently than because of the pace of technology innovation. >>And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really report it's about continuous strategy in all cases. Yet an example is one of the techniques we talk about forever beta, which is, you know, think about a Tesla, you know, companies that, you know, it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along, you know, the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we, we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions, you know, might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days. As Paul was saying, >>It's interesting because that's the kind of the trend you're seeing with more data, more automation. But the human plays a much critical role. And, and just as a side on the Tesla example, you know, is well documented, I think I wrote about in a post just this week that during the model three Elon wanted full automation and had to actually go off script and get to humans back in charge cuz it wasn't working properly. Now they have a balance. But that brings up the, the part two, which I like, which is, you know, this human piece of it, you know, we always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that, that second half, you know, trust, talent experiences, that's the more the person's role, either individually as part of a collective group is talent. The scarce resource now where that's the, that's the goal, that's the, the key because I mean, it all could point to that in a way, you know, skills gap kind of points to, hey, you know, humans are valuable, in fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think, you know, that's something that is not kind of nuance point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >>Yeah, it's, go ahead Jim. I was gonna say it, you know, we're, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book. You know, really zooming in on talent. I think, you know, you might think that for every, you know, a hundred dollars that you put into a technology initiative, you know, you might put 50 or 75 into reskilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw a, a economic analysis recently that pointed out that for every $1 you spend on technology, you are likely gonna need to spend about $9 on intangible human capital. That means, you know, on talent, on, on getting the best talent on reskilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >>That's a huge point. >>I think some of the elements of talent that become really critical that we, we talked about in the book are, are becoming a talent creator. We believe that the successful companies of the future are gonna be able not, not just to post, you know, post a job opening and hire, hire people in because there's not gonna be enough. And a lot of the jobs that companies are creating don't exist, you know, cause the technology changing so fast. So companies that succeed are gonna know how to create talent, bring in people, apprentices and such and, and, and, you know, shape to tail as they go. We're doing a significant amount of that in our own company. They're gonna be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what you know, employees want. And then democratizing access to technology, You know, things like, you know, Amazon's honey code is an example, you know, low code, no code development to spread, you know, development to wider pools of people. Those types of things are really critical, you know, going forward to really unlock the talent potential. And really what you end up with is, yeah, the, the human talent's important, but it's magnified to multiplied by the power of people, you know, giving them in essence superpowers in using technology in new >>Ways. I think you nailed it, That's super important. That point about the force multiplier, when you put things in combination with it's group constructs, two pizza teams, flexing, leveraging the talent. I mean, this is kind of a new configuration. You guys are nailing it there. I love that piece. And I think, you know, groups and collectives, you're gonna start to see a lot more of that. But again, with talent comes trust when you start to have these kind of, you know, ephemeral and or forming groups that are forming production systems or, or, or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously Metaverse is a pretext to the virtual world where we're gonna start to create these group experiences and create new force multipliers. How does the Metaverse play into this new radically human world and and what does it mean for the future of business? >>Yeah, I think the Metaverse is radically, you know, kind of misunderstood to use the word title, word of a, when we're not with the title of our book, you know, and we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So, you know, that that's the potential of the metaverse. And it's about, it's not just about the consumer things, it's about metaverse in the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I, I believe you know that it is, has tremendous potential. We write about that in the book and it really takes radically human to another level. >>And one way to think about this is cloud is really becoming the operating system of business. You, you have to build your enterprise around the cloud as you go forward that's gonna shape the way you do business. AI becomes the insight and intelligence in how you work, you know, in infused with, you know, the human talent and such as we said. And the metaverse then reshapes the experience layers. You have cloud AI building on top of this metaverse providing a new way to, to generate experiences for, for employees, citizens, consumers, et cetera. And that's the way it unfolds. But trust becomes more important because the, just as AI raises new questions around trust, you know, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five part framework or or five, you know, essential, you know, parts of the framework around how you establish trust as you implement these new technologies. >>Yeah, we're seeing that, you know, about three quarters of companies are really trying to figure out trust, you know, certainly with issues like the metaverse more broadly across their it, so they're, you know, they're focusing on security and privacy transparency, especially when you're talking about AI systems. Explainability. One of the, you know, the more surprising things that we learned when doing the book, when we're doing the research is that we saw that increasingly consumers and employees want systems to be informed by kind of a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, the, they're, they're actually training the system by emulating human behavior. So kind of turning the cameras on test drivers to see how they learn and then training the AI kind of using that sense of humanity cuz you know, the other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that that AI system is learning from or some really interesting innovations kind of happening in that trust space. John, >>Jim, I think you bring up a great point that's worth talking more about because you know, you're talking about how human behaviors are being put into the, the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and you know, we've been calling it super cloud, some call it multicloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's gonna happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with Chad and some video, you know, it's, it's group behavior, it's group con groups, convening, talking, getting things done, you know, debating doing things differently. And so this idea of humans informing design decisions or software with low code no code, this completely changes strategy. I mean this is a big point of the book. >>Yeah, no, I go back to, you know, one of the, the, the, the e and the ideas frameworks is expertise. And we talk about, you know, from machine learning to machine teaching, which, which is exactly that, you know, it's, you know, machine learning is, you know, maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with ai? One of the examples we give is one of the, the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to code in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create, you know, amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >>Well you, what's interesting is that I wanna to get your thoughts as we can wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in, in the enterprise of their businesses, as they look at the horizon, they see the, the future, they gotta start thinking about things like generative AI and how they can bring some of these technologies to the table where, you know, we were, we were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are, these are new things you guys are hitting on this in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge, certainly that is an opportunity. How, how do you apply all this stuff for, for business >>Now? I'll go first then Jim Canad. But the, the first thing I think starts with, with recognizing the role that technology does play and investing accordingly in it. So the right, you know, technology, talent, you know, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why, you know, the fact you're at reinvent is so important because companies are, you know, again rebuilding that, that operating system of their business in the cloud. And you need that, you know, as the foundation to go forward, to do, you know, to, to build the other, other types of capabilities. And then I think it's developing those talent systems as well. You know, do you, do you have the right the, do you have the right talent brand? Are you attacking the right, attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward and then you marry the two together and that's what, you know, gives you the radically human formula. >>Yeah. When, you know, when we were developing that first part of the book, Paul and I did quite a bit of, of research, and this was ju and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. You know, one statistic is that 70% of, there was a, there was a of companies that had never tried AI before, went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies are not, or we're not trying to do it themselves and to, you know, to necessarily, you know, build an it, a AI department. They were partnering and it's really important to, to find a partner, often a cloud partner as a way to get started, start small scale and then scale up doing experiments. So that was one of the, that was one of the key insights that we had. You don't need to do it all yourself. >>If you see the transformation of just aws, we're here at reinvent just since we've been covering the events since 2013, every year there's been kind of a thematic thing. It was, you know, startups, enterprise now builders and now, now change your company this year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and, and running a SaaS application on the cloud. People are are changing and refactoring and replatforming, categorical applications in for this new era. And you know, we're calling it super cloud super services, super apps cuz they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools or talent pools in certain ways. So this is real, something's happening here and you know, we've been talking about a lot lately, so I have to ask you guys, how does a company know if they're radical enough? Like when, what is radical? How do, how can I put a pin in that say that could take a temperature or we like radical enough what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening. How do you know if you're, you're you're pushing the envelope radical enough to, to take advantage? >>Yeah, I think one, yeah, I was gonna say one of the, one of the tests is is you know, the impact on your business. You have to start by looking at all this in the context of your business and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. Yeah. That that's still something you need to do. But now we, our focus, you know, with a lot of our customers is on how do you innovate and grow your business in the cloud? What's, what is, you know, how, how, what's the platform you know, that you're using to, you know, for your, the new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test. Whether being radical, you know, radical enough is on the one hand, is this really, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping, you know, people, your human talent with the capabilities they need to perform in very different ways? And those are the the two tests that I would give. Totally agree. >>Yeah. You know, interesting enough, we, you know, we, we love this topic and guys, again, the book is spot on. Very packs a big punch on content, but very relevant in today. And I think, you know, one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like ideas your framework and understand where they are and what's available and what's coming around the corner. They stand out in the, in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean some, you're building clouds on top of clouds or, or something's happening. You can, I think you see it like look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >>Yeah, and that's a good example and it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows the portability of being able to connect and use data across cloud environments and such is, is, is is tremendously powerful. And I think that's why, you know, you talk about companies doing things differently, that's why it's great again that you're at reinvents. If you look at the index of our book, you'll see, you'll see AWS mentioned a number of times cuz we tell a lot of cus of cus customer and company stories about how they're leveraging aws, AWS capabilities in cloud and AI to really do transformative things in your, in their business. And I, I think that's what it's, that's what it's all about. >>Yeah, and one of the things too in the book, it's great cuz it has kind of a, the systems thinking it's got really relevant information but you know, you guys have seen the, seen the movie before. I think one of the wild cards in this era is global. You know, we're global economy, you've got regions, you've got data sovereignty, you're seeing, you know, all kinds of new things, emerging thoughts on the global impact cuz you, you take your book and you overlay that to business. Like you gotta, you gotta operate all over the world as a human issue. It's a geography issue. What's your guys take on the global impact? >>Well that's, that's why the, the, you gotta think about cloud as as one technology, you know, we talked about in the book and cloud is a lot, I think a lot of people think, well clouds it's almost old news. Maybe it's been around for a while. As you said, you've been going to reinvent since 2013. You know, cloud is really just getting, you know, just getting started. And, and it's cuz the reasons you said, when you look at what you need to do around sovereign cloud capability, if you're in Europe for many companies it's about multi-cloud capabilities. You need to deploy, you know, differently in different, in different regions. And they need to, in some cases for good reason, they have hybrid, hybrid cloud, you know, capability that they, they match on their own. And then there's the edge capability which is comes into play in, in different ways. >>And, and so the architecture becomes very complex and we talk the A in and ideas is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and mod and you know, just modularity was kind of the key thing you thought about. It's more the idea of a living system, of living architecture that's, that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the, with the pace of technology advancement. >>You know, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is gonna be a big discussion as these new flipped assumptions start to generate more activity. It's gonna be very interesting to watch. Gentlemen, thank you so much for spending the time here on the queue as we break down your new book, Radically Human and how it, how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at reinvent. Thanks so much for, for sharing and congratulations on a great book. >>You know, Thanks John. And just one point I'd add is that one of the, the things we do talk about in talent is the need to reskill talent. You know, people who need to, you know, be, be relevant to the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those who need to reskilling. And the final point I mentioned is that we mentioned at the end of the book that all proceeds for the book are being donated to not NGOs and nonprofits that are focused on reskilling. Those who need a skill refresh in light of the radically human new, you know, change in technology that's happening >>Great by the book proceeds go to a great cause and it's a very relevant book if you're in the middle of this big way that's coming. This is a great book. There's a guidepost and also give you some great ideas to, to reset re flip the scripts. Refactor, re-platform. Guys, thanks for coming on and sharing, really appreciate it. Again, congratulations. >>Thanks, John. John, great discussion. >>Okay, you're watching the Cube here, covering the executive forum here at AWS Reinvent 22. I'm John Furrier, your host with aen. Thanks for watching.

>>Hello, and welcome to this cubes presentation with unstoppable domains. It's a showcase we're featuring all the best content in web three. And with unstabled a showcase I'm John furrier, your host of the cube. We've got a great guest here, Matt Miscavige. Covich who's the chief revenue officer of unstoppable domains. Matt, welcome to the showcase. Appreciate it. >>Thank you for having me. So >>The theme of this segment is the potential of the web three marketplace with unstoppable domains, the chief revenue officer, you guys have a very intriguing, interesting concept. That's going extremely well. Congratulations, but you're using NFTs for access and domains. Of course, the, the metaverse is huge. People want their own domains, but it's not just like real estate in the sense of a website. It's bigger than that. It's a lot going on. So take us through what is the value proposition and what is the product? >>Absolutely. So for the past 20 years, most of us have been interacting on the internet. Using usernames issued to us by big corporations like Facebook, Google, Twitter, tech talks, Snapchat, et cetera. Whenever we get these usernames for free it's because we in our data are the product as some of the recent leaks. And the media has shown incentives. Individuals and companies are not always aligned. And most importantly, individuals are not in control of their own digital identity and the data, which means they can economically benefit from the value they create online. Think of Twitter as a two-sided marketplace with 0% revenue share back to its creators. We're now having in the creator economy and we believe that individuals should see the economic rewards of what they do in create online. That's all we're trying to do here at unstoppable domains is provide user own take control identity to four and a half billion internet users. >>It's interesting to see change that's happening with web three. And just in cultural terms, users are expecting to be part of the creative, the personality of the company. There's this almost this disintermediation of the middleman. You know, whether it's an ad network or a gatekeeper of any kind people going direct, right? So if I'm an artist, I can go direct to my fans. >>Exactly. So web through really shifts the power away from aggregators, aggregators and marketplaces have been some of the best business models. The last 20 years onto the internet, the web three is going to dramatically change that over the next decade, paying more power back in the hands of consumers. >>What type of companies do you guys work with and partner with that we see out there, what's give us some examples of the kinds of companies you're doing business with and partnering with. >>Yeah. So let's talk about use cases. First actually is the big use case that we identified initially for NFT domain names was around cryptocurrency transfers. Anyone who's ever bought cryptocurrency and tried to transfer it between the council while it's is familiar with these awkwardly long hexadecimal strings of random numbers and letters, where if you make a single type of money is lost forever. That's a pretty scary experience that exists today in our $2 trillion asset class with 250 million users. So the first set of partners that we worked on integrating with who actually cook the wilds and exchanges. So we will allow users to do is replace all their long hexadecimal wallet addresses with a single human readable name, like John dot NFT or Maxim needs give each dot crypto to allow for simple crypto transfers. >>And how did the exchange work with you guys on that as it is? Is it a plugin? Is it co-locating code together? What's the, what's the, what's the relationship between exchanges and unstoppable domains? >>Yeah, absolutely. A great question. So exchange has actually have to do a little bit of an engineering lift to work with us, and they can do that by either using our resolution libraries or using one of our API APIs or in order to look up an unstoppable name and figure out all the wallet addresses that's associated with that name. So today we work with dozens of the world's top exchanges and wallets ranging from Oko DX to Coinbase wallet, to trust wallet, to bread wallet, and many, many others. >>I got to ask you on the wallet side, is that a requirement in terms of having specific code and are there wallets that you work well with? Explain the wallet dynamic between unstoppable domains and wallets. >>Yeah. So while it's all have this huge usability problem for their users, because every single cryptocurrency held by every single one of their users has a different hexadecimal wallet address. And once again, every user is subject to the same human fallacies and errors, where they make a single type where their money can be lost forever. So we enable these wallets to do is to make crypto transfer as simple and as less scary than the current status code by giving the users on a sub well name that they can use to attach to all the waltz addresses on the backend. So companies like trust world, for example, which has 10 million users or Coinbase wallet. When you go to the crypto transfer fields, they can just type in an unstoppable name. They'll correctly, route the currency to the right person, to the right world, without any chance for human error. >>You know, when these big waves come, I gotta ask you this question. Cause a lot of people in the mainstream are getting into it. Now reminds me of the web wave that hit the big thing was how many people are coming online. It was one of the key metrics and how many web pages are being developed was another metric, which meant that people were building out web pages. And it's hard to look back and think, wow, that was actually a KPI. So internet users and webpages were the two proxies cause then search and just came out and everything else happened. So I'm going to ask you, there are people watching, they're seeing that on commercials on TV, they're seeing it everywhere stadiums are named after crypto companies. So the bottom line is people want to know how NFT domains take the fear out of working with crypto and sending crypto. >>Yeah, absolutely. So imagine if we had to navigate the web using IP addresses rather than typing in google.com, you'd have to type in a random string of words and numbers that you'd have to memorize. That would be super painful for users. And didn't, it wouldn't have gotten to where it is today with this, you know, almost 5 billion people online, the history of computer networks. We have human readable naming systems built on top. In every single instance. It's almost crazy that we got to a $2 trillion asset class with 250 million users worldwide 13 years after this, the Toshi white paper without a human readable naming system, other than supple domains and a few of our competitors, that's a fundamental problem that we need to solve in order to go from 250 million crypto users in 2022 to 5 billion crypto users, a decade from now. >>And just to point out and not to look back and maybe make a correlation, but I will, if you look at the naming system of DNS, what it did to IP addresses, that's one major innovation that enabled the web. Then you look at what keyword navigation has done on top of DNS, what that did for the industry. And that basically birthed Googled keywords, basically ads. So that's trillions and trillions of dollars again. Now shifting to you guys, is that how you see it? Obviously it's decentralized, so what's different. Okay. I get, so if you compare, Hey, Google was successful, you know, keyword advertising industry for less than 25 years or 20 years. >>Yeah. Yeah. What's different. Now is the technology inflection points. So blockchains have evolved to a point where they enable high throughput, high transaction volume and true decentralized ownership. The NFT standard, which is only a couple of years old know, has taken off massively around trading of profile pictures like crypto punks and the boy apes yacht club where they use cases extended much more than just, you know, a cool JPEG that goes up in value two or three X year over year. There is the true use case here around ownership of identity ownership over a data set, decentralized log-in authentication and permission data sharing. One of the sad things that happened in Jeanette on the internalized decade really was that the platforms built out have now allowed developers to built on top of them and a trustless permissionless way. Developers who build applications on top of some of the early monopolies in the last decade, got the rules changed on them. APIs, cutoff, new fees instituted. That's not going to happen in web three because all permissionless custody in a user's own wallet, we cannot take the way they will continue to exist in eternity, regardless of what happens to unstoppable domains, which gives developers a lot more confidence in building new products for the web three identity standard that we're building out. >>You guys amazing is that's a whole nother generational shift. I'm always been a big fan of abstractions when innovation is needed, when they're problems that need to be solved, messes to be cleaned up. Good abstraction layer on top of new architecture is really, really phenomenal. I guess the key question for I have for you is, you know, the queue, we have all this video where where's our NFT should, how should we implement NFTs? >>There's a couple of different ways you could think about it. You could do proof of attendance, protocol NFTs, which are really interesting way for users to show that they were at particular events. So just in the same way that people collect, t-shirts some conferences, people will be collecting. And if