>> Announcer: From the SiliconANGLE Media office in Boston, Massachusetts, it's theCube! (bright music) Now here's your host, Dave Vellante. >> Hi everybody, welcome to this special presentation in the Marlborough offices of theCube. My name is Dave Vellante, and I'm here with a friend, a colleague, a mentor of mine, David Moschella who is an author and a Fellow at Leading Edge Forum. Dave, thanks for coming in. It's great to see you. >> Hey, great to see you again. So we're going to talk about your new book, Seeing Digital: A Visual Guide to Industries, Organizations, and Careers of the 2020s. I got it here on my laptop. Got it off of Amazon, so check it out. We're going to be unpacking what's in there today. This is your third book I believe, right? Waves of Power and... >> David: Customer-Driven IT. >> Customer-Driven IT which was under the '03 timeframe coming out of the dot-com, and to me this is your most significant work, so congratulations on that. >> Well, thank you. >> Dave: I know how much work goes into it. >> You bet. >> So what was the motivation for writing this book? >> Well it's a funny thing when books are a lot of work, and during those times you wind up asking yourself why am I (laughing) doing this because they put in so much time. But for the last seven or eight years our group, the Leading Edge Forum, we've been doing a lot of work mostly for large organizations and our clients told us that the work we've been doing in consumerization, in Cloud, in disruption, in machine intelligence was really relevant to not just them but to their wider audiences of their partners, their customers, their employees. And so people are asking can we get this to a wider audience, and really that is what the book is trying to do. >> Yeah, you guys have done some great work. I know when I can get my hands on it I consume it. For those of you who don't know, Dave originally came up with the theory of disintegration to kind of explain the shift from centralized mainframe era to the sort of open distributed competition along different lines which really defined the Wintel era. So that was kind of your work really explaining industry shifts in a way that helped people and executives really understand that. And then the nice thing about this book is you're kind of open-sourcing a decade's worth of research that yourself and your colleagues have done. So talk about the central premise of the book. We're entering a new era. We're sort of exiting the Cloud, Web 2.0 era. We're still trying to figure out what to call this. But what's the central premise of the book? >> Yeah, the central premise is that the technologies of the 2020s will indeed define a new era, and the IT era industry just evolves. We had the mainframe era, the mini era, the PC and the Internet era, the mobility era, and now we're going in this era of intelligence and automation and blockchains and speech and things that are just a entire new layer of intelligence, and that that layer to us is actually more the powerful than any of the previous layers we've seen. If you think back, the first Web was founded around technologies like search and email and surfing the Web, quite simple technologies and created tremendous companies. And then the more recently we have sort of the social era for Facebook and Salesforce. And all these companies, they sort of took advantage of the Cloud. But again, the technologies are relatively simple there. Now we're really looking at a whole wave of just fundamentally powerful technology and so trying to anticipate what that's going to mean. >> So going from sort of private networks to sort of public networks to a Cloud of remote services to now this set of interrelated digital services that are highly accessible and essentially ubiquitous is what you put forth in the book, right? >> Yeah, and we put a lot of emphasis on words. Why do words change? We had an Internet that connected computers and a Web that sort of connected pages and documents and URLs. And then we started talking about Cloud of stuff out there somewhere in cyberspace. But when we look at the world that's coming and we use those words, pervasive, embedded, aware, autonomous, these aren't words that are really associated with a Cloud. And Cloud is just a metaphor, that word, and so we're quite sure that at some point a different word will emerge because we've always had a different word for every era of change and we're going into one of those eras now. >> So a lot of people have questions about we go to these conferences and everybody talks about digital disruption and digital transformation, and it's kind of frankly lightweight a lot of times. It doesn't have a lot of substance to it. But you point out in the book that CEOs are asking the question, "How do I get digital right?" They understand that something's happening, something's changing. They don't want to get disrupted, but what are some of the questions that you get from some of your clients? >> Yeah, that first question, are we getting digital right sort of leads to almost everything. Companies look at the way that a Netflix or Amazon operates, and then they look at themselves and they see the vast difference there. And they ask themselves, "How can we be more like them? "How can we be that vast, that innovative, that efficient, "that level of simple intuitive customer service?" And one of the ways we try to define it for our clients is how do they become a digital first organization where their digital systems are their face to the marketplace? And most CEOs know