 Live from New York, it's theCUBE. Covering Big Data New York City 2016. Brought to you by headline sponsors, Cisco, IBM, NVIDIA, and our ecosystem sponsors. Now, here are your hosts, Dave Vellante and Jeff Britt. Welcome back to New York City, everybody. This is theCUBE, the worldwide leader in live tech coverage. Rob Thomas is here, he's the GM of products for IBM Analytics. Rob, always good to see you, man. Yeah, Dave, great to see you. Jeff, great to see you as well. It's your world traveler. Been all over the place, but good to be here back in New York, close to home for one day. Yeah, at least a day. But the whole community is abuzz with this article that hit, you wrote it last week, it hit new co-shift, I guess just today or yesterday, the end of tech companies. Yes. And you got some really interesting charts in there. You got some ugly charts. You got, you know, HTTP, you got, let's see. Got Imperva. Teradata. Teradata, Imperva. Yes. Looking pretty, we talked about this last year, just about a year ago, we said, you know, the nose of the plane is up, but the planes are losing altitude and when the funding dries up, look out. Interesting, some companies still are getting funding, so there's some mixed rip currents, but in general, it's not pretty for pure play sort of Hadoop companies. Something that you guys predicted a long time ago, I guess. So I think there's a macro trend here, and this is really, I did a couple months of research and this is what went into that end of tech companies post and it's interesting. So you look at it in the stock market today, the five highest valued companies are all tech companies, what we call, and that's not a coincidence. The reality is, I think we're getting past the phase of there being tech companies and tech is becoming the default and either you're going to be a tech company or you're going to be extinct. I think that's the MO that every company has to operate with, whether you're a retailer or in healthcare or insurance or banking, it doesn't matter. If you don't become a tech company, you're not going to be a company. That's what I was getting at. And so some of the pressures that I was highlighting was, I think what's played out in enterprise software is what will start to play out in other traditional industries over the next five years. Well, you know, it's interesting. We talk about these things years and years and years in advance and people just kind of ignore it. Like Benioff even said, more SaaS companies are going to come out of non-tech companies than tech companies, okay. We've been talking for years about how the practitioners of big data are actually going to make more money than the big data vendors. Peter Goldmacher is actually the first. That was one of his predictions that hit you. Many of them didn't. Peter's a good friend of mine as well. So I always like pointing out what he says that's wrong. But we sort of ignored that and now it's all coming to fruition, right? Your article talks about, it's a long read but it's not too long to read, so please read it. But it talks about how basically every industry of course getting disrupted, we know that, but every company is a tech company. Right. Or else. Right. And you know, what I was, so John Battelle called me last week. He said, hey, I want to run this. He said, because I think it's going to hit a nerve with people. And we were talking about why is that? Is it because of the election season or whatever? People are concerned about the macro view of what's happening in the economy. And I think this kind of strikes at the nerve that says one is you have to make this transition. And then I go into the article with some specific things that I think every company has to be doing to make this transition. It starts with you got to rethink your capital structure because the investments you made, the distribution you model that you had that got you here is not going to be sufficient for the future. You have to rethink the tools that you're utilizing in the workforce because you're going to have to adopt a new way to work. And that starts at the top by the way. And so I go through a couple different suggestions of what I think companies should look at to make this transition. And I guess what scares me is I visit companies all over the world. I see very few companies making these kind of moves because it's a major shakeup to culture. It's a major shakeup to how they run their business. And I use the Warren Buffett quotes. When the tide goes out, you can see who's been swimming naked. The tide may go out pretty soon here. And it will be in the next five years. I think you're going to see a lot of companies that thought they could never be threatened by tech if you will, go the wrong way because they're not making those moves now. Well, let's take cognitive now that we're on this subject because you're having a pretty frank conversation here. A lot of times when you talk to people inside of IBM about cognitive and the impact it's going to have, they don't want to talk about that, but it's real. Machines have always replaced humans. And now we're seeing that replacement of cognitive functions. And so that doesn't mean value can't get created. In fact, way more value is going to be created than we can even imagine. But you have to change the way in which you do things in order to take advantage of that. Right. So one thing I was saying in the articles, I think we're on the cusp of the great re-skilling, which is you take all the traditional IT jobs, I think over the next decade, half those jobs probably go away, but they're replaced by a new set of capabilities around data science and machine learning and advanced analytics, things that are leveraging cognitive capabilities, but doing it with human focus as well. And so you're going to see a big shift in skills. This is why we're partnering with companies like Galvanize, I saw Jim Dieter when I was walking in, Galvanize at the forefront of helping companies do that re-skilling. We want to help them do that re-skilling as well. And we're going to provide them a platform that automates the process of doing a lot of these analytics. That's what the new project data works, a new Watson project is all about, is how we begin to automate what have traditionally been very cumbersome and difficult problems to solve an organization, but we're helping clients that haven't done that re-skilling yet, we're helping them go ahead and get an advantage through technology. We're also going to follow up too on a concept on the capital markets and how this stuff is measured, because as you pointed out in your article, the valuations of the top companies are huge. That's not a multiple of data right now. We haven't really figured that out and it's