Ts to show, there were in person attending in person cultural moments, whether they were acquired an event online or offline, you could do NFTs for employees to show that they were at your company during certain periods of the company's growth. So think of replacing the resume with a cryptographically secure resume like this on the blockchain and perpetuity. Now more than half of all the resumes contain lies, which is a pretty gnarly problem as a hiring manager, or you constantly have to sort through as ways that this can impact that side of the market as well. >>I saw some, and I think it was a use case for everything. Appreciate that. And of course we can have the most favorite, cute moments. It could be a cube host NFT at 40 apes out there. Why not have a board cube host going on and, and >>Auction for charity on open? >>All right, great stuff. Now let's get into some of the cool tech nerd stuff, which is really the login piece, which I think is fascinating. The having NFTs be a login mechanism is another great innovation. Okay. So this is cool. Cause it's like think of it as one click and FTS, if you will. What's the response been on this? Log-in with unstoppable for that product? What some of the use gates is. Can you give some examples of the momentum and traction? >>Yeah, absolutely. So we launched the product less than 90 days ago. We already have 90 committed or integrated partners live today with a login product. And this replaces login with Google login with Facebook, with a way that's user owned and user controlled. And over time, people will be capturing additional information back to their NFP domain names, such as their reputation, their history, things they've done online and be able to permission to share that with applications that they interact with in order to get any rewards, once you own all your data and you can choose to share it with companies or incentivize you to share data. For example, imagine you just bought a new house and you have 3000 square feet to furnish. You could tell that fact and prove it to a company like Wayfair. Would they be incentivized to give you discounts? We're spending 10, 20, $30,000 and you'll do all of your purchasing there rather than spread across other e-commerce retailers. For sure they would. But right now, when you go to that website, you're just another random email address. They have no idea who you are, what you've done, what your credit score is, whether you house buyer or not. But if you could permission to share that to using a log-in open software product, I mean the web would just be much, much different. >>And I think one of the things too, as these, I call them analog old school companies, old guard companies is referred to in the cube talk here, but we were still always called that old guard is the people who aren't innovating. You could think about companies having more community too, because if you have more sharing and you have this marketplace concept and you have these new dynamics of how people are working together, sharing will provide more transparency, but yet security on identity. Therefore things are going to be happening organically. That's a community dynamic. What's your view on that? And what's your reaction >>Communities are such an important part of web three and the cryptos ecosystem in general, people are very tightly knit and they all support each other. There's a huge amount of collaboration in this space because we're all trying to onboard the next billion users into the ecosystem. And we know we have some fundamental challenges and problems to solve, whether it's complex wallet addresses, whether it's the lack of portable data sharing, whether it's just simple education, right? I'm sure, you know, tens of millions of people got into crypto for the first time during the super bowl face on some of those awesome ads that ran. >>Yeah. Love the QR code. That's a direct response. I remember when the QR code has been around for a long time. I remember in the nineties, late nineties, it was a thing, a device at red QR codes that did navigation to a webpage. So I mean, QR codes are super cool, great way to get, and we all using it to, with the pandemic to ordering food. So I think QR codes are here to stay. In fact, we should have a QR code on all of our images here on the screen too. So we'll work on that, but I gotta ask you on the project side, now let's get into the devs and kind of the applications, the users that are adopting unstoppable and this new way of doing things, why are they gravitating towards this login concepts? Can you give some examples and put, give some color commentary to why are these D application distribute application guys and gals programming and with you guys? >>Yeah. They all believe that the potential for why we're trying to create a round user own the controlled identity. We're the only company in the market right now with a product that's live and working today. There's been a lot of promises made and we're the first ones to actually deliver to companies like cook finance, for example, are seeing the benefit of being able to have their users go through a simple process to check in and authenticate into the application, using your NFT domain name, rather than having to create an email address and password combination as a login, which inevitably leads to problems such as lost passwords, password resets, all those fun things that we used to deal with on a daily basis. >>Okay. So now I got to ask you the kind of partnerships you guys are looking at doing. I can only imagine the old, old school days you had a registry and you had registrars, you had a sales mechanism. I noticed you guys are selling NFT kind of like domain names on your website. Is that a kind of a current situation? Is that going to be ongoing? How do you envision your business model evolving and what kind of partnerships do you see coming along? >>Yeah, absolutely. So we're working with a lot of different companies from browsers that took changes to wallets, to individual NFT projects, to more recently even exploring partnership, partnership opportunities with fashion brands. For example, the Tyree market is moving so so fast. And what we're trying to essentially do here is create the standard naming system for web three. So a big part of that for us, we'll be working with partners like blockchain.com and with circle who's behind the DC coin on creating registries, such as dot blockchain and dot coin and making those available to tens of millions and ultimately hundreds of millions and billions of users worldwide. We want an ensemble domain name to be the first asset that every user in crypto gets, even before they buy their Bitcoin Ethereum or dovish coin. >>It makes a lot of sense obstruct the way the long hexadecimal string. We all know that we all write down putting a safe, hopefully you don't forget about it. You know, I always say, make sure you tell someone where your addresses. So in case something happens, you don't lose all that crypto. All good stuff. I got to ask the question around the ecosystem. Okay, can you share your view and vision of either your purse, yourself or the company when you have this kind of new market, you have all kinds of, and we meant the web was a good example, right? Web pages, you need web development tools. You had HTML by hand. Then you had all these tools. So you had tools and platforms and things kind of came well, grew together. How was the web three stakeholder ecosystem space evolving? What's what are some of the white spaces? What are some of the clearly defined areas that are developing? >>Yeah, I mean, we've seen an explosion in new smart contract blockchains and the past couple of years actually going live, which is really interesting because they support a huge number of different use cases, different trade-offs on each. We recently partnered and moved over a primary infrastructure to polygon, which is a leading EVM compatible smart chain, which allows us to provide free gas fees to users for maintaining and managing their domain name. So we're trying to move all obstacles around user adoption. Here. We all need to have Ethereum in your wallet. You know, it'd be an unstoppable domains customer or user. You don't have to worry about paying transaction fees. Every time you want to update the wallet, addresses associated with your domain name. We want to make this really big and accessible for everybody. And that means driving down costs as much as possible. Yeah, >>It's a whole nother wave. It's a wave that's built on the shoulders of others. It's a shift and infrastructure, new capabilities, new new applications. I think it's a, it's a great thing. You guys doing the naming system makes a lot of sense. This abstraction layer creates that ease of use. It simplifies things makes things easier. I mean, this is, was the promise of, of these abstraction layers. Final question. If I want to get involved, say we want to do a cube NFT with unstoppable. How do we work with you? How do we engage? Can you give a quick plug on what companies can do to engage with you guys on a business level? >>Yeah, absolutely. So we're looking to partner with wallets, exchanges, browsers, and companies who are in the crypto space already and realize they have a huge problem around usability with crypto transfers and wild addresses. Additionally, we're looking to partner with decentralized applications as well as web to companies who perhaps want to offer log-in with unstoppable domain functionality. In addition to, or in replacement of the login with Google and log-in with Facebook buttons that we all know and love. And we're looking to work with fashion brands and companies in the sports sector who perhaps want to claim their unstoppable names, free of charge from us. I might add in order to use that on Twitter or other marketing materials that they may have out there in the world to signal that they're not only forward looking, but that they're supportive of this huge wave that we're all riding at the most. >>May I great insight, chief revenue officer ensemble domains. Thanks for coming on the showcase, the cube and unstoppable domain share in the insights. Thanks for coming on. Okay. This cubes coverage here with the unstoppable domain showcase. I'm John furrier, your host. Thanks for watching.

(upbeat music) >> Hey, welcome back to Las Vegas. theCUBE is live at AWS re:Invent 2021. I'm Lisa Martin. We have two live sets, theCUBE. We are running one of the largest hybrid tech events, most important events of the year with AWS and its massive ecosystem of partners like as I said. Two live sets, two remote sets. Over a hundred guests on the program talking about the next generation of cloud innovation. I'm pleased to welcome a first timer to theCUBE. Seth Rao, the CEO of FirstEigen joins me. Seth, nice to have you on the program. >> Thank you nice to be here. >> Talk to me about FirstEigen. Also explain to me the name. >> So FirstEigen is a startup company based out of Chicago. The name Eigen is a German word. It's a mathematical term. It comes from eigenvectors and eigenvalues which is used and what it's called is principal component analysis, which is used to detect anomalies, which is related to what we do. So we look for errors in data and hence our name FirstEigen. >> Got it. That's excellent. So talk to me. One of the things that has been a resounding theme of this year's re:Invent is that especially in today's age, every company needs to be a data company. >> Yeah. >> It's all one thing to say it's as a whole other thing to be able to put that into practice with reliable data, with trustworthy data. Talk to me about some of the challenges that you help customers solve 'cause some of the theme about not just being a data company but if you're not a data company you're probably not going to be around much longer. >> Yeah, absolutely .So what we have seen across the board across all verticals, the customers we work with is data governance teams and data management teams are constantly firefighting to find errors in data and fix it. So what we have done is we have created the software DataBuck that autonomously looks at every data set and it will discover errors that are hidden to the human eye. They're hard to find out, hard to detect. Our machine learning algorithms figure out those errors before those errors impact the business. In the usual way, things are sorted out, things are done. It's very laborious, time-consuming and expensive. You have taken a process that takes man-years or even man-months and compressed it to a few hours. >> So dramatic time-savings there. >> Absolutely. >> So six years ago when you guys were founded, you realize this gap in the market, thought it's taking way too long. We don't have this amount of time. Gosh, can you imagine if you guys weren't around the last 22 months when certainly time was of the essence? >> Absolutely. Yeah. Six years ago when we founded the company, my co-founder who's also the CTO. He has extensive experience in validating data and data quality. And my own background and my own experiences in AI and ML. And what we saw was that people are spending an enormous amount of time and yet errors were getting down through to the business side. And at that point it comes back and people are still firefighting. So it was a waste of time, waste of money, waste of effort. >> Right. But also there's the potential for brand damage, brand reputation. Whatever products and services you're producing, if your employees don't have the right data, if there's errors there of what's going out to the consumers is wrong then you've got a big problem. >> Absolutely. Interesting you should mention that because over the summer there was a Danish bank, a very big name Danish bank that had to send apology letters to its customers because they overcharged them on the mortgage because the data in the backend had some errors in it and didn't realize it was inadvertent. But somebody ultimately caught it and did the right thing. Absolutely correct. If the data is incorrect and then you're doing analytics or you're doing reporting or you're sending people a bill that they need to pay it better be very accurate. Otherwise it's a serious brand damage. It has real implications and it has a whole bunch of other issues as well. >> It does and those things can snowball very quickly. >> Yeah. >> So talk to me about one of the things that we've seen in the recent months and years is this explosion of data. And then when the pandemic struck we had this scattering of people and data sources or so much data. The edge is persistent. We've got this work from anywhere environment. What are some of the risks for organizations? They come to you and saying help us ensure that our data is trustworthy. I mean that the trust is key but how do you help organizations that are in somewhat a flux figure out how to solve that problem? >> Yeah. So you're absolutely correct. There is an explosion of data, number one. And along with that, there is also an explosion of analytical tools to mine that data. So as a consequence, there is a big growth. It's exponential growth of microservices, how people are consuming that data. Now in the old world when there were a few consumers of data, it was a lot easier to validate the data. You had few people who are the gatekeepers or the data stewards. But with an explosion of data consumers within a company, you have to take a completely different approach. You cannot now have people manually looking and creating rules to validate data. So there has to be a change in the process. You start validating the data. As soon as the data comes into your system, you start validating if the data is reliable at point zero. >> Okay. >> And then it goes downstream. And every stage the data hops that is a chance that data can get corrupted. And these are called systems risks. Because there are multiple systems and data comes from multiple systems onto the cloud, errors creep in. So you validate the data from the beginning all the way to the end and the kinds of checks you do also increase in complexity as the data is going downstream. You don't want to boil the ocean upfront. You want to do the essential checks. Is my water drinkable at this point, right? I'm not trying to cook as soon as it comes out of the tap. Is it drinkable? - Right. >> Good enough quality. If not then we go back to the source and say, guys, send me better quality data. So sequence, the right process and check every step along the way. >> How much of a cultural shift is FirstEigen helping to facilitate within organizations that now don't... There isn't time to, like we talked about if an error gets in, there's so many downstream effects that can happen, but how do you help organizations shift their mindset? 'Cause that's hard thing to change. >> Fantastic point. In fact, what we see is the mindset change is the biggest wall for companies to have good data. People have been living in the old world where there is a team that is a group, much downstream that is responsible for accurate data. But the volume of data, the complexity of data has gone up so much that that team cannot handle it anymore. It's just beyond their scope. It's not fair for us to expect them to save the world. So the mindshift has to come from an organization leadership that says guys, the data engineers who are upfront who are getting the data into the organization, who are taking care of the data assets have to start thinking of trustable data. Because if they stopped doing it, everything downstream becomes easy. Otherwise it's much, much more complex for these guys. And that's what we do. Our tool provides autonomous solution to monitor the data. It comes out with a data trust score with zero human input. Our software will be able to validate the data and give an objective trust score. Right now it's a popularity contest. People are saying they vote. Yeah, I think I like this. I like this and I like that. That's okay. Maybe it's acceptable. But the reason they do it is because there is no way to objectively say the data is trustable. If there is a small error somewhere, it's a needle in the haystack. It's hard to find out, but we can. With machine learning algorithms our software can detect the errors, the minutest errors, and to give an objective score from zero to a hundred, trust or no trust. So along with a mindset, now they have the tool to implement that mindset and we can make it happen. >> Talk to me about some of the things that you've seen from a data governance perspective, as we've seen, the explosion, the edge, people working from anywhere. This hybrid environment that we're going to be in for quite some time. >> Yeah. >> From a data governance perspective and Dave Vellante did his residency. We're seeing so many more things pop up, you know different regulations. How do you help facilitate data governance for organizations as the data volume is just going to continue to proliferate? >> Absolutely correct. So data governance. So we are a key component of data governance and data quality and data trustworthiness, reliability is a key component of it. And one of the central, one of the central pillars of data governance is the data catalog. Just like a catalog in the library. It's cataloging every data asset. But right now the catalogs, which are the mainstay are not as good as they can be. A key information that is missing is I know where my data is what I don't know is how good is my data? How usable is it? If I'm using it for an accounts receivable or an accounts payable, for example, the data better be very, very accurate. So what our software will do is it'll help data governance by linking with any data governance tool and giving an important component which is data quality, reliability, trustability score, which is objective to every data asset. So imagine I open the catalog. I see where my book is in the library. I also know if there are pages missing in the book is the book readable? So it's not good enough to know that I have a book somewhere but it's how good is it? >> Right >> So DataBuck will make that happen. >> So when customers come to you, how do you help them start? 'Cause obviously the data, the volume it's intimidating. >> Yeah. >> Where do they start? >> Great. This is interestingly enough a challenge that every customer has. >> Right. >> Everybody is ambitious enough to say, no, I want to make the change. But the previous point was, if you want to do such a big change, it's an organizational change management problem. So the way we recommend customers is start with the small problem. Get some early victories. And this software is very easy. Just bring it in, automate a small part. You have your sales data or transactional data, or operational data. Take a small portion of it, automate it. Get reliable data, get good analytics, get the results and start expanding to other places. Trying to do everything at one time, it's just too much inertia, organizations don't move. You don't get anywhere. Data initiatives will fail. >> Right. So you're helping customers identify where are those quick wins? >> Yes. And where are the landmines that we need to be able to find out where they are so we can navigate around them? >> Yeah. We have enough expedience over 20 years of working with different customers. And I know if something can go wrong we know where it'll go wrong and we can help them steer them away from the landmines and take them to areas where they'll get quick wins. 'Cause we want the customer to win. We want them to go back and say, look, because of this, we were able to do better analytics. We are able to do better reporting and so on and so forth. We can help them navigate this area. >> Do you have a favorite example, customer example that you think really articulates that value there, that we're helping customers. We can't boil the ocean like you said. It doesn't make any sense, but customer that you helped with small quick wins that really just opened up the opportunity to unlock the value of trustable data. >> Absolutely. So we're working with a fortune 50 company in the US and it's a manufacturing company. Their CFO is a little in a concern whether the data that she's reporting to the Wall Street is acceptable, does it have any errors? And ultimately she signing off on it. So she had a large team in the technology side that was supporting her and they were doing their best. But in spite of that, she's a very sharp woman. She was able to look and find errors and saying, "Something does not look right here guys. Go back and check". Then it goes back to the IT team and they go, "Oh yeah, actually, there was an error". Some errors had slipped through. So they brought us in and we were able to automate the process, What they could do. They could do a few checks within that audit window. We were able to do an enormous number of checks more. More detailed, more accurate. And we were able to reduce the number of errors that were slipping through by over 98%. >> Big number. >> So, absolutely. Really fast. Really good. Now that this has gone through they feel a lot more comfortable than the question is, okay. In addition to financial reporting, can I use it to iron out my supply chain data? 'Cause they have thousands of vendors. They have hundreds of distributors. They have products all over the globe. Now they want to validate all the data because even if your data is off in a one or 2%, if you're a hundred plus billion dollar company, it has an enormous impact on your balance sheet and your income statement. >> Absolutely. Yeah. >> So we are slowly expanding as soon as they allow us. They like us now they're taking it to other areas from beyond finance. >> Well it sounds like you have not only great technology, Seth but a great plan for helping customers with those quick wins and then learning and expanding within and really developing that trusted relationship between FirstEigen and your customers. Thank you so much for joining me on the program today. Introducing the company, what you guys are doing really cool stuff. Appreciate your time. >> Thank you very much. >> All right. >> Pleasure to be here. >> For Seth Rao, I'm Lisa Martin. You're watching theCUBE. 