that their own firm doesn't operate that way. And probably the most obvious way of seeing that is so many companies now feeling the need to appoint a Chief Digital Officer because they need to give that task to someone, and CDOs are no panacea but they speak to this need that so many companies feel now of really getting it right and having a leadership team in place that they have confidence in. And it's very hard work, and a lot of our clients, they still struggle with it. >> One of the other questions you ask in the book that is very relevant to our audience given that we have a big presence in Silicon Valley is can Silicon Valley pull off a dual disruption agenda? What do you mean by that? >> Yeah, if you look at the Valley historically you could see them essentially as arms merchants. They were selling their products and services to whoever wanted to buy them, and companies would use them as they saw fit. But today in addition to doing that they are also what we say is they're an invading army, and they are increasingly competing with the very customers they've traditionally supplied, and of course Amazon being perhaps the best example of that. So many companies dependent on AWS as a platform, but there's Amazon trying to go after them in health care or retail or grocery stores or whatever business they're in. Yeah, content, every business under the sun. And so they're wearing these two dual disruptions hats. The technologies of our time are very disruptive, machine intelligence, blockchains, virtual reality, all these things have disruptive technology. But that second disruptive agenda of how do you change insurance, how do you change health care, how do change the car industry, that's what we mean, those two different types of disruptions. And they're pursuing both at the same time. >> And because it's digital and it's data, that possibility now exists that a company, a technology company can traverse industries which historically haven't been able to be penetrated, right? >> Yeah, absolutely, in our view every industry is going to be transformed by data one way or another. Whether it is disrupted or not is a second question, but the industry'll be very different when all of these technologies come into play, and the tech companies feel like they have the expertise and the vision of it. But they also have the money, and they're going to bet heavily to pursue these areas to continue their growth agenda. >> So one of the other questions of course that IT people ask is what does it mean for my job, and maybe we can, if we have time, we can talk about that. But you answer many of these questions with a conceptual framework that you call the Matrix which is a very powerful, you said words matter, a very powerful concept. Explain the Matrix. >> Okay, yeah. If we start and go back they have this idea that every generation of technology has its own words, Internet, Web, Cloud, and now we're going to a new era, so there will be a new word. And so we use the word Matrix as our view of that, and we chose it for two reasons. Obviously there's the movie which had its machine intelligence and virtual worlds and all of that. But the real reason we chose it is this concept that a matrix as in matrix mathematics is a structure that has rows and columns. And rows and columns is sort of the fundamental dynamic of what's going on in the tech sector today, that traditionally every industry had its own sort of vertical stack of capabilities that it did and it was sort of top to bottom silo. But today those horizontal platforms, the PayPals, the AWSs, the Facebooks, they run this, Salesforce, all these horizontal services that cut across those firms. And so increasingly every industry is leveraging a common digital infrastructure, and that tension between the traditional vertical stacks and these enormously powerful horizontal technology firms is really the structural dynamic that's in play right now. >> And at the top of that Matrix you have this sort of intelligence and automation layer which is this new layer. You don't like the term artificial intelligence. You make the point in the book there's nothing really artificial about it. You use machine intelligence. But that's that top layer that you see powering the next decade. >> Absolutely, if you look at the vision that everybody tends to have, autonomous cars, personalized health care, blockchain-based accounting, digital cash, virtual education, brain implants for the media, every one of those is essentially dependent on a layer of intelligence, automation, and data that is being built right now. And so just as previous layers of technology, the Web enabled a Google or an Amazon, the Cloud enabled AWS or Salesforce, this new layer enables companies to pursue that next layer of capabilities out there to build that sort of intelligent societal infrastructure of the 2020s which will be vastly different than where we are today. >> Will the adoption of the Matrix, in your opinion, occur faster because essentially it's built on the Internet and we have the Internet, i.e. faster than say the Internet or maybe some other major innovations, or is it going to take time for a lot of reasons? >> I think the speed is actually a really interesting question because the technology of the 2020s are extremely powerful, but most of them are not going to be immediate hits. And if you look back, say, to search, when search came out it was very powerful and you could scale it massively quickly. You look at machine learning, you look at blockchains, you look at