 Live from Las Vegas, extracting the signal from the noise. It's theCUBE, covering IBM Insight 2015, brought to you by IBM. Now your host, Dave Vellante and George Kilburn. We're back, welcome to Las Vegas everybody. This is theCUBE, we're here at IBM Insight 2015, in he chose, here she's vice president of strategy and business development for IBM analytics. Are you Bob Picchino's right arm or left arm? I always get confused. Both, both, ha ha, right. Depends on the situation. Welcome back, great to see you again. This is the big show for you guys, you know? It's an excellent show for us, and it's really exciting. It's not Bob this morning, he was on, look good, Chris, great message. Oh, a huge lineup of amazing clients, large enterprise, some startups. We've got some, and our partnerships with the weather company, Twitter and Box, all on stage. Yeah, we're going to talk about that. It's true, I was saying earlier, riding down in the elevator, it's like, okay, JP Morgan Chase, B of A, you know, RADPAD, you know, the whole spectrum, you know, it's great. So, you know, we go to a lot of these events in he and the partners are like, okay, you know, we're going to make SAP run faster, we're going to make IBM run faster, whatever it is, we're going to do some converged infrastructure. We have a new channel announcement. You guys are doing partnerships with Box, Twitter, the weather channel, really interesting lineup. Strategy in your title, talk about the partnership strategy. You know, this is so important because most clients say, look, I want to integrate not only the data that I have in my enterprise, I actually want to make sense of it with external data sets, and it could be around behavior patterns, right? Sentiment, understanding of preferences, being able to address real-time opportunities. The second category is kind of unexpected disruptions and environmental conditions actually account for almost a half a trillion of economic loss on an annual basis just in the U.S. alone. So, our opportunity to kind of put what we consider like atmospheric science, you know, data analytics and that rigor of precision forecasting and predictive to really fundamentally change business decision making is a huge opportunity for every client to kind of transform. And so this is what's really exciting about all these partnerships. Yeah, so the weather channel was really interesting talking about how they've transformed their business from one that's sort of, you know, periodic to ones that's, you know, real-time. And we had Dave Haseon, who was the ultra-cyclist. Yes. And IBM helped him predict sort of when to sleep so you have the better weather, maybe not a tailwind, but not a headwind. So we're starting to be able to actually predict the weather, that's kind of relatively new. It is, and not just predict it like for the day or even the hour, but it's 45 days in advance. So if you can do that, then all of a sudden you can do merchandising, inventory management, supply chain in a completely different way. If you could do 45 days in advance, you could also do safety management. I mean, think about the hurricane that was coming up the Pacific side, right? The ability to kind of get people out of danger zones in advance because you have that degree of precision is a huge opportunity to not only be much more effective and efficient, but it's actually protecting citizen safety. So you talk about, you know, sentiment and the like. We heard Coca-Cola at the keynotes this morning talking about going beyond listening. You know, John and I have always talked about, you know, listening, that's nice, but acting is really what people want to do. So what's changed? Is it just that we have the data now? We have the tooling? Talk about what's been able to do. Yeah, I think a number of things have changed. One is the economics of the available technology and compute. Quite honestly, why wouldn't you take advantage of it? And some of that is accelerated not only because of cloud, but it's actually accelerated because of the types of analytic tools and really the software capabilities that are available. And I would say almost every company in some way, is codifying kind of their business in code. So that's point one. The second piece that we're really seeing is new partnerships and where business models are transforming across multiple industries where you see telematics as a great example. Intersection of not only behavior-based driving, understanding aspects of automation within the automobile and transportation logistics, but then you're also linking that into things like insurance to understand risk and risk assessment. That intersection of disrupting various industries is a huge element that's fundamentally different. Would it be fair to say that now that information is a critical input, that we're sort of like reconfiguring the supply chains. It's not just making a better decision about the resupply of your inventory based on weather, but you have new data feeds that are part of your supply chain. And in fact, the insurance companies and the telematics data they can gather can advise you, you the driver, as to how to be a better driver. Absolutely. The machine generated data