 Live from Las Vegas, it's theCUBE. Covering IBM Think 2018, brought to you by IBM. Welcome back to theCUBE. We are live on day one of our three days of coverage of IBM Think, the inaugural single event from IBM. I'm Lisa Martin with Dave Vellante. We're at the Mandalay Bay, beautiful sunny Las Vegas, and we're excited to welcome to theCUBE for the first time Steve Hill, the global head of innovation at KPMG. Welcome. Thanks, I'm gonna be here. So you are giving a talk, Wednesday you said at the event, want to get a little bit into your role at KPMG as well as your session. So talk to us a little bit about what your role is, the global head of innovation. So innovation's an overused word. I don't particularly like the word innovation, but in the context of my role, it really is taking a look at our business and our clients, and saying what is it that our clients need for their futures? What's going to create relevance for our clients as we go forward? And how does our portfolio of services relate to that relevance? And if we have gaps where we see our services not serving them best, or not going to serve them best in the future, my job responsibility really is to help for strategy purposes and for investment purposes, bring those points to bear, and to get either investment into those areas, or changes in the business as appropriate, to make KPMG more relevant to our clients, and to their relevance to their clients, right? That's the whole idea. Well, so, Lisa and I talked to a lot of people in theCUBE, and we talk about invention, startups inventing something, or new technology that gets invented, but innovation to us, and I think KPMG is at the heart of this, is taking an invention and actually applying it to affect change, getting it adopted, and changing a business or changing a, it's a societal change potentially, is that? That's right, I mean, our short phrase for it is, idea to cash for our clients, right? I mean, at the end of the day, and I think this is profound in certainly corporate governance evolution, right? We've seen the advent of lots of S-curve changes of how companies have been managed, enterprises have been managed, right? The Dutch started with the East India Trading Company, one of the first large global enterprises. Since that time, we've seen the maturation, new roles, the CIO role, didn't exist much prior to 1950, right? Today, we're starting to see innovation to be a very important skill and capability for all corporations, all enterprises, including government, right? And I think we're starting to see a maturation of corporate capability, I would say, in the innovation space, because you've got the pace of change is so fast today, the political, economic, technological, social trends are so complex that you've got to get something in your muscle memory that helps you change your business as much as operated effectively. I'd love to know who you're talking to within organizations, you know, you mentioned CIO role, the CISO role, Chief Data Officer. Right. What, who are the minds that you're helping to bring together so that an enterprise that needs to digitalize to be competitive will survive, right? Really survive these days. How do you help them really embrace a culture of innovation as really there's no other choice? How do you get these minds collectively agreeing, yes, this is the direction we need to go in? Yeah, I think, I mean, first of all, this is a C-suite conversation and a board conversation in many cases. But the reality is when you start to look at the lack of innovation in an organization, right? And when the environment changes, competitors start to change, and the more complex it is, it's harder and harder for companies to pivot and to reinvent themselves. And we're seeing, you know, a lot of unbundling of businesses in today's environment, whether it's, you know, a company that moves packages, right? Or a professional services firm, or a company that used to distribute videos, right? I mean, things change. And some of the ironies are sometimes the innovation in companies like Kodak. Steve Sammons invented digital camera. It took eight minutes to go from a snap to a picture, but they invented digital technology from cameras. And that, the distribution of digital videos is actually would help to, you know, further the demise of that organization. So that notion of how do you take change going on in the environment that you're working in, and more importantly, your customers and clients, how does that convert into your business? That's a C-suite conversation. And I think innovation can be embodied in a person to help build process, meaning how do you take an idea? How do you look at the marketplace and get sensory input? Convert that to ideas for strategy and for investment. And the investments have to be deployed to the field, to the business. And that relationship, that whole life cycle of innovation requires a lot of people from the enterprise to be involved in it. And I would argue the culture has to evolve. Because, you know, until recently, most people, in fact, I would say, including recent, you know, current times, most people and organizations are rewarded for doing what they do well, not breaking what they do, not rethinking what they do. And