 Live from the Mandalay Convention Center in Las Vegas, Nevada, it's The Cube at IBM Insight 2014. Here are your hosts, John Furrier and Dave Vellante. Okay, welcome back everyone here live in Las Vegas for IBM Insight. This is The Cube, where we go out to the events, extract the silver from the noise. I'm John Furrier. My co-host Dave Vellante and our next guest is Glenn Finch, global leader of Big Data Analytics at IBM, 25 years in banking. You've been around the block, but Big Data is certainly driving a lot of value. Welcome to The Cube. Thanks John. Hey Dave, thanks. So the surveys are out there. We were going to talk about a survey you're getting behind and really that teases out the big thing, which is, and Kobielus was on earlier, and he's like, okay, speed is the key advantage. That's something that's in some of your work you've done, you're kind of teasing out the key trends. Speed sees me number one. Can you share some thoughts on this new survey? Sure. Every year for the last six years, we publish this survey. I got to tell you, in Vegas, to be talking about the number six, it's not a great day to be talking about. Anyway, so. Just add one. Yeah, that's right. I want to get to seven next year, you know what I'm saying? Anyway, so. We want to get to game seven. That's right, that's right. Six years doing this. Last year, everybody was talking about value. This year, everybody's talking about speed, and not just a little bit of speed, but radical change in speed. Big speed. Big speed. Big data, big speed. But we have what's goofy though. Last year, everybody was talking about volumes of data. Now they're talking about velocity of data. And in the consulting business, when things move a percent or two, that's like, it puts people to sleep. This year, we're talking about stuff moving 20, 30, 40%. Big swings around this whole concept of velocity. Does that make sense, guys? Yeah, totally. Well, so let me ask you, how were they defining value? How were they quantifying value? What was it? Saving money, making money? What was value last year? That's a great question, Dave. So, I wouldn't say that the metrics have changed around value from year to year, right? You kind of have this split last year, 75% of value definition was around customer acquisitions, revenue, growth, cross sell, and 25% was around operations. Big change this year, 53%. So the 75 goes down to 53% with customer, and the piece on operations grows from about 25% to 40%. So you've got a little bit more cost reduction creeping back in this year, right? But the wild thing that hit this year, 63%, 63% of all the clients said they're getting value from data projects within a year. So no more two year, three year, big data warehousing projects, 63% say that they're getting it in year. Massive, massive shift. Now, our data shows a couple interesting things. One is that there's a schism, actually, between the IT people and their definition of value and the business people. Are you seeing a sort of similar dissonance, or are you seeing more alignment? You know what's interesting, what's starting to happen is with big data, where people aren't taking two years to build a warehouse, right? Where you're throwing data into a reservoir and you're coming up with findings now, actually that schism is closing somewhat, right? Because the guys that are online in business can see that you're answering their questions quick. Because there's no way you can get to value in less than a year if you're not answering business questions, big, big difference, right? So value is a proxy for, I'm interested in the topic, speed isn't a proxy for this stuff happening. Right. What's next, get the speed? Outcomes, like results? I mean, so what's year seven? Let's go to your mind next year. What do you want to see in next year's report? If speeds today, that means I'm buying in memory flash, I'm doing some integration, I got some apps coming out there, I'm probably developing in real time, focusing on real time stuff, engagement, okay, I got that, do speed for a few years? So John, you hit it on this whole thing about outcomes, right? The concept of doing outcome-based work changes everything. So that instead of committing to project 32, you know what I'm saying? We commit to a change in a business outcome, right? Increased sales or, you know, add budget reduction or something. Right, not completing project 32. Right, right, not completing project two, but to change a fundamental business driver, right? So, we had a couple clients on stage with us today. One of them, they're going to drive hundreds of millions of dollars of benefit by shrinking how much fraud hits them. Hundreds of millions of dollars in fraud. It's an insurance company, right? They're paying out too much money in claims because people are doing some unscrup- Right, it's a bad outcome. Right, but back to the speed thing. We're doing that. In fact, we went live today in less than eight months. So the concept of moving quick and driving outcomes, that's what we're seeing. Now you know the goofy part. There's one thing we didn't talk about in this study. 7% of the respondents said that we're spending time on the office of the CFO. Now this is the goofiest darn thing I think. So he asked me what I expect to see next year. So I was on CNBC this year. We released our CFO study. CFO studies says CFOs are spending 250% more time integrating data. I'm thinking you better go to the place where the money is and help that person, right? Go help the CFO. So I think we're going to see more outcomes and I think we're going to see more stuff in the office of the CFO. You can appreciate this joke. Steve Herrod, who was used to be the CTO of VMware now as an adventure capitalist said, why do people rob banks? Because that's where the money is. That's where the money is. Exactly, exactly. So back to business outcomes. What do you work on first? Where's the money? Right, and that's what I was thinking like, it's the CFO for God's sakes, right? You're going to go ask the CFO to fund a project, but you're only spending 7% of your time with the CFO. There's a, you're biting the hand that's feeding you there. So I think we're going to see some pretty big swells. So you think the data's going to level the playing field for what I call the