(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)

(bright, upbeat music playing) >> Hello, Brilliant Cloud community and welcome back to AWS re:Invent, where we are live all day everyday from the show floor, here in Las Vegas, Nevada. I'm Savannah Peterson joined by my beautiful co-host, Lisa Martin here on theCUBE. Lisa, you're smiling, you're radiating, day three, you would think it was day one. How you doing? >> Amazing. I can't believe the energy that has been maintained >> It's been a theme. on this show floor, since Monday night at 4:00 pm. >> I know, and I kind of thought today we might see some folks trickling out. It is packed, as our guests and I were, we were all just talking about, right before the segment, almost too packed which is a really great sign for AWS. >> It is. We're hearing north of 55,000 people here. And of course, we only get a little snapshot of what's at the Venetian. >> Literally this corner, yeah. We don't get to see anything else around The Strip, that's going on, so it's massive. >> Yeah, it is very massive. I'm super excited. We've got two guests from Infosys with us on this last segment from this stage today. David and Anant, welcome to the show. How you doing? >> Awesome. >> You're both smiling and I am really excited. We have our first prop of the show, (David and Anant laughing) and it's a pretty flashy, sexy prop. Anant, what's going on here? >> Oh, so this is something that we are very proud of. Last year we won one award, which was very special for us because it was our first award with AWS, and that was, "The Industry Partner of The Year Award." And on the back of that, this year we won three awards and this is super awesome for us, because all of them are very special. One was in collaboration, second was in design, and third was in sustainability. So we are very proud, and we thank AWS, and it's a fantastic partnership. >> Yeah, congratulations. >> Anant: Yes. I mean that's huge. >> Yes, it's absolutely huge. And the second one is, we are the Launch Partner for MSK, which again is a very proud thing for us. So I think those are the two things that we wanted to talk about. >> How many awards are you going to win next year then? (all laughing) >> We want to target more than three. (Savannah chuckles) >> Keep it going up. >> Probably five, right? >> So it's the odd numbers, one, three, five, seven, ten. Yeah. Yeah. Yeah. >> Savannah: There you go. >> I think we got that question last year and we said we'd get two, and we ended up over-delivering with three, so who knows? >> Hey, nothing wrong with setting the bar low and clearing it. And I mean, not setting it low, setting it with one and clearing it with three is pretty fantastic. We talk about it as an ego thing sometimes with awards and it feels great for internal culture, but David, what does it mean on the partnership side to win awards like that? >> So what's really important for us with our partners is to make sure that we're achieving their goals, and when their goals are achieved in our partnership it's just the byproduct that we're achieving our own with our clients. The awards are a great representation of that to see, you know, again, being recognized in three different categories really shows that we've had success with AWS, and in turn, you know, Anant and I can attest to it. We've been very successful at the partnership on our side. >> Yeah, and I bet it's really exciting for the team. Just speaking for Energy (indistinct) >> And there's celebration, you know, there's been a few cocktails being raised... >> Has there? In Las Vegas? >> David: I know. Cocktails? >> Lisa Martin: Shocking! I'm shocked! >> Lisa Martin: I know! (all laughing) I wouldn't mind one right now to be really, really honest. Let's dig into the product a little bit. Infosys Cobalt. What's the scoop, Anant? >> Yeah, so first of all, we were the first ones to actually launch a Cloud brand called Cobalt, right? We were the first ones in the world. In fact, one of our competitor followed us soon after. So essentially what we did was we brought all our Cloud offerings into one brand called Cobalt. It becomes very clear to our customers on what our proposition is. It is very consistent to the market in terms of what our narrative is. And it's a little easy for our customers to understand what we bring to the table. So Cobalt is not one product or what one platform it's a set of services, solutions and platforms that we bring to accelerate customer's journey where they're leveraging Cloud. So that's what Cobalt is. >> Awesome, everyone wants to do everything faster. >> Yes. >> Lisa Martin: Yeah. >> And the booth was packed. I walked by earlier, it was absolutely buzzing. >> Yes. >> Yeah. Nobody wants to do, you know, wants less data slower. >> Anant: Yes. (Savannah laughs) >> It's always more faster. >> Anant: More faster. And we're living in this explosion unlike anything this swarm of data unlike anything that we've ever seen before. Every company, regardless of industry has to be a data company. >> Anant: Yes. But they have to be able to work with the right partners to extract, to first of all harness all that data, extract insights in real time, because of course on the consumer side we're not patient anymore. >> Anant: Yes. We expect a personalized, realtime, custom experience. >> Anant: Absolutely. >> How do you work with AWS to help deliver that and how do the partners help deliver that as well? >> Well I'll start with on the partner side of it. You walk through the hallways here or down the aisles you see partners like MongoDB, Snowflake, Databricks and such, they're all attesting their commitment and their strong partnership with AWS, and coincidentally they're also very good partners of our own. And as a result... >> Savannah: One big happy family here at AWS when you met. >> And this is something that I'm calling, coining the phrase sub-ecosystems. These are partnerships where one is successful with each other, and then the three come together, and we go together with an integrated solution. And it's really taking off. It's something that's really powerful. The fun thing about re:Invent here is isn't just that we're having amazing discussions with our clients and AWS, but we're also having with the other partners here about how we can all work together so... And data analytics is a big one, security is another hot one-- >> Lisa Martin: Security is huge. >> Savannah: Yeah. Cost optimization from the start. >> Absolutely. And Ruba was saying this, right? Ruba said, like she was giving example of a marathoner. Marathon is not a single man or a single woman sport, right? So similarly Cloud journey is a team's, sort of you know, team journey, so that's why partners play a big role in that and that's exactly what we are trying to do. >> So you guys get to see a lot of different companies across a lot of different industries. We're living in very interesting times, how do you see the Cloud evolving? >> Oh, yeah. So what we did when we launched Cobalt in 2020 we have now evolved our story. We call it Cobalt 2.0. And essentially what we wanted to do was to focus on industry Clouds. So it's not just about taking a workload and moving it from point A to point B or moving data to Cloud or getting out of data centers, but it's also being very specific to the industry that this specific customer belongs to, right? So for example, if we go to banking they would say we want to better our security posture. If we go to a retailer they want to basically have smart stores. If we go to a manufacturing customer they want to have a smart factory. So we want to make sure that there are specific industry blueprints and specific reference architectures that we bring and start delivering outcomes. So we call it something called... >> Savannah: I know you're hot on business outcomes. >> Yes. >> Savannah: Yes. So we call it something called the link of life forces. So there are six technologies; Cloud, Data, Edge, IOT, 5G, and AI. They will come together to deliver business outcomes. So that's where we are heading with Cobalt 2.0, And that's essentially what we want to do with our customers. >> Savannah: It's a lot to think about. >> Yes. >> David: Yes. >> And, yeah, go for it David. >> I was just saying from a partnering perspective, you know prior to Cloud, we were talking about transactional type businesses where if you ask a technology company who their partner is its generally a reseller where they're just basically taking one product and selling it to their client. What's happened with cloud now it's not about the transaction upfront it's about the actual, you know, the consumption of the technology and the bringing together all of these to form an outcome, it changes the model dramatically, and quite honestly, the global system integrators like Infosys are in great position because we can pull that together to the benefit of our partners, put our own secret sauce around it and take these solutions to market and drive consumption because that's what the Cloud's all about. >> Right. Well, how are you helping customers really treat Cloud as a strategic focus? You know we often hear companies talk about we're Cloud first. Well not everything belongs in the Cloud. So then we hear companies start talking about being Cloud smart. >> Anant: Yes. How are you helping, and so we'll go with that. How are you helping enterprises really become Cloud smart and where is the partner angle? So we'll start with you and then we'll bring the partner angle in. >> Oh yeah, big time. I think one of the things that we have been educating our customers is Cloud is not about cost takeout. So Cloud is about innovation, Cloud is about growth. And I'll give two examples. One of the beauty products companies they wanted to set up their shop in US and they said that, you know, "we don't have time to basically buy the infrastructure, implement an ERP platform, and you know, or roll it out, test it and go into production. We don't have so much time. Time to market is very important for us." And they embarked on the Cloud journey. So expanding into new market, Cloud can play a big role. That is one of the ways to expand and you know, grow your business. Similarly, there is another company that they wanted to go into retail banking, right? And they didn't have years to launch a product. So they actually use AWS and it's a joint Infosys and AWS customer. A pretty big bank. They launched retail banking and they did it in less than six months. So I think these are some of the examples of cloud not being cost takeout but it's about innovation and growth. So that's what we are trying to tell customers. >> Savannah: Big impacts. >> Big impact. Yes, absolutely. >> And that's where the Cobalt assets come into play as well. You know, as Anant mentioned, we have literally thousands of these industries specific and they're derived in a lot of cases in partnership with the companies you see down the aisles here, and AWS. And it accelerates the deployments and ensures a successful adoption, more so than before. You know, we have clients that are coming to us now that used to buy, run their own procurement. You know they would have... Literally there was one bank that came to us with a over a hundred products >> The amount of work. I'm just seeing it... >> A list of a hundred products. Some they bought directly from a vendor, some they went through a distributor, some they went through a reseller and such, >> Savannah: It's so ad-hoc. And they're looking at this in a completely different way and they're looking to rationalize those technologies, again, look for companies that will contract for a business outcome and leverage the cloud and get to that next era, and it's a fun time. We're really excited. >> I can imagine you're really a part of the transformation process for a lot of these companies. >> Anant: Absolutely. Anant when we were chatting before we went live you talked about your passion for business outcomes. Can you give us a couple examples of customers or business outcomes that really get you and the team excited? Same thing to you David, after. >> Well, absolutely. Even our contractual structures are now moving into business outcomes. So we are getting paid by the outcomes that we are delivering, right? So, one of the insurance customers that we have we actually get paid by the number of claims that we process, right? Similarly there is a healthcare customer where we actually get paid by the number of customers that we cater to from a Medicare and Medicaid standpoint, right? >> Savannah: Tangible results processed and projected-- >> Successful process of claims. >> Interesting. >> Anant: Exactly. >> Yeah. (indistinct) reality. >> Yeah, reality, (chuckles) What a novel idea. >> Yeah. (Savannah and Lisa chuckle) >> One of the great examples you hear about airplane engines now that the model is you don't buy the engine, you basically pay for the hours that it's used, and the maintenance and the downtime, so that you take the risk away. You know, you put that in the context of the traditional business. You're taking away the risk of owning the individual asset, the maintenance, any of the issues, the bug fixes. And again, you're partnering with a company like Infosys, we'll take on that based upon our knowledge and based upon our vast experience we can confidently contract in that way that, you know, years ago that wasn't possible. >> Savannah: It's kind of a sharing economy at scale style. >> David: Exactly. >> Anant: Absolutely. >> Yeah, which is really exciting. So we have a new challenge here on theCUBE this year at re:Invent. We are looking for your 32nd Instagram real sizzle soundbite. Your hot take, your thought leadership on the biggest theme or most important thing coming out of this year's show. David, we'll start with you. We've been starting with Anant, so I'm going to go to you. We're making eye contact right now so you're in the hot seat. (all laugh) >> Well, I think there was a lot of time given to sustainability on the stage this week, and I think that, you know, every CEO that we talk to is bringing that up as a major priority and that's a very important element for us as a company and as a service provider. >> Savannah: I mean, you're obviously award winning in the sustainability department. >> Exactly. Nice little plug there. >> Yeah. >> You know, and I think the other things that have come up we saw a lot about data analytics this week. You know, I think new offerings from AWS but also new partnerships that we're going to take advantage of. And again, security has been a hot topic. >> Absolutely. Anant, what's your hot take? >> Yeah. I think one very exciting thing for partners like us is the re-imagining that is being done by Ruba for the partners, right? The AWS marketplace. I think that is a big, big thing that I took out. Of course, sustainability is huge. Like Adam said, the fastest way to become sustainable is to move to Cloud, right? So rather than overthinking and over-engineering this whole topic just take your workloads and move it to Cloud and you'll be sustainable, right? So I think that's the second one. And third is of course cybersecurity. Zscaler, Palo Alto, CrowdStrike, these are some of the big companies that are at the event here, and we have been partnering with them. Many more. I'm just calling out three names, but many more. I think cybersecurity is the next one. So I think these are three on top of my mind. >> Just a few things you casually think about. That was great. Great responses from both of you Anant, David, such a pleasure to have you both with us. We hope to have you back again. You're doing such exciting things. I'm sure that everything we talked about is going to be a hot topic for many years to come as people navigate the future as well as continue their business transformations. It is always a joy to sit next to you on stage my dear. >> Likewise. And thank all of you, wherever you're tuning in from, for joining us here at AWS re:Invent live from Las Vegas, Nevada. With Lisa Martin, I'm Savannah Peterson, and for the last time today, this is theCUBE, the leader in high tech coverage. (bright, upbeat music playing)