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(bright upbeat music) >> Hello everyone. And we're back at AWS Re:Invent. You're watching theCUBE and we're here, day two. Actually we started Monday night and we got wall-to-wall coverage. We going all the way through Thursday, myself. I'm Dave Volante with the co-host, David Nicholson. Lisa Martin is also here. Of course, John Furrier. Partners, technologists, customers, the whole ecosystem. It's good to be back in the live event. Of course we have hybrid event as well a lot of people watching online. Anshu Sharma is here. He is the co-founder and CEO of Skyflow, new type of privacy company, really interested in this topic. Great to see you. Thanks for coming on. >> Thank you, thanks for bringing me here. >> It's timely, you know. Privacy, security, they're kind of two sides of the same coin. >> Yes. >> Why did you found Skyflow? >> Well, the idea for Skyflow really comes from my background in some ways. I spent my first nine years at Oracle, six years at Salesforce. And whether we were building databases or CRM products, customers would come to us and say, "Hey, you know, I have this very different type of data. It's things like social security numbers, frequent flyer card numbers, card numbers. You know, can you secure it better? Can you help me manage things like GDPR?" And to be honest, there was never a clear answer. There's a lot of technology solutions out there that do one thing at a time, you can walk around the booths here, there's like a hundred companies. And if you use all those hundred things correctly, maybe you could go tell your board that maybe a social security number is not going to be lost anymore. And I was like, "You know, we've simplified everything else. Why is it so hard to protect my social security number? It should be easy. It should be as easy as using Stripe or Twilio." And this idea just never went away and kept coming back till a few years ago, we learned about the Facebook privacy challenges, the Equifax challenges. And I was like, boy, it's the time. It's time to go do it now. >> You started the company in 2019. Right? >> Yes. >> I mean, your timing was pretty good, right? So what are the big sort of Uber trends that you're seeing? Obviously GDPR, the California Consumer Privacy Act. I heard this morning. Did you hear this? That like, if you post a picture on social media now without somebody's permission, you're now violating their privacy. It's like, you can see the smiles on Anshu's face. >> Its like every week, we're like every week, there's a new story that could be like, well, Skyflow. The new story is the question, the answer is Skyflow. But honestly I think what's happened is, the issue is put very simple. You know all we're trying to do is protect people's social security numbers, phone numbers, credit card numbers, things we hold dear. At the same time, it's complex. Like what does it mean to protect your social security number let's say? Does that mean I don't get to use it for filing your taxes? Well, I need your credit card number to process a payment. And we were like, this is just too complicated. Why, how do companies like Apple do it? How do companies like Netflix manage not have as many breaches as my hotel that barely has any data. And the answer is those companies actually have evolved to a completely different architecture, the zero trust data architecture. And that was our inspiration for starting this company. >> Yeah. I mean. How many times have you been asked to give your social security number? And you're like, why? why do you want it? What are you going to do with it? How do you protect it? And they go, "I don't know." >> You know, what's even, my favorite is like, you give your social security number to say TurboTax, how many days of the year do they need to use it? One. How many days of the year do they have it? And the thing is, it's a liability for those CTOs too. >> Yeah right. >> The CTO of Walgreens, the CTO of Intuit. They don't really want that social security number just so they can process your card once a year, or your social security number once a year. It's almost like we're forcing them to hold onto data. And then they have to bear the burden of having these stories. Like, you know, everybody wants to prevent a New York Times story that says, what Robin Hood had a breach, Twitter had a breach. >> So walk us through how Skyflow would address something like that. So take the, you know, take the make a generic version of TurboTax, social security members. There they are right now, they're sitting in a database somewhere. Hopefully there's some security wrapped around it in some way or another. What would you advise a customer like that to do? And what are you actually doing for them? >> So, look, it's very simple. You are not going to put your username passwords in a generic database. You're going to use something like OD Zero or Octa to do it. We're living in a world where we have polyglot data stores. Like there's a key value store. There's a time series database. There is a search database like Elastic. There's a log database like Splunk. But PII data, Somehow we think just fine. If it's in a hundred places and our answer is that we should do the same thing that companies like Apple, Netflix, Google, everybody, does. They take this data. They completely isolate it from the databases. And it gets stored in a custom data store in our case, that would be Skyflow. And essentially we'd give you encrypted tokens back and you can use these encrypted tokens that look like fake social security number. It's called a Format Preserving Encryption. So if you think about all the breakthroughs we've had in homomorphic encryption, on secure elements, like the way your phone works, the credit card number is stored in a secure element. So it's the same idea. There's a secure part of your data stack, which is Skyflow. That basically keeps the data always protected. And because we can compute and search on encrypted data, this is important, everybody can encrypt data at rest. Skyflow is the first company that's come out and said, "Look, you can keep your phone number and social security number, encrypted while I can run an aggregation query." So I can tell you what's the balance of your customer's account balance. And i can run that query without decrypting, a single row of data. The only other company I know that can do that internally is a certain Cupertino based company. >> So think about it. Anybody can walk something up to a certain degree, but allowing frictionless access at the same time. >> While it's encrypted. So how do you make that? Are you, is a strategy to make that a horizontal service? That I can put into my data protection service or my E-commerce service or whatever. >> It's a cloud-based service that runs on AWS and other clouds. We basically given instance just like, you'll get an instance of a post-grad store or you get an API handled to OD Zero. You basically instantiate Skyflow of what gets created. It can be in your AWS environment, dedicated VPC. So it's private to you and then you have a handle and then basically you just start using it. >> So how, how do you, what's the secret sauce? How do you do that? >> The secret source. Well, now that we filed the patents on it, I can reveal the secret sauce. So the holy grail of encryption right now, if you go talk to people at a leading company, is there's something called Fully Homomorphic Encryption. That's fundamentally the foundation on which things like Bitcoin are built actually. But the hard part about Fully Homomorphic Encryption is it works. You can actually do mathematical computations on it without decrypting the data, but it's about a million times slower. >> Yes slower, right. >> So nobody uses it. My insight was that we don't need to do multiplications and additions on phone numbers. You never take my phone number and divide by your social security number. (Dave laughing) These numbers are not numbers, they are data structures. So our insight was if you treat them as specialized data structures, we're all talking about basically about 80 different types of data across the globe. Every human being has an ID, date of birth, height, color of eyes. There's not that many fields. What we can do then is create specialized encryption schemes for each data type. We call this polymorphic data encryption. Poly means multiple. As a result of that, we can actually store the data encrypted and build indexes on it. Since we can index interpret data, it's kind of like, imagine you can run real-time queries on data that's encrypted. Every other data store, When you encrypt the data, it becomes invisible to database. And that's why we had to build this as a full stacked service. Just like the Snowflake guys had to start with the foundation of storage, rethink indexing, and build Snowflake. We did the same thing, except we built it for encrypted indexes Whereas they built it for encrypted, for regular data stores. >> So thinking, if you think about today's tech stack, it's evolving, right? The data protection and security are coming together. Where does this fit? Is it sort of now becoming a fundamental part of the-- >> We think every leading company, whether you're building a new brokerage application or you are the largest bank in the world, and we're talking to some of them right now. They're all going to have an internal service called a PII wall. This wall just like Apple and Google have their own internal walls. You're going to have a wall service in your service oriented architecture, essentially. And it's going to basically be the API. Every other application and database in your company is not going to store my social security number. The SSNs don't belong in 600 databases at a leading bank. They don't belong inside your customer support system. Think about what happened with Robinhood two weeks ago, right? Someone tricked one call center guy into giving the keys up, which is fine happens. But why did the call center guy have access to like a million email addresses? He's never used going to use that. So we think if you isolate the PII, every leading company is going to end up with a PII Wall, as part of their core architecture. Just like today, we have an Alt API, you have a Search API, you have a Logging API, you're going to have a PII API. And that's going to be part of your modern data stack. >> So okay. So this is definitely not a bolt on, right? It's going to be a fundamental company, just like security is, just like backup is. It's now, you got to have it. It's-- >> Yes. I mean, if you think about it, it just logically makes sense. Like you should be isolating this data. You don't keep your money and gold around at home. You put it either in a locker or a bank. I think the same applies for PII. We just haven't done it because companies would pay off a fine for $10,000 or a million dollars. And. >> Yeah. So you've recently raised $45 million to expand your efforts. Obviously that means that people are looking at this and saying there's opportunity, right? What does that look like when you think of growth, where during your go to market strategy at first you're convincing people that it's a good idea to do it. Do you think or hope for, hope one day that there's an inflection point where it's not that people are thinking, you know, let's do this because it's a good idea, but people are like, I have to do this because if I don't, it's irresponsible and I'm going to be penalized for not having it. It becomes something that isn't really a choice. It's something where you just do it. >> So, you know, when we were starting the company, we didn't even have a word to explain what we were trying to do. We would say things like what if there was a cloud service for XYZ. And, but over the last one year, I don't want to take credit for creating this market, but this market has been created in the last year and a half. And you know, we get tons of people, including some of the largest institutions emailing us, saying, "I'm looking to build a PII wall, API service inside my company. Can you tell me why your product meets that need?" And I thought that would take us three to five years to get there. And, you know, we've ended up creating a category, basically just like other companies have. And I think, you know, you don't get, I believe in market permission. You don't get to create a category. The market gives somebody the permission to create a category. Saying, "Look, this makes sense. Something like this should emerge." And if you're there at the right time, like you said. >> Yep. >> You get to take the opportunity. >> So where are you at as a company say for some, some capital is great. When do you scale? >> We're scaling now? So we just doubled our headcount in the last nine to 10 months. We're now 75 people. We think we'll be about 150 to 200 people in the next year. We are hiring across all regions. We just hired a head of Asia pack from segment.com. We just hired our first, you know, lead on international expansion. And in the US, we have an office in Palo Alto. We have an office in Bangalore. We just announced a data residency solution for Europe, data residency solution for India and emerging markets. Because data residency is another one of those things that's just emerging right now. And irrespective of whether you believe in security and privacy. Data residency is one of those things that you are mandated to implement. >> And where are you hiring? Is it combination to go to market? Tell me about your go to market. >> The go to market. We are direct sales organization, but we work with partners. So we haven't announced some of these partnerships, but you're working with some of the companies here who either are large database companies, large security companies. We think there is a win-win relationship between us and some of the partner. >> You're a partner model, partner channel model. >> So, direct sales but partner assisted. >> Yeah. Right. All right. We got to go. Hey, awesome story. Congratulations. Best of luck. >> Very interesting. >> Love to have you back and track the progress. >> Thank you, thank you so much. >> Okay. Thank you for watching theCUBE, the leader in and high-tech coverage. We're at Re-Invent 2021. Be right back (upbeat music)

welcome back to the cube's presentation of the aws executive summit at re invent 2021 made possible by accenture my name is dave vellante we're going to look at how digital infrastructure is helping to transform consumer experiences specifically how an insurance company is changing its industry by incentivizing and rewarding consumers who change their behavior to live healthier lives a real passion of of mine and getting to the really root cause of health with me now are simon guest who's the chief executive officer of generality vitality gmbh and niels mueller who's the managing director at the cloud first application engineering lead for the european market at accenture gentlemen welcome to the cube thanks for having us you're very welcome simon generally vitality it's a really interesting concept that you guys have envisioned and now put into practice tell us how does it all work sure no problem and thanks for for having us on dave it's a pleasure to be here so look uh generally vitality is in its uh it's core pretty simple concepts so it's uh it's a program that you have on your phone and the idea of this program is that it's a it's a wellness coach for you as an individual and it's going to help you to understand your health and where you are in terms of the state of your health at the moment and it's going to take you on a journey to improve your your lifestyle and your wellness and hopefully help you to lead a healthier and a more sort of mindful life i guess is is the best way of summarizing it from um from our point of view with insurance company of course you know our historical role has always been to uh be the company that's there if something goes wrong you know so if unfortunately you pass away or you have sickness in your in your life or in your family's life that's that's historically been our role but what we see with generality vitality is something a little bit different so it's a program that really is uh supposed to be with you every day of your life to help you to live a healthier life it's something that we already have in in four european markets in fact in five from this week i'm a little bit behind the time so we're live already in in germany in france in austria and italy and in spain and fundamentally what we what we do dave is too is to say to customers look if you want to understand your health if you want to improve it by moving a little bit more by visiting the doctor more by eating healthier by healthy choices on a daily basis we're going to help you to do that and we're going to incentivize you for going on this journey and making healthy choices and we're going to reward you for for doing the same so you know we partner up with with great companies like garmin like adidas like big brands that are let's say invested in this health and wellness space so that we can produce really an ecosystem for customers that's all about live well make good choices be healthy have an insurance company that partners you along that journey and if you do that we're going to reward you for for that so you know we're here not just in the difficult times which of course is one of our main roles but we're here as a partner as a lifetime partner to you too to help you feel better and live a better life i love it i mean it sounds so simple but but it's i'm sure it's very complicated to to make the technology simple for the user you've got mobile involved you've got the back end and we're going to get into some of the tech but first i want to understand the member engagement and some of the lifestyle changes simon that you've analyzed what's the feedback that you're getting from your customers what does the data tell you how do the incentives work as well what what is the incentive for the the member to actually do the right thing sure look i think actually the the covered uh situation that we've had in the last sort of two years has really crystallized the fact that this is something that we really ought to be doing and something that our customers really value so i mean look just to give you a bit of a sort of information about how it works for for customers so what we try to do with them is is to get customers to understand uh their current health situation you know using their phone so uh you know we ask our customers to go through a sort of health assessment around how they live what they eat how they sleep you know and to go through that sort of process uh and to give them what a vitality age which is a sort of uh you know sort of actuarial comparison with their real age so i'm i'm 45 but unfortunately my my vitality age is 49 and it means i have some work to do to bring that back together uh and what we see is that you know two-thirds of our customers take this test every year because they want to see how they are progressing on an annual basis in terms of living a healthier life and if what if what they are doing is having an impact on their life expectancy and their lifespan and their health span so how long are they going to live healthier for so you see them really engaging in this in this approach of understanding their current situation then what we know actually because the program is built around this model that uh really activity and moving and exercise is the biggest contributor to living a healthier life we know that the majority of deaths are caused by lifestyle illness is like you know poor nutrition and smoking and drinking alcohol and not exercising and so a lot of the program is really built around getting people to move more and it's not about being an athlete it's about you know getting off the the underground one station earlier walking home or making sure you do your 10 000 steps a day and what we see is that that sort of 40 of our customers are on a regularly basis linking either their phone or their their exercise device to our program and downloading that data so that they can see how how much they are exercising and at the same time what we do is we set we set our customers weekly challenges to say look if you can move a little bit more than last week we are going to to reward you for that and we see that you know almost half of our customers are achieving this weekly goal every week and it's really a fantastic level of engagement that normally is an insurer uh we don't see the way the rewards work is is pretty simple it's similar in a way to an airline program so every good choice you make every activity you do every piece of good food that you eat when you check your on your health situation we'll give you points and the more points you get you go through through a sort of status approach of starting off at the bottom status and ending up at a gold and then a platinum status and the the higher up you get in the status that the higher the value of the rewards that we give you so almost a quarter of our customers now and this is accelerated through provide they've reached that platinum status so they are the most engaged customers that we we have and those ones who are really engaging in the in the program and what we really try to create is this sort of virtuous circle that says if you live well you make good choices you improve your health you you progress through the program and we give you better and stronger and more uh valuable rewards for for doing that and some of those rewards are are around health and wellness so it might be that you get you get a discount on on gym gear from adidas it might be that you get a discount on a uh on a device from garmin or it might be actually on other things so we also give people amazon vouchers we also give people uh discounts on holidays and another thing that we we did actually in the last year which we found really powerful is that we've given the opportunity for our customers to convert those rewards into charitable donations because we we work in generality with a with a sort of um campaign called the human safety net which is helping out the poorest people in society and some what our customers do a lot of the time is instead of taking those financial rewards for themselves they convert it into a charitable donation so we're actually also thinking wellness and feeling good and insurance and some societal good so we're really trying to create a virtuous circle of uh of engagement with our customers i mean that's a powerful cocktail i love it you got the the data because if i see the data then i can change my behavior you got the gamification piece you actually have you know hard dollar rewards you could give those to charities and and you've got the the most important which is priceless can't put a value on good health i got one more question for simon and niels i'd love you to chime in as well on this question how did you guys decide simon to engage with accenture and aws and the cloud to build out this platform what's the story behind that collaboration was there unique value that you saw that that you wanted to tap that you feel like they bring to the table what was your experience yeah look i mean we worked at accenture as well because the the the sort of construct of this vitality proposition is a pretty a pretty complex one so you mentioned that the idea is simple but the the build is not so uh is not so simple and that that's the case so accenture's been part of that journey uh from the beginning they're one of the partners that we work with but specifically around the topic of rewards uh you know we're we're a primarily european focused organization but when you take those countries that i mentioned even though we're next to each other geographically we're quite diverse and what we wanted to create was really a sustainable and reusable and consistent customer experience that allowed us to go and get to market with an increasing amount of efficiency and and to do that we needed to work with somebody who understood our business has this historical let's say investment in in the vitality concept so so knows how to bring it to life but that what then could really support us in making uh what can be a complex piece of work as simple and as as replicable as possible across multiple markets because we don't want to go reinventing the wheel every time we do we move to a new market so we need to find a balance between having a consistent product a consistent technology offer a consistent customer experience with the fact that we we operate in quite diverse markets so this was let's say the the reason for more deeply engaging with accenture on this journey thank you very much niels why don't you comment on on that as well i'd love to to get your thoughts and and really really it's kind of your role here i mean accenture global si deep expertise in industry but also technology what are your thoughts on this topic yeah i'd love to love to comment so when we started the journey it was pretty clear from the outset that we would need to build this on cloud in order to get this scalability and this ability to roll out to different markets have a central solution that can act as a template for the different markets but then also have the opportunity to localize different languages different partners for the rewards there's different reward partners in the different markets so we needed to build in an asset basically that could work as a tempos centrally standardizing things but also leaving enough flexibility to to then localize in the individual markets and if we talk about some of the more specific requirements so one one thing that gave us headaches in the beginning was the authentication of the users because each of the markets has their own systems of record where the basically the authentication needs to happen and we somehow needed to still find a holistic solution that comes through the central platform and we were able to do that at the end through the aws cognito service sort of wrapping the individual markets uh local idp systems and by now we've even extended that solution to have a standalone cloud native kind of idp solution in place for markets that do not have a local idp solution in place or don't want to use it for for this purpose yeah so you had you had data you have you had the integration you've got local laws you mentioned the flexibility you're building ecosystems that are unique to the to the local uh both language and and cultures uh please you had another comment i interrupted you yeah i know i just wanted to expand basically on the on the requirements so that was the central one being able to roll this out in a standardized way across the markets but then there were further requirements for example like being able to operate that platform with very low operations overhead there is no large i.t team behind generally vitality that you know works to serve us or can can act as this itis backbone support so we needed to have basically a solution that runs itself that runs on autopilot and that was another big big driver for first of all going to cloud but second of all making specific choices within cloud so we specifically chose to build this as a cloud native solution using for example manage database services you know with automatic backup with automatic ability to restore data that scales automatically that you know has all this built in which usually maybe a database administrator would take care of and we applied that concept basically to every component to everything we looked at we we applied this requirement of how can this run on autopilot how can we make this as much managed by itself within the cloud as possible and then land it on these services and for example we also used the the api gateway from from aws for our api services that also came in handy when for example we had some response time issues with the third party we needed to call and then we could just with a flick of a button basically introduce caching on the level of the api gateway and really improve the user experience because the data you know wasn't updated so much so it was easier to cache so these are all experiences i think that that proved in the end that we made the right choices here and the requirements that that drove that to to have a good user experience niels would you say that the architecture is is a sort of a data architecture specifically is it a decentralized data architecture with sort of federated you know centralized governance or is it more of a centralized view what if you could talk about that yeah it's it's actually a centralized platform basically so the core product is the same for all the markets and we run them as different tenants basically on top of that infrastructure so the data is separated in a way obviously by the different tenants but it's in a central place and we can analyze it in a central fashion if if the need arises from from the business and the reason i ask that simon is because essentially i look at this as a as largely a data offering for your customers and so niels you were talking about the local language and simon as well i would imagine that that the local business lines have specific requirements and specific data requirements and so you've got to build an architecture that is flexible enough to meet those needs yet at the same time can ensure data quality and governance and security that's not a trivial challenge i wonder if you both could comment on that yeah maybe maybe i'll give a start and then simon can chime in so um what we're specifically doing is managing the rewards experience right so so our solution will take care of tracking what rewards have been earned for what customer what rewards have been redeemed what rewards can be unlocked on the next level and we we foreshadow a little bit to to motivate