the more you get into that operational mindset and I want to, you know, wring all the efficiencies out of this process that I can, right, the more you're wed to the status quo, the more somebody comes in from the side and takes you out. So I love this conversation because Steve, you're able to take the long view and then I want to sort of shorten it up and then maybe put it into a longer term context. So over our year guys, 20 plus year careers, mine a little longer. Most of this industry has marched to the cadence of Moore's law. That's where innovation came from. How do you take advantage of Moore's law? How do you go to client, server, software, whatever it was. The innovation equation is changing now. It seems to be a function of, these guys have been hearing me say this all day, but data that's not siloed, but data that you have access to, applying machine intelligence, and then getting cloud scale economics and network effects and then applying it to your business. So talk about how you see the new wave of innovation in this world of digital or however you phrase it. Well, it's interesting. I mean, I don't hear a lot of people phrase it the way you did, which I think is spot on, which is, in my words are ubiquitous access to technology, which is cloud data. And that's a huge question mark in a big C-suite conversation. Having a lot of data isn't the key. Having the right lot of data is the key. So Dyson's moving into automaking today. They have a lot of data and it's very different from what the incumbents have. Is it better or worse? We're going to see. And then of course smart computers, which is the machine intelligence. Those three elements, I think are fundamentally changing labor productivity. And what I would say is to your question, is that innovation is really important here because if all you do is take those three elements and you just digitize a status quo process, you might get marginal benefits. You might get some labor productivity enhancement. You may get some margin improvement. You may change an outsourcing agreement to an onshore, you know, RPA deal. But if that's all you do, you're setting yourself up for disappointment because what's really going to happen with thinkers, i.e. those that have innovation is they're going to rethink the process. Most of our analog systems are created around people checking people. So you may have nine steps on making it up in a process that in a digital world only requires one or two or zero with blockchain in some cases. And so if you can rethink that process to go from a nine step to a zero step process or a one step that's a nanosecond long, that changes the dynamic of the process. In fact, that's not even nirvana, right? The real nirvana is can you change your business model? Right? And I would use IBM since we're here as an example of going from a big box and a lot of people running around it called IBM of the past, Watson, to an API engine that David Kenny has helped to build that says we're going to have a platform business model leveraging network effects. And I want to have a supply and a demand curve that are much faster growing than my sort of organic, you know, ways of growing a network could be, right? Through people point clicking. So IBM's an interesting company because there's a company with a lot of legacy but I think gets, as you just described it, when you look at the top five companies by market value today, they're, you know, six, $700 billion market cap companies. They are data companies, not just with a lot of data, but they put data at the core. So it's, you know, it's Amazon, it's Apple, it's Facebook, it's Google, et cetera. They put data at the core whereas most organizations, I'm sure many that you deal with, they have human expertise built around other assets that aren't data. It might be factories. It might be the bottling plant, et cetera. So there's a gap, I don't know, machine AI gap between sort of those that are innovating today. Now granted, the stock market can change and who knows, maybe the oil companies will be back in Vogue, not to throw up. But how do you deal, how do you advise your clients on how to close that gap? That seems like a huge challenge. Well, it is a huge challenge. And I think, you know, going back to the three elements, you know, it would be very easy for you to dive bomb into a transformation effort and say, oh, I'm going to go get some smart computers and hire a bunch of people that know machine intelligence and natural language processing and all that stuff and put them in a room and go create some applications. The bottom line is, that's not unimportant. You've got to get your hand on the mountain and start climbing, but the data piece, I mean, if you don't understand how data is going to be relevant to your business and to your clients and their clients, right, in the future, you lose. And the reason why those five that you talked about earlier are so successful is they think a couple of steps ahead on the data strategy, right? And they're not thinking about, most organizations, by the way, they'll say we want a data strategy and then they'll relegate the strategy thinking part to their businesses, which are bifurcated and they look at the world in silence. And they're