>>Hello, brilliant cloud community and welcome back to AWS Reinvent, where we are live all day every day. From the show floor here in Las Vegas, Nevada. I'm Savannah Peterson, joined by my beautiful cohost Lisa Martin here on the cube. Lisa, you're smiling. You're radiating Day three. You would think it was day one. How you doing? >>Amazing. I can't believe the energy that has been maintained omni show floor since Monday night at 4:00 PM >>I know. And I, I kind of thought today we might see some folks trickling out. It is packed as our, as our guests and I were, we were all just talking about right before the segment, almost two packed, which is a really great sign for aws. It is. We're >>Hearing worth of 55,000 people here. And of course we only get a, a little snapshot of which literally >>This corner, >>We don't get to see anything else around the strip that's going on. So it's massive. Yeah, >>It is a very massive, I'm super excited. We've got two guests from Infosys with us on this last segment from this stage today. David and Anant, welcome to the show. How you doing? >>Awesome. >>You're both smiling and I am really excited. We have our first prop of the show and it's a pretty flashy, sexy prop. Anant, what's going on here? >>Oh, so this is something that we are very proud of. Last year we won one award, which was very special for us because it was our first award with aws and that was the industry partner of the year award. And on the back of that, this year we won three awards. And this is super awesome for us because all of them are very special. One was in collaboration, second was in design, and third was in sustainability. So we are very proud and we thank AWS and it's a fantastic partnership. Yeah. And >>Congratulations. Yes. I mean that's >>Huge. Yes, it's absolutely huge. And the second one is we are the launch partner for msk, which again is a very proud thing for us. So I think those are the two things that we wanted to talk about. >>How many awards are you gonna win next year then? >>Do you want to target more than three? >>So we keep going up probably fine, >>Right? I >>Love, >>That's the odd numbers. 1, 3, 5, 7, 10. There you go. >>Yeah, >>I think you, we got that question last year and we said we get two and we ended up overdelivering with three. So who >>Knows? Hey, nothing. Nothing wrong with the setting the bar low and clearing it and I mean, not setting it low, setting it with one and clearing it with three is pretty fantastic. Yes, yes. We talk about it as an ego thing sometimes with awards and it feels great for internal culture. But David, what does it mean on the partnership side to win awards like that? So >>What's really important for us with our partners is to make sure that we're achieving their goals and when, when their goals are achieved in our partnership, it's just the byproduct that we're achieving our own with our clients. The awards are a great representation of that to see, you know, again, being recognized three in three different categories really shows that we've had success with AWS and in turn, you know, know and not, I can attest to it, we've been very successful with the partnership on our side. >>Yeah. And I bet it's really exciting for the team. Just speaking for energy, are your >>Team sponsor? Absolutely. There's celebration, you know, there's been a few cocktails being raised >>In Las Vegas >>Cocktail. Oh, >>I wouldn't mind one right now to be really be really honest. Let's dig into the, into the product a little bit. Infosys Cobalt, what's the scooping on? >>Yeah, so first of all, we were the first ones to actually launch a cloud brand called Cobalt. Right? We are the first ones in the world. In fact, one of our competitor followed us soon after. So essentially what we did was we brought all our cloud offerings into one brand called Cobalt. It becomes very clear to our customers on what our proposition is. It is very consistent to the market in terms of what our narrative is. And it's little easy for our customers to understand what we bring to the table. So is not one product or one platform. It's a set of services, solutions and platforms that we bring to accelerate customers journey where they're leveraging cloud. So that's what Cobalt is. >>Awesome. Everyone wants to do everything faster. Yes. And Booth was packed. I walked by earlier, it was absolutely buzzing. Yes. >>Yeah. Nobody wants to do it, you know, wants less data slower. Yes. Always more faster. More faster. And we're living in this explosion unlike anything, this swarm of data, unlike anything that we've ever seen before. Yes. Every company, regardless of industry, has to be a data company. Yes. But they have to be able to work with the right partners. Absolutely. To extract, to first of all, harness all that data. Yes. Extract insights in real time. Yes. Because of course, on the consumer side, we're not patient anymore. Yes. We expect a personalized, real time custom experience. Absolutely. How do you work with AWS to help deliver that and how do the partners help deliver that as well? >>Well, I'll start with on the partner side of it. You walk through the hallways here or down the aisles, you see partners like MongoDB, snowflake, data Bricks and and such. They're all attest their commitment and their strong partnership with aws. And coincidentally, they're also very good partners of our own. And as a result, what >>Big happy family here at AWS when you >>Met? Yes, and this, this is something that I'm, I'm calling coining the phrase sub ecosystems. These are partnerships where one is successful with each other and then the three come together and we go together with an integrated solution. And it's really taking off. It's something that's really powerful. The, the fun thing about, you know, reinvent here is it's just that we're having amazing discussions with our clients and aws, but we're also having it with the other partners here about how we can all work together. So, and data analytics is a big one. Security is another hot one. This is huge. >>Yeah. Optimization. >>The absolutely. And I, and Ruba was saying this, right? Ruba said like she was giving example of a marathon or Marathon is not a single man or a single woman sport. Right? So similarly cloud journey is a team's sort of, you know, team journey. Yeah. So that's why partners play a big role in that and that's exactly what we are trying to do. >>So you guys get to see a lot of different companies across a lot of different industries. We've, we're living in very interesting times. How do you see the cloud evolving? >>Oh yeah. So, so what we did when we launched Cobalt in 2020, we have now evolved our story, we call it Cobalt 2.0. And essentially what we want to do was to focus on industry clouds. So it's not just about taking a workload and doing it from point A to point B or moving data to cloud or getting out of data centers, but also being very specific to the industry that this specific customer belongs to. Right? So for example, if you go to banking, they would say, we want to better our security posture. If you go to a retailer, they want to basically have smart stores. If we go to a manufacturing customer, they want to have a smart factory. So we want to make sure that there are specific industry blueprints and specific reference architectures that we bring and start delivering outcomes. So we have, we call it something called, >>I know you're hot on business outcomes. Yes, yes. >>So we call it something called the link of life forces. So there are six technologies, cloud, data Edge, iot, 5g, and ai. They will come together to deliver business outcomes. So that's where we are heading with Cobalt 2.0. And that's essentially what we want to do with our customers. >>That's a lot to think about. Yes. And yeah, go for it. >>David. I just say from a partnering perspective, you know, prior to cloud we were talking about transactional type businesses where if you ask a technology company who their partner is, is generally a reseller where they're just basically taking one product and selling it to their, their client. What's happened with cloud now, it's not about the transaction up front, it's about the, the actual, you know, the consumption of the technology and the bringing together all of these to form an outcome. It changes the model dramatically. And, and quite honestly, you know, the global system integrators like emphasis are in a great position cuz we can pull that together to the benefit our of our partners put our own secret sauce around it and take these solutions to market and drive consumption. Cuz that's what the cloud's all about. >>Absolutely. Right. How are you helping customers really treat cloud as a strategic focus? You know, we, we often hear companies talk about we're we're cloud first. Well, not everything belongs in the cloud. So then we hear companies start talking about being cloud smart. Yes. How are you helping? And so we'll go with that. How are you helping enterprises really become cloud smart and where is the partner angle? So we'll start with you and then we'll bring the partner angle in. >>Sure. Oh yeah, big time. I think one of the things that we have been educating our customers is cloud is not about cost takeout. So cloud is about innovation, cloud is about growth. And I'll give two examples. One of one of the beauty products companies, they wanted to set up their shop in us and they said that, you know, we don't have time to basically buy the infrastructure, implement an er p platform and you know, or roll it out, test it, and go into production. We don't have so much time, time to market is very important for us. And they embarked on the cloud journey. So expanding into new market cloud can play a big role. That is one of the ways to expand and, you know, grow your business. Similarly, there is another company that they, they wanted to get into retail banking, right? And they didn't have years to launch a product. So they actually use AWS and it's a joint infos and AWS customer, a pretty big bank. They launched into, they launched retail banking and they did it in less than six months. So I think these are some of the examples of, wow, it's Snap Cloud not being cost takeout, but it's about innovation and growth. So that's what we are trying to tell >>Customers. Big impacts, big impact. >>Absolutely. And that's where the, the Cobalt assets come into play as well. We, you know, as as not mentioned, we have literally thousand of these industries specific, and they're derived in, in a lot of cases in, in, in partnership with the, the companies you see down the, the aisles here and, and aws. And it accelerates the, the, the deployments and ensures a accessible adoption more so than before. You know, we, we have clients that are coming to us now that used to buy, run their own procurement. You know, they, they would have literally, there was one bank that came to us with a over a hundred, >>The amount of work. Yeah. >>A list of a hundred products. Some they bought directly from a, a vendor, some they went through a distributor, something went through a, a seller and such. And they're, they're, now they're looking at this in a completely different way. And they're looking to rationalize those, those technologies, again, look for companies that will contract for a business outcome and leverage the cloud and get to that next era. And it's, it's a, it's a fun time. We're really excited. >>I can imagine you, you're really a part of the transformation process for a lot of these companies. Absolutely. And when we were chatting before we went live, you talked about your passion for business outcomes. Can you give us a couple examples of customers or business outcomes that really get you and the team excited? Same thing to you, David, after. Yeah, >>Well, absolutely. Even our contractual structures are now moving into business outcomes. So we are getting paid by the outcomes that we are delivering, right? So one of the insurance customers that we have, we actually get paid by the number of claims that we process, right? Similarly, there is a healthcare customer where we actually get paid by the number of customers that we cater to from a Medicare and Medicaid standpoint, right? >>Tangible results versus >>Projected forecast. Successful process of >>Claims. That's interesting. Exactly. Yeah. I love reality. Yeah, reality. What a novel idea. Yeah. >>One of the great examples you hear about airplane engines now that the model is you don't buy the engine. You basically pay for the hours that it's used and the maintenance and the downtime so that they, you take the risk away. You know, you put that in the context of a traditional business, you're taking away the risk of owning the individual asset, the maintenance, any, any of the issues, the bug fixes. And again, you're, you're partnering with a company like Emphasis will take on that based upon our knowledge and based upon our vast experience, we can confidently contract in that way that, you know, years ago that wasn't possible. >>It's kind of a sharing economy at scale style. >>Exactly. Absolutely. >>Yeah. Which is really exciting. So we have a new challenge here on the cube this year at ve We are looking for your 32nd Instagram real sizzle sound bite, your hot take your thought leadership on the, the biggest theme or most important thing coming out of this year's show. David, we'll start with you. We've been starting with it on, I'm to go to you. We're making eye contact right now, so you're in the hot seat. >>Well, let's, I I think there's a lot of time given to sustainability on the stage this week, and I think that, you know, every, every CEO that we talk to is bringing that up as a major priority and that's a very important element for us as a company and as a service >>Provider. I mean, you're obviously award-winning and the sustainability department. Exactly. >>Yes. Nice little plug there. You know, and I, I think the other things that have come up, we saw a lot about data analytics this week. You know, I think new offerings from aws, but also new partnerships that we're gonna take advantage of. And, and again, security has been a hot topic. >>Absolutely. And not, what's your hot take? >>Yeah. I think one, one very exciting thing for partners like us is the, the reimagining that is being done by rhu for the partners, right? The AWS marketplace. I think that is a big, big thing that I took out. Of course, sustainability is huge. Like Adam said, the fastest way to become sustainable is to move to cloud, right? So rather than overthinking and over-engineering this whole topic, just take your workloads and move it to cloud and you'll be sustainable. Right. So I think that's the second one. And third is of course cyber security. Zscaler, Palo Alto, CrowdStrike. These are some of the big companies that are at the event here. And we have been partnering with them many more. I'm just calling out three names, but many more. I think cyber security is the next one. So I think these are three on top of my mind. >>Just, just a few things you casually think about. That was great, great responses from both of you and David, such a pleasure to have you both with us. We hope to have you back again. You're doing such exciting things. I'm sure that everything we talked about is gonna be a hot topic for many years to come as, as people navigate the future, as well as continue their business transformations. It is always a joy to sit next to you on stage. Likewise. Thank you. And thank all of you wherever you're tuning in from. For joining us here at AWS Reinvent Live from Las Vegas, Nevada, with Lisa Martin. I'm Savannah Peterson. And for the last time today, this is the cube, the leader in high tech coverage.

(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.

>>Okay. We're here with the rest of the child who was the chief product officer at Altryx and Adam Wilson, the CEO of Trifacta. Now of course, part of Altryx just closed this quarter. Gentlemen. Welcome. >>Great to be here. >>Okay. So rest, let me start with you. In my opening remarks, I talked about Altrix is traditional position serving business analysts and how the hyper Anna acquisition brought you deeper into the business user space. What does Trifacta bring to your portfolio? Why'd you buy the company? >>Yeah. Thank you. Thank you for the question. Um, you know, we see, uh, we see a massive opportunity of helping, um, brands, um, democratize the use of analytics across their business. Um, every knowledge worker, every individual in the company should have access to analytics. It's no longer optional, um, as they navigate, uh, their businesses with that in mind, you know, we know designer and are the products that Ultrix has been selling the past decade or so do a really great job, um, addressing the business analysts, uh, with, um, hyperaware, um, now kind of renamed, um, Altrix auto insights. Uh, we even speak with the, uh, business owner of the line of business owner. Who's looking for insights that aren't real in traditional dashboards and so on. Um, but we see this opportunity of really helping the data engineering teams and it organizations, um, to also make better use of analytics. Um, and that's where the drive factor comes in for us. Um, drive factor has the best data engineering cloud in the planet. Um, they have an established track record of working across multiple cloud platforms and helping data engineers, um, do better data pipelining and work better with, uh, this massive kind of cloud transformation that's happening in every business. Um, and so Trifacta made so much sense for us. >>Yeah. Thank you for that. I mean, look, you could have built it yourself. Would've taken, you know, who knows how long, but, uh, so definitely a great time to market move, Adam. I wonder if we could dig into Trifacta some more, I mean, I remember interviewing Joe Hellerstein in the early days. You've talked about this as well, uh, on the cube coming at the problem of taking data from raw refined to an experience point of view. And Joe in the early days, talked about flipping the model and starting with data visualization, something Jeff, her was expert at. So maybe explain how we got here. We used to have this cumbersome process of ETL and you may be in some others changed that model with ELL and then T explain how Trifacta really changed the data engineering game. >>Yeah, that's exactly right. Uh, David, it's been a really interesting journey for us because I think the original hypothesis coming out of the campus research, uh, at Berkeley and Stanford that really birthed Trifacta was, you know, why is it that the people who know the data best can't do the work? You know, why is this become the exclusive purview of the highly technical and, you know, can we rethink this and make this a user experience, problem powered by machine learning that will take some of the more complicated things that people want to do with data and really helped to automate those. So, so a, a broader set of users can, um, can really see for themselves and help themselves. And, and I think that, um, there was a lot of pent up frustration out there because people have been told for, you know, for a decade now to be more data-driven and then the whole time they're saying, well, then give me the data, you know, in the shape that I can use it with the right level of quality and I'm happy to be, but don't tell me to be more data driven and then, and, and not empower me, um, to, to get in there and to actually start to work with the data in meaningful ways. >>And so, um, that was really, you know, what, you know, the origin story of the company. And I think as, as we, um, you know, saw over the course of the last 5, 6, 7 years that, um, you know, a real, uh, excitement to embrace this idea of, of trying to think about data engineering differently, trying to democratize the, the ETL process and to also leverage all of these exciting new, uh, engines and platforms that are out there that allow for processing, you know, ever more diverse data sets, ever larger data sets and new and interesting ways. And that's where a lot of the push down or the ELT approaches that, you know, I think it could really won the day. Um, and that, and that for us was a hallmark of the solution from the very beginning. >>Yeah, this is a huge point that you're making. This is first of all, there's a large business, it's probably about a hundred billion dollar Tam. Uh, and the, the point you're making is we've looked, we've contextualized most of our operational systems, but the big data pipelines hasn't gotten there. And maybe we could talk about that a little bit because democratizing data is Nirvana, but it's been historically very difficult. You've got a number of companies it's very fragmented and they're all trying to attack their little piece of the problem to achieve an outcome, but it's been hard. And so what's going to be different about Altryx as you bring these puzzle pieces together, how is this going to impact your customers who would like to take that one? >>Yeah, maybe, maybe I'll take a crack at it. And Adam will, um, add on, um, you know, there hasn't been a single platform, uh, for analytics automation in the enterprise, right? People have relied on, uh, different products, um, to solve kind of, uh, smaller problems, um, across this analytics, automation, data transformation domain. Um, and, um, I think uniquely altereds has that opportunity. Uh, we've got 7,000 plus customers who rely on analytics for, um, data management, for analytics or AI and ML, uh, for transformations, uh, for reporting and visualization for automated insights and so on. And so by bringing drive factor, we have the opportunity to scale this even further and solve for more use cases, expand the scenarios where it's gets applied and so multiple personas. Um, and now we just talked about the data engineers. They are really a growing stakeholder in this transformation of data and analytics. >>Yeah, good. Maybe we can stay on this for a minute cause you, you you're right. You bring it together. Now that at least 3% is the business analyst, the end user slash business user. And now the data engineer, which is really out of an it role in a lot of companies, and you've used this term, the data engineering cloud, what is that, how is it going to integrate in with, or support these other personas? And, and how's it going to integrate into the broader ecosystem of clouds and cloud data warehouses or any other data stores? >>Yeah, no, that's great. Uh, yeah, I think for us, we really looked at this and said, you know, we want to build an open and interactive cloud platform for data engineers, you know, to collaboratively profile pipeline, um, and prepare data for analysis. And that really meant collaborating with the analysts that were in the line of business. And so this is why a big reason why this combination is so magic because ultimately if we can get the data engineers that are creating the data products together with the analysts that are, uh, in the line of business that are driving a lot of the decision-making and allow for that, what I would describe as collaborative curation of the data together, so that you're starting to see, um, uh, you know, increasing returns to scale as this, uh, as this rolls out. I just think that is an incredibly powerful combination and, and frankly, something that the market has not cracked the code on yet. And so, um, I think when we, when I sat down with Suresh and with mark and the team at Ultrix, that was really part of the, the, the big idea, the big vision that that was painted and, and got us really energized about the acquisition and about the potential of the combination. >>Yeah. And you're really, you're obviously riding the cloud and the cloud native wave. Um, and, but specifically we're seeing, you know, I almost don't even want to call it a data warehouse anyway, because when you look at what's, for instance, snowflake is doing, of course their marketing is around the data cloud, but I actually think there's real justification for that because it's not like the traditional data warehouse, right. It's, it's simplified get there fast, don't necessarily have to go through the central organization to share data. Uh, and, and, and, but it's really all about simplification, right? Isn't that really what the democratization comes down to. >>Yeah. It's simplification and collaboration. Right. I don't want to, I want to kind of just, um, what Adam said resonates with me deeply, um, analytics is one of those, um, massive disciplines, an enterprise that's really had the weakest of tools. Um, and we just have interfaces to collaborate with, and I think truly this was Alteryx's and a superpower was helping the analysts get more out of their data, get more out of the analytics, like imagine a world where these people are collaborating and sharing insights in real time and sharing workflows and getting access to new data sources, um, understanding data models better, I think, um, uh, curating those insights. I boring Adam's phrase again. Um, I think that creates a real value inside the organization, uh, because frankly in scaling analytics and democratizing analytics and data, we're still in such early phases of this journey. >>So how should we think about designer cloud, which is from Altryx it's really been the on-prem and the server desktop offering. And of course Trifacta is with cloud cloud data warehouses. Right. Uh, how, how should we think about those two products? >>Yeah, I think, I think you should think about them and, uh, um, as, as very complimentary right design a cloud really shares a lot of DNA and heritage with, uh, designer desktop, um, the low code tooling and that interface, uh, that really appeals to the business analysts, um, and gets a lot of the things that they do well, we've also built it with interoperability in mind, right. So if you started building your workflows in designer desktop, you want to share that with design and cloud, we want to make it super easy for you to do that. Um, and I think over time now we're only a week into, um, this Alliance with, um, with Trifacta. Um, I think we have to get deeper inside to think about what does the data engineer really need what's business analysts really need and how to design a cloud, and Trifacta really support both of those requirements, uh, while kind of continue to build on the tri-factor on the amazing tri-factor cloud platform. >>You know, >>I was just going to say, I think that's one of the things that, um, you know, creates a lot of, uh, opportunity as we go forward, because ultimately, you know, Trifacta took a platform, uh, first mentality to everything that we built. So thinking about openness and extensibility and, um, and how over time people could build things on top of, by factor that are a variety of analytic tool chain, or analytic applications. And so, uh, when you think about, um, Ultrix now starting to, uh, to move some of its capabilities or to provide additional capabilities, uh, in the cloud, um, you know, Trifacta becomes a platform that can accelerate, you know, all of that work and create, uh, uh, a cohesive set of, of cloud-based services that, um, share a common platform. And that maintains independence because both companies, um, have been, uh, you know, fiercely independent, uh, and really giving people choice. >>Um, so making sure that whether you're, uh, you know, picking one cloud platform and other, whether you're running things on the desktop, uh, whether you're running in hybrid environments, that, um, no matter what your decision, um, you're always in a position to be able to get out your data. You're always in a position to be able to cleanse transform shape structure, that data, and ultimately to deliver, uh, the analytics that you need. And so I think in that sense, um, uh, you know, this, this again is another reason why the combination, you know, fits so well together, giving people, um, the choice. Um, and as they, as they think about their analytics strategy and their platform strategy going forward, >>Yeah. I make a chuckle, but I, one of the reasons I always liked Altryx is cause you kinda did the little end run on it. It can be a blocker sometimes, but that created problems, right? Because the current organization said, wow, there's big data stuff is taken off, but we need security. We need governance. And, and it was interesting because he got, you know, ETTL has been complex, whereas the visualization tools, they really, you know, really weren't great at governance and security. It took some time there. So that's not, not their heritage. You're bringing those worlds together. And I'm interested, you guys just had your sales kickoff, you know, what was their reaction like, uh, maybe Suresh, you could start off and maybe Adam, you could bring us home. >>Yeah. Um, thanks for asking about our sales kickoff. So we met for the first time and kind of two years, right. For, as, as it is for many of us, um, in person, uh, um, which I think was, uh, was a real breakthrough as Qualtrics has been on its transformation journey. Uh, we had a Trifacta to, um, the, the party such as the tour, um, and getting all of our sales teams and product organizations, um, to meet in person in one location. I thought that was very powerful for us, the company. Uh, but then I tell you, um, um, the reception for Trifacta was beyond anything I could have imagined. Uh, we were working Adam and I were working so hard on, on the deal and the core hypothesis and so on. And then you step back and you kind of share the vision, uh, with the field organization and it blows you away, the energy that it creates among our sellers, our partners, and I'm sure Adam will, and his team were mocked every single day with questions and opportunities to bring them in. >>But Adam, maybe he's chair. Yeah, I know it was, uh, it was through the roof. I mean, uh, uh, the, uh, the amount of energy, the, uh, certainly how welcoming everybody was, uh, uh, you know, just, I think the story makes so much sense together. I think culturally, the company is, are very aligned. Um, and, uh, it was a real, uh, real capstone moment, uh, to be able to complete the acquisition and to, and to close and announced, you know, at the kickoff event. And, um, I think, you know, for us, when we really thought about it, you know, when we ended the story, that we was just, you have this opportunity to really cater to what the end-users, you know, care about, which is a lot about interactivity and self-service, and at the same time. And that's, and that's a lot of the goodness that, um, that Ultrix has brought, you know, through, you know, you know, years and years of, of building a very vibrant community of, you know, thousands, hundreds of thousands of users. >>And on the other side, you know, Trifacta bringing in this data engineering focus, that's really about, uh, the governance things that you mentioned and the openness, um, that, that it cares deeply about. And all of a sudden, now you have a chance to put that together into a complete story where the data engineering cloud and analytics, automation, you know, coming together. And, um, and I just think, you know, the lights went on, um, you know, for people instantaneously and, you know, this is a story that, um, that I think the market is really hungry for. And certainly the reception we got from, uh, from the broader team at kickoff was, uh, was a great indication of that. >>Well, I think the story hangs together really well, you know, one of the better ones I've seen in, in this space, um, and, and you guys coming off a really, really strong quarter. So congratulations on that Jensen. We have to leave it there. I really appreciate your time today. Yeah. Take a look at this short video. And when we come back, we're going to dig into the ecosystem and the integration into cloud data warehouses and how leading organizations are creating modern data teams and accelerating their digital businesses. You're watching the cube, your leader in enterprise tech coverage.