something that we're looking at. The Wikibon team is how do you value the data from it used to be a liability because you had to put it on machines and pay for it. Now it's really the driver. There's some multiple of data value that's driving those top line valuations that you point out in that article. You know, it's interesting and nobody has really figured that out because you don't see it showing up, at least I don't think in any stock prices. Maybe costar would be one example where it probably has. They've got a lot of data around commercial real estate. That one sticks out to me, but I think about in the current era that we're in, there's three ways to drive competitive advantage. One is economies of scale, low-cost manufacturing. Another is through network effects, number of social media companies have done that well. But third is machine learning on a large corpus of data is a competitive advantage. If you have the right data assets and you can get better answers, your models will get smarter over time. How's anybody going to catch up with you? They're not going to. So I think we're probably not too far from what you say, Jeff, which is companies starting to be looked at as a value of their data assets. And maybe data should be on the balance sheet. Well, that's what I'm saying. And eventually it doesn't move to the balance sheet as something that you need to account for because clearly there's something in the Apple number and the alphabet number and the Microsoft number that's more than regular. Exactly, it's not just about the distribution model. You know, large companies for a long time, certainly in tech, we had a huge advantage because of distribution, our ability to get to other countries face-to-face. But as the world has moved to the internet and digital sales and try-by, it's changed that. Distribution can still be an advantage, but it's no longer the advantage. And so companies are trying to figure out what are the next set of assets. It used to be my distribution model, now maybe it's my data, or perhaps it's the insight that I developed from the data, that's really changed. Yeah, in the early days of the so big data meme taken off, people would ask, okay, how can I monetize the data as opposed to what they're, I think, really asking is, how can I use data to support making money? Right, right. And that's something that a lot of people, I don't think really understood, it's starting to come into focus now. And then once you figure that out, you can figure out what data sources and how to get quality in that data and enrich that data and trust that data, right? I mean, those are, is that sort of a logical sequence that companies are now going through? It's an interesting observation because you think about it, the companies that were early on in purely monetizing data, companies like Dunn and Bradstreet come to mind, Nielson come to mind, they're not the super fast-growing companies today. So it's kind of like there was an era where data monetization was a viable strategy and there's still some of that now, but now it's more about how do you turn your data assets into a new business model? There was actually a great, New Clay Christiansen article was published, I think last week, talking about companies need to develop new business models. We're at the time, everybody has kind of developed and we sell hardware, we sell software, we sell services or whatever we sell. And his point was now is the time to develop a new business model. And those will, now my view, those will largely be formed on the basis of data, so not necessarily just monetizing the data to your point, Dave, but on the basis of that data. So I love the music industry because they're always kind of out at the front of this evolving business model for digital assets in this new world and it keeps jumping, right? It jumped, it was free, then people went ahead and bought stuff on iTunes, now Spotify has flipped it over to a subscription model and the innovation of changing the business model not necessarily the products that much, it's very different. I think it's interesting, it's just the digital assets don't have scarcity, right? They're scarcity around the data but not around the assets per se. So it's a very different way of thinking about distribution and kind of holding back. How do you integrate with other people's data? It's not the same. So think about, that's an interesting example because think about the music and there's a great documentary on Netflix about tower records and how kind of tower records went through the big spike and now it's kind of obviously no longer really around. Same thing goes for the blockbusters of the world. They got disrupted by digital because their advantage was a distribution channel that was in the physical world and that's kind of my assertion in that post about the end of tech companies is that every company is facing that. They may not know it yet but if you're in agriculture and you're a traditional dealer network is how you got to market, whether you know it or not that is about to be disrupted. I don't know exactly what the form that will take but it's going to be different and so I think every company to your point on you look at the music industry kind of use that as a map. That's an interesting way to look at a lot of industries in terms of what could play out in the next five years. It's interesting that you say though in all your travels that people aren't, I would think they would be like clamoring, oh my gosh, I know it's coming, what do I do? Because I know it's coming from an angle that I'm not aware of as opposed to it's like you see a lot of people don't see it coming. It's not my industry, it's not going to happen to me. You know, it's funny, I think, I hear one perception I hear as well, we're not a tech company so we don't have to worry about that which is totally flawed. Two is, I hear companies that, I'd say they use the right platitudes. We need to be digital. Okay, that's great to say but are you actually changing your business model to get there, maybe not. So I think people are starting to wake up to this but it's still very much in its infancy and some people are going to be left behind. So the tooling and the new way to work are sort of intuitive. What about capital structure? What's the implication to capital structures? How do you see that changing? So it's a few things. One is you have to relook at where you're investing capital today. The majority of companies are still investing in what got them to where they are versus where they need to be. So you need to make a very conscious shift and I use the old McKinsey model of horizon one, two and three but I insert the idea that there should be a horizon zero where you really think about