virtual realities, you look at algorithms, speech and these areas, they're tremendously powerful. But there's no scenario where those things happen overnight. And so we do not see an accelerating pace of change. In fact it might be people often overestimate the speed of change in our business and consistently do that. But what we see is a sort of fundamental transformation over time, and that's why we put a lot of emphasis on the 2020s because we do not see two years from now this stuff all being in place. >> And you have some good examples in the book going back to the early days of even telephony. So it's worth checking that out. I want to talk about, bring it back to data, Amazon, Google, Apple, Microsoft, and Facebook, top five companies, public companies in terms of market cap. Actually it's not true after the Facebook fake news thing. I mean Berkshire Hathaway is slightly past Facebook. >> It'll be back (laughs). But I agree, it'll be back, but the key point there is these companies are different, they've got data at their core. When you compare that to other companies even financial services industry companies that are really data companies but the data's very bespoken, it's in silos. Can those companies, those incumbent companies, can they close that gap? Maybe you could talk about that a little bit. >> Yeah, we do a lot of work in the area of machine intelligence, artificial, whatever you want to call it. And one of the things you see immediately is this ridiculously large gap between what these leading companies do versus most traditional firms because of the talent, the data, the business model, all the things they have. So you have this widening gap there. And so the big question is is that going to widen or is it going to continue, will it narrow? And I think that the scenario for narrowing it I think is a fairly good one. And the message we say to a lot of our clients is that you will wind up buying a lot more machine intelligence than you will build because these companies will bring it to you. Machine intelligence will be in AWS. It'll be in Azure. It'll be in Salesforce. It'll be in your devices. It'll be in your user interfaces. It'll be in the speech systems. So the supply-side innovations that are happening in the giants will be sold to the incumbents, and therefore there will be a natural improvement in today's situation where a lot of incumbents are sort of basically trying to build their own stuff internally, and they're having some successes and some not. But that's a harder challenge. But the supply side will bring intelligence to the market in a quite powerful way and fairly soon. >> Won't those incumbents, though, have to sort of reorganize in a way around those new innovations given that they've got processes and procedures that are so fossilized with their existing businesses? >> Absolutely, and the word digital transformation is thrown around everywhere. But if it means anything it is having an organization that is aligned with the way technology works. And a good example of that is when you use Netflix today there's no separate sales experience, market experience, customer service, it's just one system and you have one team that builds those systems. In a typical corporation of course you have the sales organization and the marketing organization and the IT organization and the customer service organization. And those silos is not the way to build these systems. So the message we send to our clients if you really want to transform yourself you have to have more of this team approach that is more like the way the tech players do it. And that these traditional boundaries essentially go away when you go in the digital world where the customer experience is all those things at the same time. >> So if I'm hearing you correctly it's sort of a natural progression of how they're going to be doing business and the services that they're going to be procuring, but there's probably other approaches. Maybe it's force, but you're seeing maybe M&A or you're seeing joint ventures. Do you see those things as accelerating or precipitating the transformation or do you think it's futile and it really has to be led from the top and at the core? >> It's one of the toughest issues out there. And the reason people talk about transformation is because they see the need. But the difficulty is enormous. Most companies would say this is a three- or four-year process to make significant change, and this in a marketplace that changes every few months. So incumbent firms, they see where they want to go and it's very hard, and this is why this whole thing of getting digital right is so important, that people need to commit to significant change programs, and we're seeing it. And my parent company, DXC, we do a lot of this with clients and they want to embark on this program and they need people who can help them do it. And so leading a transformation agenda in most firms is really what digital leadership is these days and who's capable of doing that which requires tremendous skills in soft skills and hard skills to do right. >> Let's talk about industries and industry disruption. When you looked at the early disrupted industries whether it was publishing, advertising, music, one maybe had the tendency to think it was a bits versus atoms thing, but you point out in the book it's really not the case because you look at taxis, you look at hotels. Those are physical businesses and they've been disrupted quite substantially. Maybe you could give us some thoughts and insight there, particularly