[Music] okay we're here with ceres vitale who's the chief product officer at alteryx and adam wilson the ceo of trifacta now of course part of alteryx just closed this quarter gentlemen welcome great to be here okay so rush let me start with you in my opening remarks i talked about alteryx's traditional position serving business analysts and how the hyperanna acquisition brought you deeper into the business user space what does trifacta bring to your portfolio why'd you buy the company yeah thank you thank you for the question um you know we see a we see a massive opportunity of helping brands democratize the use of analytics across their business every knowledge worker every individual in the company should have access to analytics it's no longer optional as they navigate their businesses with that in mind you know we know designer and our the products that alteryx has been selling the past decade or so do a really great job addressing the business analysts with hyper rana now kind of renamed alteryx auto insights we even speak with the business owner the line of business owner who's looking for insights that aren't revealed in traditional dashboards and so on um but we see this opportunity of really helping the data engineering teams and i.t organizations to also make better use of analytics and that's where trifacta comes in for us trifacta has the best data engineering cloud in the planet they have an established track record of working across multiple cloud platforms and helping data engineers um do better data pipelining and work better with this massive kind of cloud transformation that's happening in every business um and so trifecta made so much sense for us yeah thank you for that i mean look you could have built it yourself would have taken you know who knows how long you know but uh so definitely a great time to market move adam i wonder if we could dig into trifacta some more i mean i remember interviewing joe hellerstein in the early days you've talked about this as well on thecube coming at the problem of taking data from raw refined to an experience point of view and joe in the early days talked about flipping the model and starting with data visualization something jeff herr was expert at so maybe explain how we got here we used to have this cumbersome process of etl and you maybe and some others change that model with you know el and then t explain how trifacta really changed the data engineering game yeah that's exactly right uh dave and it's been a really interesting journey for us because i think the original hypothesis coming out of the campus research at berkeley and stanford that really birthed trifacta was you know why is it that the people who know the data best can't do the work you know why is this become the exclusive purview the highly technical and you know can we rethink this and make this a user experience problem powered by machine learning that will take some of the more complicated things that people want to do with data and really help to automate those so so a broader set of users can can really see for themselves and help themselves and and i think that um there was a lot of pent up frustration out there because people have been told for you know for a decade now to be more data driven and then the whole time they're saying well then give me the data you know in the shape that i can use it with the right level of quality and i'm happy to be but don't tell me to be more data driven and they'll don't then and and not empower me um to to get in there and to actually start to work with the data in meaningful ways and so um that was really you know what you know the origin story of the company and i think as as we saw over the course of the last five six seven years that um you know a real uh excitement to embrace this idea of of trying to think about data engineering differently trying to democratize the the etl process and to also leverage all these exciting new uh engines and platforms that are out there that allow for you know processing you know ever more diverse data sets ever larger data sets and new and interesting ways and that's where a lot of the push down or the elt approaches uh you know i think it really won the day um and that and that for us was a hallmark of the solution from the very beginning yeah this is a huge point that you're making this is first of all there's a large business probably about a hundred billion dollar tam uh and and the the point you're making is we look we've contextualized most of our operational systems but the big data pipelines hasn't gotten there but and maybe we could talk about that a little bit because democratizing data is nirvana but it's been historically very difficult you've got a number of companies it's very fragmented and they're all trying to attack their little piece of the problem to achieve an outcome but it's been hard and so what's going to be different about alteryx as you bring these puzzle pieces together how is this going to impact your customers who would like to take that one yeah maybe maybe i'll take a crack at it and adam will add on um you know there hasn't been a single platform [Music] for analytics automation in the enterprise right people have relied on different products to solve kind of smaller problems across this analytics automation data transformation domain and i think uniquely alteryx has that opportunity we've got 7000 plus customers who rely on analytics for data management for analytics for ai and ml for transformations for reporting and visualization for automated insights and so on and so by bringing trifecta we have the opportunity to scale this even further and solve for more use cases expand the scenarios where angles gets applied and serve multiple personas um and now we just talked about the data engineers they are really a growing stakeholder in this transformation of data analytics yeah good maybe we can stay on this for a minute because you're right you bring it together now at least three personas the business analyst the end user size business user and now the data engineer which is really out of an i.t role in a lot of companies and you've used this term the data engineering cloud what is that how is it going to integrate in with or support these other personas and and how's it going to integrate into the broader ecosystem of clouds and cloud data warehouses or any other data stores yeah you know that's great uh you know i think for us we really looked at this and said you know we want to build an open and interactive you know cloud platform for data engineers you know to collaboratively profile pipeline um and prepare data for analysis and and that really meant collaborating with the analysts that were in the line of business and so this is why a big reason why this combination is so magic because ultimately if we can get the data engineers that are creating the data products together with the analysts that are in the line of business that are driving a lot of the decision making and allow for that what i would describe as collaborative curation you know of the data together so that you're starting to see um uh you know increasing returns to scale as this uh as this rolls out i just think that is an incredibly uh powerful combination and frankly something that the market has not cracked the code on yet and so um i think when we when i sat down with surash and with mark and and the team at ultrix that was really part of the the big idea the big vision that that was painted and and got us really energized um about the acquisition and about the the potential of the combination yeah and you're really you're obviously riding the cloud and the cloud native wave um and but specifically we're seeing you know i almost don't even want to call it a data warehouse anyway because when you look at what princeton snowflake is doing of course their marketing is around the data cloud but i i actually think there's real justification for that because it's not like the traditional data warehouse right it's it's simplified get there fast don't necessarily have to go through this central organization to share data uh and and but it's really all about simplification right isn't that really what the democratization comes down to yeah it's simplification and collaboration right i don't want to i want to kind of just uh what what adam said resonates with me deeply um analytics is one of those massive disciplines inside an enterprise that's really had the weakest of tools um and weakest of interfaces to collaborate with and i think truly this was alteryx's end of superpower was helping the analysts get more out of their data get more out of the analytics like imagine a world where these people are collaborating and sharing insights in real time and sharing workflows and getting access to new data sources understanding data models better i think curating those insights i borrowing adam's phrase again i think that creates a real value inside the organization because frankly in scaling analytics and democratizing analytics and data we're still in such early phases of this journey so how should we think about designer cloud which is from alteryx it's really been the on-prem the server or desktop you know offering and of course trifecta is about cloud cloud data warehouses right um how should we think about those two products yeah i think i think you should think about them and as very complementary right designer cloud really shares a lot of dna and heritage with designer desktop the low code tooling and the interface that really appeals to the business analysts and gets a lot of the things that they do well we've also built it with interoperability in mind right so if you started building your workflows in designer desktop you want to share that with designer cloud we want to make it super easy for you to do that and i think over time now we're only a week into this alliance with uh with trifacta i think we have to get deeper and start to think about what does the data engineer really need what business analysts really need and how to design a cloud and try factor really support both of those requirements uh while kind of continue to build on the trifecta on the amazing trifecta cloud platform you know and i think let's go ahead i'm just to say i think that's one of the things that um you know creates a lot of opportunity as we go forward because ultimately you know trifacta took a platform uh first mentality to everything that we built so thinking about openness and extensibility and um and how over time people could build things on top of trifacta that are a variety of analytic tool chain or analytic applications and so when you think about um alteryx now starting to uh to move some of its capabilities or to provide additional capabilities uh in the cloud um you know trifacta becomes uh a a platform that can accelerate you know all of that work and create a cohesive set of of cloud-based services that share a common platform and that maintains independence because both companies um have been uh you know fiercely independent uh in really giving people choice um so making sure that whether you're uh you know picking one cloud platform another whether you're running things on the desktop uh whether you're running in hybrid environments that no matter what your decision you're always in a position to be able to get out your data you're always in a position to be able to cleanse transform shape structure that data and ultimately to deliver uh the analytics that you need and so i think in in that sense um uh you know this this again is another reason why the combination you know fits so well together giving people um the choice um and as they as they think about their analytics strategy and and their platform strategy going forward you know i make a chuckle but one of the reasons i always liked alteryx is because you kind of did did a little end run on i.t i.t can be a blocker sometimes but that created problems right because the organization said wow this big data stuff is taken off but we need security we need governance and and it's interesting because you got you know etl has been complex whereas the visualization tools they really you know really weren't great at governance and security it took some time there so that's not not their heritage you're bringing those worlds together and i'm interested you guys just had your sales kickoff you know what was the reaction like uh maybe suresh you could start off and maybe adam you could bring us home yeah um thanks for asking about our sales kickoff so we met uh for the first time in kind of two years right for as it is for many of us um in person uh um which i think was a was a real breakthrough as alteryx has been on its transformation journey uh we had a try factor to um the the party such as it were um and getting all of our sales teams and product organizations um to meet in person in one location i thought that was very powerful for us as a company but then i tell you um the reception for trifecta was beyond anything i could have imagined uh we were working adam and i were working so hard on on the the deal and the core hypotheses and so on and then you step back and kind of share the vision with the field organization and it blows you away the energy that it creates among our sellers our partners and i'm sure adam and his team were mobbed every single day with questions and opportunities to bring them in but adam maybe you should share yeah no it was uh it was through the roof i mean uh the uh the amount of energy the uh when so certainly how welcoming everybody was uh you know just i think the story makes so much sense together i think culturally the companies are very aligned um and uh it was a real uh real capstone moment uh to be able to complete the acquisition and to and to close and announce you know at the kickoff event and um i think you know for us when we really thought about it you know when we and the story that we told was just you have this opportunity to really cater to what the end users you know care about which is a lot about interactivity and self-service and at the same time and that's and that's a lot of the goodness that um that alteryx is has brought you know through you know you know years and years of of building a very vibrant community of you know thousands hundreds of thousands of users and on the other side you know trifecta bringing in this data engineering focus that's really about uh the governance things that you mentioned and the openness that that it cares deeply about and all of a sudden now you have a chance to put that together into a complete story where the data engineering cloud and analytics automation you know come together and um and i just think you know the lights went on um you know for people instantaneously and you know this is a story that um that i think the market is really hungry for and and certainly the reception we got from from the broader team at kickoff was uh was a great indication of that well i think the story hangs together really well you know one of the better ones i've seen in this space um and and you guys coming off a really really strong quarter so congratulations on that gents we have to leave it there really appreciate your time today yeah take a look at this short video and when we come back we're going to dig into the ecosystem and the integration into cloud data warehouses and how leading organizations are creating modern data teams and accelerating their digital businesses you're watching the cube your leader in enterprise tech coverage [Music]

>>Hello, and welcome to the cubes. Continuous coverage of AWS reinvent 2021. I'm Dave Nicholson, and we're running an incredible event this year. One of the most important technology events. It's a hybrid event with two live stages. Two sets here in Las Vegas. Two studios we've interviewed more than a hundred guests and two distinguished guests that I have here from emphasis today have joined us. Thank you very much. Uh, Mr., who's the executive vice president of Infosys cobalt. And we'll talk about what that is exactly in a moment along with David Wilson, Wilson, I'm sorry, senior vice president and head of global alliances in the partner ecosystem for Infosys gentlemen. Welcome. Thank you. Thank you very much. So let's cut right to the chase cobalt. And when you tell your family that you're executive vice-president of cobalt, do they just smile and immediately nod? Like they know what it is? Absolutely. >>In fact, uh, in fact it is so exciting for us, uh, what we did at Infosys, just to define cobalt in one sentence, it is a set of services, solutions, and products that we are bringing together to solve, you know, accelerate our customer's journey or what we call as the customer's digital journey. So in slough, everybody talking about Kala cloud in a different way, with different narratives, different value proposition we had in forces. And by the way, we were the first ones in the world to combine all of this and the one brand called cobalt. So that's essentially what cobalt is. So anything and everything that we do in cloud, it's all under this brand called cobalt and that's Infosys cobalt. >>So does, does Infosys cobalt include a combination of bespoke solutions, cheering for people as well as packaged standardized things? How do you, how do you strike a balance because you can't have a one size fits all? Uh, what does that look like? How do you segregate those? >>Yes. Great question. So, so essentially what you are done with a cobalt is a delicate cobalt. In two ways. One is there are customers who want a solutions to solve technology problems. It could be getting out of data centers, it could be migrating workloads to cloud. It could be analytics on cloud ERP on cloud daddy's mainframe modernization, and, you know, getting off mainframes. And at the same time, there are industry verticals like financial services, retail manufacturing, and of course, life sciences, and many more who want to understand what are the business solutions and what are the solutions that we have for solving their business problems. So essentially cobalt is a bespoke solutions. It has products, it has platforms, and we have brought all of this together and we take it to our customers. So essentially these are industry blueprints. These are reference architectures. So we have 250 industry blueprints and around 25,000, that's it that we can actually take to our customers to help their digital journey. >>So, David, I imagine that key to the success of cobalt is, uh, uh, the idea of partnerships, talk about the alliances, uh, uh, that, uh, that you're involved with specifically the way that cobalt interacts with the AWS yes. >>Universe. Absolutely. So the, you know, as we designed our cobalt strategy, the partners are a major component of this. They contribute to it. They're part of the design. And ultimately when we go to the clients with these solutions, these assets, uh, our partners, components are baked right into the solution. In the case of AWS, we've been so successful with it that we recognize this week, uh, as their industry solutions partner of the year. Congratulations. Yeah. So I was joking. We should bring our trophy and put it in between, but we emphasis is invested heavily in developing the, the partner ecosystem, you know, gone are the days where our clients are, uh, putting out an RFP and purchasing individual piece parts, and then, you know, searching at NSI. They're looking for a business outcomes and, uh, uh, emphasis along with our cobalt strategy is able to work with partners like AWS and go there and sell an outcome and accelerate the whole. >>Well, you mentioned RFPs. Uh, what is your, uh, what is your go-to market strategy look like in terms of engaging with those end user clients? Um, is it in partnership with AWS? Is it led by Infosys bringing in AWS where appropriate some mix of the two? What does that look like in this world of cooperation and petition that we're in, >>It's actually a mix of two. So essentially the way we go to market is that there are solutions that Infosys has built on AWS that we will take to our customers. There are solutions that you have built, which are cloud neutral, and those are some things that we take to the customers. And the third one, which is very important is co-creating solutions for our customers along with AWS. So our go to market is a combination of all of them, and that's what makes it exciting. >>So a non-test running cobalt, you're, you're responsible for alliances. You guys are probably in contact a lot with one another. All of these crazy new things are announced at AWS. I'm sure you get a little bit of a preview of it. It's not a complete, it's not a complete surprise when you arrive, but you've gotta be screaming for teams and solutions to leverage some of the coolest stuff within cobalt. How does that, how does that conversation go? >>Yeah, so David David and I work very closely, right? In fact, uh, uh, the way, the way we do things is our go to market cannot be complete without partners. So similarly my strategy and our strategy and global cannot be complete without David. So we actually worked together to identify, in fact, we have been visiting a lot of boots. We got to create, we've gone to a lot of great ideas. We want to see how we can bring them into the cobalt framework and bundle some of that as part of our solutions. So we keep looking at those, we'll look at the announcements that were made and we'll solve, you know, identify many more sales motions that we can take to the, >>So David talk about some of the things you've seen here at re-invent this week that are specifically relevant for cobalt and emphasis customer. >>Well, what's some of the most exciting discussions we've been having is with, uh, not only, uh, AWS themselves about the, the announcements and the way in which we can leverage them, leverage them and go to market. But, uh, AWS has built out their own partner ecosystem, uh, that we then interact with. So we've had some exciting conversations with AWS's ISV partners, their, uh, their other solution providers about how we can bring this together and go to market together. You know, when, when an example, we had a lot of discussions this week was about, uh, how we're doing it, right? The mainframe services, uh, that were announced and how we can support them in building out our industry specific assets. So, you know, taking a kernel of what AWS provides and then wrapping our secret sauce around it, in partnership with other companies and then take into our clients, you know, that's what we're, I, it, the good part is we can quickly go from a discussion to a, go to market, a dialogue with our direct clients who are also here, which have been in real-time having those discussions. >>So emphasis a non has been a trusted advisor for clients predating the Dawn of cloud, if you will. Uh, and I'm sure that certain slices of your revenue don't wanna make this too uncomfortable. A question certain slices of your revenue are still dependent upon all of that. 80% of it. That's still on prem. How do you manage that? You're, you're laser focused on cobalt and you've got alliances. Um, everybody's looking towards the cloud. How do you balance that with the very real needs of Infosys as a business? Aren't you in the same boat as your customers, in terms of transformation? >>Well, you know, I, I would, I'm sorry, >>My eyes go back and forth. See, I told you it was gonna be easy for us to have a conversation. Yeah. Jump into >>W when you, when you look at the different partners out there, we have a discussion about being asset heavy asset light emphasis. Um, we, we grew up through application management, uh, and now as we're seeing these transformations go forward, the last thing we wanted to be is a server huggers. Uh, we're ready to accelerate these transformations as fast as possible. And, uh, you know, partners like AWS are recognizing that, uh, a non steam can go in there and be the disruptor to actually accelerate those transformation. >>Absolutely. In fact, involved when we spoke to some of the AWS executives, uh, we want to be the challenger, right? Because we don't carry any baggage. Uh, we clearly believe, as Gartner says that a cloud is going to be the, for business innovation, and we want to drive innovation and transformation for our customers. So essentially we want to make this relationship with AWS much bigger and better. We want to be the partners with our clients to drive business innovation with industry segments, industry clouds, solutions that drive opening, new markets, building better products and solutions, helping get better customer intimacy and those kinds of things. And so that's essentially what our thought processes with, uh, what we want to do. >>It's been mentioned a few times here that, uh, somewhere around 80 to 85% of it spend is still on premises. It's not in the cloud yet. So despite how large, we all think the AWS AWS universe has become so far, we're really just at the beginning stages. But what are you seeing in terms of clients hesitancy towards cloud at this point, has that changed over the last couple of years? Uh, what are the inhibiting factors that you see? What are the accelerants that you see at this stage of the game? >>Well, in fact, in fact, COVID unfortunately Colbert, uh, while it was all a very bad thing, but it actually helped accelerate customer's journey to cloud. Uh, in fact, uh, the, we have several customers who used to say that, you know, everybody has to come to office to work. Nobody can work remotely because there are security constraints that is, there will be impacted the security posture, but to when we hit March, 2020, and everybody had to work remote, it's the same set of customers who decided to go to cloud and started limited him to part of cloud. So I would say COVID in short has accelerated customers knowledge about cloud. They are no longer worried about security. They're no longer worried about, uh, latency and bandwidth. I think I don't see any major hesitancy at this point of time. Uh, but the trend that we're seeing towards cloud is cloud is going to be used more for innovation. And it's not just going to be about, take my data center and moving to cloud, right? So it's not going to be just those tactical reasons. Uh, and that's exactly what we did. We actually came out with a report, which says, moving from cloud chaos to cloud clarity, and it talks about all these facets of what are those strengths that customer should look for. So that's essentially what we use. >>So I imagine cobalt one of the kind of main ideas behind it is to remove friction associated with that move to cloud, to the extent that you can not be reinventing the wheel every single time you're engaging a customer. Is that, is that a fair statement? >>In fact, you know, many customers of ours, in fact, almost all of them are saying, we do not want to reinvent the wheel. So how can you help us? So what we have done as part of cobalt is to bring these reference architectures, right? So for example, if a financial services customer wants to fight fraud, fraud analytics is a reference architecture that we have. Uh, if the telco customer wants to implement 5g, we have a framework and a reference architecture for OSS BSS on cloud. Uh, if there is licenses customer who wants to basically look at drug discovery, we have an architecture for that. So we want to make it more and more in a inference architecture based without reinventing the wheel and bring the best practices from other customers to drive those scenarios. So that's essentially what we do. >>So cobalt underway, you've been recognized for a performance to this point. It's a lot of pressure for 2022. So what are you going to, what do you, what, what, what are you going to slap on the desk in 2022? When we get back together, >>We do plan to up bookends by this time next year, to, to able to pre >>It is perfectly acceptable by the way, to share both the 20, 21 and 2022 award on stage, because we have to make up for 2019 when we weren't here physically. >>But to build off of, with a, knotless saying about the, uh, you know, what's going on in the last 18 to 24 months, you know, we're seeing clients now that we have one that, uh, came to us with a 114 list of products that they bought from various partners, either directly through distributors and such and saying, listen, we no longer want to be in the procurement function. You know, we want to take these hundred and 14 products. We recognize we're going to get it down to 30 or 40 of the key ones, obviously a shifting a lot of that to cloud. And we were able to leverage emphasis cobalt to actually accelerate that and incorporate our partner components to help that shift. So I think next year, I think that will be a major theme that you're seeing clients recognize that the, the way in which they procure and they develop their it platform will be much different. And emphasis with the design we put in place will be in a key position to, to support them at that. Well, >>We recorded this. I'm not sure if you realized we were actually recording this, so we're going to go, we can go back and review this tape next year and we'll see. And I hope to see you then, David, thank you so much for joining us here at the cube and for the cube here in our continuous coverage at AWS reinvent 2021 live in Las Vegas. I'm Dave Nicholson saying stay tuned because there's always more on the cube. And I'd like to remind you that we are your leader in hybrid tech event coverage.