to incentivize the customer and as that data sits in an aws database in a tenant by tenant fashion and you can run analysis on top of that maybe what you're getting into is also the let's say the exercise data the fitness device tracking data that is not specifically part of what my team has built but i'm sure simon can comment a little bit on that angle as well yeah please yeah sure sure yeah sure so look i think them the topic of data and how we use it uh in our business is a very is very interesting one because it's um it's not historically being seen let's say as the remit of insurers to go beyond the you know the the data that you need to underwrite policies or process claims or whatever it might be but actually we see that this is a whole point around being able to create some shared value in in this kind of product and and what i mean by that is uh look if you are a customer and you're buying an insurance policy it might be a life insurance or health insurance policy from from generali and we are giving you access to this uh to this program and through that program you are living a healthier life and that might have a you know a positive impact on generali in terms of you know maybe we're going to increase our market share or maybe we're going to lower claims or we're going to generate value out of that then one of the points of this program is that we then share that value back with customers through the rewards on the platform that we that we've built here and of course being able to understand that data and to quantify it and to value that data is an important part of the of the the different stages of how you of how much value you are creating and it's also interesting to know that you know in a couple of our markets we we operate in the corporate space so not with retail customers but with with organizations and one of the reasons that those companies give vitality to their employees is that they want to see things like the improved health of a workforce they want to see higher presenteeism lower absenteeism of employees and of course being able to demonstrate that there's a sort of correlation between participation in the vitality program and things like that is also is also important and as we've said the markets are very different so we need to be able to to take the data uh that we have out of the vitality program uh and be able in in the company that that i'm managing to to interpret that data so that in our insurance businesses we are able to make good decisions about the kind of insurance products we i think what's interesting to uh to make clear is that actually that the kind of health data that we generate stays purely within the vitality business itself and what we do inside the vitality business is to analyze that data and say okay is this is this also helping our insurance businesses to to drive uh yeah you know better top line and bottom line in the in the relevant business lines and this is different per company and per mark so yeah being able to interrogate that data understand it apply it in different markets and different uh distribution systems and different kinds of approaches to insurance is an is an important one yes it's an excellent example of a digital business in in you know we talk about digital transformation what does that mean this is what it means i i'd love i mean it must be really interesting board discussions because you're transforming an industry you're lowering overall cost i mean if people are getting less sick that's more profit for your company and you can choose to invest that in new products you can give back some to your corporate clients you can play that balancing act you can gain market share and and you've got some knobs to turn some levers uh for your stakeholders which is which is awesome neil something that i'm interested in i mean it must have been really important for you to figure out how to determine and measure success i mean you're obviously removed it's up it's up to generality vitality to get adoption for for their customers but at the same time the efficacy of your solution is going to determine you know the ease of of of delivery and consumption so so how did you map to the specific goals what were some of the key kpis in terms of mapping to their you know aggressive goals besides the things we already touched on i think one thing i would mention is the timeline right so we we started the team ramping in january or february and then within six months basically we had the solution built and then we went through a extensive test phase and within the next six months we had the product rolled out to three markets so this speed to value speed to market that we were able to achieve i think is one of the key um key criteria that also simon and team gave to us right there was a timeline and that timeline was not going to move so we needed to make a plan adjust to that timeline and i think it's both a testament to to the team's work that they did that we made this timeline but it also is enabled by technologies like cloud i have to say if i go back five years ten years if if you had to build in a solution like this on a corporate data center across so many different markets and each managed locally there would have been no way to do this in 12 months right that's for sure yeah i mean simon you're a technology company i mean insurance has always been a tech heavy company but but as niels just mentioned if you had to do that with it departments in each region so my question is is now you've got this it's almost like non-recurring engineering costs you've got that it took one year to actually get the first one done how fast are you able to launch into new markets just from a technology perspective not withstanding any you know local regulations and figuring out to go to market is that compressed yeah so if you are specifically technology-wise i think we would be able to set up a new market including localizations that often involves translation of because in europe you have all the different languages and so on at i would say four to six weeks we probably could stand up a localized solution in reality it takes more like six to nine months to get it rolled out because there's many other things involved obviously but just our piece of the solution we can pretty quickly localize it to a new market but but simon that means that you can spend time on those other factors you don't have to really worry so much about the technology and so you've launched in multiple european markets what do you see for the future of this program come to america you know you can fight you can find that this program in america dave but with one of our competitors we're not we're not operating so much in uh but you can find it if you want to become a customer for sure but yes you're right so look i think from from our perspective uh you know to put this kind of business into a new market it's not it's not an easy thing because what we're doing is not offering it just as a as a service on a standalone basis to customers we want to link it with with insurance business in the end we are an insurance business and we want to to see the value that comes from that so there's you know there's a lot of effort that has to go into making sure that we land it in the right way also from a customer publishing point of view with our distribution and they are they are quite different so so yeah look coming to the question of what's next i mean it comes in three stages for me so as i mentioned we are uh in five markets already uh in next in the first half of 2022 we'll also come to to the czech republic and poland uh which we're excited to to do and that will that will basically mean that we we have this business in in the seven main uh general markets in europe related to life and health business which is the most natural uh let's say fit for something like vitality then you know the next the sort of second part of that is to say okay look we have a program that's very heavily focused around uh activity and rewards and that that's a good place to start but you know wellness these days is not just about you know can you move a bit more than you did historically it's also about mental well-being it's about sleeping good it's about mindfulness it's about being able to have a more holistic approach to well-being and and covert has taught us and customer feedback has taught us actually that this is something where we need to to go and here we need to have the technology to move there as well so to be able to work with partners that are not just based on on on physical activity but also also on mindfulness so this is how one other way we'll develop the proposition and i think the third one which is more strategic and and we are you know really looking into is there's clearly something in the whole uh perception of incentives and rewards which drives a level of engagement between an insurer like generali and its customers that it hasn't had historically so i think we need to learn you know forget you know forgetting about the specific one of vitality being a wellness program but if there's an insurer there's a role for us to play where we offer incentives to customers to do something in a specific way and reward them for doing that and it creates value for us as an insurer then then this is probably you know a place we want to investigate more and to be able to do that in in other areas means we need to have the technology available that is as i said before replicable faster market can adapt quickly to to other ideas that we have so we can go and test those in in different markets so yes we have to we have to complete our scope on vitality we have to get that to scale and be able to manage all of this data at scale all of those rewards at real scale and uh to have the technology that allows us to do that without without thinking about it too much and then to say okay how do we widen the proposition and how do we take the concept of vitality that sits behind vitality to see if we can apply it to other areas of our business and that's really what the future is is going to look like for us you know the the isolation era really taught us that if you're not a digital business you're out of business and pre-kov a lot of these stories were kind of buried uh but the companies that have invested in digital are now thriving and this is an awesome example jeff another point is that jeff amebacher one of the founders of cloudera early facebook employee famously said about 10 12 years ago the best and greatest engineering minds of our my generation are trying to figure out how to get people to click on ads and this is a wonderful example of how to use data to change people's lives so guys congratulations best of luck really awesome example of applying technology to create an important societal outcome really appreciate you your time on the cube thank you thanks bye-bye all right and thanks for watching this segment of thecube's presentation of the aws executive summit at reinvent 2021 made possible by accenture keep it right there for more deep dives [Music] you

(upbeat music) >> Welcome back to theCUBE's presentation of the AWS Executive Summit at re:Invent 2021 made possible by Accenture. My name is Dave Vellante. We're going to look at how digital infrastructure is helping to transform consumer experiences, specifically how an insurance company is changing its industry by incentivizing and rewarding consumers who changed their behavior to live healthier lives, a real passion of mine, and getting to the really root cause of health. With me now are Simon Guest, who's the Chief Executive Officer of Generali Vitality, GmbH, and Nils Muller-Sheffer, who's the Managing Director at the Cloud First Application Engineering Lead for the European market at Accenture. Gentlemen, welcome to theCUBE. >> Thanks for having us. >> You're very welcome Simon. Simon, Generali Vitality is a really interesting concept that you guys have envisioned and now put it into practice. Tell us how does it all work? >> Sure. No problem. And thanks for having us on David, pleasure to be here. So look, Generali Vitality is in its core a pretty simple concept. It's a program that you have on your phone. And the idea of this program is that it's a wellness coach for you as an individual, and it's going to help you to understand your health and where you are in terms of the state of your health at the moment, and it's going to take you on a journey to improve your lifestyle and your wellness, and hopefully help you to live a healthier and a more sort of mindful life, I guess, is the best way of summarizing it. From our point of view as an insurance company, of course, our historical role has always been to be the company that's there if something goes wrong. So if unfortunately you pass away or you have sickness in your life or your family's life, that's historically been our role. But what we see with Generali Vitality is something a little bit different. So it's a program that really is supposed to be with you every day of your life to help you to live a healthier life. It's something that we already have in for European markets and in fact, in five from this week, I'm a little bit behind the times. So we're live already in Germany, in France, in Austria, in Italy and in Spain. And fundamentally what we do Dave, is to say to customers, "Look, if you want to understand your health, if you want to improve it by moving a little bit more, or by visiting the doctor more, by eating healthier, by healthy choices on a daily basis, we're going to help you to do that. And we're going to incentivize you for going on this journey and making healthy choices. And we're going to reward you for doing the same." So, we partner up with great companies like Garmin, like Adidas, like big brands that are, let's say, invested in this health and wellness space so that we can produce really an ecosystem for customers that's all about live well, make good choices, be healthy, have an insurance company that partners you along that journey. And if you do that, we've going to reward you for that. So, we're here not just in a difficult times, which of course is one of our main roles, but we're here as a partner, as a lifetime partner to you to help you feel better and live a better life. >> I love it, I mean, it sounds so simple, but I'm sure it's very complicated to make the technology simple for the user. You've got mobile involved, you've got the back end and we're going to get into some of the tech, but first I want to understand the member engagement and some of the lifestyle changes Simon that you've analyzed. What's the feedback that you're getting from your customers? What does the data tell you? How do the incentives work as well? What is the incentive for the member to actually do the right thing? >> Sure, I think actually that the COVID situation that we've had in the last sort of two years is really crystallized the fact that this is something that we really ought to be doing and something that our customers really value. Just to give you a bit of a sort of information about how it works for our customers. So what we try to do with them, is to get customers to understand their current health situation, using their phone. So, we asked our customers to go through a sort of health assessments around how they live, what they eat, how they sleep, and to go through that sort of process and to give them all the Vitality age, which is a sort of actuarial comparison with their real age. So I'm 45, but unfortunately my Vitality age is 49 and it means I have some work to do to bring that back together. And what we see is that, two thirds of our customers take this test every year because they want to see how they are progressing on an annual basis in terms of living a healthier life. And if what they are doing is having an impact on their life expectancy and their lifespan and their health span. So how long are they going to live healthier for? So you see them really engaging in this approach of understanding that current situation. Then what we know actually, because the program is built around this model that's really activity and moving, and exercise is the biggest contributors to living a healthier life. We know that the majority of deaths are caused by lifestyle illnesses like poor nutrition and smoking and drinking alcohol and not exercising. And so a lot of the program is really built around getting people to move more. And it's not about being an athlete. It's about, getting off the underground one station earlier and walking home or making sure you do your 10,000 steps a day. And what we see is that that sort of 40% of our customers are on a regularly basis linking either their phone or their exercise device to our program and downloading that data so that they can see how much they are exercising. And at the same time, what we do is we set our customers weekly challenges to say, look, if you can move a little bit more than last week, we are go into to reward you for that. And we see that almost half of our customers are achieving this weekly goal every week. And it's really a level of engagement that normally as an insurer, we don't see. The way that rewards work is pretty simple. It's similar in a way to an airline program. So every good choice you make every activity to every piece of good food that you eat. When you check your on your health situation, we'll give you points. And the more points you get, you go through through a sort of status approach of starting off at the bottom status and ending up at a golden and a platinum status. And the higher up you get in the status, the higher the value of the rewards that we give you. So almost a quarter of our customers now, and this has accelerated through COVID have reached that platinum status. So they are the most engaged customers that we have and those ones who are really engaging in the program. And what we really tried to create is this sort of virtuous circle that says If you live well, you make good choices, you improve your health, you progress through the program and we give you better and stronger and more valuable rewards for doing that. And some of those rewards are around health and wellness. So it might be that you get a discounts on gym gear from Adidas, it might be that you get a discount on a device from Garmin, or it might be actually on other things. We also give people Amazon vouchers. We also give people discounts on holidays. And another thing that we did actually in the last year, which we found really powerful is that we've given the opportunity for our customers to convert those rewards into charitable donations. Because we work in generosity with a sort of campaign called The Human Safety Net, which is helping out the poorest people in society. And so what our customers do a lot of the time is instead of taking those financial rewards for themselves, they convert it into a charitable donation. So we're actually also linking wellness and feeling good and insurance and some societal goods. So we're really trying to create a virtuous circle of engagement with our customers. >> That's a powerful cocktail. I love it. You've got the data, because if I see the data, then I can change my behavior. You've got the gamification piece. You actually have hard dollar rewards. You could give those to charities and you've got the most important, which is priceless, you can't put a value on good health. I got one more question for Simon and Nils I'd love for you to chime in as well on this question. How did you guys decide, Simon, to engage with Accenture and AWS and the cloud to build out this platform? What's the story behind that collaboration? Was there unique value that you saw that you wanted to tap, that you feel like they bring to the table? What was your experience? >> Yeah, we work with Accenture as well because the sort of constructs of this Vitality proposition is a pretty complex one. So you mentioned that the idea is simple, but the build is not so simple and that's the case. So Accenture has been part of that journey from the beginning. They are one of the partners that we work with, but specifically around the topic of rewards, we're primarily European focused organization, but when you take those countries that I mentioned, even though we're next to each other geographically, we're quite diverse. And what we wanted to create was really a sustainable and reusable and consistent customer experience that allowed us to go get to market with an increasing amounts of efficiency. And to do that, we needed to work with somebody who understood our business, has this historical, let's say investment in the Vitality concepts and so knows how to bring it to life, but then could really support us in making what can be a complex piece of work, as simple, as replicable as possible across multiple markets, because we don't want to go reinventing the wheel every time we knew we moved to a new market. So we need to find a balance between having a consistent product, a consistent technology offer, a consistent customer experience with the fact that we operate in quite diverse markets. So this was, let's say the reason for more deeply engaging with Accenture on this journey. >> Thank you very much, Nils, why don't you comment on that as well? I'd love to get your thoughts and really is kind of your role here, an Accenture global SI, deep expertise in industry, but also technology, what are your thoughts on this topic? >> Yeah, I'd love to love to comment. So when we started the journey, it was pretty clear from the outset that we would need to build this on cloud in order to get this scalability and this ability to roll out to different markets, have a central solution that can act as a template for the different markets, but then also have the opportunity to localize different languages, different partners for the rewards, there's different reward partners in the different markets. So we needed to build an asset basically that could work as a template, centrally standardizing things, but also leaving enough flexibility to then localize in the individual markets. And if we talk about some of the most specific requirements, so one thing that gave us headaches in the beginning was the authentication of the users because each of the markets has their own systems of record where the, basically the authentication needs to happen. And if we somehow needed to still find a holistic solution that comes through the central platform, and we were able to do that at the end through the AWS cognitive service, sort of wrapping the individual markets, local IDP systems. And by now we've even extended that solution to have a standalone cloud native kind of IDP solution in place for markets that do not have a local IDP solution in place, or don't want to use it for this purpose. >> So you had data, you had the integration, you've got local laws, you mentioned the flexibility, you're building ecosystems that are unique to the local, both language and cultures. Please, you had another comment, I interrupted you. >> No, I just wanted to expand basically on the requirements. So that was the central one being able to roll this out in a standardized way across the markets, but then there were further requirements. For example, like being able to operate the platform with very low operations overhead. There is no large IT team behind Generali Vitality that, works disservice or can act as this backbone support. So we needed to have basically a solution that runs itself that runs on autopilot. And that was another big, big driver for first of all, going to cloud, but second of all, making specific choices within cloud. So we specifically chose to build this as a cloud native solution using for example, managed database services, with automatic backup, with automatic ability to restore data that scales automatically that has all this built in which usually maybe in a database administrator would take care of. And we applied that concept basically to every component, to everything we looked at, we applied this requirement of how can this run on autopilot? How can we make this as much managed by itself within the cloud as possible, and then lend it on these services. For example, we also use the API gateway from AWS for our API services that also came in handy when, for example, we had some response time issues with the third party we needed to call. And then we could just with a flick of a button basically, introduced caching on the level of the API gateway and really improve the user experience because the data wasn't updated so much, so it was easier to cache. So these are all experiences I think that that proved in the end that we made the right choices here and the requirements that drove that to have a good user experience. >> Would you say that the architecture is a sort of a, data architecture specifically, is it a decentralized data architecture with sort of federated, centralized governance? Or is it more of a centralized view, wonder if you could talk about that? >> Yeah, it's actually a centralized platform basically. So the core product is the same for all the markets and we run them as different tenants basically on top of the infrastructure. So the data is separated in a way, obviously by the different tenants, but it's in a central place and we can analyze it in a central fashion if the need arises from the business. >> And the reason I asked that Simon is because essentially I look at this as largely a data offering for your customers. And so Nils, you were talking about the local language and Simon as well. I would imagine that the local business lines have specific requirements and specific data requirements. And so you've got to build an architecture that is flexible enough to meet those needs yet at the same time can ensure data quality and governance and security. And that's not a trivial challenge. I wonder if you both could comment on that. >> Yeah, maybe I'll give a start and then Simon can chime in. So what we're specifically doing is managing the rewards experience, so our solution will take care of tracking what rewards have been earned for what customer, what rewards have been redeemed, what rewards can be unlocked on the next level, and we foreshadow a little bit to motivate incentivize the customer and asset that data sits in an AWS database by tenant fashion. And you can run analysis on top of that. Maybe what you're getting into is also the, let's say the exercise data, the fitness device tracking data that is not specifically part of what my team has built, but I'm sure Simon can comment a little bit on that angle as well. >> Yeah, please. >> Yeah, sure. I think the topic of data and how we use it in our business is a very interesting one because it's not historically been seen, let's say as the remit of insurance to go beyond the data that you need to underwrite policies or process claims or whatever it might be. But actually we see that this is a whole point around being able to create some shared value in this kind of products. And what I mean by