with regard to things like health care, financial services which haven't been disrupted. >> And there's a huge part of the work that I've been doing for years. And as you say, if you look at the industries that actually have been disrupted, they're all relatively low-security, low-risk businesses, music, advertising, taxis, retail. All these businesses have had tremendous changes. But the ones that haven't are all the ones where the stakes are higher, banking, insurance, health care, aerospace, defense. They've been hardly disrupted at all. And so you have this split between the low-risk industries that have changed and the high-risk ones that haven't. But what's interesting to me about that is that these technologies of the 2020s are aimed almost directly at those high-risk industries. So machine intelligence is aimed directly at health care and autonomous systems is aimed directly at defense and blockchains are aimed directly at banking and insurance. And so the technologies of the past if you look at Internet and the Web and the Cloud eras, they were not aimed at these industries. But today's are, so you now have at least a highly plausible scenario where those industries might change too. >> When to talk to companies in those industries that haven't been disrupted do you get a sense of complacency that ah well, we haven't been disrupted, We're going to wait and see, or do you see a sense of urgency? >> No, complacency is baked in for years of people saying, "We've heard all this before. "We're doing just fine. "Maybe it's their industry but not ours." >> Dave: You don't buy it. >> Or the main one is, "I'll be (laughing) retired "before any of this stuff matters for the senior execs." And the thing about all four of those is they're probably true. They have heard all this before because there was a lot of excessive hype. Many of them are doing just fine. Well the one about the other industries is a wrong one, but and many of them will be retired before the things really bite if executive's in their late in their career. So the inertia and the complacency is an enormous issue in most traditional companies. >> So let's do a little lightning round if we can. Oh, actually I just want to make a point. In the book you lay out disruption scenarios for each industry which is really worthwhile. We don't have time to go through that here, but let's do a little lightning round here, some of the questions that you ask that I'd love to get your opinion on of which of course there are no right answers but we can maybe frame it. Let's start with retail. Do you think large retail stores are going to disappear? >> Well the first I say is that disruption is never total. There are still bookstores, there are still newspapers, there are still vinyl records. >> Dave: Mainframes, saving IBM. >> (laughing) Indeed, indeed, but real disruption means that the center of gravity is just totally moved on. And when you look at retail from that point of view, absolutely. And will large ones totally disappear? No, but Wal-Mart is teetering. If you go into a large, Best Buy, a company that strong hero locally, you go into there, there's hardly anybody in there. And so those stores are in tremendous trouble. The grocery stores, the clothing stores, they'll have probably a better future, but by and large they will shrink, and the nature of malls will change quite substantially going forward. People are going to have to find other uses for those spaces, and that's actually going on right now. >> It's funny, it is, and certainly some of the more remote malls you find that they're waning. But then some of the higher-end malls, they seem, you can't find a parking space. What's your sense of that, that that's still inevitable or it's because it's more clothing or maybe jewelry? >> And there's some parts of America that have a lot of money, and therefore they fill up malls. But I think if you look at what's going on in the malls, though, they're becoming more like indoor cities full of restaurants and health clubs and movie theaters and sometimes even college courses and health care centers, daycare centers, air conditioning. Think of them as an indoor environment where you might have the traditional anchor stores but they're less necessary over time. Quite a bit less necessary. >> You mentioned college courses. Education's something we haven't talked about which is again ripe for disruption. Machines, will they make better diagnoses than doctors? >> Yeah, you see this already in image processing, anything that has to do with an image, X-rays and mammograms, cancers, anything, tissues. The machine learning progress there has been tremendous and to the point where schools now should be seriously thinking about how many radiologists do they really want to train because those people are not going to be needed as much. However they're still part of the system. They approve things, but the work itself is increasingly done by machines. And it means increasingly that it's not just done by machine, it's done by one machine somewhere else rather than every hospital setting up its own operations to do this stuff. And health care costs are crazy high in every country in the world, especially here in America. But if you're ever going to crack those costs you have to get some sort of scale, and these machine learning-based systems are the way to do it. And so it is to me not just a question of should this happen, it's that this is so what needs to happen. It's really the only sort of economic path that might work. >> You