>>Fly from San Francisco. It's the cube covering RSA conference, 2020 San Francisco brought to you by Silicon angle media. >>Welcome to the cubes coverage here in Moscone in San Francisco for RSA copper's 2020. I'm John hosted the cube and you know, cyber security is the hottest thing. Transforming businesses and you know, old. It has to transform into not only playing defense but playing off fence and understand the threats, how to organize around it. And that's really been a big part of this new next generation architecture operations and just mindset. We've got a great guest here to share his perspective. Luke Wilson, who's the vice president, intelligence for four IQ hot startup but also former FBI counter terrorism of right other DOD state department. Uh, tons of experience on both sides. Now on the commercial side. Luke, thanks for coming on. Thanks for having me. So obviously your background gives you a unique perspective and you know, I've been in uh, in the commercial side, I haven't done any government service like you have, but I can tell you it in the enterprise it's been boring. >>Oh yeah. He has storage, provisioning, storage, business servers, cloud comes in, it gets exciting. Yeah. Startups are doing cloud native lot more robust scale and you starting to see the new applications with that, the security perimeter is gone. It's now a huge surface area. So the enterprise has to get more FBI like or more smarter around how they organize, how they hire. Yeah. This is your, this is your world. Yes, it is. What's your take on this? What's it, what's your view of the industry right now? Well, I think right now what you're seeing is this change from, uh, you know, I hate to be cliche about it, but for years we've been playing whack-a-mole against the bad guys. I've see Matt, you know, uh, at my time at the FBI and various government, different agencies there, um, we're starting to see a shift of alright, we want, they want to know, okay, how is this happening to them? >>So it's just not the, the, what's happened. It's like who's behind it. And you know, in today's, in today's, uh, arena with the, you know, with cyber security, you have to start figuring out what entity is behind these attacks, uh, what they're going after. So you can start protecting that, but then also using that information, that intelligence from there, sharing it with other business sectors and then also turn in that big backend side so you can have some kind of preventive maintenance as well. I mean, you've got a lot going on. There used to be a nice little neat little industry in a box security by some software. You've got the servers, you have firewalls, all that nice stuff. Now you're talking about elaboration. Operating models are changing. A whole new dimension and open source has given a, an ability to cloak, whether it's nation States can now be operating under stealth mode. >>Oh yeah. You have all kinds of new dynamics. What is, what does the company do? You know, how do people solve this? There, there is no one answer or that, you know, it's got, it's gonna take a community, uh, the community of protectors and, uh, groups that want to help solve these issues. Uh, you know, and law enforcement, we always say, you know, it's a, it's a cat and mouse game. We catch up to them and then they change a little, you know, maybe a little bit here and there and then we catch up to him again and, uh, we're just gonna keep playing that game. But you know, uh, businesses, commercial businesses are starting to get into that, into that mode as well of, Hey, just because I defeated something today doesn't mean it's going to be right back at my door tomorrow. You know, you and I saw each other last night at the general Alexander's, uh, talk, uh, and he's always been all about offense, defense and understanding visibility and signals. >>Um, you know, there's a lot to do there. Um, you got to know where things are coming from. There's a lot of shared responsibility, but shared work, right? It's like, yes, we want, there's a lot of redundancy going on in security now. Oh yeah. And within and without pumping. So the collaboration, you mentioned the big part, how do you see that evolving that you work with the FBI counterterrorism, you kind of see how this kind of thinking renders itself. How does that work in a commercial world? How do you see that evolving? Well, you have certain cyber centers that are built for that kind of model, uh, for, uh, helping, you know, commercial, uh, industries, uh, deal with that threat. You know, there's no, uh, one tool, one company that can protect itself from a nation state attack. Uh, we've seen that, you know, so, uh, the best thing that's happening right now is people are starting to understand in order to get the entire, um, I would say the topology of the attack, that's that that's affecting you. >>You're going to have to share this information. You're going to have to learn from other groups. Uh, law enforcement, intelligence agencies are sharing. Um, and, you know, it's quite frankly, it's, it's, we're kind of late in the game of sharing, which the criminals have been doing this now for years, you know, sharing that information and understanding who to attack them, when to attack. Yeah. And they've been been winning. So I gotta ask you, as someone who's been in the industry now, and I'm book both sides, you look at RSA this year, um, besides the headline of the coronavirus who's got a backdrop to all of this, there's still a huge show here and, and the trends are changing. It seems to be the scene game, whack a mole on steroids, but now you've got cloud. What's new out there that, that's getting you excited? What do you think people should be paying attention to? >>Why? I think what people should be paying attention to is now a lot of the, I would say the products and the tools that are coming out are actually being developed by people who are practitioners have been in that space and understand what it takes in order to defeat, uh, the, the types of criminals that you're facing every day. Um, you know, I, I see a lot of products, uh, getting into the, the hoop, you know, and for me, I think that's a very, uh, a very strong point now that you can't just keep saying, I closed this court and that court in this sport and we're good. No, they're just gonna change little thing and come right back in. Um, so I see a lot of tools or act or identification or identification time attribution, um, people are trying to get to the who in this space now in order to turn that back around for prevention as well. >>So something where normally this is, you know, an FBI, uh, uh, you know, a federal government, uh, uh, agency trying to figure out the who, a lot of the tools and, and some of the, uh, you know, the data today is helping out with that for private industry. So that are great point gradient site by the way. I love that. I love that angle on that. What about meal time? Because now real time is a big one and people are overworked. It's a pile of threat detection out there. Like, Hey, there's some stuff happening in another company. So people are buying feeds. I get it right now. You need a data processing perspective. You've got to get the data. How does that, how do you see that whole challenge become an opportunity? Well, you know, uh, we're a data driven society now, right? So everything has data connected to it. >>Um, you know, and, and you're getting that amount of data stream float into your commercial entity. You know, first of all, it needs to be automated. You're going to have, you know, a lot, a lot of data to sift and sort through to understand what's actually happening here. So I think the, the, you know, that that live feed going real time is very helpful, but also content, uh, you know, put some context context behind that and having and having that, that information fully digested so you can understand what's the threat, how's it coming at you. And then using that for prevention. Super exciting time. I want to get into your experience and how that translates into maybe your advice for people that are kinda kind of waking up from lack of multiple, kind of being more of a kind of a versatile athlete, if you will, athletes, cyber athletes. >>Um, but I gotta ask you about, um, the idea of threats that are coming in that you seen in the FBI that enterprises should be paying attention. Because I'll give you an example. I'll say, Luke, I'm good. My it department covering this for years. I don't really have anything that's valuable, right? So I'm good. I got my patches done, so I don't really need to buy anything from you or I'm good, right? Not everyone's saying that, but that can be the mentality at different spectrum of, all right, so what do, what do you say to that? Well, you know, besides, I'm an idiot, you know, we see that a lot and I think, um, you have to, that, that's a very big naive approach about it. Um, you know, you also have to start thinking about, are you good with your insider threat? Are you good with your third party risks, you know, threats. >>Um, so there's so many things going down the line. When you look at what it takes for, let's say a large financial institution to run, would it take for a large, uh, company like an Uber or Lyft to run? Um, you know, there's, there's threats there and if you're saying you don't have any threats and you're, you're, you're OK, then uh, you know, I would say that's a, that's another, it's being polite, being polite. What you're saying is, no, you're not. Okay. Well, I mean, cause if, think about it, if you're just running a main small little manufacturing operation, I don't have any IP, but your operations is your IP. You might be exposed for ransomware or some, you know what I'm saying? There's always disruption. This has been kind of an interesting, there's a mindset. It's not just what you think you have. There's a holistic view. >>What's your take on the reaction to that? Yeah. It isn't the holistic view. You have to take that approach. You've seen what's happening nowadays, especially within the ransomware. Uh, you know, it's, it may come from a third party that basically didn't secure their systems, but they knew exactly what they went with, the cyber criminal, exactly what they were doing because they solely wanted to attack you and they knew the weakest link was three steps down from you. And so that's exactly where they went to. You know, I love these conversations and not, you know, a lot. I'm a Patriot and I love to help our country. I do my best. I don't really serve in the government, but one of the things I feel strongly about and people know I rant about this all the time when I'm on the cube is that digital war is happening and I really believe that, you know, our, we're a free society. >>You can't lock every door in this country. You've got borders, physical borders, so digital borders or if we're open society, you can't really be defensive all the time. Yeah. So if someone does strike us, our answers especially been counter strike back with a vengeance. Exactly. Which is how the deterrent is. But digitally, where's that line? I mean if you drop chips in Manhattan, you know you're, we're a tapping attack. What's the digital drawing in your opinion? Because this is something that Noah's talking about, but it's kind of paper cuts is that there's a line of knowing is are we being attacked? It's the who. What's your view on this? I know it's a new emerging area. Yeah. Aye. Aye. Aye. I seem to I think a little bit on both sides here. I want to do something back, but I don't think I'm most special, especially commercial businesses. >>Understand what that means. Actually find some attribution and then say, you know, it is this entity or this country that's doing that and it's kind of a slippery slope when you start getting out of that cutting edge societal issue. Because I mean the government has a military to protect me, right? But if I'm a cyber company, I going to build my own military digital military. Now what are we talking about here? I mean, it's interesting. It's, it's again, that's why I start seeing a lot. If you look at the place, you know around here you start looking at some of these tools, they are offensive weapons. When you look at them, these are weapons to understand, well not weapons, but tools to understand who and you already know what happened. And so now you get the who and the why, right? Yeah. You can't really strike back. >>But what you could do is turn that back inward and say, okay, I'm going to start preventing this stuff. Yeah. Right. But then also, Hey, I can go to the, you know, the FBI and say, here's a nice neat packet of information on what happened to me and who we believe it to be. And that's where that conversation starts to happen. And I'm really excited by the digital twin and the simulation environments where you can start having flex, you can flex scenarios to do, use some of this scenario based planning so you can protect and plan for scenarios which is reacting to it. Yeah. Yeah. The digital training space, when he got there, you know, and it just like you stated earlier, right? You know, the, the, the United States military goes out here and trains for certain scenarios all the time. Companies have to start doing that because that's what's happening to them. >>You know, they're, you're right on the money. I love the insight. Thanks for sharing. Greetings. I love that you got to get the reps and you got to do the operations. You got to nail that. So just give a quick plug before IQ. Thanks for sharing your awesome insight. What do you guys do and what are you guys all about? What's your value proposition? Great. Yeah, we're, we're identity intelligence company. Oh, what that means is that we have tools and products that's going to allow our clients get to that who, you know, uh, and we also have tools that allow them to get to the what as well. So we're on both sides of a, of the fence there. Um, we're trying to get left of boom, what they call it. Um, but our data and our intelligence allows us clients to find the bad guy. >>A very simple, we have some AI and machine learning built into there where it's almost like a click of a button, I can expand and figure out who these individuals are and understand their TTPs. And what we want to do is make automation of these different types of tools easier and faster for the clients to use. So you want to bring intelligence into their visibility space or data space or, yes, I actionable intelligence. Yeah. So basically in their, into their digital space of understanding, you know, their attack surface, understanding what problems that they're having. And then we have, um, you know, like I said, a lot of tools and, and, and, and, and, um, it's, I would call it tell who calls you out, who's the customer, who's the buyer, the IOC show? Is it, uh, uh, off-gas? What's the, who's buying your stuff? So mainly what we're into a lot of, um, cyber fraud, fusion centers, just like that. >>Law enforcement intelligence agencies. Um, I would say, you know, I, I know for a fact that I wouldn't use this, you know, if I had this tool and the FBI. Um, and, and, and a lot of, you know, if you have a large digital footprint, uh, we have cryptocurrency companies using this as well. Um, you know, you're, you're seeing some, some, some pretty bad guys attacking your systems, trying to defraud you. Our product helps you out with that. Right. Luke, great conversation. Thanks for coming on. Appreciate RSA coverage. Taking the show. What's the hot thing at the show? What's your favorite moment here? What's, what's the big story here at RSA? I w I would say, uh, for me it's this, uh, sit in the one, uh, Ashton Martin sit now, you know, every year there's something different. You know, I go to these Bitcoin conferences and I see they usually have Lamborghinis out for it. And now I think this is happening. So yeah, I don't know if we're trending in that direction now. Get in that car and we're gonna erase away. Great. Luke Wilson, VP of intelligence before I Q a here inside the cube, the cube coverage show our say I'm John furrier. Thanks for watching.