that is, if you are a customer and you're buying an insurance policy, it might be a life insurance or health insurance policy from Generali, and we're not giving you access to this program. And through that program, you are living a healthier life and that might have a positive impact on generosity in terms of, maybe we're going to increase our market share, or maybe we are going through lower claims, or we're going to generate value of that then. One of the points of this program is we then share that value back with customers, through the rewards on the platform that we've built here. And of course, being able to understand that data and to quantify it and to value that data is an important part of the different stages of how much value you are creating. And it's also interesting to know that, in a couple of our markets, we operate in the corporate space. So not with retail customers, but with organizations. And one of the reasons that those companies give Vitality to their employees is that they want to see things like the improved health of a workforce. They want to see higher presenteeism, lower absenteeism of employees, and of course, being able to demonstrate that there's a sort of correlation between participation in the Vitality program and things like that is also important. And as we've said, the markets are very different. So we need to be able to take the data that we have out of the Vitality Program and be able in the company that I'm managing to interpret that data so that in our insurance businesses, we are able to make good decisions about kind of insurance product we have. I think what's interesting to make clear is that actually that the kind of health data that we generate states purely within the Vitality business itself and what we do inside the Vitality business is to analyze that data and say, is this also helping our insurance businesses to drive better top line and bottom line in the relevant business lines? And this is different per company. Being able to interrogate that data, understand it, apply it in different markets, in different distribution systems and different kinds of approaches to insurance is an important one, yes. >> It's an excellent example of a digital business and we talked about digital transformation. What does that mean? This is what it means. It must be really interesting board discussions because you're transforming an industry, you're lowering overall costs. I mean, if people are getting less sick, that's more profit for your company and you can choose to invest that in new products, you can give back some to your corporate clients, you can play that balancing act, you can gain market share. And you've got some knobs to turn, some levers, for your stakeholders, which is awesome. Nils, something that I'm interested in, it must've been really important for you to figure out how to determine and measure success. Obviously it's up to Generali Vitality to get adoption for their customers, but at the same time, the efficacy of your solution is going to determine, the ease of delivery and consumption. So, how did you map to the specific goals? What were some of the key KPIs in terms of mapping to their aggressive goals. >> Besides the things we already touched on, I think one thing I would mention is the timeline. So, we started the team ramping in January, February, and then within six months basically, we had the solution built and then we went through a extensive test phase. And within the next six months we had the product rolled out to three markets. So this speed to value, speed to market that we were able to achieve, I think is one of the key criteria that also Simon and team gave to us. There was a timeline and that time I was not going to move. So we needed to make a plan, adjust to that timeline. And I think it's both a testament to the team's work that we met this timeline, but it also is enabled by a technology stack cloud. I have to say, if I go back five years, 10 years, if you had to build in a solution like this on a corporate data center across so many different markets and each managed locally, there would've been no way to do this in 12 months, that's for sure. >> Yeah, Simon, you're a technology company. I mean, insurance has always been a tech heavy company, but as Nils just mentioned, if you had to do that with IT departments in each region. So my question is now you've got this, it's almost like nonrecurring engineering costs, it took one year to actually get the first one done, how fast are you able to launch into new markets just from a technology perspective, not withstanding local regulations and figuring out the go to market? Is that compressed? >> So you asked specifically technology-wise I think we would be able to set up a new market, including localizations that often involves translation of, because in Europe you have all the different languages and so on, I would say four to six weeks, we probably could stand up a localized solution. In reality, it takes more like six to nine months to get it rolled out because there's many other things involved, obviously, but just our piece of the solution, we can pretty quickly localize it to a new market. >> But Simon, that means that you can spend time on those other factors, you don't have to really worry so much about the technology. And so you've launched in multiple European markets, what do you see for the future of this program? Come to America. >> You can find that this program in America Dave, but with one of our competitors, we're not operating so much in the US, but you can find it if you want to become a customer for sure. But yes, you're right. I think from our perspective, to put this kind of business into a new market is not an easy thing because what we're doing is not offering it just as a service on a standalone basis to customers, we want to link it with insurance business. In the end, we are an insurance business, and we want to see the value that comes from that. So there's a lot of effort that has to go into making sure that we land it in the right way, also from a customer proposition points of view with our distribution, they are all quite different. Coming to the question of what's next? It comes in three stages for me. So as I mentioned, we are in five markets already. In the first half of 2022, we'll also come to the Czech Republic and Poland, which we're excited to do. And that will basically mean that we have this business in the seven main Generali markets in Europe related to life and health business, which is the most natural at let's say fit for something like Vitality. Then, the sort of second part of that is to say, we have a program that is very heavily focused around activity and rewards, and that's a good place to start, but, wellness these days is not just about, can you move a bit more than you did historically, it's also about mental wellbeing, it's about sleeping good, it's about mindfulness, it's about being able to have a more holistic approach to wellbeing and COVID has taught us, and customer feedback has taught is actually that this is something where we need to go. And here we need to have the technology to move there as well. So to be able to work with partners that are not just based on physical activity, but also on mindfulness. So this is how one other way we will develop the proposition. And I think the third one, which is more strategic and we are really looking into is, there's clearly something in the whole perception of incentives and rewards, which drives a level of engagement between an insurer like Generali and its customers that it hasn't had historically. So I think we need to learn, forgetting about the specific one or Vitality being a wellness program, but if there's an insurer, there's a role for us to play where we offer incentives to customers to do something in a specific way and reward them for doing that. And it creates value for us as an insurer, then this is probably a place that we'd want to investigate more. And to be able to do that in other areas means we need to have the technology available, that is, as I said before, replicable faster market can adapt quickly to other ideas that we have, so we can go and test those in different markets. So yes, we have to, we have to complete our scope on Vitality, We have to get that to scale and be able to manage all of this data at scale, all of those rewards that real scale, and to have the technology that allows us to do that without thinking about it too much. And then to say, okay, how do we widen the proposition? And how do we take the concept that sits behind Vitality to see if we can apply it to other areas of our business. And that's really what the future is going to look like for us. >> The isolation era really taught us that if you're not a digital business, you're out of business, and pre COVID, a lot of these stories were kind of buried, but the companies that have invested in digital are now thriving. And this is an awesome example, and another point is that Jeff Hammerbacher, one of the founders of Cloudera, early Facebook employee, famously said about 10, 12 years ago, "The best and greatest engineering minds of my generation are trying to figure out how to get people to click on ads." And this is a wonderful example of how to use data to change people's lives. So guys, congratulations, best of luck, really awesome example of applying technology to create an important societal outcome. Really appreciate your time on theCUBE. Thank you. >> Bye-bye. >> All right, and thanks for watching this segment of theCUBE's presentation of the AWS Executive Summit at re:Invent 2021 made possible by Accenture. Keep it right there for more deep dives. (upbeat music)

>>Yeah. Hello and welcome back to the cubes coverage of AWS public sector summit here in Washington D. C. We're live on the ground for two days. Face to face conference and expo hall and everything here but keith brooks who is the director and head of technical business development for a dress government Govcloud selling brains 10th birthday. Congratulations. Welcome to the cube. Thank you john happy to be E. C. 2 15 S three is 9.5 or no, that maybe they're 10 because that's the same day as sqs So Govcloud. 10 years, 20 years. What time >>flies? 10 years? >>Big milestone. Congratulations. A lot of history involved in Govcloud. Yes. Take us through what's the current situation? >>Yeah. So um let's start with what it is just for the viewers that may not be familiar. So AWS Govcloud is isolated. AWS cloud infrastructure and services that were purposely built for our U. S. Government customers that had highly sensitive data or highly regulated data or applications and workloads that they wanted to move to the cloud. So we gave customers the ability to do that with AWS Govcloud. It is subject to the fed ramp I and D O D S R G I L four L five baselines. It gives customers the ability to address ITAR requirements as well as Seaga's N'est ce MMC and Phipps requirements and gives customers a multi region architecture that allows them to also designed for disaster recovery and high availability in terms of why we built it. It starts with our customers. It was pretty clear from the government that they needed a highly secure and highly compliant cloud infrastructure to innovate ahead of demand and that's what we delivered. So back in august of 2011 we launched AWS GovCloud which gave customers the best of breed in terms of high technology, high security, high compliance in the cloud to allow them to innovate for their mission critical workloads. Who >>was some of the early customers when you guys launched after the C. I. A deal intelligence community is a big one but some of the early customers. >>So the Department of Health and Human Services, the Department of Veterans Affairs, the Department of Justice and the Department of Defense were all early users of AWS GovCloud. But one of our earliest lighthouse customers was the Nasa jet propulsion laboratory and Nasa Jpl used AWS GovCloud to procure Procure resources ahead of demand which allowed them to save money and also take advantage of being efficient and only paying for what they needed. But they went beyond just I. T. Operations. They also looked at how do they use the cloud and specifically GovCloud for their mission programs. So if you think back to all the way to 2012 with the mars curiosity rover, Nasa Jpl actually streamed and processed and stored that data from the curiosity rover on AWS Govcloud They actually streamed over 150 terabytes of data responded to over 80,000 requests per second and took it beyond just imagery. They actually did high performance compute and data analytics on the data as well. That led to additional efficiencies for future. Over there >>were entire kicking they were actually >>hard core missing into it. Mission critical workloads that also adhere to itar compliance which is why they used AWS GovCloud. >>All these compliance. So there's also these levels. I remember when I was working on the jetty uh stories that were out there was always like level for those different classifications. What does all that mean like? And then this highly available data and highly high availability all these words mean something in these top secret clouds. Can you take us through kind of meetings >>of those? Yeah absolutely. So it starts with the federal compliance program and the two most popular programs are Fed ramp and Dodi srg fed ramp is more general for federal government agencies. There are three levels low moderate and high in the short and skinny of those levels is how they align to the fisma requirements of the government. So there's fisma low fisma moderate fisma high depending on the sensitivity of the government data you will have to align to those levels of Fed ramp to use workloads and store data in the cloud. Similar story for D. O. D. With srg impact levels to 45 and six uh impacts levels to four and five are all for unclassified data. Level two is for less sensitive public defense data levels. Four and five cover more sensitive defense data to include mission critical national security systems and impact level six is for classified information. So those form the basis of security and compliance, luckily with AWS GovCloud celebrating our 10th anniversary, we address Fed ramp high for our customers that require that and D. O. D impact levels to four and five for a sensitive defense guy. >>And that was a real nuanced point and a lot of the competition can't do that. That's real people don't understand, you know, this company, which is that company and all the lobbying and all the mudslinging that goes on. We've seen that in the industry. It's unfortunate, but it happens. Um, I do want to ask you about the Fed ramp because what I'm seeing on the commercial side in the cloud ecosystem, a lot of companies that aren't quote targeting public sector are coming in on the Fed ramp. So there's some good traction there. You guys have done a lot of work to accelerate that. Any new, any new information to share their. >>Yes. So we've been committed to supporting the federal government compliance requirements effectively since the launch of GovCloud. And we've demonstrated our commitment to Fed ramp over the last number of years and GovCloud specifically, we've taken dozens of services through Fed ramp high and we're 100% committed to it because we have great relationships with the Fed ramp, Jabor the joint authorization board. We work with individual government agencies to secure agency A. T. O. S. And in fact we actually have more agency A. T. O. S. With AWS GovCloud than any other cloud provider. And the short and skinny is that represents the baseline for cloud security to address sensitive government workloads and sensitive government data. And what we're seeing from industry and specifically highly regulated industries is the standard that the U. S. Government set means that they have the assurance to run control and classified information or other levels of highly sensitive data on the cloud as well. So Fed ramp set that standard. It's interesting >>that the cloud, this is the ecosystem within an ecosystem again within crossover section. So for instance um the impact of not getting Fed ramp certified is basically money. Right. If you're a supplier vendor uh software developer or whatever used to being a miracle, no one no one would know right bed ramp. I'm gonna have to hire a whole department right now. You guys have a really easy, this is a key value proposition, isn't it? >>Correct. And you see it with a number of I. S. V. S. And software as the service providers. If you visit the federal marketplace website, you'll see dozens of providers that have Fed ramp authorized third party SAAS products running on GovCloud industry leading SAAS companies like Salesforce dot com driven technology Splunk essay PNS to effectively they're bringing their best of breed capabilities, building on top of AWS GovCloud and offering those highly compliant fed ramp, moderate fed ramp high capabilities to customers both in government and private industry that need that level of compliance. >>Just as an aside, I saw they've got a nice tweet from Teresa Carlson now it's plunk Govcloud yesterday. That was a nice little positive gesture uh, for you guys at GovCloud, what other areas are you guys moving the needle on because architecturally this is a big deal. What are some areas that you're moving the needle on for the GovCloud? >>Well, when I look back across the last 10 years, there were some pretty important developments that stand out. The first is us launching the second Govcloud infrastructure region in 2018 And that gave customers that use GovCloud specifically customers that have highly sensitive data and high levels of compliance. The ability to build fault tolerant, highly available and mission critical workloads in the cloud in a region that also gives them an additional three availability zones. So the launch of GovCloud East, which is named AWS GovCloud Us East gave customers to regions a total of six availability zones that allowed them accelerate and build more scalable solutions in the cloud. More recently, there is an emergence of another D O D program called the cybersecurity maturity model, C M M C and C M M C is something where we looked around the corner and said we need to Innovate to help our customers, particularly defense customers and the defense industrial based customers address see MMC requirements in the cloud. So with Govcloud back in December of 2020, we actually launched the AWS compliant framework for federal defense workloads, which gives customers a turnkey capability and tooling and resources to spin up environments that are configured to meet see MMC controls and D. O. D. Srg control. So those things represent some of the >>evolution keith. I'm interested also in your thoughts on how you see the progression of Govcloud outside the United States. Tactical Edge get wavelength coming on board. How does how do you guys look at that? Obviously us is global, it's not just the jet, I think it's more of in general. Edge deployments, sovereignty is also going to be world's flat, Right? I mean, so how does that >>work? So it starts back with customer requirements and I tie it back to the first question effectively we built Govcloud to respond to our U. S. Government customers and are highly regulated industry customers that had highly sensitive data and a high bar to meet in terms of regulatory compliance and that's the foundation of it. So as we look to other customers to include those outside of the US. It starts with those requirements. You mentioned things like edge and hybrid and a good example of how we marry the two is when we launched a W. S. Outpost in Govcloud last year. So outpost brings the power of the AWS cloud to on premises environments of our customers, whether it's their data centers or Coehlo environments by bringing AWS services, a. P. I. S and service and points to the customer's on premises facilities >>even outside the United States. >>Well, for Govcloud is focused on us right now. Outside of the U. S. Customers also have availability to use outpost. It's just for us customers, it's focused on outpost availability, geography >>right now us. Right. But other governments gonna want their Govcloud too. Right, Right, that's what you're getting at, >>Right? And it starts with the data. Right? So we we we spent a lot of time working with government agencies across the globe to understand their regulations and their requirements and we use that to drive our decisions. And again, just like we started with govcloud 10 years ago, it starts with our customer requirements and we innovate from there. Well, >>I've been, I love the D. O. D. S vision on this. I know jet I didn't come through and kind of went scuttled, got thrown under the bus or whatever however you want to call it. But that whole idea of a tactical edge, it was pretty brilliant idea. Um so I'm looking forward to seeing more of that. That's where I was supposed to come in, get snowball, snowmobile, little snow snow products as well, how are they doing? And because they're all part of the family to, >>they are and they're available in Govcloud and they're also authorized that fed ramp and Gov srg levels and it's really, it's really fascinating to see D. O. D innovate with the cloud. Right. So you mentioned tactical edge. So whether it's snowball devices or using outposts in the future, I think the D. O. D. And our defense customers are going to continue to innovate. And quite frankly for us, it represents our commitment to the space we want to make sure our defense customers and the defense industrial base defense contractors have access to the best debris capabilities like those edge devices and edge capable. I >>think about the impact of certification, which is good because I just thought of a clean crows. We've got aerospace coming in now you've got D O. D, a little bit of a cross colonization if you will. So nice to have that flexibility. I got to ask you about just how you view just in general, the intelligence community a lot of uptake since the CIA deal with amazon Just overall good health for eight of his gum cloud. >>Absolutely. And again, it starts with our commitment to our customers. We want to make sure that our national security customers are defense customers and all of the customers and the federal government that have a responsibility for securing the country have access to the best of breed capability. So whether it's the intelligence community, the Department of Defense are the federal agencies and quite frankly we see them innovating and driving things forward to include with their sensitive workloads that run in Govcloud, >>what's your strategy for partnerships as you work on the ecosystem? You do a lot with strategy. Go to market partnerships. Um, it's got its public sector pretty much people all know each other. Our new firms popping up new brands. What's the, what's the ecosystem looks like? >>Yeah, it's pretty diverse. So for Govcloud specifically, if you look at partners in the defense community, we work with aerospace companies like Lockheed martin and Raytheon Technologies to help them build I tar compliant E. R. P. Application, software development environments etcetera. We work with software companies I mentioned salesforce dot com. Splunk and S. A. P. And S. To uh and then even at the state and local government level, there's a company called Pay It that actually worked with the state of Kansas to develop the Icann app, which is pretty fascinating. It's a app that is the official app of the state of Kansas that allow citizens to interact with citizens services. That's all through a partner. So we continue to work with our partner uh broad the AWS partner network to bring those type of people >>You got a lot of MST is that are doing good work here. I saw someone out here uh 10 years. Congratulations. What's the coolest thing uh you've done or seen. >>Oh wow, it's hard to name anything in particular. I just think for us it's just seeing the customers and the federal government innovate right? And, and tie that innovation to mission critical workloads that are highly important. Again, it reflects our commitment to give these government customers and the government contractors the best of breed capabilities and some of the innovation we just see coming from the federal government leveraging the count now. It's just super cool. So hard to pinpoint one specific thing. But I love the innovation and it's hard to pick a favorite >>Child that we always say. It's kind of a trick question I do have to ask you about just in general, the just in 10 years. Just look at the agility. Yeah, I mean if you told me 10 years ago the government would be moving at any, any agile anything. They were a glacier in terms of change, right? Procure Man, you name it. It's just like, it's a racket. It's a racket. So, so, but they weren't, they were slow and money now. Pandemic hits this year. Last year, everything's up for grabs. The script has been flipped >>exactly. And you know what, what's interesting is there were actually a few federal government agencies that really paved the way for what you're seeing today. I'll give you some examples. So the Department of Veterans Affairs, they were an early Govcloud user and way back in 2015 they launched vets dot gov on gov cloud, which is an online platform that gave veterans the ability to apply for manage and track their benefits. Those type of initiatives paved the way for what you're seeing today, even as soon as last year with the U. S. Census, right? They brought the decennial count online for the first time in history last year, during 2020 during the pandemic and the Census Bureau was able to use Govcloud to launch and run 2020 census dot gov in the cloud at scale to secure that data. So those are examples of federal agencies that really kind of paved the way and leading to what you're saying is it's kind >>of an awakening. It is and I think one of the things that no one's reporting is kind of a cultural revolution is the talent underneath that way, the younger people like finally like and so it's cooler. It is when you go fast and you can make things change, skeptics turned into naysayers turned into like out of a job or they don't transform so like that whole blocker mentality gets exposed just like shelf where software you don't know what it does until the cloud is not performing, its not good. Right, right. >>Right. Into that point. That's why we spend a lot of time focused on education programs and up skilling the workforce to, because we want to ensure that as our customers mature and as they innovate, we're providing the right training and resources to help them along their journey, >>keith brooks great conversation, great insight and historian to taking us to the early days of Govcloud. Thanks for coming on the cube. Thanks thanks for having me cubes coverage here and address public sector summit. We'll be back with more coverage after this short break. Mhm. Mhm mm.