doing exactly what they should do, which is take care of those businesses. But when you step back into those five companies you've talked about, they step back from those sides and say, what is the enterprise implications and how do I create new businesses with correlations of data that I didn't have before? I think that requires a whole different level of strategy. It's C-suite and board that has to guide those kinds of decisions. You don't see a lot of people really getting in their hands dirty around intense forward-thinking data strategies at the enterprise level, like we're talking about here. You believe we're entering or going to enter shortly a productivity renaissance? Sort of talking about our off-camera conversation. Explain why you think that, compared to the industrial revolution, take us through your scenario. So when you think about labor, one of the things that I think those three elements will give us as a society, as a global community, is a pretty big escurb jump in labor productivity. In fact, we have in KPMG some efforts to quantify what that might be, looking at what we call frontier firms and applying those practices back to incumbents. 90% of most industry players are saying, what are those differences that we can model? The fact of the matter is, when you go back to the mechanical revolution, the industrial revolution, people did everything by hand prior, right? Equipment helped them do things, whether it was, even the printing press saw changes in society and labor. But when you started getting into heavy manufacturing in the industrial revolution, productivity was enhanced dramatically. And instead of putting all these people who were doing things by hand out of business and out of work, it actually created more jobs, a lot more jobs and a lot more wealth for society. I think we're heading for a similar escurb change with smart computers, cloud and with data and that the roboticism of people is going to be automated and people are going to be allowed to practice and use what's between their ears a lot more. That's going to create value, insight, new questions to be asked. I mean, how many times have you heard this? Every time you answer a question on something that's very important, you want to understand there's two more questions to be asked. Medicine is that way for sure. But you're going to start to see massive advancement in areas where people have had to use a lot of cognitive skills, right? Severely under leveraged because they were doing so much roboticism and doing things that computers can start to do now. So I think you're going to start to see a renaissance, if you will, of people using their noggers in ways we haven't seen before. And that's going to change the dynamics of productivity and labor in a way that's going to create wealth for everyone. And it's going to change industry. So okay, so I got a bunch of questions for you then. Here we go. And I asked this earlier, but I didn't really get an answer. Will machines- From me or from somebody else? No, from somebody else. Okay. Machines make better diagnoses than doctors. And when? You know, look, I mean, what's the regression line? The sample said, I think today you'll find machines giving better diagnoses than doctors in some cases. Okay. I don't know what their regression line sits today, but if you look at the productivity of doctors going a hundredfold in memorial slum catering around lung cancer, it's impressive. And do you want a doctor involved? Yes, you do. Because part of it's an orthodoxy of trust, which by the way, 10 years ago you wouldn't put your credit card online to buy anything, right? It's the same kind of orthodoxy. But I do think that machines can read so much more data, interpolate so many more correlations than people that when you add that to an oncologist, for example, in cancer, you have a super oncologist capabilities, which is really what you're looking for. We're not looking to replace the oncologist per se. What we're looking to is get the productivity of the oncologist from two to two hundred. I'm talking about diagnoses, so you would say yes. Okay. Will large retail stores mostly disappear in your opinion? No, I think they'll change. I think that the customer experience is still, we're still people, we need physical space and we need physical things to touch and smell and feel. I think those things will change, but we'll still need experience. I'm going to keep going because Steve's playing along. Will driving and owning your own car become an exception? Yes. Okay. Well, traditional. I can elaborate if you want. You please, yeah, go ahead. So, I mean, the first, I mean, we actually did a KPMG study called Islands of Autonomy, which modeled LA at San Diego, Atlanta and Chicago, and we modeled how do people move? And we did this for a reason because autonomous vehicles are oftentimes amalgamated as one thing. You know, oh, well, autonomous vehicles are coming, so you better sell your sports cars and your SUVs. Not so fast. The reality is mobility is very different based on where you are. If you're in the middle of, you know, middle of Kansas or something, you're going to need a truck to run around your farm. But if you're in LA or Atlanta or Chicago, you're going to move