(techno music) >> From Cambridge, Massachusetts, it's theCUBE. Covering MIT Chief Data Officer and Information Quality Symposium 2019. Brought to you by SiliconANGLE Media. >> Welcome back to Cambridge, Massachusetts everybody, we're here with theCUBE at the MIT Chief Data Officer Information Quality Conference. I'm Dave Vellante with my co-host Paul Gillin. Susan Wilson is here, she's the vice president of data governance and she's the leader at Informatica. Blake Anders is the corporate vice president of data governance at New York Life. Folks, welcome to theCUBE, thanks for coming on. >> Thank you. >> Thank you. >> So, Susan, interesting title; VP, data governance leader, Informatica. So, what are you leading at Informatica? >> We're helping our customers realize their business outcomes and objectives. Prior to joining Informatica about 7 years ago, I was actually a customer myself, and so often times I'm working with our customers to understand where they are, where they going, and how to best help them; because we recognize data governance is more than just a tool, it's a capability that represents people, the processes, the culture, as well as the technology. >> Yeah so you've walked the walk, and you can empathize with what your customers are going through. And Blake, your role, as the corporate VP, but more specifically the data governance lead. >> Right, so I lead the data governance capabilities and execution group at New York Life. We're focused on providing skills and tools that enable government's activities across the enterprise at the company. >> How long has that function been in place? >> We've been in place for about two and half years now. >> So, I don't know if you guys heard Mark Ramsey this morning, the key-note, but basically he said, okay, we started with enterprise data warehouse, we went to master data management, then we kind of did this top-down enterprise data model; that all failed. So we said, all right, let's pump the governance. Here you go guys, you fix our corporate data problem. Now, right tool for the right job but, and so, we were sort of joking, did data governance fail? No, you always have to have data governance. It's like brushing your teeth. But so, like I said, I don't know if you heard that, but what are your thoughts on that sort of evolution that he described? As sort of, failures of things like EDW to live up to expectations and then, okay guys over to you. Is that a common theme? >> It is a common theme, and what we're finding with many of our customers is that they had tried many of the, if you will, the methodologies around data governance, right? Around policies and structures. And we describe this as the Data 1.0 journey, which was more application-centric reporting to Data 2.0 to data warehousing. And a lot of the failed attempts, if you will, at centralizing, if you will, all of your data, to now Data 3.0, where we look at the explosion of data, the volumes of data, the number of data consumers, the expectations of the chief data officer to solve business outcomes; crushing under the scale of, I can't fit all of this into a centralized data at repository, I need something that will help me scale and to become more agile. And so, that message does resonate with us, but we're not saying data warehouses don't exist. They absolutely do for trusted data sources, but the ability to be agile and to address many of your organizations needs and to be able to service multiple consumers is top-of-mind for many of our customers. >> And the mind set from 1.0 to 2.0 to 3.0 has changed. From, you know, data as a liability, to now data as this massive asset. It's sort of-- >> Value, yeah. >> Yeah, and the pendulum is swung. It's almost like a see-saw. Where, and I'm not sure it's ever going to flip back, but it is to a certain extent; people are starting to realize, wow, we have to be careful about what we do with our data. But still, it's go, go, go. But, what's the experience at New York Life? I mean, you know. A company that's been around for a long time, conservative, wants to make sure risk averse, obviously. >> Right. >> But at the same time, you want to keep moving as the market moves. >> Right, and we look at data governance as really an enabler and a value-add activity. We're not a governance practice for the sake of governance. We're not there to create a lot of policies and restrictions. We're there to add value and to enable innovation in our business and really drive that execution, that efficiency. >> So how do you do that? Square that circle for me, because a lot of people think, when people think security and governance and compliance they think, oh, that stifles innovation. How do you make governance an engine of innovation? >> You provide transparency around your data. So, it's transparency around, what does the data mean? What data assets do we have? Where can I find that? Where are my most trusted sources of data? What does the quality of that data look like? So all those things together really enable your data consumers to take that information and create new value for the company. So it's really about enabling your value creators throughout the organization. >> So data is an ingredient. I can tell you where it is, I can give you some kind of rating as to the quality of that data and it's usefulness. And then you can take it and do what you need to do with it in your specific line of business. >> That's right. >> Now you said you've been at this two and half years, so what stages have you gone through since you first began the data governance initiative. >> Sure, so our first year, year and half was really focused on building the foundations, establishing the playbook for data governance and building our processes and understanding how data governance needed to be implemented to fit New York Life in the culture of the company. The last twelve months or so has really been focused on operationalizing governance. So we've got the foundations in place, now it's about implementing tools to further augment those capabilities and help assist our data stewards and give them a better skill set and a better tool set to do their jobs. >> Are you, sort of, crowdsourcing the process? I mean, you have a defined set of people who are responsible for governance, or is everyone taking a role? >> So, it is a two-pronged approach, we do have dedicated data stewards. There's approximately 15 across various lines of business throughout the company. But, we are building towards a data democratization aspect. So, we want people to be self-sufficient in finding the data that they need and understanding the data. And then, when they have questions, relying on our stewards as a network of subject matter experts who also have some authorizations to make changes and adapt the data as needed. >> Susan, one of the challenges that we see is that the chief data officers often times are not involved in some of these skunkworks AI projects. They're sort of either hidden, maybe not even hidden, but they're in the line of business, they're moving. You know, there's a mentality of move fast and break things. The challenge with AI is, if you start operationalizing AI and you're breaking things without data quality, without data governance, you can really affect lives. We've seen it. In one of these unintended consequences. I mean, Facebook is the obvious example and there are many, many others. But, are you seeing that? How are you seeing organizations dealing with that problem? >> As Blake was mentioning often times what it is about, you've got to start with transparency, and you got to start with collaborating across your lines of businesses, including the data scientists, and including in terms of what they are doing. And actually provide that level of transparency, provide a level of collaboration. And a lot of that is through the use of our technology enablers to basically go out and find where the data is and what people are using and to be able to provide a mechanism for them to collaborate in terms of, hey, how do I get access to that? I didn't realize you were the SME for that particular component. And then also, did you realize that there is a policy associated to the data that you're managing and it can't be shared externally or with certain consumer data sets. So, the objective really is around how to create a platform to ensure that any one in your organization, whether I'm in the line of business, that I don't have a technical background, or someone who does have a technical background, they can come and access and understand that information and connect with their peers. >> So you're helping them to discover the data. What do you do at that stage? >> What we do at that stage is, creating insights for anyone in the organization to understand it from an impact analysis perspective. So, for example, if I'm going to make changes, to as well as discovery. Where exactly is my information? And so we have-- >> Right. How do you help your customers discover that data? >> Through machine learning and artificial intelligence capabilities of our, specifically, our data catalog, that allows us to do that. So we use such things like similarity based matching which help us to identify. It doesn't have to be named, in miscellaneous text one, it could be named in that particular column name. But, in our ability to scan and discover we can identify in that column what is potentially social security number. It might have resided over years of having this data, but you may not realize that it's still stored there. Our ability to identify that and report that out to the data stewards as well as the data analysts, as well as to the privacy individuals is critical. So, with that being said, then they can actually identify the appropriate policies that need to be adhered to, alongside with it in terms of quality, in terms of, is there something that we need to archive. So that's where we're helping our customers in that aspect. >> So you can infer from the data, the meta data, and then, with a fair degree of accuracy, categorize it and automate that. >> Exactly. We've got a customer that actually ran this and they said that, you know, we took three people, three months to actually physically tag where all this information existed across something like 7,000 critical data elements. And, basically, after the set up and the scanning procedures, within seconds we were able to get within 90% precision. Because, again, we've dealt a lot with meta data. It's core to our artificial intelligence and machine learning. And it's core to how we built out our platforms to share that meta data, to do something with that meta data. It's not just about sharing the glossary and the definition information. We also want to automate and reduce the manual burden. Because we recognize with that scale, manual documentation, manual cataloging and tagging just, >> It doesn't work. >> It doesn't work. It doesn't scale. >> Humans are bad at it. >> They're horrible at it. >> So I presume you have a chief data officer at New York Life, is that correct? >> We have a chief data and analytics officer, yes. >> Okay, and you work within that group? >> Yes, that is correct. >> Do you report it to that? >> Yes, so-- >> And that individual, yeah, describe the organization. >> So that sits in our lines of business. Originally, our data governance office sat in technology. And then, our early 2018 we actually re-orged into the business under the chief data and analytics officer when that role was formed. So we sit under that group along with a data solutions and governance team that includes several of our data stewards and also some others, some data engineer-type roles. And then, our center for data science and analytics as well that contains a lot of our data science teams in that type of work. >> So in thinking about some of these, I was describing to Susan, as these skunkworks projects, is the data team, the chief data officer's team involved in those projects or is it sort of a, go run water through the pipes, get an MVP and then you guys come in. How does that all work? >> We're working to try to centralize that function as much as we can, because we do believe there's value in the left hand knowing what the right hand is doing in those types of things. So we're trying to build those communications channels and build that network of data consumers across the organization. >> It's hard right? >> It is. >> Because the line of business wants to move fast, and you're saying, hey, we can help. And they think you're going to slow them down, but in fact, you got to make the case and show the success because you're actually not going to slow them down to terms of the ultimate outcome. I think that's the case that you're trying to make, right? >> And that's one of the things that we try to really focus on and I think that's one of the advantages to us being embedded in the business under the CDAO role, is that we can then say our objectives are your objectives. We are here to add value and to align with what you're working on. We're not trying to slow you down or hinder you, we're really trying to bring more to the table and augment what you're already trying to achieve. >> Sometimes getting that organization right means everything, as we've seen. >> Absolutely. >> That's right. >> How are you applying governance discipline to unstructured data? >> That's actually something that's a little bit further down our road map, but one of the things that we have started doing is looking at our taxonomy's for structured data and aligning those with the taxonomy's that we're using to classify unstructured data. So, that's something we're in the early stages with, so that when we get to that process of looking at more of our unstructured content, we can, we already have a good feel for there's alignment between the way that we think about and organize those concepts. >> Have you identified automation tools that can help to bring structure to that unstructured data? >> Yes, we have. And there are several tools out there that we're continuing to investigate and look at. But, that's one of the key things that we're trying to achieve through this process is bringing structure to unstructured content. >> So, the conference. First year at the conference. >> Yes. >> Kind of key take aways, things that interesting to you, learnings? >> Oh, yes, well the number of CDO's that are here and what's top of mind for them. I mean, it ranges from, how do I stand up my operating model? We just had a session just about 30 minutes ago. A lot of questions around, how do I set up my organization structure? How do I stand up my operating model so that I could be flexible? To, right, the data scientists, to the folks that are more traditional in structured and trusted data. So, still these things are top-of-mind and because they're recognizing the market is also changing too. And the growing amount of expectations, not only solving business outcomes, but also regulatory compliance, privacy is also top-of-mind for a lot of customers. In terms of, how would I get started? And what's the appropriate structure and mechanism for doing so? So we're getting a lot of those types of questions as well. So, the good thing is many of us have had years of experience in this phase and the convergence of us being able to support our customers, not only in our principles around how we implement the framework, but also the technology is really coming together very nicely. >> Anything you'd add, Blake? >> I think it's really impressive to see the level of engagement with thought leaders and decision makers in the data space. You know, as Susan mentioned, we just got out of our session and really, by the end of it, it turned into more of an open discussion. There was just this kind of back and forth between the participants. And so it's really engaging to see that level of passion from such a distinguished group of individuals who are all kind of here to share thoughts and ideas. >> Well anytime you come to a conference, it's sort of any open forum like this, you learn a lot. When you're at MIT, it's like super-charged. With the big brains. >> Exactly, you feel it when you come on the campus. >> You feel smarter when you walk out of here. >> Exactly, I know. >> Well, guys, thanks so much for coming to theCUBE. It was great to have you. >> Thank you for having us. We appreciate it, thank you. >> You're welcome. All right, keep it right there everybody. Paul and I will be back with our next guest. You're watching theCUBE from MIT in Cambridge. We'll be right back. (techno music)

>> Live from Las Vegas It's theCUBE covering the AWS Accenture Executive Summit. Brought to you by Accenture. >> Welcome back everyone to theCUBE's live coverage of the AWS Executive Summit here at the Venetian in Las Vegas. I'm your host, Rebecca Knight. We have two guests for this segment. We have Mike Moore, Senior Principal at Accenture Research, and Andrew Wilson, Chief Information Officer at Accenture. Thank you both so much for returning to theCUBE. >> Good to see you as ever, Rebecca, and to be back in Las Vegas as well. >> Exactly, back in Sin City, right, here we are. So our topic is innovation. A buzzword that is so buzzy it's almost boring. Let's start the conversation with just defining innovation. What does innovation mean? >> An objective, a behavior, a way of working. To me, innovation is what we need to do with modern technology to enable the enterprise and the business world and be creative humans and to use disciplines which we didn't typically bring to work before. >> And is it creativity, or is there sort of logic and rationale too? >> I think there's logic and rationale. But there's also entertainment, fun, modern consumer-like experimentation, risk-taking, things of that nature. >> I think that a big key is actually striking a balance between creativity and logic and rationale and that's the really tricky bit, because you need to give your employees the license to be creative but within a certain set of boundaries as well. >> The rules of work have definitely changed, and behaviors that we encourage, even the clothes we wear, how we work, when we work, those are all characteristic of a more innovative, accepting diverse world, and a world that can keep up with the modern technology and the advancements and the announcements like we're hearing about here at re:Invent. >> It's the ultimate right brain, left brain behavior and activity. So Mike, you've done some research recently about the hallmarks of innovative companies, what they do differently from the ones that are not innovative, that are failing here, so tell our viewers a little bit about what you've found in your research. >> We surveyed 840 executives from a variety of different companies, different industries, different geographies, to understand their approach to innovation, and those who were doing it particularly well, and those maybe not so well. And around about 14 percent of our respondents were turning their investments in innovation into accelerated growth, and there were lots of different reasons for their success but three things really stood out. So first of all their outcome lacked in terms of the way they approach innovation, so they put a clear set of processes around their innovation activities, and then linked those to operational and financial performance metrics. They're also disruption minded, so they're not just pursuing incremental tweaks to their products and services, but their investing in disruptive technologies that could actually create entirely new markets. And then finally they're change orientated. They're not just using innovation to change their products and services, but also to fundamentally change the nature of their own organizations as a whole. >> So 14 percent are knocking it out of the park. Does that mean the rest of them are all laggards or are sort of some in the middle? What is the state of innovation in industry today, would you say, Andrew? >> I would say it's hugely variable by industry, geography, type of company, and individual instance of leader and culture, but I am sure that the most successful companies, those that are pivoting to the new, those that are imaginative, those that have recently arrived, all have that DNA that we're describing, all have that way of working, all have that ability to operate cleverly, intelligently, humorously, and at speed. I think innovation is very much characterized by something that can be fast-failed, do, step, move sideways, do again. The way of working has changed in modern enterprises. We as CIO's have to accept that. We have to speed up. We have to create the environment in where that productivity, where that creation can occur, and I think all of that's key. >> You keep mentioning this, the way of working has changed, and I think we all sort of know what you mean but explain a little bit what you're seeing. >> Experimentation, the ability to get more done with the resources that you have. So here we are at AWS re:Invent, cloud-based operations. Cloud gives you, gives me as a CIO the means to do more, more quickly, more rapidly, on a greater scale, in more places that I ever could have imagined in my old old-fashioned data senses. So the services we can consume, the data we can connect together, the artificial intelligence we can bring to it, the consumer-like experience. All of those things, which by the way, are drawing on innovative behaviors in their own right, are absolutely what the game is about now. >> How does AWS figure into your cloud transformation? >> Well for our cloud transformation at Accenture, AWS is one of the core cloud platform providers who power Accenture. We are nearly 95 percent in cloud. So as an organization that's very pronounced, and typically ahead of most organizations. But we sort of have to be, don't we? I mean, we have to be our own North Star. I can't sit here and explain the virtues of what Accenture can bring to a client's cloud transformation if we haven't already done it to ourselves. And by the way, that drew on innovative approaches, risk-taking approaches because over the last three years we've moved Accenture to the cloud. >> So I love how you said it, we are our own North Star, and other people would say we eat our own dog food, I mean that's just kind of more gross, but in terms of having experienced this transformation yourselves, how do you use what you've learned to help your companies transform as well? And make these moves, take these risks, what would you say to that? >> Well I think we keep an eye on the research with our colleagues there, they're our own North Star. I think we look at the ecosystem, we assess readiness for enterprise, security compliance, scale, availability, and then we also look and say, and what's ready for prime time in terms of Accenture scale, half a million people nearly. You bring all of those things together and it's a recipe, and that's why we consult our business, that's why we guide and educate and experiment and innovate together. And that's very much how we adopted cloud, it's very much how we do a number of other things, and the creative services we have. >> In terms of, let's get back to the research. So how do you, I mean as you said, the research is, as Andrew said, it's something that executive leaders are looking at to figure out what's actually happening in the market as well as what's happening within the organization itself. So how do you set your research agenda in terms of figuring out where you want to focus your time and energy and resources. >> Well I think we do it in a very similar way to in which we consult with clients, we speak to them. We talk to them about some of the key issues that they're facing and we always interview a series of executives and also academics to get their perspective at the start of their project. And that's something that we did in this particular instance and what we heard from many executives was that, to the point that Andrew was making before, the speed and scale of innovation today is happening at a completely different pace than in the past. So product cycle times are just diminishing in every single industry and as a consequence, executives now need to build new innovation units to make sure that they can respond to that changing market. So that's we wanted to explore through the research. >> So in this research, with the 14 percent doing it well, the 86 percent sort of either, somewhere on the spectrum of doing terribly or figuring things out, getting better, what are their pain points, and what's your advice to those companies? >> Well I think, and we take the positive spin on it in terms of what the companies are doing well, one of the points that Andrew was making before was how Accenture works with other partners to become more innovative itself. And that's something that we saw many of the high performing companies doing. So many of them were what we call networks powers. Not just innovating using their own resources, their own people, but their drawing on a broader ecosystem of partners to bring the very best products and services to their customers, and their spending not just on R and D internally but also on accelerators, incubators, technology based M and A, and actually their spending as much on inorganic innovation as they are on organic innovation. >> At Accenture we actually help our clients look for trap value, and what we mean by that is if an organization with a history, with a set of business processes, a set of technologies, and a set of disciplines and employees that have been successful and worked possibly for decades in that model, then they're going to be in some pretty tight guide rails. How do you innovate out of that, to deal with all of the destruction that's now available, good healthy disruption, that actually reveals the next level of efficiency, customer satisfaction, product creativity, and innovation in it's own right, so that's innovation in action, if you like. >> I want to ask, here we are at AWS re:Invent, Andy Jassy on the main stage this morning announcing a dizzying number of new products, services, and AWS, this is Amazon, this is a huge company that really seems to know how to innovate, and do it constantly, but is that is that, can every company be Amazon? You know what I'm saying? I mean, is this really possible and attainable? >> Is such a thing as innovation fatigue perhaps? >> Well, exactly, right! >> My view is that you have to find a way to make innovation a constant and a norm. It doesn't mean that you always will have to operate with the same ridiculous pace, but creativity and pace do go hand in hand to a point, but to be ahead, to stay ahead, and to lead an organization of technologists, who can comprehend all of these announcements, so you have to innovate in both how you lead and operate as well. It's not just your product, it's your behaviors, because there's just so much coming all the time. >> Right, and we've seen a number of large companies, not necessarily technology companies, but I'm thinking of Sears and Toys-R-Us, that have really, you've seen what can happen, the cautionary tales. >> Look at the attrition in the Fortune 500, and you can see how companies have a, a half life now, which perhaps is very different to 20 or 30 years ago. >> Right, right, exactly. Well, Mike and Andrew, thank you so much for coming on theCUBE. This was a really fascinating discussion. >> Thanks. >> Thank you, good to see you again. >> I'm Rebecca Knight, stay tuned for more of theCUBE's live coverage of the AWS Executive Summit. (techno music)