(upbeat music) >> Welcome to the CUBE Conversation. I'm Lisa Martin. I'm talking next with Sanzio Bassini, the Head of High Performance Computing at Cineca, at DELL technologies customer. Sanzio, welcome to the CUBE. >> Thank you, it's a pleasure, it's a pleasure. >> Likewise, nice to see you. So tell us a little bit about Cineca. This is a large computing center, but a very large Italian nonprofit consortium. Tell us about it. >> Yes, Cineca been founded 50 years ago, from the university systems in Italy. For a statutory mission, which is to support, the scientific discovery, and the industry innovations, using the High Performance Computing and the correlated methodologies like a, Artificial Intelligence, which is one of the, you see the more, in a, in a adopted in those days, but together with the big data processing and and simulation. Yes, we are a consortium, which means that this is a private not-for-profit organizations. Currently, our member of the consortium, almost all the universities in Italy and also all the national agencies for those selected structures. Uh. The main quarter of Cineca is in Bologna, which is in the heart Nation, with the bunch of presence in Milan, in Rome and in Naples, so we are a consultation organization. >> And I also read that you were, are the top 10 out of the top 500 of the world's fastest super computers. That's a pretty big accomplishment. >> Yes. That is a part of our institutional missions, the last 10 to 15 years we have been to say, frequent flyers in the top 10. There been at least two, three systems that have been ranked at the top 10. Apart, the.., whatever would be the meaning of such an advance market, there's a lot of its criticalities. We are well aware. The idea is that we're enabling the scientific discovery, by means of providing the most advanced systems and the co-designing, the most advanced HPC systems to promote and support the, what is the, excellence in science. And that being part of European high-performance computing IT system. That is the case. >> Excellent. Now, talk to me about some of the challenges that Cineca is trying to solve in particular, the Human Brain Project. Talk to us a little bit about that and how you're leveraging high-performance computing to accelerate scientific discovery. >> Um, The Human Brain Project is one of the flagship project that has been co-founded by the European commission and that the participating member states. Is not as another situations that are undertaking, it's definitely a joint collaboration between members states and the European commission. There are two different right now, flagships together with another, that is in progress, which is that the quantum of flagship, the first two flagship abroad that that has been lost. The commission for operation with the participating states has been one on the digraph vein on which also we are participating in directly together with the CNR, is the national business counselor. And the second for which we are core partners of the HPC that is, the Human Brain Project. That, that is a big flagship, one million offer, of newer investment, co-founded by the participating states and that the European commission. The project it's going to set up, in what to do be the, third strategic grant agreement that they will go over the next three years, the good, the complete that the, the whole process. Then we see what is going to happen at Africa. We thought that their would be some others progress offer these big projects. It's project that would combine both the technology issues, like the designing the off high-performance computing systems that meet the requirements of the community and the big challenge, scientific challenges correlated to the physiological functions of the human brain center, including the different farm show survey to do with the behavior of the human brain. A from the pathological point of view, from the physiological point of view, that better understand the could be the way for, for a facing that. Let's say the pathology, some of those are very much correlated with respect to aging, and that it would impact the, the health, the public health systems. Some other that are correlating with what would be the support for the physiological knowledge of the, of the human brains. And finally that they, let me say, technological transfer stuff that represented the knowing off at the physiological, behavior of the human brain. Just to use a sort of metaphor to have happen from the point of view of there computational performance, the human brain is a, a, a, more than Exoscale systems, but with a energy consumption, which is very low, we are talking about some hundreds of Watts. So some hundreds of watts of energy, would provide a an extreme and computational performance. So if would could organized the technology of the high-performance computing in terms of interconnections now we're morphing the computing systems and exploitations of that kind of technologies, in I build a system that it might provide the computational power that would represent a tremendous and tremendous step ahead, in order to facing the big challenges of our base, like energies, personalized medicine, try not to change food for all those kinds of big socioeconomic challenges that we are facing. >> Yes I was reading that besides, sorry Sanzio I was reading that besides the Human Brain Project, there are other projects going on, such as that you mentioned, I'd like to understand how Cineca is working with Dell technologies. You have to translate, as you've mentioned a minute ago, the scientific requirements for discovery into high-performance computing requirements. Talk to me about how you've been doing that with partners like Dell technologies. >> Yes, in particularly in our computing architectures, we had the need to address the capability to facing the data processing involved with backed off the Human Brain Project and general speaking that is backed off the science vendor, that would combine the capability also to provide the cloud access to the system. So by main soft containers technologies and the capability also, to address what would be the creation of a Federation. So Piper problems with people proceeded in a new world. So at the end that the requirements and the terms of reference of the would matter will decline and the terms of a system that would be capable to manage, let's say, in a holistic approach, the data processing, the cloud computing services and the opportunity before for being integrated that in a Federation of HSBC system in Europe's, and with this backed off, that kind of thing, we manage a competitive dialogue procurement processor, I think I the sentence would share together with the different potential technology providers, what would be the visuals and those are the constraints (inaudible) and those other kinds of constraints like, I don't want to say, I mean, environmental kind of constraints and uh, sharing with this back of the technology provider what would it be the vision for this solution, in a very, let's say hard, the competitive dialogue, and at the end, results in a sort of, I don't want to say Darwinian processes, okay. So I mean, the survivors in terms of the different technology providers being Dell that shown the characteristics of the solution that it will be more, let's say compliant. And at the same time are flexible with respect of the combinations of very different constraints and requirements that has been the, the process that has been the outcomes of such a process. >> I like that you mentioned that Darwinian survival of the fittest and that Dell technologies has been, it sounds like a pretty flexible partner because you've got so many different needs and scientific needs to meet for different researchers. Talk to me about how you mentioned that this is a multi-national effort. How does Cineca serve and work with teams not only in Italy, but in other countries and from other institutes? >> Definitely the volume commitment that together with the, European member states is that by means of scientific merits and the peer review process, roughly speaking the arc of the production capacity, would be shared at the European level. That it's a commitment that, that there's been, that there's been a shared of that together with France, Germany, Spain, and, and with the London. So, I mean, our, half of our production capacity, it's a share of that at the European level, where also of course the Italian scientist can apply in the participates, but in a sort of offer emulations and the advanced competition for addressing what it would be the excellence in science. The remaining 50% of our production capacity is for, for the national community and, somehow to prepare and support the Italian community to be competitive on the worldwide scenario on the European and international scenario, uh that setting up would lead also to the agreement at the international level, with respect of some of the options that, that are promoted the progress in a US and in Japan also. So from this point of view, that mean that in some cases also the, access that it would come from researchers the best collaborations and the sharing options with the US researchers their or Japanese researchers in an open space. >> Open space for, it sounds like the Human Brain Project, which the HPC is powering, which has been around since 2013 is really facilitating global collaboration. Talk to me about some of the results that the high-performance computing environment has helped the Human Brain Project to achieve so far. >> The main outcomes that it will be consolidated in the next phase that will be need the by rural SPC that is the Jared undertaking um entities, that has been created for consolidating and for progressing the high-performance computing ecosystem in Europe. It represented by the Federations of high-performance computing systems at European level, there is a, a, an option that, that has been encapsulated and the elaborated inside the human brain flagship project which is called the FEHIPCSE that stand for Federation of a High-Performance Computing System in Europe. That uh provide the open service based on the two concepts on one, one is the sharing of the Heidi at a European level, so it means that the, the high demand of the users or researchers more properly. It's unique and Universal at the European level. That didn't mean better the same, we see identity management, education management with the open, and the access to the Cineca system, to the SARS system in France, to the unique system in, uh Germany to the, Diocese system in a Switzerland, to the Morocco System in a Spain. That is the part related to what will be the federated, the ID management, the others, et cetera, related to what will be the Federation off the data access. So from the point of view, again, the scientific community, mostly the community of Human Brain Project, but that will be open at other domains and other community, make sure that data in a seamless mode after European language, from the technological point of view, or let's say from the infrastructure point of view, very strong up, from the scientific point of view, uh what they think they may not, will be the most of the options is being supported by Cineca has to do with the two specific target. One is the elaboration of the data that are provided by the lands. The laws are a laboratory facility in that Florence. That is one of the four parts, and from the bottom view of the provisions of the data that is for the scattering, the, the data that would come from the mouse brains, that are use for, for (inaudible) And then the second part is for the Mayor scale studies of the cortex of the of the human brain, and that got add-on by a couple of groups that are believing that action from a European level their group of the National Researcher Counsel the CNR, that are the two main outcome on which we are in some out reference high-performance computing facilities for supporting that kind of research. Then their is in some situations they combinations of the performance a, capability of the Federation systems for addressing what will be the simulations of the overall human brain would take a lot of performance challenge simulation with bacteria that they would happen combining that they SPC facility as at European level. >> Right! So I was reading there's a case study by the way, on Cynic that Dell technologies has published. And some of the results you talked about, those that the HPC is facilitating research and results on epilepsy, spinal cord injury, brain prostheses for the blind, as well as new insights into autism. So incredibly important work that you're doing here for the Human Brain Project. One last question Sanzio, for you, what advice would you give to your peers who might be in similar situations that need to, to build and deploy and maintain high-performance computing environments? Where should they start? >> (coughs laughs) I think that at, at a certain point, that specific know how would became sort of a know how that is been, I mean, accumulated and then by some facilities and institutions around the world. There are the, the federal labs in US, the main nation model centers in Europe, the big facilities in Japan. And of course the, the big university facilities in China that are becoming, how do you say, evident and our progressively occupied increasing the space, that to say that that is somehow it, that, that, that the, those institutions would continues collaborate and sharing that there are periods I would expect off what to do, be the top level systems. Then there is a continuous sharing of uh knowledge, the experience best practices with respect off, let's say the technologies transfers towards productions and services and boosterism. Where the situation is big parenta, in the sense that, their are focused what it would be, uh the integration of the high-performance computing technology into their production workflow. And from the point of view, there is the sharing of the experience in order to provide the, a sort of, let's say, spreads and amplifications of the opportunity for supporting innovation. That is part of are solution means, in a Italy but it also, eh, er sort of um, see objective, that is addressed by the European options er supported by the European commission. I think that that sort of (inaudible) supply that in US, the, that will be coming there, sort of you see the max practice for the technology transfer to support the innovation. >> Excellent, that sharing and that knowledge transfer and collaboration. It seems to be absolutely fundamental and the environment that you've built, facilitates that. Sanzio thank you so much for sharing with us, what Cineca is doing and the great research that's going on there, and across a lot of disciplines, we appreciate you joining the program today. Thank you. >> Thank you, it's been a pleasure, thank you very much for the opportunity. >> Likewise, for Sanzio Bassini. I'm Lisa Martin. You're watching this cube conversation. (calming music)

>>Good morning or good afternoon or good evening, depending on where you are and welcome to this session, reduce claims, fraud, we're data, very excited to have you all here. My name is Winnie castling and I'm Cloudera as managing director for the insurance vertical. First and foremost, we want to let you know that we know insurance. We have done it for a long time. Collectively, personally, I've done it for over 30 years. And, you know, as a proof of that, we want to let you know that we insure, we insure as well as we do data management work for the top global companies in the world, in north America, over property casualty, general insurance health, and, um, life and annuities. But besides that, we also take care of the data needs for some smaller insurance companies and specialty companies. So if you're not one of the huge Glomar conglomerates in the world, you are still perfectly fine with us. >>So >>Why are we having this topic today? Really digital claims and digital claims management is accelerating. And that's based on a couple of things. First and foremost, customers are asking for it. Customers are used to doing their work more digitally over the last descending year or two. And secondly, with the last year or almost two, by now with the changes that we made in our work processes and in society at large around cuvettes, uh, both regulators, as well as companies have enabled digital processing and the digital journey to a degree that they've never done before. Now that had some really good impacts for claims handling. It did meant that customers were more satisfied. They felt they have more control over their processes in the cloud and the claims experience. It also reduced in a lot of cases, both in commercial lines, as well as in personal lines, the, um, the, the time periods that it took to settle on a claim. However, um, the more digital you go, it, it opened up more access points for fraud, illicit activities. So unfortunately we saw indicators of fraud and fraud attempts, you know, creeping up over the last time period. So we thought it was a good moment to look at, you know, some use cases and some approaches insurers can take to manage that even better than they already >>Are. >>And this is how we plan to do that. And this is how we see this in action. On the left side, you see progress of data analytics and data utilization, um, around, in this case, we're talking about claims fraud, but it's a generic picture. And really what it means is most companies that start with data affords pretty much start around data warehousing and we eliminate analytics and all around BI and reporting, which pretty much is understanding what we know, right? The data that we already have utilizing data to understand better what we know already. Now, when we move to the middle blue collar, we get into different types of analytics. We get into exploratory data science, we get to predictions and we start getting in the space of describing what we can learn from what we know, but also start moving slowly into predicting. So first of all, learn and gather insights of what we already know, and then start augmenting with that with other data sets and other findings, so that we can start predicting for the future, what might happen. >>And that's the point where we get to AI, artificial intelligence and machine learning, which will help us predict which of our situations and claims are most likely to have a potential fraud or abuse scenario attached to it. So that's the path that insurers and other companies take in their data management and analytics environments. Now, if you look at the right side of this light, you see data complexity per use cases in this case in fraud. So the bubbles represent the types of data that are being used, or the specific faces that we discussed on the left side. So for reporting, we used a TPA data, policy verification, um, claims file staff data, that it tends to be heavily structured and already within the company itself. And when you go to the middle to the more descriptive basis, you start getting into unstructured data, you see a lot of instructor texts there, and we do a use case around that later. >>And this really enables us to better understand what the scenarios are that we're looking at and where the risks are around. In our example today, fraud, abuse and issues of resources. And then the more you go to the upper right corner, you see the outside of the baseball field, people refer to it, you see new unstructured data sources that are being used. You tend to see the more complex use cases. And we're looking at picture analysis, we're looking at voice analysis there. We're looking at geolocation. That's quite often the first one we look at. So this slide actually shows you the progress and the path in complexity and in utilization of data and analytical tool sets to manage data fraud, fraud, use cases, optimally. >>Now how we do that and how we look at at a Cloudera is actually not as complicated as, as this slight might want to, um, to, to give you an impression. So let's start at the left side at the left side, you see the enterprise data, which is data that you as an organization have, or that you have access to. It doesn't have to be internal data, but quite often it is now that data goes into a data journey, right? It gets collected first. It gets manipulated and engineered so that people can do something with it. It gets stored something, you know, people need to have access to it. And then they get into analytical capabilities who are inside gathering and utilization. Now, especially for insurance companies that all needs to be underpinned by a very, very strong security and governance, uh, environment. Because if not the most regulated industry in the world, insurance is awfully close. >>And if it's not the most regulated one, it's a close second. So it's critically important that insurers know, um, where the data is, who has access to it for Rodriguez, uh, what is being used for so terms like lineage, transparency are crucial, crucially important for insurance. And we manage that in the shared data experience. So it goes over the whole Cloudera platform and every application or tool or experience you use would include Dao. And on the right side, you see the use cases that tend to be deployed around claims and claims fraud, claims, fraud management. So over the last year or so, we've seen a lot of use cases around upcoding people get one treatment or one fix on a car, but it gets coded as a more expensive one. That's a fraud scenario, right? We see also the more classical fraud things and we see anti money laundering. So those are the types of use cases on the right side that we are supporting, um, on the platform, uh, around, um, claims fraud. >>And this is an example of how that actually looks like now, this is a one that it's actually a live one of, uh, a company that had, um, claims that dealt with health situations and being killers. So that obviously is relevant for health insurers, but you also see it in, um, in auto claims and counterclaims, right, you know, accidents. There are a lot of different claims scenarios that have health risks associated with it. And what we did in this one is we joined tables in a complex schema. So we have to look at the claimant, the physician, the hospital, all the providers that are involved procedures that are being deployed. Medically medicines has been utilized to uncover the full picture. Now that is a hard effort in itself, just for one claim and one scenario. But if you want to see if people are abusing, for example, painkillers in this scenario, you need to do that over every instant that is member. >>This claimant has, you know, with different doctors, with different hospitals, with different pharmacies or whatever that classically it's a very complicated and complex, um, the and costly data operation. So nowadays that tends to be done by graph databases, right? So you put fraud rings within a graph database and walk the graph. And if you look at it here in batch, you can see that in this case, that is a member that was shopping around for being killers and went through different systems and different providers to get, um, multiple of the same big LR stat. You know, obviously we don't know what he or she did with it, but that's not the intent of the system. And that was actually a fraud and abuse case. >>So I want to share some customer success stories and recent, uh, AML and fraud use cases. And we have a couple of them and I'm not going to go in an awful lot of detail, um, about them because we have some time to spend on one of them immediately after this. But one of them for example, is voice analytics, which is a really interesting one. And on the baseball slide that I showed you earlier, that would be a right upper corner one. And what