with autonomy, with autonomous vehicles, and then you're going to really enable mobility as a service very clearly, but differently. The way people move in these cities is different, and if the US auto industry understands those differences and extrapolates those to a global marketplace, they're going to be very advantaged as mobility as a service becomes real. But the first car that goes, I hate all the viewers that love this category, but sedan's the first cars to go. I would say sports cars, I race cars, so I love sports cars. People still ride horses today, but they don't need them for transportation. And SUVs, right, specialty vehicles that you made, it may not, the economies may not be there, but as we know transportation and car ownership, it's going to change fundamentally, and that's going to have a massive effect on FS, right, insurance companies, banks that are doing loans today. It's going to have a big effect on healthcare. Mobility as a service is going to transcend to healthcare, mobile healthcare in ways that we can't see. You've got great perspective. I got one more for you, maybe a couple more. Do you think traditional banks will lose control over payment systems? Well, a lot of them are already nervous about that, wouldn't you think? Yeah, but it hasn't happened yet though. I understand, the bottom line is no, because I think the traditional banks are getting smarter and they're leveraging their own innovation horsepower to understand things like blockchain and how to incorporate those things into their business models. So the answer is, I think the way they do, look, banks exist because of one reason, trust. They have trusted brands, right? As long as they can stay current enough to be relevant to your banking needs, you're going to stay with that trusted brand. I think the trick for banks is how do they move fast enough, leverage the technologies that make your life easier, not waiting three or four days for bank clearing to have a check, for example. I was going to say if you're... And get to that trust in a new way. Unless you're a Bitcoin millionaire, or a billionaire. You still need a bank. Maybe somewhere down the line. Yeah, yeah. Okay, last one, I promise. Will robots and maybe even RPA reverse offshore manufacturing advantages? Yes. Can you elaborate and give us a sense of time for that? Look, I think, first of all, if you really look at what RPA is doing in many ways, it's disintermediating the value of geographic location in many ways, right? So where I may have had, again, this is important to understand, so I can still go offshore today and get labor arbitrage and get margin. But I'm not rethinking the business. What I really want to do is own, I want to have more control and I want to have more flexibility and growth in that back office function. So it would behoove me when you think about RPA and bringing in RPA technology, so I have it one on shore, to leverage the data more securely, potentially, and then leverage that data as part of my lake to say, how do I use that data to correlate to get to what I really need, which is customer relevance at the front office, right? So, look, I think that this whole notion of you're in a different country and therefore the labor pools are different and therefore there's arbitrage and you will get benefits from that. Those days are over. I mean, it's just a question of when does it die? The data value offsets that arbitrage advantage. Well, forget that, the arbitrage is dead itself because you're talking about orders of magnitude cheaper per unit cost for RPA, for a bot to do something that it is for a person that has to eat, sleep, take vacation, get sick and all that stuff. So no matter where they are in the world, so what I would say is that notion is dead. It's just not buried and over time we're going to migrate into machines doing all that robotic stuff. But again, those people, they're going to do different things. It's not like we're going to see hordes, hundreds of thousands and millions of people not being able to work. I think they're going to be doing different things using their heads in different ways. I like that. Thanks for playing. It was good. There's a prize somewhere? I'm absolutely wrong. I just don't know how wrong. Yes. It was fun to think about and you provided some context. It was very useful, so thank you. And I imagine folks that are attending your session and IBM Think on Wednesday are going to hear a little bit more into that. So thanks for sharing. Well, they'll see some specifics, yeah. Thanks for sharing your insight, Stephen, for joining us on theCUBE. You guys said the innovation equation is changing and I thank you for letting me sit between a very innovative and informative conversation. Well, thank you both. It was fun. Next to you. Dave Vellante, I am Lisa Martin. You're watching theCUBE live on day one of IBM Think 2018. Head over to thecube.net to watch all of our videos with our guests and siliconanglemedia.com for all the written articles about that. Also check out Wikibon. Find out what our analysts are saying about all things digital transformation, blockchain, AI, ML, et cetera. Dave and I are going to be right back after a short break with our next guest. We'll see you then.