is one of the hottest growing data sets, whether it's images, video, it could be in the form of text, not to mention sensor data that's coming off of everything, right? Temperature, degree, position, even movement, long lat. And the ability to kind of harness that in a much more economically efficient way, but you really want to tie that to a point that you're making a business decision. I guess somebody else wants to join this interview too. Just tweet us, just tweet us your question, we'll get it in. It's all good, so you know it's live. So it's about making that decision right when you want to make it impactful. The other piece is the users, right? The person that's actually making the decision at that moment may not always be technically proficient, and so what you're seeing is new capabilities that are really designed by role. So one of the things that we've done kind of in a very innovative way in our partnership with Box is working with mobile-first iOS apps around tech experts. So if you think about a knowledge worker technician in field that's trying to remediate, let's say, network problems or your direct TV cable problems or your local internet connectivity, there may be a whole host of issues. They want to be able to access a knowledge repository very quickly and do that in a very seamless experience in the cloud. So that combination of technology, that combination of digital disruption, and then availability of unstructured content is really important. So taking that to the next step, would you be aggregating into data feed portals just the way you would put together functionality for iOS apps that are on the iPad? You could bring in these external feeds where otherwise it might have been left to the user or the corporation that's the consumer of that app. Yeah, we are doing some of that. One of the kind of announcements or let's say class of announcements that you're seeing this week is really around these new insight services and the insight services around things like how weather disrupts not only insurance and health, but emergency management. You're going to see opportunities to put, integrate social sentiment and behavior analytics into areas such as banking and commerce and retail. You're also going to see capabilities around how to enhance security features in the cloud as well. So there's a number of capabilities all around sourcing data from different places, sort of the variety of content and then applying new forms of analytics on. What you're describing is like, as Yogi Berra would have said, deja vu all over again, because the difference between Bloomberg and the Wall Street Journal is, Wall Street Journal saw itself as a newspaper provider of business information. Bloomberg saw itself as a provider of business information. Sounds like IBM is seeing itself as a provider of actionable sort of role-based insights for vertical industries and not just a software or hardware provider. That's a very profound change. It's a huge change in our portfolio actually, shifting into what I consider much higher value solutions and solutions that are oriented by vertical. One of our major announcements was around Watson Health and it's about redefining the way patient care is delivered, understanding everything from what may happen in the hospital to the quality of the care, the diagnostics, clinical treatment, as well as what happens downstream, post in terms of the way information in terms of individual information about behavior tied to your improvements around your health activities. It's all about outcome. So let's talk about strategy. It's in your title. I love to talk strategy. A lot of people come in the queue and say, what's your strategy? Well, our strategy is to make a dupe enterprise ready. And they're like, okay, good, go do that. And then they do it, okay, fine. When you were in discussions three, four, five years ago about the strategy for IBMs, what now is a, well let's see, last, I think public number was $17 billion in analytics business, but it's growing at 20% a year. So you're throwing off, it's at $3 billion a year in new business, which is just mind boggling when you think about the profitless, overcrowded, overfunded, sort of big data field. But anyway, that's a different topic. Maybe we could talk about that too. When you're in strategy sessions, so take us back. When IBM had this sort of diverse portfolio of stuff and you had to create this analytics powerhouse, what were the strategy conversations like? Oh, geez. Take us inside. You want to be a fly on the fly. Yeah, yeah, I mean, it's all history now. We want to see how the sausages were made. So, the thing about analytics, if you think about for the longest time, so at a very fundamental level, leaders always want to make better decisions. And to do that, there's been an evolution of the tools that have been available. And it's always been about how do you extract that knowledge with a degree of confidence then to take action on it? Now, what we were thinking was, how do you actually automate that more into a business process? So, it's not just analytics done on the side, but it's analytics, understanding, instrumented in action, decision, management, right? And