bullshit projects. You know when you say project 32, there's a handful of stuff going on that's going to like, okay, why are we doing that? Why are resources being committed to it? So internal analytics are also important. Well, or the metrics of success in project 32 is, hey, it works, the server light is green. Exactly. We're done. Right. And the business guy says, well, what did I get? Right. And that's the issue. That's the disconnect between IT and the business US. And that's the thing that's starting to draw business people and technology people more together because they can see outcomes from some of these, you know, quick little mercenary kind of analytical projects, right? Not the big two year, 100 million dollar, see you later and hope. But I know, so I got to ask you about the CFO. Yeah. Is the CFO, the office of the CFO qualified to do that data integration? Or is some, certainly in financial services, you've seen this chief data officer emerge. Who's responsible for data integration? That's where the money is. We see it in our surveys too. Data integration, number one tool set and challenge for big data practitioners. Right. How to integrate the data, data quality, data governance. Who owns that? What an awesome question. So, you know, this whole concept of the office of the CDO, the CFO, first of all, I'm not going to say that somebody is not qualified to do something because I don't want to whack at any, you know, CFOs out in the audience. But let me say this. Let me say this. But if I'm a CFO, I'm not sure I want to own it. No, no, you don't want to, right? You have had to build this cottage industry of fixing data as a CFO because nobody's doing it for you, right? So when somebody's spending two and a half times, more time doing something, think about the CFO for God's sake. They shouldn't be spending time there, right? So you see- And maybe it made sense post-Enron. It did, right? But now, a different animal. It doesn't. So that's why you're starting to see a lot of the chief data officer roles pop up, right? And you're starting to see a lot of people question, how can I integrate all this stuff that I just spent all this money putting in? Because there's a lot of SAP projects out there, a lot of Oracle projects, a lot of those kind of big financial transformation things. You would think that the amount of time integrating data would be going down, and it's not, right? So that tells me there's a real opportunity. And because the amount of data is exponentially growing, the metrics of success are changing, like you said, it's velocity now, it's not just amount. Yeah, unbelievable. Now, the office of the CFO, what we're seeing them start to do is to look deeper, you know, data breeds data, right? So you see the CFO starting to look for more and more things within the data. So they now start to have some level of data integration, and they say, I wonder what's causing this? So they dig deeper. Well, to dig deeper and find causality, they got to go get more data, right? So it's like a giant, ongoing mining exercise. So Glenn, I got to ask you back to my question earlier, because this is a good tie back into some of the things I was doing about the green light being on Project 32, server works, yeah, we're done. Speaks to what Wikibon is coming out in a different market in the Hadoop space where IT grades themselves, they're doing pretty good. They rolled out the POC and it's up and running and they give themselves high grades. Yet the business unit says, no, you suck. I mean, we need more value. So that's been going on in IT in business for ever since computing's been on. It's been quiet, yeah, 25 years you've been banking. Certainly banks are doing a lot of cutting edges for the money, they got to protect it. So you see an early indicator. What are you seeing as the way to arbitrate between those two groups? What's the key force right now that you're seeing in the customer environments where people are making, where it's certainly a collision course, it has to be a team effort. That's clearly coming out of the data we're seeing from all the conversations is that hey, we've got to get along, it's a team effort, the cloud helps, there's a lot of leverage, more creativity. So how do they make that work? What are the successful use cases and don't name names, but you can just say success and where it's not working? Yeah, so one of my favorite stories is with the leading coffee company we've worked with. They had the same store sales problem, right? Now they thought their same store sales problem had to do with food products. So they went out and fundamentally changed all the food products that they had. Change the menu. Right, go buy a bakery. It's definitely not the coffee. For God's sakes, I drink so much of that stuff every day for this particular coffee. It was their sacred cow. It is, right. So they went and bought a bakery, didn't change things, and then they said okay, we don't know where to go, so let's pull a bunch of data together. So we pulled weather data and economic data and you name the data, right? To get that done, you can't have IT and data people there. You got to have the business people, everybody's staring at the data, looking for what it's about to say. Remember when Agile was so cool when you're building, remember that whole, sure. That's kind of what big data is right now because everybody's moving in a very agile manner. If in a space of a few weeks you can put data into a reservoir and start finding things, it's unbelievable. Guys, I got a question back for you. What do you think the single greatest predictor of same store sales for this coffee company was? What do you think? Ah, weather. Weather? What was the problem again? Same store sales. Yeah, same store sales. Same store, you say weather. Okay. Okay, I'll help you out. I'd say, go ahead. I'd say quality. It was the barista. The person, the barista. Oh yeah? Yeah, the person making the coffee. It's the service. It is, so it's that experience, exactly, the personal experience. They didn't know that. The data. How they greeted, how they exit. Did they get, they had a nice smoozing experience. Dave, John, you want the latte? It's whether or not they smile. Right, right. They know their name, you know. Yes, so I think what you're