>> Narrator: Live from Las Vegas, it's the CUBE covering Service Now Knowledge 2018. Brought to you by Service Now. >> Welcome back to Service Now Knowledge 18 this is the CUBE's live coverage. We are the leader in live technology coverage. We extract the signal from the noise. I'm Rebecca Knight your host along with my cohost Dave Vellante. We've got a great panel right now. We have Andrew Wilson who is the CIO of Accenture and Ellen Shook who is the chief leadership in human resources officer at Accenture. Thanks so much for coming on the show. >> Thanks for having us. >> Hello great to be back. >> Good to see you again. >> Before the cameras were rolling we were talking about people driven change. But Accenture not but, and Accenture is a huge organization. 400,000 plus individuals working around the world. How do you drive change in such a large and dispersed organization? >> Well I think the most important thing is that change isn't human driven but humans need to be at the center of all change and I think that's why Andrew and I show up in a lot of places together. Because we do use technology to elevate the human experience at Accenture. And the more digital an organization becomes the more important human connection is and that's what we do is create truly compelling experiences for our people. >> Because we don't have separate agendas at Accenture. The relationship that Ellen and I have I think is one of the most important in our enterprise. Where we're driving digital transformation for our clients and within our own business and it's equal parts technology, talent, and change. And so you have to bring those things together and so what we're doing at Knowledge is talking a lot about the outcomes that we drive. Where we're in an experience rich culture our people, our employees, our citizens, our customers. They demand an experience which is very different to how the old IT posture had to deliver. So if we get the partnership right we create a culture and an environment that they'll have fun in and enjoy and not just have to turn up at work for. >> So Ellen what's the outcome that you're trying to achieve? Let's work backwards from there when you think about your human experience? >> Well really what we're trying to do is create an environment where our people can be successful both professionally and personally. Because you, we really require huge diversity at Accenture because in order to bring innovative solutions to our clients we truly need very broad diversity and in order to discover and inspire diverse base of talent. We need to create world class experiences that really unlock their full potential. >> We're all human beings after all. But human beings whether or not we're delivering services or whether we're consuming them. So under Ellen's leadership we talk about truly human and I think that's really important because we must reflect and understand the community we serve. So if we don't have the diversity, if we don't have the gender mix. If we're not looking like the humans who we need to look after then there's going to be a barrier and I think that's at the heart of a lot of modern transformation. >> Now hang on. I heard you say today you have a lot of nn human workers. >> I do, I do. >> So they're not all humans. Who are they, are they robots? >> Well the future of work and the future workforce is a combination of human and machine. Because you need both and you need both working in a way that compliments each other. So we're often asked does the machine replace the human. No it doesn't it changes the content of the work and frees the human to do more interesting work and we need both in a modern agenda. >> And quite simply we do have a very strong belief that technology elevates humans and does not eliminate humans. >> And I'm an optimist too but when I go to the airport I see kiosks, more kiosks than humans. When I drive down the highway out of Heathrow I see all the billboards and they're neon now or electronic so clearly machines have always replaced humans in jobs and clearly as humans we've always overcome. So I'm an optimist too but it seems different this time around because, it cognitive functions and it seems like a whole new set of skills. You guys are experts at this. What are your thoughts? >> I think we are building a set of skills is the new that's absolutely essential for the modern enterprise. So when you drive down the road from Heathrow you don't see the data scientists, you don't see the design thinkers. You don't see the humans that are listening to and talking with their customers and surfacing insights. We think about applying intelligence in the enterprise. Now the humans wouldn't have time to do that if they had to deal with all the old transactions. Free them up from that and then they can do all of this interesting work and that's the future of work. >> One of the things you were talking about on the main stage Andrew was about the changing role of the CIO and you said I actually think of myself as a chief experience officer. Can you refine that a little bit? >> Well I think Ellen and I both care about the experience of all of our employees, all of our humans, all of our citizens and all of our customers and clients as well. So the days of operating in a data center, of buildings systems are long gone. Accenture is now 90% in the cloud and I have to think about services which are really flexible, agile that deliver outcomes. So if my customers are not enjoying the experience and having fun and feeling at home. They're going to walk away so I care much more and that's why I think I lead with experience as the chief experience officer. >> So one just, to bring that down to an example. We hire about a 100,000 people a year and if you think of kind of the old paradigm when someone starts at your company. They have to get assigned a desk, a computer, a security badge you know get onto payroll and all of that historically has been done very siloed function by function. What Andrew and I are trying to create is an exciting experience when you show up for work on the first day where all of that is frictionless. All of that process goes to the backstage and how you feel about showing up as a new employee on your first day is just a glorious experience. >> So we always talk about people process and technology as a CIO you understand. Well the technology will continue to progress it's the people in process that are hard part. But can you actually achieve that vision without a technology platform that is flexible, that enables that type of work environment? >> The technology problem is really what is the enabler of the experiences we're trying to create. But the most important thing that the technology does for us is enables us to create truly world class human experiences. >> Before the cameras were rolling you were talking about how you have five generations of workers at Accenture. How do you cater to them? I mean as you said you want, coming to work everyday whether it's your first day or your, you know you've been there for 20 years to be a glorious experience. How do you make sure you are taking this empathetic people centered approach for each of these different kind of workers? >> I call it with my team sweating the small stuff and that's not worrying about bureaucracy and process. That's worrying about the individual. So we do have five generations working side by side both serving our clients and serving our business and the most important thing is truly understanding what's most important to the human? Not what generation they're coming from or were born during. >> Those five generations have a lot in common before they come to work they typically watch the news. They may have read the Wall Street Journal. They may have consumed content on YouTube. They may have looked at Twitter, they may have subscribed to Netflix. They may have asked Alexa or Cortana for advice and guidance. When they get to work what changes? It has to feel and be exactly like that and Ellen and I will be creating the services that do that so that it feels welcoming and sticky and so I want to stay. Which is really important in the modern enterprise when there's so much opportunity out there for the human. >> And to go back to the question you were asking and talking about driving out of Heathrow and not seeing humans. I think the thing that CEOs really need to understand is that employees are excited about the opportunity that technology is going to bring to their job. In fact we did a piece of research that we launched earlier this year that says over 80% of people are excited about how technology is going to improve their work. Because of the very reason they Google things at home. They use you know Amazon or whatever to go buy their things that they need for themselves. And so they see the opportunity and it's companies and organization's roles to tap into that excitement and really change the future of work. >> Here's a really good example of that. So there is nothing more boring than security training. >> I agree. >> So inside Accenture why don't you subscribe to a TV show that looks like 24. The TV show, the 24 that's episodic. We drop a season that has actors portraying the implications of if you don't get your security rights as a human and as an individual. It gets great ratings, great viewing figures. So it's ratings and viewing figures that tell us we're communicating with our employees. That's what being in the new is about. >> And that's really innovative. I was going to ask you about training and education because the example of Heathrow you don't see the data scientist the person who's putting paper and glue and doesn't have the skill sets of that data scientist. So I know Accenture big on training, education. You guys invest a lot there. My question is as you span five generations is the training regimen... Sort of how do you tailor it to those different needs? >> Well what we're finding frankly is that all of our people really want to stay relevant to their clients and to their people and so what we did was we worked together to democratize our learning platforms. So you no longer have to be tapped on the shoulder and invited to take training. We've enabled our training platform to be available real time and on demand and when you create a culture in which people are hungry to learn. You see some amazing things happen and we can see on our dashboard that Andrew's team has built all of the trending topics on any given day in any day of the week. That our people are doing through self learning. >> And that's shared and open? So there's a little bit of game theory going on here. >> Because transparency builds trust. Absolutely. >> What you want, where you want, when you want it, why you want it and at the rate you want it. Because everybody has different sets of needs. Well they'll stay relevant, they'll stay liquid and they'll be able to keep up with modern technology because we're a technology business in our case. That's wat training is about and they'll be more effective and they'll have fun and they'll have job security and none of that is threatened by other aspects of technology. >> But one point to add to that because I think Andrew's brilliance doesn't always fully come through is that everything that he's built for our people has a social component it. So for example on the learning platform I can recommend different learning experiences that I've gone through to my colleagues, to my peers and when you see the interaction among the people and how you can create real change. With just each other, without driving change top down. That social experience really changes the whole dynamic in an organization. >> I think one of the things that Ellen and I have had a chance to leave our mark on is that we have both democratized training and we socialize training as well and both are really important. >> You talked about, oh sorry. Go ahead please. >> You said you hire a 100,000 people a year and at a time where the skill set is really changing. Because so many of the repetitive automate the task are being automated and so really the skillsets that we need are more empathetic, more creative. How are you finding those people? Particularly at a time we really are in a war for talent? >> We talk about discovering new sources of talent rather than attracting talent to us. So we really try to go digital where the people are. So that's where people are, that's where we go look for them but the most important thing is that we are investing in new skilling our people. So we're not just hiring people in with new skills we're giving all of the 442,000 humans at Accenture the opportunity to continue to keep themselves relevant. >> So rather than coders and testers we now have data scientists and I do think we have new talent sources inside and outside the company. So I'm delighted to say that 54% of my team in China happen to be ladies and there's a really good solid data science gene in them which is helping us with our analytics and surfacing insights in a way that my organization didn't used to do. So we've tapped into new talent, many of them we already had it's just how you free them to do the job that they are very very capable of doing. >> Well Andrew, Ellen thank you so much for coming on the CUBE. It was great to have you here. >> Thanks for having us. >> Great to see you guys. >> I'm Rebecca Knight for Dave Vellante, we will have more from Service Now Knowledge 18 just after this.

(upbeat music) >> Announcer: From the Fairmont Hotel, in the heart of Silicon Valley, it's theCUBE. Covering, When IoT met AI: The Intelligence of Things. Brought to you by Western Digital. >> Welcome back everybody. Jeff Frick here with theCUBE. We're at Downtown San Jose at the Fairmont Hotel at a small little conference, very intimate affair, talking about IoT and AI, The Intelligence of Things. When IoT met AI. Now, they've got a cool little start up, kind of expo hall. We're excited to have our next guest here from that. It's Mike Wilson, he's the CEO of BriteThings. Mike, welcome. >> Good to be here, Jeff, how you doin'? >> Absolutely. So, BriteThings. What are BriteThings? >> BriteThings are intelligent plugs, power strips, wall sockets, anything that fits into the plug load space. It learns users behavior and then provides them an intelligent on-off schedule. The goal here is to turn stuff off when it's on and not being needed. >> Right. >> So wasted energy. Nights and weekends in the workspace, for example. >> It sounds like such a simple thing. >> Totally. >> But we were talking before we turned the cameras on, this actually has giant economic impact >> It does. >> in building maintenance, which is a huge category >> Yup. >> as you said, I'll let you kind of break down the numbers as to where >> Sure. >> that energy's being spent and the impact that you guys are having. >> Well our customers are building owners and operators, and they pay an electrical bill to run that building. It's a cost of running the building. About 27% of it goes to lighting, about 38% goes to heating and cooling, and all the rest goes to plug loads. And where we come to the market it, of course there's huge lighting companies, famous names, same with HVAC, but no one's doing anything about plug loads, and the reason is is because plug loads are distributed, they're hard to control. And so what we bring to the market is a product that is small, inexpensive, and can suddenly give owners and operators all the control that they enjoy with lighting and HVAC over their plug loads. >> So it's kind of like Dest, in that it takes a relatively simple function, now because of the cloud, because of the internet, you can add a lot more intelligence into a relatively, I don't want to say dumb device, but the device itself doesn't have to have that much power 'cause you can put the application somewhere else. >> Exactly, so if you just imagine, you're sitting here with me right now. Probably at your workplace and at home there's a bunch of stuff turned on, you're not using it, >> Right >> but you're spending money to keep it powered up, and that's causing CO2 to be generated at power plant down the road. So that's bad for your pocket, it's bad for the environment. So if we can automatically turn that stuff off, then people don't have to worry about it. We can measure it, so here's where the money is. >> Right. >> Not only energy savings, but data. So I can tell you when you turned your stuff on and off, so that means human presence. When you're at work, there's a value to that. If you're going to put a floor of an office building out there and heat it or light it, we can tell you if people are there or not. So you can look at that and make, and save even more money. >> Jeff: Right. >> We've got one customer that uses our product for inventory management. If it plugs in, you can see it on our screen, and you can see if it's on or off, if it's connected and how it's running. So that kind of data ends up being valuable, not only for energy savings, because we turn stuff on and off, but human presence, inventory control, the list goes on and on. Our customers actually every year are coming up with new ways to use our device. >> Right. And just for the baseline savings, you just basically plug it in and turn it on, and you're reporting some huge savings just by just the basic operation of your strips versus a regular strip. >> Exactly. So just imagine, this device is learning your behavior, so that's part of our, you know, that's kind of our core competency here, is these devices measure the amount of energy you're using. When you're not using something, it goes into standby mode, or sleep mode. Then we turn that off to save you the money. But the way we're able to do that is using artificial intelligence to learn patterns, and take those patterns and you can basically guess the best optimized schedule for your devices to be turned and off. >> Right. >> On and off. So if you imagine you've got 100,000 employees, 100,000 different schedules, this thing has to be smart and it can't affect worker productivity. >> Right. >> So we have to be smart enough to know when to turn it on before you come into work, when to turn it off to save you the max amount of money, and be able to measure all of that so you can roll that up and see how much money you're saving. How much CO2 are you reducing? >> Right. >> You know, so sustainability officers love our product too. >> So do you integrate with other types of intelligent systems in that space? The lightings, and the HVAC? >> Yeah. Exactly. So one of the most important things is, I've got a portfolio, my office building is a portfolio of devices and systems, so just one of them is our plug load management, right? So I want to be able to see my plug load in my current control panel. So we've got APIs where our cloud technology is able to take that reporting and stick it into, for example, a Lucid control panel. We're working with Trane right now to integrate their BACnet solution for their building control management. >> Right, right. >> So that their customers are able to see lighting, HVAC, and plug load, >> Just what I was going to say. >> right off the same old screen and operating tools that they've always used. >> Right, right. What's kind of the typical ROI that you pitch people just for the straight-up money savings that they're going to get? >> We got our foot in the door by saying we can reduce your plug load cost a minimum of 30%, and what we're seeing on average is about 40 to 45%. >> Wow. >> It's a huge huge reduction. >> Now where do you go next? >> Well, conquer the world. (Jeff laughs) You know, so imagine this, anywhere in the commercial office space where there's a plug, so let your mind go, how many power strips are out there? >> Right, right. >> How many of those-- >> We're using about 20 of them right here. >> Yeah, so, just, you know, every person at every desk is a potential customer. Every time there's a coffeemaker or a break room, a fax machine, you know, any piece of equipment that's plugged in, we can save you money. Vending machines. We have a customer with these, you know, raise and lower desks. Crazy, they want to just see, they don't want to save energy, they want to know who's using that and how often. >> Jeff: Right, right. >> Our device can do that, too. >> Right. >> And that's that data I was telling you about. Once you start collecting data of how people use plugged-in devices, I'm collecting information about you, how you use your laptop, how you use your charger, how often. >> Because the signature on the draw is different depending on the activity of the device. >> You got it. Exactly. >> I love this. You know, it's so funny because the second-order impact of all these types of things is so much more significant than people give it credit, I think. >> It's about the data. >> Jeff: Yeah. >> And our customer's just love that, because the data gives them control, and when you have control, cost savings. >> And is it just commercial, or you sell them for regular retail customers as well? Or do you-- >> I imagine some day in the future that's a potential, but you know, our focus right now, 'cause the big problem out there is that buildings use 40% of all the energy generated in the United States, and commercial space is the big opportunity, because nights and weekends. >> Right. >> Stuff should be turned off, and we can do that right now. >> Right, right. >> We're the market doing it. >> Buildings with big, big POs. >> Yup. (Jeff laughs) >> Alright, Michael, sounds like exciting stuff, can't wait til I can get one at Best Buy or Office Depot, or something. >> Coming to a store near you, or www.britethings.com. >> Alright, thanks a lot, he's Mike Wilson. Save some energy, get one of these things when they're available, or at least tell the boss to get one at the office. (Michael laughs) >> Definitely. >> Alright, I'm Jeff Frick, you're watching theCUBE. When IoT meets AI in San Jose, California. Thanks for watching. (upbeat music)