then implemented in workflow that's actually governed in the end. So, when we were thinking about next form of analytics, we thought about a number of things. One was at an architectural level, the next generation of the platform. And we were investing and thinking about Hadoop long before Hadoop was ever sexy or hot. It was actually one of our core research projects and assets. The next level we really thought about was, how is that information going to move across various clouds, whether it's on-prem in public clouds, because there's an element of data gravity that's a really important point that people sort of lose sight of. Once you start putting data somewhere, it's really hard to move it around. So, how do you put analytics closer and closer to where the computation is actually occurring and where the data is, right? Then another level we said was, look, what we care about most is outcome. And outcome is only delivered by understanding the full holistic business process, as well as the roles that are involved that are making that decision. And to do that, we had to redefine the experiences around the tool set. And redefining the experience was all about Watson analytics, so we'll go to kind of the original genesis around Watson analytics. It was really about redefining kind of that experience, where you're sort of unleashing for everybody that superhero power. So if you weren't a data architect, you could now do things without requiring one necessarily. Or maybe you weren't as great at visualization and graphics, but now as a data scientist, in addition to that, you could do some of those things. Or maybe data preparation wasn't your thing, but you were really great at some of the search and visual aspects, in which case now you're being powered by the self-discovery, but doing it in an unbiased way, right? Really being driven by the analytics and the rigor of kind of the application in the system. So you started with platform, not products. That's right. Because platforms beat products, it seems, these days. And then you started to build off from their cloud connections, you made that point, Watson. And then the one piece you didn't talk about, which we talked about at the beginning, but I want to sort of tie it into strategies, the ecosystem and the partnerships. Oh, that's a huge, we actually spent a huge amount of time in, I would say, over the course of this last year, because you guys interviewed me last year, actually this day before we made the Twitter announcement. So I was behind the scenes here at the event, as we were trying to furiously sign up all the details of the announcement. The pace of innovation is so fast and every, I would say company across every industry is really competing with the speed of change. And part of the ecosystem thought is, there's going to be new players, new innovations, and I believe that IBM can't necessarily provide everything across all those dimensions. And the only way we can do that is actually do it in partnership and be very grounded in areas that we have deep expertise. We are one of the absolute leaders, not only around analytics, but around deep industry expertise. So you marry that with someone like Box who's really kind of innovated around the edges of enterprise content collaboration platform in the cloud. And then you marry that with someone such as the weather company that's been incredibly digitally disruptive around precision forecasting, atmospheric science, and then you add in consumer applications and advertising. It's a very different mix. Well, you mentioned Box. When I saw the Box, I said, no, IBM's doing a cloud deal. Turns out it's not a cloud deal, it's an analytics deal. It is. With Twitter, obviously, you know, analytics deal, it makes sense, weather, data, okay, yeah. But Box started in your group. That's right, it did. It was good. It was an analytics play. You know what, we have a shared vision. So Aaron and Neil and the whole Box team, Bob and I, we sat down and we said, look, the possibility for us to redefine hybrid implementations around enterprise content, it can be pretty transformative. And if you think about things like workflow and governance and sharing information across knowledge workers and do that by profession and by industry, then there's a whole set of capabilities that you want to enhance on that, whether you're understanding the logic of the data, storing that knowledge, capturing it, processing it, routing it to the right decision makers, that's part of that re-imagining enterprise content in that kind of hybrid implementation that spans globally and internationally. And it was a real excitement about that. And also then kind of innovating together in new R&D areas. So we're really excited to generate net new offerings to market together too. So I'm trying to put a mental model together of you've got data feeds, often external, that you could apply analytics to or that could have analytics come with them. You've got operational applications, often that you might implement perhaps in iOS. You have the analytic output that might come from Watson and then you have your ecosystem. This is a multi kind of dimensional Rubik's cube to me. Can you put