happened there is that an insurance company utilized the, uh, the voice records they got from the customer service people to try to predict which one were potentially fraud list. And they did it in two ways. They look at actually the contents of what was being said. So they looked at certain words that were being used certain trigger words, but they also were looking at tone of voice pitch of voice, uh, speed of talking. >>So they try to see trends there and hear trends that would, um, that would bring them for a potential bad situation. Now good and bad news of this proof of concept was it's. We learned that it's very difficult just because every human is different to get an indicator for bad behavior out of the pitch or the tone or the voice, you know, or those types of nonverbal communication in voice. But we did learn that it was easier to, to predict if a specific conversation needed to be transferred to somebody else based on emotion. You know, obviously as we all understand life and health situations tend to come with emotions, or so people either got very sad or they got very angry or so the proof of concept didn't really get us to a firm understanding of potential driverless situation, but it did get us to a much better understanding of workflow around, um, claims escalation, um, in customer service to route people, to the right person, depending on what they need. >>And that specific time, another really interesting one was around social media, geo open source, all sorts of data that we put together. And we linked to the second one that I listed on slide here that was an on-prem deployment. And that was actually an analysis that regulators were asking for in a couple of countries, uh, for anti money laundering scams, because there were some plots out there that networks of criminals would all buy the low value policies, surrendered them a couple of years later. And in that way, God criminal money into the regular amount of monetary system whitewashed the money and this needed some very specific and very, very complex link analysis because there were fairly large networks of criminals that all needed to be tied together, um, with the actions, with the policies to figure out where potential pain points were. And that also obviously included ecosystems, such as lawyers, administrative offices, all the other things, no, but most, you know, exciting. >>I think that we see happening at the moment and we, we, you know, our partner, if analytics just went live with this with a large insurer, is that by looking at different types that insurers already have, um, unstructured data, um, um, their claims nodes, um, repour its claims, filings, um, statements, voice records, augmented with information that they have access to, but that's not their ours such as geo information obituary, social media Boyd on the cloud. And we can analyze claims much more effectively and efficiently for fraud and litigation and alpha before. And the first results over the last year or two showcasing a significant degree is significant degrees in claims expenses and, um, and an increase at the right moment of what a right amount in claims payments, which is obviously a good thing for insurers. Right? So having said all of that, I really would like to give Sri Ramaswami, the CEO of infinite Lytics, the opportunity to walk you through this use case and actually show you how this looks like in real life. So Sheree, here >>You go. So >>Insurers often ask us this question, can AI help insurance companies, lower loss expenses, litigation, and help manage reserves better? We all know that insurance industry is majority. Majority of it is unstructured data. Can AI analyze all of this historically and look for patterns and trends to help workflows and improve process efficiencies. This is exactly why we brought together industry experts at infill lyrics to create the industries where very first pre-trained and prebuilt insights engine called Charlie, Charlie basically summarizes all of the data structured and unstructured. And when I say unstructured, I go back to what money basically traded. You know, it is including documents, reports, third-party, um, it reports and investigation, uh, interviews, statements, claim notes included as well at any third party enrichment that we can legally get our hands on anything that helps the adjudicate, the claims better. That is all something that we can include as part of the analysis. And what Charlie does is takes all of this data and very neatly summarizes all of this. After the analysis into insights within our dashboard, our proprietary naturally language processing semantic models adds the explanation to our predictions and insights, which is the key element that makes all of our insights >>Actually. So >>Let's just get into, um, standing what these steps are and how Charlie can help, um, you know, with the insights from the historical patterns in this case. So when the claim comes in, it comes with a lot of unstructured data and documents that the, uh, the claims operations team have to utilize to adjudicate, to understand and adjudicate the claim in an efficient manner. You are looking at a lot of documents, correspondences reports, third party reports, and also statements that are recorded within the claim notes. What Charlie basically does is crunches all, all of this data removes the noise from that and brings together five key elements, locations, texts, sentiments, entities, and timelines in the next step. >>In the next step, we are basically utilizing Charlie's built-in proprietary, natural language processing models to semantically understand and interpret all of that information and bring together those key elements into curated insights. And the way we do that is by building knowledge, graphs, and ontologies and dictionaries that can help understand the domain language and convert them into insights and predictions that we can display on the dash. Cool. And if you look at what has been presented in the dashboard, these are KPIs and metrics that are very interesting for a management staff or even the operations. So the management team can basically look at the dashboard and start with the summarized data and start to then dig deeper into each of the problematic areas and look at patterns at that point. And these patterns that we learn from not only from what the system can provide, but also from the historic data can help understand and uncover some of these patterns in the newer claims that are coming in so important to learn from the historic learnings and apply those learnings in the new claims that are coming in. >>Let's just take a very quick example of what this is going to look like a claims manager. So here the claims manager discovers from the summarized information that there are some problems in the claims that basically have an attorney involved. They have not even gone into litigation and they still are, you know, I'm experiencing a very large, um, average amount of claim loss when they compare to the benchmark. So this is where the manager wants to dig deeper and understand the patterns behind it from the historic data. And this has to look at the wealth of information that is sitting in the unstructured data. So Charlie basically pulls together all these topics and summarizes these topics that are very specific to certain losses combined with entities and timelines and sentiments, and very quickly be able to show to the manager where the problematic areas are and what are those patterns leading to high, severe claims, whether it's litigation or whether it's just high, severe indemnity payments. >>And this is where the managers can adjust their workflows based on what we can predict using those patterns that we have learned and predict the new claims, the operations team can also leverage Charlie's deep level insights, claim level insights, uh, in the form of red flags, alerts and recommendations. They can also be trained using these recommendations and the operations team can mitigate the claims much more effectively and proactively using these kind of deep level insights that need to look at unstructured data. So at the, at the end, I would like to say that it is possible for us to achieve financial benefits, leveraging artificial intelligence platforms like Charlie and help the insurers learn from their historic data and being able to apply that to the new claims, to work, to adjust their workflows efficiently. >>Thank you very much for you. That was very enlightening as always. And it's great to see that actually, some of the technology that we all work so hard on together, uh, comes to fruition in, in cost savings and efficiencies and, and help insurers manage potential bad situations, such as claims fraud batter, right? So to close this session out as a next step, we would really urge you to a Sasha available data sources and advanced or predictive fraud prevention capabilities aligned with your digital initiatives to digital initiatives that we all embarked on over the last year are creating a lot of new data that we can use to learn more. So that's a great thing. If you need to learn more at one to learn more about Cloudera and our insurance work and our insurance efforts, um, you to call me, uh, I'm very excited to talk about this forever. So if you want to give me a call or find a place to meet when that's possible again, and schedule a meeting with us, and again, we love insurance. We'll gladly talk to anyone until they say in parts of the United States, the cows come home about it. And we're dad. I want to thank you all for attending this session and hanging in there with us for about half an hour. And I hope you have a wonderful rest of the day. >>Good afternoon, I'm wanting or evening depending on where you are and welcome to this breakout session around insurance, improve underwriting with better insights. >>So first and >>Foremost, let's summarize very quickly, um, who we're with and what we're talking about today. My name is goonie castling, and I'm the managing director at Cloudera for the insurance vertical. And we have a sizeable presence in insurance. We have been working with insurance companies for a long time now, over 10 years, which in terms of insurance, it's maybe not that long, but for technology, it really is. And we're working with, as you can see some of the largest companies in the world and in the continents of the world. However, we also do a significant amount of work with smaller insurance companies, especially around specialty exposures and the regionals, the mutuals in property, casualty, general insurance, life, annuity, and health. So we have a vast experience of working with insurers. And, um, we'd like to talk a little bit today about what we're seeing recently in the underwriting space and what we can do to support the insurance industry in there. >>So >>Recently what we have been seeing, and it's actually accelerated as a result of the recent pandemic that we all have been going through. We see that insurers are putting even more emphasis on accounting for every individual customers with lotta be a commercial clients or a personal person, personal insurance risk in a dynamic and a B spoke way. And what I mean with that is in a dynamic, it means that risks and risk assessments change very regularly, right? Companies go into different business situations. People behave differently. Risks are changing all the time and the changing per person they're not changing the narrow generically my risk at a certain point of time in travel, for example, it might be very different than any of your risks, right? So what technology has started to enable is underwrite and assess those risks at those very specific individual levels. And you can see that insurers are investing in that capability. The value of, um, artificial intelligence and underwriting is growing dramatically. As you see from some of those quotes here and also risks that were historically very difficult to assess such as networks, uh, vendors, global supply chains, um, works workers' compensation that has a lot of moving parts to it all the time and anything that deals with rapidly changing risks, exposures and people, and businesses have been supported more and more by technology such as ours to help, uh, gone for that. >>And this is a bit of a difficult slide. So bear with me for a second here. What this slide shows specifically for underwriting is how data-driven insights help manage underwriting. And what you see on the left side of this slide is the progress in make in analytical capabilities. And quite often the first steps are around reporting and that tends to be run from a data warehouse, operational data store, Starsky, Matt, um, data, uh, models and reporting really is, uh, quite often as a BI function, of course, a business intelligence function. And it really, you know, at a regular basis informs the company of what has been taken place now in the second phase, the middle dark, the middle color blue. The next step that is shore stage is to get into descriptive analytics. And what descriptive analytics really do is they try to describe what we're learning in reporting. >>So we're seeing sorts and events and sorts and findings and sorts of numbers and certain trends happening in reporting. And in the descriptive phase, we describe what this means and you know why this is happening. And then ultimately, and this is the holy grill, the end goal we like to get through predictive analytics. So we like to try to predict what is going to happen, uh, which risk is a good one to underwrite, you know, watch next policy, a customer might need or wants water claims as we discuss it. And not a session today, uh, might become fraud or lists or a which one we can move straight through because they're not supposed to be any issues with it, both on the underwriting and the claims side. So that's where every insurer is shooting for right now. But most of them are not there yet. >>Totally. Right. So on the right side of this slide specifically for underwriting, we would, we like to show what types of data generally are being used in use cases around underwriting, in the different faces of maturity and analytics that I just described. So you will see that on the reporting side, in the beginning, we start with rates, information, quotes, information, submission information, bounding information. Um, then if you go to the descriptive phase, we start to add risk engineering information, risk reports, um, schedules of assets on the commercial side, because some are profiles, uh, as a descriptions, move into some sort of an unstructured data environment, um, notes, diaries, claims notes, underwriting notes, risk engineering notes, transcripts of customer service calls, and then totally to the other side of this baseball field looking slide, right? You will see the relatively new data sources that can add tremendous value. >>Um, but I'm not Whitely integrated yet. So I will walk through some use cases around these specifically. So think about sensors, wearables, you know, sensors on people's bodies, sensors, moving assets for transportation, drone images for underwriting. It's not necessary anymore to send, uh, an inspection person and inspector or risk, risk inspector or engineer to every building, you know, be insurers now, fly drones over it, to look at the roofs, et cetera, photos. You know, we see it a lot in claims first notice of loss, but we also see it for underwriting purposes that policies out there. Now that pretty much say sent me pictures of your five most valuable assets in your home and we'll price your home and all its contents for you. So we start seeing more and more movements towards those, as I mentioned earlier, dynamic and bespoke types of underwriting. >>So this is how Cloudera supports those initiatives. So on the left side, you see data coming into your insurance company. There are all sorts of different data. There are, some of them are managed and controlled by you. Some orders you get from third parties, and we'll talk about Della medics in a little bit. It's one of the use cases. They move into the data life cycle, the data journey. So the data is coming into your organization. You collected, you store it, you make it ready for utilization. You plop it either in an operational environment for processing or in an analytical environment for analysis. And then you close on the loop and adjusted from the beginning if necessary, no specifically for insurance, which is if not the most regulated industry in the world it's coming awfully close, and it will come in as a, a very admirable second or third. >>Um, it's critically important that that data is controlled and managed in the correct way on the old, the different regulations that, that we are subject to. So we do that in the cloud era Sharon's data experiment experience, which is where we make sure that the data is accessed by the right people. And that we always can track who did watch to any point in time to that data. Um, and that's all part of the Cloudera data platform. Now that whole environment that we run on premise as well as in the cloud or in multiple clouds or in hybrids, most insurers run hybrid models, which are part of the data on premise and part of the data and use cases and workloads in the clouds. We support enterprise use cases around on the writing in risk selection, individualized pricing, digital submissions, quote processing, the whole quote, quote bound process, digitally fraud and compliance evaluations and network analysis around, um, service providers. So I want to walk you to some of the use cases that we've seen in action recently that showcases how this work in real life. >>First one >>Is to seize that group plus Cloudera, um, uh, full disclosure. This is obviously for the people that know a Dutch health insurer. I did not pick the one because I happen to be dodged is just happens to be a fantastic use case and what they were struggling with as many, many insurance companies is that they had a legacy infrastructure that made it very difficult to combine data sets and get a full view of the customer and its needs. Um, as any insurer, customer demands and needs are rapidly changing competition is changing. So C-SAT decided that they needed to do something about it. And they built a data platform on Cloudera that helps them do a couple of things. It helps them support customers better or proactively. So they got really good in pinging customers on what potential steps they need to take to improve on their health in a preventative way. >>But also they sped up rapidly their, uh, approvals of medical procedures, et cetera. And so that was the original intent, right? It's like serve the customers better or retain the customers, make sure what they have the right access to the right services when they need it in a proactive way. As a side effect of this, um, data platform. They also got much better in, um, preventing and predicting fraud and abuse, which is, um, the topic of the other session we're running today. So it really was a good success and they're very happy with it. And they're actually starting to see a significant uptick in their customer service, KPIs and results. The other one that I wanted to quickly mention is Octo. As most of you know, Optune is a very, very large telemedics provider, telematics data provider globally. It's been with Cloudera for quite some time. >>This one I want to showcase because it showcases what we can do with data in mass amounts. So for Octo, we, um, analyze on Cloudera 5 million connected cars, ongoing with 11 billion data points. And really what they're doing is the creating the algorithms and the models and insurers use to, um, to, um, run, um, tell them insurance, telematics programs made to pay as you drive pay when you drive, pay, how you drive. And this whole telemedics part of insurance is actually growing very fast too, in, in, still in sort of a proof of concept mini projects, kind of initiatives. But, um, what we're succeeding is that companies are starting to offer more and more services around it. So they become preventative and predictive too. So now you got to the program staff being me as a driver saying, Monique, you're hopping in the car for two hours. >>Now, maybe it's time you take a break. Um, we see that there's a Starbucks coming up on the ride or any coffee shop. That's part of a bigger chain. Uh, we know because you have that app on your phone, that you are a Starbucks user. So if you stop there, we'll give you a 50 cents discount on your regular coffee. So we start seeing these types of programs coming through to, again, keep people safe and keep cars safe, but primarily of course the people in it, and those are the types of use cases that we start seeing in that telematic space. >>This looks more complicated than it is. So bear with me for a second. This is a commercial example because we see a data work. A lot of data were going on in commercial insurance. It's not Leah personal insurance thing. Commercial is near and dear to my heart. That's where I started. I actually, for a long time, worked in global energy insurance. So what this one wheelie explains is how we can use sensors on people's outfits and people's clothes to manage risks and underwrite risks better. So there are programs now for manufacturing companies and for oil and gas, where the people that work in those places are having sensors as part of their work outfits. And it does a couple of things. It helps in workers' comp underwriting and claims because you can actually see where people are moving, what they are doing, how long they're working. >>Some of them even tracks some very basic health-related information like blood pressure and heartbeat and stuff like that, temperature. Um, so those are all good things. The other thing that had to us, it helps, um, it helps collect data on the specific risks and exposures. Again, we're getting more and more to individual underwriting or individual risk underwriting, who insurance companies that, that ensure these, these, um, commercial, commercial, um, enterprises. So they started giving discounts if the workers were sensors and ultimately if there is an unfortunate event and it like a big accident or big loss, it helps, uh, first responders very quickly identify where those workers are. And, and, and if, and how they're moving, which is all very important to figure out who to help first in case something bad happens. Right? So these are the type of data that quite often got implements in one specific use case, and then get broadly moved to other use cases or deployed into other use cases to help price risks, betters better, and keep, you know, risks, better control, manage, and provide preventative care. Right? >>So these were some of the use cases that we run in the underwriting space that are very excited to talk about. So as a next step, what we would like you to do is considered opportunities in your own companies to advance risk assessment specific to your individual customer's need. And again, customers can be people they can be enterprises to can be other any, any insurable entity, right? The please physical dera.com solutions insurance, where you will find all our documentation assets and thought leadership around the topic. And if you ever want to chat about this, please give me a call or schedule a meeting with us. I get very passionate about this topic. I'll gladly talk to you forever. If you happen to be based in the us and you ever need somebody to filibuster on insurance, please give me a call. I'll easily fit 24 hours on this one. Um, so please schedule a call with me. I promise to keep it short. So thank you very much for joining this session. And as a last thing, I would like to remind all of you read our blogs, read our tweets. We'd our thought leadership around insurance. And as we all know, insurance is sexy.