>> Narrator: Brought to you by ServiceNow. >> We're back in Orlando, I'm Dave Velanto with Jeff Frick and this is theCUBE, the leader in live tech coverage. We go up to the events, we extract the signal from the noise. Andrew Wilson is here, he's the CIO of Accenture and TV personality (laughing). Good to see you again. >> Good to see you gents again. Welcome, congratulations on a great show so far coming out of the Knowledge17. >> Yeah and back to you, we were at the Accenture event last night, it was pretty good. You had a lot of really great customers there and ServiceNow was there in force, so when a company like Accenture stamps it's impremature on a community like this, excuse me, that is a testament. So, how do you feel? >> We enjoy being a major player in the ecosystem. It's an ecosystem of platforms. We consume a lot of tech for ourselves. We have 400,000 people, we're in 55 countries, 200 cities around the world. So I've got to make them feel good, I've got to create great tech, I've also got to put tech out there that our clients see, and I've really got to get there first so that they can emulate us. I want to be a sandbox. So I'm here as a consumer but also as a service provider of ServiceNow. I think it's a great event so far. >> How do you spend your time as a CIO. I mean, especially inside a company like Accenture, I would imagine, you're getting pulled in a lot of different directions. >> I think the role and the time has changed. It used to be about running big programs, doing big builds, integration testing and big programatical old fashioned data center IT. The world's changed. I'm the Chief Experience Officer now. It's around orchestrating, brokering new experiences a lot that I'm procuring in and configuring, the platforms like ServiceNow. And other big, major brands like 0365 and Salesforce, etc. I'm focused on end to end experience, employee experience. We've got 100,000 new people arriving every year, they all bring their own tech. If mine isn't good, they will just use their own. So I want to compete with that, I want to be better than that, I want to be sticky, I want it to be like YouTube, Netflix, things like that. >> I wonder if you could dig into that a little bit because that's one of the themes we see over and over and over all the shows. The consumerization of IT and people's expectations of the way enterprise IT should work based on what I do on my phone and on my consumer apps. >> Well they should just work all the time, shouldn't it? It should work all the time, it should require no training, it should be fun, it should be bite-sized and it should all be there on my mobile device and upgrade automatically. And by the way, it's all free as well. (laughing) >> Little different than an old school SAP implementation from back in the day. >> Absolutely and, I mean SAP are a good platform provider, and we still...And they've had to change. The platforms deliver big agile releases now and we have to re-present tech. But those days of setting a course, annual spending, big functional requirements and then delivering and not course changing, that's all out the window. We have to listen, feedback, course-correct, be agile ourselves. And I also think inject fun. Tech has to be fun, modern, light-hearted, light-touch. It's a part of all aspects of life now. >> And has to have loud music. (laughing) >> Thumping in the background. >> You're a consumer, you said of ServiceNow as well. What's your ServiceNow experience like? >> We've been in production on ServiceNow for over a year. I like it, I think it's a good platform, well-architected for Cloud. It allows me to create rich moments of experience for my team. I bought it initially to do IT, SM type stuff. But I've had a learning experience that it's much broader. I like the adding analytics and intelligence into the platform that we've been hearing about here in Orlando. We're using it to power HR processes, legal processes, new contract set up. In the end, I want people to be enjoying the process and experience through life at Accenture. I don't want them to be thinking about what system I am, what platform I own? That's all under the hood. Experience first, experience only. Process based. ServiceNow is really helping us do that. >> One of the things as a CIO you're looking at, you said Chief Experience Officer, what are some of the things that are exciting you? You hear a lot of AI, nobody talks about big data anymore. It's all AI and machine-learning. >> It's all cognizance. >> Deep learning, right? Is it same wine, new bottle? Is it real? What do you see as a CIO? >> It is changing. A lot of... Like the Cloud a few years ago. A lot of talk but we're not all there yet. We're 71% in Cloud. We got on with it. I think we're about to get on with AI. I think about enterprise insight, that's what gets me excited. It's not a technology service anymore. It's a data and analytics service. The things are coming of age, we can now deliver it for the enterprise. >> When you think about strategy, vision, the role of the CIO, how do you see that changing? >> Well, I'm a broadcaster, like you. So I'm a Chief Communications person. I'm producing content. I'm not just running the cameras and the green-screen studios, I'm doing my own show. I'm not writing emails. We're popping up studios around the world. We're ingesting content into something which is beginning to feel a lot like a live network. And that's how people want to consume. They don't want to sit there and watch an hour long training course. And if they want to learn about security, and how we do it at Accenture, they want to watch something that looks and sounds like 24, we call it Hackerland. It's a series of dramatized episodes. That's the future of how we consume tech. >> So what are some of the topics that you're covering? First of all, what's the objective of your show and what are some of the things you're talking about? >> My show exists primarily to glue my family of eight or 9,000 IT workers around the world together so that they can stay current in a fast-moving, changing world of our own strategy. We course correct our strategy, we do hundreds of releases of different services every month. Being the CIO team that does that, I want them very aware so it's our internal, stay ahead, under the hood, stay ahead of our broader user base. By the way, practice new techniques because we're amongst friends with our CIO audience, before our CEO and the others start using the services as well. >> Have you done a show that related to service management? >> Uh not... oh well we've certainly talked about ServiceNow deployment, but the show we like to mix. So we'll have different teams and projects on. We'll have news reports, we'll have some humor. We don't do an hour of the same thing, because they'd switch off. >> You do a lot of events like this, I presume? >> I go to a lot of events like this. We don't do the show for most events. We take our show on the road. We've done the show live from India. We're about to go, two weeks time to Dublin in Ireland. And then we'll be going down Buenos Aires. So it's a global show. When I'm here, I'm typically on others' stage, like I'm here with you guys today. Talking about our work in the market and how we power all of our client work through these platforms. >> It's so different, cause I remember long time ago, at a small software company, we were trying to break in with Accenture and it was a roadshow. You guys had little shows all over the place, whether it be the Vertical Group, the Industry Group, the Horizontal Group. They'd bring the partners together and that was the way that new technologies were communicated. We'd set up a little expo, and they would all come in, we'd pitch our wares and that was it. So different than what you're talking about now in this communication, video-- >> Accenture's a global company, global brand. It's actually a series of businesses. Technologists, operators, strategists, consultants. I think we are platform practitioners and we are a major service provider. So we use ServiceNow to support hundreds of our own clients. So I'm not just using it to power Accenture, we're powering all our client work as well. It's a new Accenture. We talk about the new in our digital strategy and at least half of the work that we do for our clients is all in this brand new space of digital. That percentage is increasing rapidly every quarter. >> How much of your time is practice leads dragging you into clients? >> Quite a bit. We do hundreds of client dialogues. I come from a business, I spend more time talking to client's as CIO than I did when I was the business. >> Excellent. Andrew, thanks so much for coming on theCUBE. It was a pleasure having you. >> Great to see you guys, good luck. >> Good luck with your show, we'll be watching. >> Thank you. >> Ya, we'll be tuning in. >> Enjoy, thank you, take care. >> Alright keep it right there everybody we'll be back with our next guest right after this short break. This is theCUBE, we're live from Knowledge17. We'll be right back.

>> Important place in that history right now is that we're-- >> Announcer: Live from Boston, Massachusetts, it's theCUBE covering Red Hat Summit 2017 brought to you by Red Hat. >> Welcome back to theCUBE's coverage of the Red Hat Summit here in beautiful Boston, Massachusetts. I'm your host Rebecca Knight. I'm joined by Todd Wilson and Shea Phillips of the BC Developers Exchange. Thanks so much for joining us today. >> Thanks for having us. >> So the BC Developer's Exchange, you described it to me before the cameras were rolling as helping the British Colombian government think differently. Talk a little, explain, unpack that a bit for our viewers. >> Sure, so it's been a journey for us. We've evolved over awhile, so we've been going for about three years now. What we wanted to do, we recognized that government had fallen behind in its technology practices and technology utilization and we were trying to participate in the tech industry that's growing in BC and we were finding that it was a pretty big gap in understanding. We didn't really speak the same language, we didn't really understand what their needs were, they didn't understand how to work with us and so we started exploring ways to connect better. So one of the things we recognized that we had on our side was technology assets of data. We have tons and tons of data that's valuable to the tech industry to use for their apps. So we first started by opening up that data and then realizing that just open data is part of the story. We need APIs so providing API access and that was just kind of part of the story. We needed to actually start collaborating on solutions. So then we brought the Province into GitHub and we're doing open source collaboration on GitHub and it's kind of morphed into a much bigger picture than we originally started with but it's been a really exciting way to work. >> And your realization that the government was a little bit behind here or you were working in a different track than the government, that's not uncommon, wouldn't you think? The government is not known for innovative practices. So did it take, did it take some persuasion on your part? >> I think that you know, it's mixed. So there are certainly factions within the government that there's a bit of pent up demand, right? So there are people who are very quick to kind of get on the train and then there are other groups who do need convincing and it's kind of a work in progress. So we're building collaboration across government all the time but we certainly didn't have trouble finding people within government and within the tech community who wanted to come along with us. >> So talk about some of the projects that you're working on to make government run better. >> Sure, so there's a couple of examples of how moving into the open source just made sense for government. One example that we've used in a sort of why GitHub makes sense for what we're doing, the Environmental Reporting Branch of the Ministry of the Environment is responsible every year for producing a report on the water quality, air quality, all the basic things that the environmentalists you know, care about and all of the different universities and academic institutions consume this report and then do their analysis on it. One of the things that was always a challenge is there was always kind of wondering, are these numbers cooked? Are you guys actually reporting on the actual findings or are you cleaning it up a little bit? So what the Environmental Reporting Office was able to do is they published the code on GitHub, the data in our Open Data Catalog and it was all there 100% transparent for anybody to recreate the results. So they could download the code, have it running on their laptop. They could download the data, bring it in and run the numbers. What ended up happening after a few months, they got an issue in GitHub. Somebody created an issue, said it's broken, it's not working, I can't get it to go and a little bit of investigation and they found out that the nature of the data, one of the datasets they were using had changed. So it broke the program and so the developer that was responsible for it wasn't going to fix that until next year, next time to run the report. So he said thanks for pointing out the error but you know, I'll be fixing that next year and a day or two went by and all of a sudden out of nowhere he got a pull request in GitHub. The guy who discovered the issue actually went away on the weekend and fixed the code himself and said here, I fixed it for you, it's all ready to go. And so that's sort of that whole community spirit that just starts to grow naturally when citizens can engage with government on such a personal level and work on something together and collaborate in a space that previous to that had been kind of adversarial. There wasn't a lot of trust there, there wasn't sort of that good feeling of are we getting the right information? All of a sudden to turn into a real collaborative partnership, that's the model that we want to see. >> Well I'm wondering if we could turn that example into a real metaphor for what we'd like to see overall with a more engaged citizenry who is people who want to work alongside or with government to solve these problems. >> Exactly yeah, we're all living in the same space. We're all using the same resources. You know, the government is there for the citizens and it's by the citizens, so to be able to work together and work openly is a real strength, real power play. >> So that environmental code that you just gave was a great example. Talk about some other ways that you're working with the government. >> So one example that we have is sort of in an internal sharing scenario. So previously when applications were built within gov, there wasn't an easy way for applications to be shared across different ministries or agencies. So they'd get built and they'd kind of get locked away and used for that one particular business function. What we've been able to do with GitHub and by having shared code is to have projects come along and actually borrow what's been done already and repurpose those applications and that gives them a great starting point. So there's a lot of common things that every application would have to figure out and so by having these starter kits essentially, development teams can get a leg up on taking on new projects and so that reduces the time to market and the cost ultimately and also makes things a little more consistent. >> And what about the project you did with the highways? >> Okay, so that was one where there was a collaboration on a standard for reporting of road incidents. So it's called Open 511 and so this was an international standard that was being developed. So there's various States in the US and Provinces in Canada and a couple of other international jurisdictions that collaborated on this specification for highway event APIs so that data could be shared easily. So the Ministry of Transportation in BC participated in that and collaborated and contributed to it but then they also exposed their data using these APIs. But then they didn't end up building anything on it, they just kind of said here, it's available to use. Go figure it out. So what we really wanted to do there is it's really not the government's job to be building all of the end product apps. We're kind of the resource store for the building blocks and then what ended up happening, an opportunity got recognized by a mobile app developer in Victoria, they saw an opportunity to take these APIs and build a little notification app so that if you put your route in, it'll ping you notifications if there's obstructions or traffic or whatever may have you and show you the webcam image that is on your route. So a really interesting solution that gov never would have built. Like we would never have built a mobile app for that. >> Do you, how do you ensure security? That's one of the biggest themes of this conference is making sure the data is in fact secure, it's what you hear over and over again as a big concern. How do you address that? >> Do you want to, oh yeah I was getting to that. So we have a data center that we run in partnership with HP and the data resides on premise in that data center. What we're using Red Hat OpenShift Container Platform is sort of all the front end facing interfaces would go through OpenShift. So when people are accessing the data, the access in controlled through gateways and however projects get set up in order to control that access. Meanwhile the data is still sitting securely in the network zone back at the mother ship. So what we've found with the OpenShift Container Platform is the developers don't necessarily need to worry about a lot of the tactical policies and network policies that are part of that security standard because that's handled by the platform. When we build OpenShift, we built it compliant to all those policies and so developers can come in to the platform, just start working and as long as they're not punching out data that has personal information out to the internet, you know of course there's things they could do wrong, but as long as they're using the platform as it was intended, they're compliant right from day one. >> In terms of recruiting and retaining talented developers and talented technologists, do you find that a challenge? I mean as we said before, you don't necessarily think of the government as this hotbed of innovation and creativity. Is it difficult to get the best and the brightest to come work for you? >> I think that was actually part of the strategy around adopting tools like containers and open source was actually to make gov more compatible with the IT market. So using the same tools that the private sector uses, so there's a more seamless transition from a recruiting perspective and people can, you know they're not sort of going back in time when they go and work with government. So that was definitely a deliberate part of the strategy. >> So it's the tools but then also the projects. Are you finding coders and engineers who are, who want to dig into these projects? >> They do but we want to work with them in a different way. So we don't necessarily want every developer to be a gov employee. That's really not the model. We would never scale properly that way. So what we've done is we've created a new procurement method. So in government, procurement is hard like it is in a lot of enterprises. Contracts and all of these things get complicated and take time and you have to wait maybe a few months before you actually get the resource that you need. So what we've done is shortened that timeline down as much as we can and also micro-sized the work as much as we can. So if a project is running on GitHub and they have an issue, they can post that issue and put a dollar sign associated with it from 1,000 to $10,000 and kind of do a bounty and say hey development community, we want this fixed, can you do it? So developers can engage with that. They can write a short proposal, 100 words or less of what they will do and then if they get assigned the work and we accept the pull request, we will pay them using PayPal or write them a check or however they want right on the spot. So we can go end-to-end from problem, proposal, code and solution literally in a couple of days whereas before that would have taken a few months and the engagement would have been much larger and much more expensive. >> And are you finding that that is in fact having the impact you want in terms of the workforce that you're trying to attract? >> Yeah, Shea, you want to? >> Yeah, I think there's definitely been interest in the private sector, kind of independent freelance developers are generally pretty excited about this and some of them are downright shocked to see that this is such a progressive thing that the gov has undertaken. >> Yeah, we've had comments from developers saying oh, I never knew working with gov was this easy and that's the way we like to hear it. >> And hopefully it will become easier, too. We think about the government and the technology industry not necessarily working together, particularly when it comes to this new digital world that we're living in and we hear so much about the benefits of automation but also the fact that automation is going to have a big impact on jobs. Do you think that the government and tech need to be thinking together about the effects of this and working together to make sure that we aren't seeing more displaced workers? >> Absolutely, I mean I think we're, you know no one has a crystal ball. Nobody can tell what's going to happen but if we don't start thinking proactively about some of these issues, workforce issues, we're going to be caught flat-footed and so one of the things that we've been trying to prove along is automation doesn't necessarily mean losing jobs and so we've been trying to explore what the workforce shift looks like. So what we find within the little corner of sort of DevOps automation that we're doing is it's not that we're taking jobs away from people, we're just moving them to a different part of the value stream. So they're usually moving further up the value stream closer to the business so that they're actually much more engaged with the day-to-day business of gov and less engaged just with the tech and the plumbing. So by moving automation in, we're actually connecting the business and the technology closer together. >> What are some of the future projects that you envisage working closely with the government to change the way citizens engage with government? >> Sure, we've got a couple of big projects coming up where we are looking at different models of reaching citizens in meaningful ways. So there's a sort of personalized service or some kind of citizen dashboard, however you want to phrase that. That's one of the things that's on our wish list of wouldn't it be great if. We also have partnerships that we're looking to explore in different areas with sort of big data and data analytics. Because government has so much rich resource data, we're looking for ways to get that out and get that available but one of the challenges is just the sheer size of it. So the big data equation and big data analytics are very interesting things for us in the future because if we can provide expertise in that area, then tech sector and industry partners can come and participate with that data and just make it better. >> Well thank you so much for joining us Todd and Shea, I appreciate your time. >> Great, thank you. >> We'll be back with more of theCUBE's coverage of the Red Hat Summit 2017 after this. (up tempo electronic tones)