make the point that health care in particular is really ripe for disruption of all industries. The next one's really interesting to me. You talked about blockchain being sort of aimed at banking and financial services and as an industry that has not really yet been disrupted. But do you think banks will lose control of the payment systems? >> Banks have been incredibly good at keeping control through cash and paper checks and credit cards and ATM machines. They've been really good about that and perhaps they will ride this one too. But you can see countries are clearly going to, they're getting rid of cash. They're going to digital currencies. There's the need to be able to send money around as simply as we send emails around, and the banking industry is not really supporting (laughing) those changes right now. So they are at risk, but they are very good at co-opting stuff, and I wouldn't count them out. >> And the government really wants to get rid of paper money. You've made that point, and the government and the financial services-- >> Work together, and yeah. >> They always work together, they have a lot to lose. >> Yeah, and way back when Satoshi Nakamoto, whoever he or she is or it, they, whatever it is, said that bitcoin would either be very, very big or it would vanish altogether. And I think that statement is still true, and we're still in that middle world. But if bitcoin vanishes, something doing a similar thing will emerge because the concepts and the capabilities there are really what people want. >> Yeah, the killer app for blockchain is for right now it's money. (laughing) >> Yeah, it's speculation, (laughing) I mean it's, (laughing) and no one uses it to buy anything. (Dave laughing) That was the original bitcoin vision of using it to go buy pizzas and coffees. It's become gold, it's digital gold. I mean it's all it is. >> The value store... >> It's digital gold that is very good in the dark Web. >> And if anybody does transact in bitcoin they immediately convert it to fiat currency. (laughing) >> Perhaps someday we'll learn that the Russians actually built bitcoin (Dave laughing) and it's Putin's in control. (David and Dave laughing) Stranger things have happened. >> It's possible. >> Hey, why keep it anonymous? >> They are the masters of the dark Web. (Dave laughing) >> Could be Russians, could be a woman. >> David: Right, right, nobody has any idea. >> Robotic process automation is really interesting with software robots, robots. Do you see that reversing sort of offshoring, offshore manufacturing and other services? >> Not really, I think in general people looked at robotics, they looked at 3D printing and said, "Maybe we can bring all this stuff back home." But the reality is that China uses robots and 3D printing too and they're really good at it. If anything's going to bring manufacturing back home it's much more political pressures, trade strategies, and all the stuff you see going on right now because we do have crazy imbalances in the world that probably will have to change. And as Ben Stein the economist once said, "Well if something can't go on forever, it won't." And I think there will be some reversals, but I think they'll be less about technology than they will be about political pressures and trade agreements and those sort of changes. >> Because the technology's widely accessible. So how far do you think we can take machine intelligence and how far should we take machine intelligence? >> Well I make a distinction right now that I think machine intelligence for particular purposes is tremendous if you want to recognize faces or eventually talk to something or have it read something or recognize an activity or read images and do all the things it's doing, it's very good. When they talk about a more general-wise machine intelligence it's actually really poor. But to me that's not that important. And one way we look at machine intelligence, it's almost like the app industry. There'll be an app for that, there'll be a machine learning algorithm for almost every little thing that we do that involves data. And those areas will thrive mightily. And then sort of the bottom line we try to at that as who's got the best data? Facebook is good at facial recognitions because it's got the faces, and Google's good at language translation because it has the books and language pairs better than anybody else. And so if you follow the data and where there's good data machine learning will thrive. And where there isn't it won't. >> The book is called Seeing Digital: A Visual Guide to the Industries, Organizations, and Careers of the 2020s, and part of that visual guide is every single page actually has a graphic. So really a new concept that you've... >> Yeah, and thanks for bringing that in. And the reason the book is called Seeing Digital is that the book itself is a visual book, that every page has a graphic, an image, a picture, and explains itself below. And just in our own work with our own clients people tell us it's just a more impactful way of reading. So it's a different format. It's great in the ebook format because you can use colors, you can do lots of things that the printed world doesn't do so well. And so we tried to take advantage of modern technologies to bring a different sort of book to the market. >> That's great. So Google it and you'll find it easily. Dave, again, congratulations. Thanks so much for coming on theCube. >> David: Thank you, a pleasure. >> All right, and thank you for watching, everybody. We'll see you next time. (bright music)