some coherence about how you decide which pieces to go to market with? Well, you know, we're fortunate because if you're a 90 billion plus company, we've got a lot of extended colleagues and skills and expertise that are globally available. And when we think about our strategy, we start with what's the client outcomes that we actually want to achieve that fundamentally transformative for them and for the industry. And then if you work from that with the vertical lens, meaning specifically how are you going to transform banking with digitally disrupting not only things like mobile payments, but that retail experience or commercial banking side or wealth management. How do you embed new analytics? How do you embed it in a way that the experience is natural to whoever the users are at a level that's different than requiring necessarily a specific expert on one functionality or feature or product that has to come in intermittently in the middle of a process, right? We're rethinking what's possible and how you blend some of those things. The other piece that we're really conscious of is the shift toward SaaS actually and having a SaaS-first mentality, mobile-first design in our experience as well. So I want to follow up on that because George and I have done a number of events recently and we talked to a lot of customers and they definitely do in cloud, as you said. The cloud fits into their strategy. They certainly do some stuff on-prem but cloud is all the momentum. And what they're doing is they're taking diverse data, bringing it in, blending it, building out this data factory, the analytic pipeline that we talk about, and then they're embedding it into the business process. That's really what, you just took us back five years. That's what you guys wanted to do. That's what they're doing. Now we're doing, yeah. Now, the cloud guys, your cloud competitors, are trying to build that end-to-end pipeline as a service. You guys are doing that same thing with Lumix and SoftLayer as well. You've got a lot of different products in there. You've got guys like Oracle saying, okay, we're going to pour all our money into Fusion middleware. You guys got Lumix. How is that all coming together? What can clients expect in terms of the seamlessness of that data pipeline? Sure. One of the fundamental aspects is the platform itself. So, where and how we've built out the Watson developer cloud in Lumix is where we want enterprise developers to actually get started. And in that environment, you should be able to pick not only the set of APIs but the run times and the special, let's say specialized services that you want to take advantage of. So, a great example is this morning you saw Amy from Wine For Me. And in that, she said, you know, she's really focused on a couple set of Watson developer APIs. It was natural language classifiers as well as speech-to-text capabilities so that any individual consumer that's trying to interact with the application can service themselves, right? So, what we're trying to do is simplify how this could kind of really accelerate new types of innovations, startups and applications. But the second piece that's really important and why you have the skill of IBM and the deep expertise is all around the consulting. You really can't underestimate the importance and the power of knowing deep expertise around if it's supply chain and it's an industrial sector and going deep into mining and all of the steps in between to understand what are the factors that impact that asset and what are the details around things like oil and utilization and fuel and what are the environmental conditions. It's a whole different game than just saying, hey, I've got a product feature over here. Go to my cloud because you just want that one product feature. Well, and one of the really smart things that Ginny did, Ginny and the team with the new organizations was they took pieces of the services organization and said, okay, they're going to go into the respective lines of business. So their analytics group possesses some of that deep industry expertise, correct? Absolutely, and that was a huge kind of reorientation this past year in terms of the alignment. So we actually have a consulting organization that leads first around client success for specific vertical applications, especially in the areas of predictive customer insight, a risk and going deep into risk analytics, also going to things like financial performance management and operations. And you want to know how that scales by getting closer to the app, don't you? Well, I actually wasn't thinking so much about scale, but it goes back to my question where I saw you had all these pieces and I was like, it sounds like a Rubik's cube, but the deja vu now isn't just Bloomberg versus the Wall Street Journal, who's a better information provider. It's actually goes back to Gersner, which was he's like, we have all these product lines and the previous CEO Acres was like I'm just going to spin them all off. And Gersner said, no, let's integrate them into solutions. And it sounds like we're doing that all over again. It's like, you've got the pieces, you've got the expertise now to pick which pieces belong together for