>> Commentator: Live from San Jose, California. It's theCUBE covering Big Data Silicon Valley 2017. >> Okay, welcome back everyone. We are here live in Silicon Valley for Big Data SV (mumbles) event in conjunction with Strata + Hadoop. Our companion event, the Big Data NYC and we're here breaking down the Big Data world as it evolves and goes to the next level up on the step function, AI machine learning, IOT really forcing people to really focus on a clear line of the side of the data. I'm John Furrier with our announcer from Wikibon, George Gilbert and our next guest, our two executives from Trifacta. The founder and Chief Strategy Officer, Joe Hellerstein and Adam Wilson, the CEO. Guys, welcome to theCUBE. Welcome back. >> Great to be here. >> Good to be here. >> Founder, co-founder? >> Co-founder. >> Co-founder. He's a multiple co-founders. I remember it 'cause you guys were one of the first sites that have the (mumbles) in the about section on all the management team. Just to show you how technical you guys are. Welcome back. >> And if you're Trifacta, you have to have three founders, right? So that's part of the tri, right? >> The triple threat, so to speak. Okay, so a big year for you guys. Give us the update. I mean, also we had Alation announce this partnering going on and some product movement. >> Yup. >> But there's a turbulent time right now. You have a lot of things happening in multiple theaters to technical theater to business theater. And also within the customer base. It's a land grand, it seems to be on the metadata and who's going to control what. What's happening? What's going on in the market place and what's the update from you guys? >> Yeah, yeah. Last year was an absolutely spectacular year for Trifacta. It was four times growth in bookings, three times growth in customers. You know, it's been really exciting for us to see the technology get in the hands of some of the largest companies on the planet and to see what they're able to do with it. From the very beginning, we really believed in this idea of self service and democratization. We recognize that the wrangling of the data is often where a lot of the time and the effort goes. In fact, up to 80% of the time and effort goes in a lot of these analytic projects and to the extent that we can help take the data from (mumbles) in a more productive way and to allow more people in an organization to do that. That's going to create information agility that that we feel really good about and there are customers and they are telling us is having an impact on their use of Big Data and Hadoop. And I think you're seeing that transition where, you know, in the very beginning there was a lot of offloading, a lot of like, hey we're going to grab some cost savings but then in some point, people scratch their heads and said, well, wait a minute. What about the strategic asset that we were building? That was going to change the way people work with the data. Where is that piece of it? And I think as people started figuring out in order to get our (mumbles), we got to have users and use cases on these clusters and the data like itself is not a used case. Tools like Trifacta have been absolutely instrumental and really fueling that maturity in the market and we feel great about what's happening there. >> I want to get some more drilled out before we get to some of these questions for Joe too because I think you mentioned, you got some quotes. I just want to double up a click on that. It always comes up in the business model question for people. What's your business model? >> Sure. >> And doing democratization is really hard. Sometimes democratization doesn't appear until years later so it's one of those elusive things. You see it and you believe it but then making it happen are two different things. >> Yeah, sure. >> So. And appreciate that the vision they-- (mumbles) But ultimately, at the end of the day, that business model comes down to how you organized. Prove points. >> Yup. >> Customers, partnerships. >> Yeah. >> We had Alation on Stephanie (mumbles). Can you share just and connect the dots on the business model? >> Sure. >> With respect to the product, customers, partners. How was that specifically evolving? >> Adam: Sure. >> Give some examples. >> Sure, yeah. And I would say kind of-- we felt from the beginning that, you know, we wanted to turn what was traditionally a very complex messy problem dealing with data, you know, in the user experience problem that was powered by machine learning and so, a lot of it was down to, you know, how we were going to build and architect the technology needed (mumbles) for really getting the power in the hands of the people who know the data best. But it's important, and I think this is often lost in Silicon Valley where the focus on innovation is all around technology to recognize that the business model also has to support democritization so one of the first things we did coming in was to release a free version of the product. So Trifacta Wrangler that is now being used by over 4500 companies, ten of thousands of users and the power of that in terms of getting people something of value that they could start using right away on spreadsheets and files and small data and allowing them to get value but then also for us, the exchange is that we're actually getting a chance to curate at scale usage data across all of these-- >> Is this a (mumbles) product? >> It's a hybrid product. >> Okay. >> So the data stays local. It never leaves their local laptop. The metadata is hashed and put into the cloud and now we're-- >> (mumbles) to that. >> Absolutely. And so now we can use that as training data that actually has more people wrangle, the product itself gets smarter based on that. >> That's good. >> So that's creating real tangible value for customers and for us is a source of very strategic advantage and so we think that combination of the technology innovation but also making sure that we can get this in the hands of users and they can get going and as their problem grows up to be bigger and more complicated, not just spreadsheets and files on the desktop but something more complicated, then we're right there along with them for products that would have been modified. >> How about partnerships with Alation? How they (mumbles)? What are all the deals you got going on there? >> So Alation has been a great partner for us for a while and we've really deepened the integration with the announcements today. We think that cataloging and data wrangling are very complimentary and they're a natural fit. We've got customers like Munich Re, like eBay as well as MarketShare that are using both solutions in concert with one another and so, we really felt that it was natural to tighten that coupling and to help people go from inventorying what's going on in their data legs and their clusters to then cleansing, standardizing. Essentially making it fit for purpose and then ensuring that metadata can roundtrip back into the catalog. And so that's really been an extension of what we're doing also at the technical level with technologies like Cloudera Navigator with Atlas and with the project that Joe's involved with at Berkeley called Ground. So I don't know if you want to talk-- >> Yeah, tell him about Ground. >> Sure. So part of our outlook on this and this speaks to the kind of way that the landscape in the industry's shaping out is that we're not going to see customers buying until it's sort of lock in on the key components of the area for (mumbles). So for example, storage, HD (mumbles). This is open and that's key, I think, for all the players in this base at HTFS. It's not a product from a storage vendor. It's an open platform and you can change vendors along the way and you could role your own and so on. So metadata, to my mind, is going to move in the same direction. That the storage of metadata, the basic component tree that keeps the metadata, that's got to be open to give people the confidence that they're going to pour the basic descriptions of what's in their business and what their people are doing into a place that they know they can count on and it will be vendor neutral. So the catalog vendors are, in my mind, providing a functionality above that basic storage that relates to how do you search the catalog, what does the catalog do for you to suggest things, to suggest data sets that you should be looking at. So that's a value we have on top but below that what we're seeing is, we're seeing Horton and Cloudera coming out with either products re opensource and it's sort of the metadata space and what would be a shame is if the two vendors ended up kind of pointing guns inward and kind of killing the metadata storage. So one of the things that I got interested in as my dual role as a professor at Berkeley and also as a founder of a company in this space was we want to ensure that there's a free open vendor neutral metadata solution. So we began building out a project called Ground which is both a platform for metadata storage that can be sitting underneath catalog vendors and other metadata value adds. And it's also a platform for research much as we did with Spark previously at Berkeley. So Ground is a project in our new lab at Berkeley. The RISELab which is the successor to the AMPLab that gave us Spark. And Ground has now got, you know, collaboratives from Cloudera, from LinkedIn. Capital One has significantly invested in Ground and is putting engineers behind it and contributors are coming also from some startups to build out an open-sourced platform for metadata. >> How old has Ground been around? >> Joe: Ground's been around for about 12 months. It's very-- >> So it's brand new. How do people get involved? >> Brand new. >> Just standard similar to the way the AMPLab was? Just jump in and-- >> Yeah, you know-- >> Go away and-- >> It comes up on GitHub. There's (mumbles) to go download and play with. It's in alpha. And you know, we hope we (mumbles) and the usual opensource still. >> This is interesting. I like this idea because one thing you've been riffing on the cue ball of time is how do you make data addressable? Because ultimately, you know, real time you need to have access to data really really low (mumbles) to see the inside to make it work. Hence the data swamp problem right? So, how do you guys see that? 'Cause now I can just pop in. I can hear the objections. Oh, security! You know. How do you guys see the protections? I'd love to help get my data in there and get something back in return in a community model. Security? Is it the hashing? What's the-- How do you get any security (mumbles)? Or what are the issues? >> Yeah, so I mean the straightforward issues are the traditional issues of authorization and encryption and those are issues that are reasonably well-plumed out in the industry and you can go out and you can take the solutions from people like Clutter or from Horton and those solutions have plugin quite nicely actually to a variety of platforms. And I feel like that level of enterprise security is understood. It's work for vendors to work with that technology so when we went out, we make sure we were carburized in all the right ways at Trifacta to work with these vendors and that we integrated well with Navigator, we integrated with Atlas. That was, you know, there was some labor there but it's understood. There's also-- >> It's solvable basically. >> It's solvable basically and pluggable. There are research questions there which, you know, on another day we could talk about but for instance if you don't trust your cloud hosting service what do you do? And that's like an open area that we're working on at Berkeley. Intel SGX is a really interesting technology and that's based probably a topic for another day. >> But you know, I think it's important-- >> The sooner we get you out of the studio, Paolo Alto would love to drill on that. >> I think it's important though that, you know, when we talk about self service, the first question that comes up is I'm only going to let you self service as far as I can govern what's going on, right? And so I think those things-- >> Restrictions, guard rails-- >> Really going hand in here. >> About handcuffs. >> Yeah so, right. Because that's always a first thing that kind of comes out where people say, okay wait minute now is this-- if I've now got, you know-- you've got an increasing number of knowledge workers who think that is their-- and believe that it is their unalienable right to have access to data. >> Well that's the (mumbles) democratization. That's the top down, you know, governance control point. >> So how do you balance that? And I think you can't solve for one side of that equation without the other, right? And that's really really critical. >> Democratization is anarchization, right? >> Right, exactly. >> Yes, exactly. But it's hard though. I mean, and you look at all the big trends where there was, you know, web one data, web (mumbles), all had those democratization trends but they took six years to play out and I think there might be a more auxiliary with cloud when you point about this new stop. Okay George, go ahead. You might get in there. >> I wanted to ask you about, you know, what we were talking about earlier and what customers are faced with which is, you know, a lot of choice and specialization because building something end to end and having it fully functional is really difficult. So... What are the functional points where you start driving the guard rails in that Ikee cares about and then what are the user experience points where you have critical mass so that the end users then draw other compliant tools in. You with me? On sort of the IT side and the user side and then which tools start pulling those standards? >> Well, I would say at the highest level, to me what's been very interesting especially would be with that's happened in opensource is that people have now gotten accustomed to the idea that like I don't have to go buy a big monolithic stacks where the innovation moves only as fast as the slowest product in the stack or the portfolio. I can grab onto things and I can download them today and be using them tomorrow. And that has, I think, changed the entire approach that companies like Trifacta are taking to how we how we build and release product to market, how we inter operate with partners like Alation and Waterline and how we integrate with the platform vendors like Cloudera, MapR, and Horton because we recognize that we are going to have to be meniacal focused on one piece of this puzzle and to go very very deep but then play incredibly well both, you know, with all the rest of the ecosystem and so I think that is really colored our entire product strategy and how we go to market and I think customers, you know, they want the flexibility to change their minds and the subscription model is all about that, right? You got to earn it every single year. >> So what's the future of (mumbles)? 'Cause that brings up a good point we were kind of critical of Google and you mentioned you guys had-- I saw in some news that you guys were involved with Google. >> Yup. >> Being enterprise ready is not just, hey we have the great tech and you buy from us, damn it we're Google. >> Right. >> I mean, you have to have sales people. You have to have automation mechanism to create great product. Will the future of wrangling and data prep go into-- where does it end up? Because enterprises want, they want certain things. They're finicky of things. >> Right, right. >> As you guys know. So how does the future of data prep deal with the, I won't say the slowness of the enterprise, but they're more conservative, more SLA driven than they are price performance. >> But they're also more fragmented than ever before and you know, while that may not be a great thing for the customers for a company that's all about harmonizing data that's actually a phenomenal opportunity, right? Because we want to be the decision that customers make that guarantee that all their other decisions are changeable, right? And I go and-- >> Well they have legacy systems of record. This is the challenge, right? So I got the old oracle monolithic-- >> That's fine. And that's good-- >> So how do you-- >> The more the merrier, right? >> Does that impact you guys at all? How did you guys handle that situation? >> To me, to us that is more fragmentation which creates more need for wrangling because that introduces more complexity, right? >> You guys do well in that environment. >> Absolutely. And that, you know, is only getting bigger, worse, and more complicated. And especially as people go from (mumbles) to cloud as people start thinking about moving from just looking at transactions to interactions to now looking at behavior data and the IOT-- >> You're welcome in that environment. >> So we welcome that. In fact, that's where-- we went to solve this problem for Hadoop and Big Data first because we wanted to solve the problems at scale that were the most complicated and over time we can always move downstream to sort of more structured and smaller data and that's kind of what's happened with our business. >> I guess I want to circle back to this issue of which part of this value chain of refining data is-- if I'm understanding you right, the data wrangling is the anchor and once a company has made that choice then all the other tool choices have to revolve around it? Is that a-- >> Well think about this way, I mean, the bulk of the time when you talk to the analysts and also the bulk of the labor cost and these things isn't getting the data from its raw form into usage. That whole process of wrangling which is not really just data prep. It's all the things you do all day long to kind of massage these data sets and get 'em from here to there and make 'em work. That space is where the labor cost is. That also means that's spaces were the value add is because that's where your people power or your business context is really getting poured in to understand what do I have, what am I doing with it and what do I want to get out of it. As we move from bottom line IT to top line value generation with data, it becomes all the more so, right? Because now it's not just the matter of getting the reports out every month. It's also what did that brilliant in sales do to that dataset to get that much left? I need to learn from her and do a similar thing. Alright? So, that whole space is where the value is. What that means is that, you know, you don't want that space to be tied to a particular BI tool or a particular execution edge. So when we say that we want to make a decision in the middle of that enables all the other decisions, what you really want to make sure is that that work process in there is not tightly bound to the rest of the stack. Okay? And so you want to particularly pick technologies in that space that will play nicely with different storage, that play nicely with different execution environments. Today it's a dupe, tomorrow it's Amazon, the next day it's Google and they have different engines back there potentially. And you want it certainly makes your place with all the analytic and visualizations-- >> So decouple from all that? >> You want to decouple that and you want to not lock yourself in 'cause that's where the creativity's happening on the consumption side and that's where the mess that you talked about is just growing on the production side so data production is just getting more complicated. Data consumption's getting more interesting. >> That's actually a really really cool good point. >> Elaborating on that, does that mean that you have to open up interfaces with either the UI layer or at the sort of data definition layer? Or does that just mean other companies have to do the work to tie in to the styles? The styles and structures that you have already written? >> In fact it's sort of the opposite. We do the work to tie in to a lot of this, these other decisions in this infrastructure, you know. We don't pretend for a minute that people are going to sort of pick a solution like Trifacta and then build their organization around it. As your point, there's tons of legacy, technology out there. There is all kinds of things moving. Absolutely. So we, a big part of being the decoder ring for data for Trifacta and saying it's like listen, we are going to inter operate with your existing investments and we're going to make sure that you can always get at your data, you can always take it from whatever state its in to whatever state you need to be in, you can change your mind along the way. And that puts a lot of owners on us and that's the reason why we have to be so focused on this space and not jump into visualization and analytics and not jump in to its storage and processing and not try to do the other things to the right or left. Right? >> So final question. I'd like you guys both to take a stab at it. You know, just going to pivot off at what Joe was saying. Some of the most interesting things are happening in the data exploration kind of discovery area from creativity to insights to game changing stuff. >> Yup. >> Ventures potentially. >> Joe: Yup. >> The problem of the complexity, that's conflict. >> Yeah. >> So how does we resolve this? I mean, besides the Trifacta solution which you guys are taming, creating a platform for that, how do people in industry work together to solve that problem? What's the approach? >> So I think actually there's a couple sort of heartening trends on this front that make me pretty optimistic. One of these is that the inside of structures are in the enterprises we work with becoming quite aligned between IT and the line of business. It's no longer the case that the line of business that are these annoying people that they're distracting IT from their bottom line function. IT's bottom line function is being translated into a what's your value for the business question? And the answer for a savvy IT management person is, I will try to empower the people around me to be rabid fans and I will also try to make sure that they do their own works so I don't have to learn how to do it for them. Right? And so, that I think is happening-- >> Guys to this (mumbles) business guys, a bunch of annoying guys who don't get what I need, right? So it works both ways, right? >> It does, it does. And I see that that's improving sort of in the industry as the corporate missions around data change, right? So it's no longer that the IT guys really only need to take care of executives and everyone else doesn't matter. Their function really is to serve the business and I see that alignment. The other thing that I think is a huge opportunity and the part of who I-- we're excited to be so tightly coupled with Google and also have our stuff running in Amazon and at Microsoft. It's as people read platform to the cloud, a lot of legacy becomes a shed or at least become deprecated. And so there is a real-- >> Or containerized or some sort of microservice. >> Yeah. >> Right, right. >> And so, people are peeling off business function and as part of that cost savings to migrate it to the cloud, they're also simplified. And you know, things will get complicated again. >> What's (mumbles) solution architects out there that kind of re-boot their careers because the old way was, hey I got networks, I got apps and stacks and so that gives the guys who could be the new heroes coming in. >> Right. >> And thinking differently about enabling that creativity. >> In the midst of all that, everything you said is true. IT is a massive place and it always will be. And tools that can come in and help are absolutely going to be (mumbles). >> This is obvious now. The tension's obviously eased a bit in the sense that there's clear line of sight that top line and bottom line are working together now on. You mentioned that earlier. Okay. Adam, take a stab at it. (mumbling) >> I was just going to-- hey, I know it's great. I was just going to give an example, I think, that illustrates that point so you know, one of our customers is Pepsi. And Pepsi came to us and they said, listen we work with retailers all over the world and their reality is that, when they place orders with us, they often get it wrong. And sometimes they order too much and then they return it, it spoils and that's bad for us. Or they order too little and they stock out and we miss revenue opportunities. So they said, we actually have to be better at demand planning and forecasting than the orders that are literally coming in the door. So how do we do that? Well, we're getting all of the customers to give us their point of sale data. We're combining that with geospatial data, with weather data. We're like looking at historical data and industry averages but as you can see, they were like-- we're stitching together data across a whole variety of sources and they said the best people to do this are actually the category managers and the people responsible for the brands 'cause they literally live inside those businesses and they understand it. And so what happened was they-- the IT organization was saying, look listen, we don't want to be the people doing the janitorial work on the data. We're going to give that work over to people who understand it and they're going to be more productive and get to better outcomes with that information and that brings us up to go find new and interesting sources and I think that collaborative model that you're starting to see emerge where they can now be the data heroes in a different way by not being the ones beating the bottleneck on provisioning but rather can go out and figure out how do we share the best stuff across the organization? How do we find new sources of information to bring in that people can leverage to make better decisions? That's in incredibly powerful place to be and you know, I think that that model is really what's going to be driving a lot of the thinking at Trifacta and in the industry over the next couple of years. >> Great. Adam Wilson, CEO of Trifacta. Joe Hellestein, CTO-- Chief Strategy Officer of Trifacta and also a professor at Berkeley. Great story. Getting the (mumbles) right is hard but under the hood stuff's complicated and again, congratulations about sharing the Ground project. Ground open source. Open source lab kind of thing at-- in Berkeley. Exciting new stuff. Thanks so much for coming on theCUBE. I appreciate great conversation. I'm John Furrier, George Gilbert. You're watching theCUBE here at Big Data SV in conjunction with Strata and Hadoop. Thanks for watching. >> Great. >> Thanks guys.

(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)