seeing is this kind of scrum-like environment, right? Where everything's moving very quickly. How do they do that? How do people, because that's what, I think people see that as like, you know, that's the value. Now the speed game kicks into your survey. Okay, now let's make that happen. You know, throw the holy water on the magic process. It's really a people issue, right? So how does that leadership get the two groups working together? Have you seen any successful formulas? I think when you have sponsorship from the top down to do something like this, as compared to the bottom up, you have people showing up game on, game up, ready to go. And just looking for new things, looking for cool, fun things that are going to happen. So approach, how they approach their job. Right, so it's about approach and showing up expecting something is going to be good. Not trying to figure out the tools. I feel like the giants beat the royals. They show up and keep on pounding away, scrapping away, you know. I don't even want you to see it's even harder, okay? Getting the nationals to play. But getting people to show up thinking that something's going to go right is a whole lot different than getting people showing up thinking that 27 things are going to go wrong if they can just figure out how to put a stop to this, right? But it's daunting when the data starts to speak. That's when new levels of leadership got to step up again. So it's unbelievable. Share what's going on in the banking financial sector because obviously that's a great early adopter on all things, engagements. So that's, I mean, all things in tech. They're buying the latest and greatest Ferrari, glass drives, drive, you name it. They got security issues and believe me, they got to protect the money. So there's certainly a lot of innovation going on, bleeding edge. What do they view security and engagement? Those two separate topics, security, clear, mandate. Engagement's a new concept because now the mobile consumer, it used to be my bank experience was how great the lobby was when I walked in, the teller, if you will. Now I have an app. Are the chairs comfortable? Now I have an online app and I've got to deal and do my online banking. Now there's fraud, oh my God, who's fishing? Talk about the dynamics in the financial sectors. And so John, you hit the topic of fraud. Clearly data finding data, this whole concept of context computing, right? Data's moving so quickly now that we don't have the ability to know what this piece of data is meaning, right? Especially in fraud, especially in risk. When you can start putting together disparate, seemingly unconnected data together, you find massive amounts of value around fraud, around risk. Now, that's kind of trying to find bad things that are happening. You can take that same approach to find the good things, right? So back to your concept of customer experience, you can know what people want and serve it up to them in a dynamically deployed app world in real time. So you've got data for good, data for bad, right? The same techniques kind of flow and drive through both things. So financial institutions are using it as you rightly put to protect the money around risk and fraud and then to drive consumer engagement. But the problem is, you got to get it linked first, right? Because just, there's so many bunny holes, there's so much noise in the data, right? You could run down the wrong path and do it and just irritate a bunch of people. Well, you look at what's going on with Apple Pay, right? Elbow in their way into financial services, but everybody wants the data. Yeah, but I think first data is powering that back end so they're not really, they're just UI and putting the UX on in front of that. So I mean, direct business model, I mean, that's the web. I mean, the internet started with the web, now we're in social business. It's changing. It's completely, the leveling of the playing field, thanks to things like Amazon and Bluemix and all the stuff going on. So just throw out the projected for next year. We're going to end the segment here, getting pressed on time, getting the hook here. Glenn, tell us. I feel it, yeah. Well, no, we actually got the hook. I want to stretch it out. I want you to say seven years out, the seven year itch is coming for you on the next survey. What do you anticipate? Speed again? I mean, there's going to be four years of speed. Is that build out? Is there going to be more speed than now let's get organizational behavior? Or what are you anticipating? You have to guess. So I think we're going to see speed again because it's just come into the fray, right? I think secondly, you know, you hit on it. We are starting to get so fast that the human dimension is unable to cope. So we're going to see a bunch of folks trying to figure out how to get people to move as fast as the data and the analytics. And then third, I think you're going to see a couple of those segments, the office of the CFO. I think we're going to see them come into the fray, where they have not been before, right? Very, very important. The stakes are high. They've got to come into the kitchen. They've got to. Absolutely. Yeah, it makes a lot of sense. And we would tell the CDO concept is that there's also compliance issues too, right? I mean, it's like, oh my God. You go another half hour on that. We could. And you know, the office of the CDO, clearly, you know, five years ago, there were five of them. This year, there's 150. And by a couple years from now, there'll be 250, right? It is the hottest job role right now because people know they've got to go game up with that, right? So how that role plays in, how it's going to affect all these answers, we're going to see a lot of change. Creative, curiosity, good communication. That seems to be the skill set for big data. We are here doing that here on theCUBE. We're curious, we're communicating. And of course, we're creative. We're talking to all the great guests here at IBM Insights. Just bringing all the data, sharing that with you. This is theCUBE inside the Social Media Insight Go Center special presentation, amazing third experience, third screen, second screen digital experience here with an IBM with their social media team. This is theCUBE, we'll be right back after this short break.