>>Um, okay, thanks to the studio there for the handoff. Appreciate it. We're here for breaking news and it's exciting that we have who's the managing director. Google is breaking some hard news here, Dave. We want to bring him in and get commentary while we end up Dave too. Honestly, the story here is cloud city. We are in the cloud city and all, thanks for coming on remotely into our physical hybrid set here. Thanks for coming >>On. Thank you, John. And very excited to be here. What Juliet. >>Well, we got Bon Jovi ready to play. Everyone's waiting for that concert in the year. The only thing standing between bunch of LV and all the great stuff. So a lot of people watching. Thanks for coming on, sir. So you guys got some big news, um, first Erickson partners with you guys on 5g platform, deal with Anthem, as well as, uh, open ran Alliance. You guys are joining huge, a Testament to the industry. I see Google with all your innovation you guys have in the big three cloud hyperscalers. Obviously you guys invented SRE, so you know, you no stranger to large scale. What's the news. Let's tell us why this Erickson news is so important. Let's start with the Erickson announcement. >>Sure. So John, I mean, we are very excited today to finally bring to the market, the strategic partnership that we've been building with Erickson for the last few months, uh, the partnership to recent retreat, which is very important to the industry is you're actually doing this in conjunction with very large CSPs. So it's not been in isolation. You are in fact in the press release that we have already launched something to get the big telecom Italia in Italy, because you will see that also in the past. And really the partnership is on three pillars. Number one, how can CSBs monetize 5g and edge, which is the real team at the moment using Google clouds solutions like the edge computing platform and, and POS, and Erikson's cutting edge 5g components, 5g solutions. And if we can onboard these together at the CSP, such as telecom Italia, that creates massive pain to market efficiency. So that's 0.1 because speed and agility is key John, but then point to it also unlocks a lot of edge use cases for a bunch of verticals, retail, manufacturing, healthcare, so on, which are already starting to launch together with that. Excellent. And so that's the second pillar. And then the final pillar of course, is this continuously cloud native innovation that you just highlighted. John, we are going to try and double down on it between ourselves and Ericsson to really time created this cloud native application suite or 5g or whatever. >>Talk about the innovations around cloud, because the message we're hearing him this year at mobile world Congress, is that the public cloud is driving the innovation. And, you know, I can be a little bit over the top. So the telcos are slow. They're like glaciers, they move slow, but they're just moving packets. They are there. They're moving the network around. The innovation is happening on top. So there's some hardened operations operating the networks. Now you have a build concept cloud native enables that. So you've got containers. You can put that encapsulate that older technology and integrated in. So this is not a rip and replace. Someone has to die to win. This is a partnership with the tellers. Can you share your thoughts on that piece? >>Smart Antone's photo? We believe that it's a massive partnership opportunity. There's zero conflict or tensions in this sort of ecosystem. And the reason for that is when you talk about that containerization and right once and deploy everywhere type architecture that we are trying to do, that's where the cloud native really helps. Like when you create Ericsson 5g solutions with the operators, adjust telecom Italia, once you build a solution, you don't have to worry about, do I need to kick it back again and again, but every deployment, as long as your mantra, genetics and working, you shouldn't be able to have the same experience. >>Yeah, I'm John. I talk all the time in the cube about how developers are really going to drive the edge. You're clearly doing that with your distributed cloud, building out a telco cloud. I wonder if you could talk a little bit more about how you see that evolving. A lot of the AI that's done today is done in the cloud. A lot of modeling being done. When you think about edge, you think about AI inferencing, you think about all these monetization opportunities. How are you thinking about that? >>So I think David, first of all, it's a fan best six Sigma in how we are looked in at analytics at the edge, right? So we, uh, we have realized that is a very, very, uh, uh, uh, data computing, heavy operation. So certainly the training of the models is still going to stay in cloud for the foreseeable future. But the influencing part that you mentioned is there something that we can offer to the edge? Why is that so important in the pandemic era, think of running a shop or a factory floor, completely autonomously meeting zero minimal human intervention. And if you want to look at an assembly line and look at AI influencing as a way to find out assembly line defects on products in manufacturing, that's very difficult problem to solve unless you actually create those influencing models at the edge. So creating that ecosystem of an Erickson and a Google cloud carrier gives you that edge placement of the workloads that would fit right next to our factory floor in our manufacturing example. And then on top of that, you could run that AI influence thing to really put in the hands of the manufacturer, a visual inspection capability to just bring this to life. >>Great. Thank you for that. And now the other piece of the announcement of course, is the open, open ran. We've been talking about that all weekend and you know, you well, remember when cloud first came out, people were concerned about security. Of course. Now everybody's asking the question, can we still get the reliability and the security that we're used to with the telcos? And of course over time we learned that you guys actually pretty good at security. So how do you see the security component, maybe first talk about the open ran piece, why that's important and how security fits? >>Sure. So first of all, open trend is something that we have taken great interest in the last year or so as it started evolving. And the reason for that is fairly simple. Dave, this aggregation of networks has been happening for some time in the radio layer. We believe that's the final frontier of sort of unlocking and dis-aggregating that radio layer. And why is it so important? 80% of the operators spend globally is on radio. 80% is on radio. If you disaggregate that. And if the internet synergies for your CSP partners and clients, that meant you have standard purpose hardware standard for software with open interfaces, number one, massive difference in VCO. Number two, the supply chain gets streamlined and become still really, really simple way to manage a fairly large distribution. That's about to get larger in 5g and the capital clarity that 5g needs. >>You're thinking of tens of thousands of micro cells and radio cells going everywhere. And having that kind of standardized hardware software with openings of Essex is an extremely important cost dimension to every new site finished that the reason we got to exact open brand was you can now run for a lot of API APIs on the radio net, cetera, that then certainly brings a whole developer community on the radio later. That then helps you do a bunch of things like closed loop automation for network optimization, as well as potentially looking at monetization opportunities by hyper personalizing, yours and mine experiences at the waist level from the self-doubt. And so that really is what is driving us towards this open grind paper. Come on, we go and >>Got a minute and a half. I want to get your thoughts real quick on, on open source and the innovation. Um, Danielle Royston, who's the CEO of telco, Dr. She's at a keynote today. And she mentioned that the iPhone 14 years ago was launched. Okay. And you think about open and you mentioned proprietary with the 5g and having Iran be more commodity and industry standard. That's going to lower the costs increase the surface here of infrastructure. Everyone wins because everyone wants more connectivity options. Software is going to be the key to success for the telco industry. And open source is driving. That is Android. The playbook that you guys pioneered, obviously at Google with the smart phones was very successful. How is that a playbook or an indicator to what could happen at telecom? >>Absolutely. John and the parallel and analogy that you raised is photon. Be believed in the telco world and tossed multi cloud as a unifying software development layer. The app development platform is the way that people will start to drive this innovation, whether it's radio or whether it's in the core or whether it's on the side of pups, same software planning, everywhere that really allows you that whole development models that we are familiar with, but on the telecom side. And that's where we are seeing some massive innovation opportunities for systems to come on board. >>That's great stuff. And I was just heard someone in the hallway just yesterday and say, you want to be the smartphone. You don't want to be the Blackberry going forward. That's pretty much the consensus here at mobile world Congress. I'm all. Thank you for coming on and sharing the hard news and Google regulations on the Erickson Anthem platform, a deal as well as the open Ranton Alliance. Uh, congratulations. Good to see you. And by the way, you'll be keynoting tomorrow on the cube featured segment. So >>Watch that in there. Thank you, John. Thank you. Glad >>To be here. Benching director telecom, industry, solicitor, Google, obviously player. He's managing that business. Big opportunities for Google because they have the technology. They got the chops, Dave, and we're going to now bring this Daniel. Russia says here when to bring up on the stage, Bon Jovi is about to go on behind us Bon Jovi's here. And this is like a nightclub, small intimate setting here in cloud city. Dave Bon. Jovi's right there. He's going to come on stage after we close down here, but first let's bring up the CEO of telco. Dr. And yeah, it was great to see she's hot off the keynote. We're going to see you to Mike. Great to see you. Oh, it's great to be there. We're going to see you tomorrow for an official unpacking of the keynote, but thanks for coming by and closing, >>Swinging by. I never closed down the show. It's been a big, it's been a big day-to-day at MWC and in cloud city, really starting to get packed. I mean, everyone's coming in the band's warming up. You can kind of hear it. Um, I think Elon Musk is about to go on as well. So I mean, it's really happening all the buzz about cloud city out there in the hallway. Yeah. Yeah, no, I mean, I think everyone's talking about it. I'm really, really excited with how it's going. >>Well, this is awesome. While we got you here, we want to put you to work being the cube analyst for the segment. You just heard Google. Uh, we broke them in for a breaking news segment. So hard news Erickson partnership. We're in the factory, former Erickson booth. They're not even here, it's now the Calco VR booth, but that's a relation. And then open ran again, open source, you got five G you got open source all happening. What's your take on this? >>You see, you know, there's two big. And I, I talked about it, my keynote this morning, and there's two big technological changes that are happening in our industry simultaneously. And I don't think we could have had it MWC 21. I certainly wanted to make it about the public cloud. I think I'm sort of successful in doing that. And I think the other piece is open ramp, right? And I think these two big shifts are happening and, um, I'm really thrilled about it. And so, yeah, >>Well I loved your keynote. We were here, live. Chloe was here filling in for Dave while David was going to do some research and some breaking stories to you are on stage. And we were talking well, he's like, there's trillions of dollars, John on the table. And I was making the point, the money is at the middle of the table and it's changing hands if people don't watch it. And then you onstage that this trillions of dollars, this is a real competitive shift with dollars on the table. And you've got cultural collision. You got operators and builders trying to figure out it feels like dev ops is coming in here. Yeah. I mean, what's the, what's the holistic vibe. What's >>The, yeah, I think my message is about, we can use the software and specifically the software, the public cloud to double your ARPU without massive cap X expenditure. And I think the CSPs is always viewed to get the increase in ARPU. I got to build out the network. I got to spend a lot of money. And with these two technologies that require might be dropped. And then in exchange for doubling our poo, why not? We should do that. Absolutely. >>You know, your message has been pretty clear that you got to get on, on the wave that arrived the way you're going to become driftwood. As John said yesterday. And I think it's pretty, it's becoming pretty clear that that's the case for the telcos. I feel like Danielle, that they were entering this decade, perhaps with a little bit more humility than they have in the past. And then, you know, maybe, especially as it relates to developers, we're just talking about building out the edge. We always talk about how developers are really going to be a key factor in the edge. And that's not a wheelhouse necessarily. It's obviously they're going to have to partner for that to have going to have to embrace cloud native. I mean, it's pretty clear that your premise is right on it. We'll see how long it takes, but if it, if they don't move fast, you know, what's going to happen. Well, I >>Think you look at it from the enterprise's perspective. And I think we just heard Google talking about it. We need to provide a tech stack that the enterprises can write to now, historically they haven't had this opportunity historically that CSPs have provided it. Now you're going to be able to write against Google's tech stack. And that's something that is documented. It's available. There's developers out there that know it. Um, and so I think that's the big opportunity and this might be the big use case that they've been looking for with 5g and looking forward to 16th. And so it's a huge opportunity for CSS. >>I think that's an important point because you got to place bets. And if I'm betting on Google or Amazon, Microsoft, okay. Those are pretty safe bets, right. Those guys are going to be around. >>I mean, they're like, no, don't trust the hyperscalers. I'm like, um, are you guys nuts? If they're safe, right. Safe >>Bets in terms of your investment in technology, now you got to move fast. Yeah. That's the other piece of it. You've got to change your business model. >>Well, you gotta be in the right side of history too. I mean, I mean, what is trust actually really mean? The snowflake trust Amazon, it sure did to get them where they are. Um, but now that's a >>Great example, John. It really is because there's a company that can move fast, but at the same time they compete with the same time they add incremental value. And so yeah, >>Here, the, you can see the narrative like, oh no, we're partnering telcos. Aren't bad. No one needs to die to bring in the new containers. Do we'll help them manage that operational legacy. But if they don't move, they're going to have an asset. That'll get rolled up into a SPAC or some sort of private equity deal. And because the old model of building cap backs and extract rents is kind of shifting because the value shifting. So to me, I think this is what we're watching still kind of unknown. Danielle Love to get your thoughts on this because if the value shifts to services, which is a consumption model like cloud, yeah. Then you can, don't have to try and extract the rents out of the cap ex >>Yeah. I don't think you need to own the entire stack to provide value. And I think that's where we are today in telco, right there. I mean, nuts and bolts of the stack, the servers, you know, the cabling, everything. And I'm like, stand on the shoulders of these amazing tech giants that have solved, you know, mega data centers, right. Huge data centers at scale, and just leverage their, their investment and uh, for your own benefit, it starts to focus. And we heard, um, all talking about it starts to focus on your subscriber and driving a great experience for us. Right? Yeah. Well, you're >>Talking about that many times they can do, but you're right. If the conversation hasn't has to go beyond, okay, we're just conductivity. It's gotta be ongoing and be like, oh, it's $10 a month for roaming charges. Ah, great. Yeah. Tick that box, right? It's those value added services that you're talking about and it's an infinite number of those that can be developed. And that's where the partnerships come in a creativity in the industry. It's just >>A blank piece of paper for, well, we, you know, everyone thinks Google knows everything about you, right. We've had the experience on our phone where they're serving of ads and you're like, how did you write Facebook? But you know, who knows more about us than, than Google or your mother, even your telco, you take your phone with you everywhere. Right? And so it's time to start unlocking all of that knowledge and using it to provide >>A really great, by the way, congratulations on the CEO to Toby and the investment a hundred million dollars. That's a game changer statement again, back to the billing. And there's a good, there's a whole new chain, even all up and down the stack of solutions, great stuff. And I want to unpack that tomorrow. I don't hold that. We're going and we're going to meet tomorrow. I want, I wanna want to leave that to stay >>In the data for a second, because you made the point before in your keynote as well. That it's, that it's the data that drives the value of these companies. Why is it that apple, Amazon, Google Facebook now trillion dollar evaluations. It's all about the data and the telcos have the data, but they can't figure out how to turn that into valuation. >>There's two parts of the data problem, which is number one, the data is trapped in on-premise siloed systems that are not open. You can't connect them and they certainly can't do without. And we talked about it, I think yesterday, you know, millions of dollars of expenditure. And I think the other piece that's really interesting is that it's not connected to a mechanism to get it out in a timely manner, right? This is data that's aging by the minute. And when it takes you weeks to get the insight it's useless. Right? And so to Togi we announced the launch to Togi, I'll get a little to Tokyo plug in there, right. To Toby is connecting that insight to the charger, to the engagement engine and getting it out to subscribers. I think that's the beginning of this connection. I think it's a hard problem to solve and would have been solved already. >>But I think the key is leveraging the public cloud to get your data out of on-premise and, and mashing it up against these great services that Google and Azure and Amazon provides to drive it into the hands of the subscriber, make it very actionable, very monetizeable right at the end, that's what they want. More ARPU, more revenue. Right. And you know, we heard some keynotes from GSA yesterday, some big, big guys, you know, talking about how, you know, it's not fair that these other communication platforms are not regulated. You know, telco is heavily regulated and they're like, it's not fair. And I'm like, yep. It's not fair. That's like right. South complaining about it and start treating your customers better. So they are, they're happy to give you more. >>Yeah. And I think that's the message about the assets do, um, well, one thing I will say is this mobile world Congress is that we've been having a lot of fun here in cloud city. I have to ask you a personal question. Have you been having fun? You look great on the keynote of spring to your staff, cloud cities. Beautiful. Spectacular here. Give us some highlights, personal highlights from your trip. So far, >>Number one, I'm, I'm psyched that the keynote is delivered and, and done. I mean, I think it takes my blood pressure down a blind, um, you know, the spring in my step, I wore these fun little tennis shoes and, and that was really fun, but yeah, I'm having, I'm having, I think a lot of things, great conversations. Yes. The attendance has reduced, um, you know, usually you see hundreds of people from the big group carriers, especially the European groups and yeah, the attendance is reduced, but the senior guys are here, right. The senior leadership teams are in the booth or having meetings, running amazing conversations. I think the last year we really did live a decade in one year. I think they woke up to the power of the public cloud. I mean, there was no way that they got business done without cloud based tools. And I think the light bulb went off, I think I'm right in the right moment. Awesome. Do you think that, >>Do you think that they'd think in there, like left money on the table because you look at the pandemic, there were three categories of companies, losers, people who held the line struggled and then winners. Yeah. Big time tailwind booming. Obviously the zooms of the world telcos did well. They were up and running. Uh, this, this was good. You think we might've left some money on the table? They could have done more. >>Yeah. I think the ones that were, you know, people talk about digital transformation where digital telco we're digitally enabled, but I think the pandemic really tested this. Right. Can you deliver a contactless SIM or do you need to go to a store in person to get to go pick it up? And I had a broken SIM during the pandemic. My provider made me go to the store and I'm like, is it even open? And so I heard other stories of telcos that were very digitally enabled, right. They were using Uber to deliver Sims, all sorts of fun, crazy stuff and new ideas. And they were able to pivot right. Agile. And so I think, I think that was a really big telemedicine booming. So >>If you were in a digital business during the pandemic in general, you're out of business maybe unless you were telco, but I think you're right. I think the light bulb went off. It was an aha moment. And they said, oh, if >>We don't, I mean, I am not kidding. Right. As an ex CEO where I was trying to collect signatures on renewals, right. Here's a DocuSign, which for the world is like, duh. I mean, our school uses DocuSign. I had telcos that required an in-person signature, right. In some country once a month on Tuesday between 10 and two. And I'm like, how are you doing business? Like that? That's like the dark ages. >>Yeah. This is where the crypto guys got it right. With know your customer. Right. >>Because they have the data. Well, there's a lot of things that come in wrong. We don't want to get the whole show on that, but then you have great to have you drop biopsy Bon Jovi's here. How did you get Bon Jovi? Huge fan, New Jersey boy Patriots fan. We'd love it. Well, >>Yeah. I mean, who doesn't love Bon Jovi. Right. Um, we knew we wanted a rocker, right. Rock and roll is all about challenging the status quo. Um, that, I mean, since the beginning and that's what we're doing here, right. We're really challenging. Like the way things have been done in telco kind of just shattering the glass ceiling and lots of different ways. Right. Calling the old guys dinosaurs. I'm sure those guys love me. Right. I mean, how much do they hate me right now? Or they're like that girl? Oh, we're punk >>Rock. They're rock and roll. Right, right. I mean, maybe we should have gotten the clash >>Right. Black flag. Right. I'm a little bit old. >>Accessible. Still >>Edgy. Yeah. So really excited to get them here. Um, I've met him before. Um, and so hopefully he'll remember me. It's been a couple of years since I've seen him. So can't wait to connect with him again. I think we have Elon Musk coming up and that's going to be, it's always exciting to hear that guy talk. So >>Yeah, it could be inspiration off after you've talked to space, space X and kind to star lake. >>Right. I mean, those guys are launching rockets and deploying satellites. And >>I think that's really interesting for >>Rural right. In telco. Right. Being able to deploy very quickly in rural where the, maybe the cost, um, you know, per gig doesn't make sense. You know, the cost for deployment of tower. I think, I mean, that's an interesting idea right there. It's exciting. It's exciting. >>He's inspirational. I think a lot of people look at the younger generation coming into this issue. Why are we doing things? A lot of people are questioning and they see the cloud. They're saying, oh, Hey, you're a B, why are we doing this? This is such an easier, better way. Yeah. I think eventually the generation shifts >>It's coming. I'm so excited to be a part of it. Yeah. Great, >>Great leadership. And I want to say that you are real innovative, glad to have us here and presenting with you here. >>Awesome team. I'm psyched to have you guys. We talked last night about how great this partnership has said. Yeah. >>Cuba's keep us rocking inside the cloud city. The streets of the city are packed in here. All stuff. Great stuff. Thanks for coming on. Thanks. Bon Jovi is here. We've got a shot. A bunch of we do we have a screenshot of Bon Jovi? Yup. There it is. Okay. He's about to come on stage and uh, we're gonna take a break here. We're gonna take and send it back to Adam and the team in the studio. Thanks guys.