what are you really going to start to just outsource or just altogether stop doing because you have to aggressively shift your investments to horizon two, horizon three. You really got to start making bets on the future. So that's one is basically a capital shift. Two is to attract this new workforce when I talked about the great re-skilling. People want to come to work for different reasons now. They want to come to work to work in the right kind of office in the right location that's going to require investment. They want a new comp structure. They're no longer just excited by a high base salary. Like they want participation in upside. Even if you're a mature company that's been around for 50 years are you providing your employees a meaningful upside in terms of bonus or stock? Most companies say, we've always reserved that stuff for executives. There's too many other companies that are providing as an alternative today. So you have to rethink your capital structure in that way. So it's how you spend your money but also as you look at the balance sheet how you actually are spreading money around the company I think that changes as well. So how does this all translate into how IBM behaves from a product standpoint? We have changed a lot of things in IBM. Obviously we've made a huge move towards what we think is the future around artificial intelligence and machine learning with everything that we've done around the Watson platform. We've made huge capital investments in our cloud capability all over the world because that is an arms race right now. We've made a huge change in how we're hiring where we're building offices. So we put an office in Cambridge downtown Boston put an office here in New York downtown. We're opening the office in San Francisco very soon. This is Park Center downtown. So we've kind of come to urban areas to attract this new type of skill because it's really important to us. So we've done it in a lot of different ways. Excellent and then tonight we're going to hear more about that right? You guys got a big announcement tonight. Big announcement tonight. Ritika was on. She showed us a little bit about what's coming but what can you tell us about what we can expect tonight? Our focus is on building the first enterprise platform for data which is steeped in our artificial intelligence. First time you've seen anything like it. You think about it, the platform business model has taken off in some sectors. You can see it in social media. Facebook is very much a platform. You can see it in entertainment. Netflix is very much a platform. There has really been a platform for enterprise data and IP. That's what we're going to be delivering as part of this new Watson project which is data works. And we think it'll be very interesting. Got a great ecosystem of partners that will be with us at the event tonight that are bringing their IP and their data to be part of the platform. It will be a unique experience. What do you, I know you can't talk specifics on M&A but just in general and concept. In terms of all the funding we talked last year at this event, how the whole space was sort of overfunded, overcrowded, you know, and something's got to give. Do you feel like there's been, given the money that went in, is there enough innovation coming out of the sort of Hadoop big data ecosystem? Or is a lot of that money just going to go poof? Well, you know what, I mean, we're an interesting time in capital markets, right? When you loan money and get back less than you loan because interest rates are negative, it's almost, there's no bad place to put money. Like you can't do worse than that. But I think, you know, the Hadoop ecosystem, I think it's played out about like we envision which is becoming cheap storage. And I do see a lot of innovation happening around that. That's why we've put so much into Spark. We're now the number one contributor around machine learning in the Spark project which we're really proud of. Number one. Yes, in terms of contributions over the last year, which has been tremendous. And, you know, in terms of companies and the ecosystem, I look, there's been a lot of money raised which means people have runway. I think what you'll see is a lot of people that try stuff, it doesn't work out, they'll try something else. Look, there's still a lot of great innovation happening. And as much as it's the easiest time to start a company in terms of the cost of starting a company, I think it's probably one of the hardest times in terms of getting time and attention and scale. And so you've got to be patient and give these bets some time to play out. So you're still sanguine on the future of big data. Good. When Rob turns negative, then I'm concerned. It's definitely, we know the end point is going to be massive data environments in the cloud, instrumented with automated analytics and machine learning. That's the future. Watson's got a great head start, so we're proud of that. Well, you've made bets there. You've also, I mean, IBM, obviously a great services company for years services led. You're beginning to automate a lot of those services, package a lot of those services into industry specific software and other SaaS products. I mean, is that the future for IBM? It is. I mean, I think you need it two ways. One is you need domain solutions, vertical eyes that are solving a specific problem. But underneath that you need a general purpose platform, which is what we're really focused on around data works is providing that. But when it comes to engaging a user, if you're not engaging a what I would call a horizontal user, a data scientist or a data engineer or a developer, then you're engaging the line of business person who's going to want something in their lingua franca, whether that's wealth management and banking or payer underwriting or claims processing in healthcare, they're going to want it in that language. That's why we've had the solutions focused that we have. And they're going to want that data science expertise to be operationalized into the products. Yes. You know, it was interesting. You know, we had Jim on and Galvanize and what they're doing and sharp partnership, Rob. You guys said, you know, I think made the right bets here and instead of chasing, you know, a lot of the shiny new toys sort of thought ahead. So congratulations on that. Well, thanks. It's still early days. We're still playing out all the bets, but yeah, we've had a good run here and we'll look forward to the next phase here with DataWorks. All right, Rob Thomas, thanks very much for coming on theCUBE. Appreciate it. It's nice to see you. All right, keep it right there, everybody. We'll be back with our next guest right after. This is theCUBE, we're live from New York City. Right back.