each customer you're going to reach. And you're doing it through software. Yeah, yeah, and George, that's really insightful about the solutions piece. And what we're trying to do now is actually, as you marry these pieces together to redefine the solutions, we believe that cognitive is one of the differentiators. Like if everyone's going to go to the cloud or everyone's going to have a digital business, what ultimately differentiates every bank, that's a digital bank, right? It's going to be the way in which cognitive and analytics is embedded in that experience to the end user that fundamentally changes it. And that's what we believe. And so all the solutions that you're going to begin to see across IBM are not only verticalized deeply, but you're going to have embedded capabilities around analytics and cognitive that really differentiates. No wonder Warren Buffett's doubling down. Well, he's, you know, Warren doesn't mind if stock price drops, he wants to buy more. It's all about, you know, the good company. So I mean, you know, this is the thing, IBM's making big bets. Wall Street is, they're impatient. You know, he used to be an analyst on Wall Street. They're not thinking for the long term, but IBM has to. And you're making some giant bets. You're not just saying, all right, let's cut here, cut here, cut here and jack up the stock price. You're saying, let's invest here, invest here, invest here and create new incremental value that's differentiable. That's actually quite unique in the big tech business. You think about it. It is, it's incredibly unique. And a colleague actually said to me, it's a great phrase because everyone's talking about speed and how fast you have to be. And he said, you know what? It's actually about velocity. It's speed with purpose. Just being fast, not knowing exactly where you're going could resolve in a completely different way. But speed with purpose is really about velocity. And when you think about velocity for any company and you look at it from that lens, you realize there's a lot of things that they want in terms of the friction taken out of the system to deliver great experiences to their clients. And that's where we're focused. And we're in a funny place right now. I mean, we, I talked about overcrowded, overfunded, you know, unprofitless. It's going to be, it's going to be interesting. We've talked about this when the, when the funding dries up, what happens. And you know, Wall Street's going to reward growth, but then they'll turn on the dime. Well, they want growth and they will also want profitable growth, right? It's a combination of both. When it, when they start to realize, so they do know this, but it just hasn't reflected in the prices of many stocks. When it costs you $2 to bring in a dollar of revenue, that's fine. But if that doesn't change, then there's going to be interesting times ahead. So I've been seeing it before. Oh yeah. Well, I mean, in our performance this year, actually through this year for analytics, we grew nearly 20%. You're crushing it. I mean, like I said, that's a huge, it's a reflection of the marketplace on how hot it is, but also the breadth of what we have to break. Yeah, that's a seven, you can say this, that's a $17 billion business plus. It's bigger than that now we know, because I think it's three quarters in a row of 20% growth. So that's over 20 billion to the math, headed to 30 billion if you can keep that cadence up, which, you know, no problem. Just a question on that is, are you leading with analytics and then bringing in the other components of the solutions as necessary as the vertical domain efforts? No kid, I know it's coming, business outcomes, no please. You got it, okay. I was going to say, it's actually about the outcome. And then, you know, with every organization, you're going to have people that make different decisions, whether it's around the technology or the application sets or an experience. And we're very much focused on the outcome. In many cases, if you want a better outcome at competitively better prices, economics, at competitively better experience levels, you're going to embed analytics. Who's not going to embed analytics where they need to? I mean, think about some of the most innovative companies that are kind of even emerging across multiple industries. They're actually embedding analytics in their services. So when you think about analytics, there are standalone products and capabilities that people want to build out because they want to really protect and extend the value of their information assets internally. But quite honestly, I think analytics is going to be embedded into everything. And that's also equally why the internet of things is so hot and the intersection of analytics and security in the internet of things is really where that pattern is merging more and more. And you have been a great friend of theCUBE. Thanks so much for stopping by. You're an awesome inspiration for young women in tech and we really always appreciate you coming on. Well, thank you. I always enjoy hanging out with you guys. All right, keep right there. We'll be back with our next guest. Right after this is theCUBE. We're live IBM Insight 2015, right back.