 Okay, welcome back, live in Las Vegas is theCUBE, IBM's Information on Demand Conference. This is theCUBE exclusive coverage, SiliconANGLE, Wikibon here live. I'm John Furrier, the founder of SiliconANGLE. I'm Joe, my co-host Dave Vellante, co-founder of wikibon.org. Our next guest is Fred Balboni, global leader, business analytics, optimization, IBM, GBS, global business services. Obviously big data is powering the world. Just the demand for information and solutions is off the charts. Fred, welcome to theCUBE. Thank you, John. There's a services angle here where services matters because one, in the channel partners, it's good gross profit for helping customers implement solutions that they have demand for. So you have a combination of a market that's exploding with demand. People know it's a game changer with big data analytics. Cloud is obviously right there on the horizon in terms of on-prem, off-prem. Then you've got obviously mobile devices bring your own device to work which is throwing off more data. And then people want to be in all the different channels of social business. CIO to CEO says, hey, this new wave is here. If we don't think about it now and get a position and understand it, the consequences of not doing anything might be higher than they are. So we've heard that. How do you look at that? And what are you guys doing? What's the strategy? Give us the quick update from GBS. I think that to make this successful, first of all, services is important. It's the last mile. That means the point you made. It's the last mile. And without that, you cannot ever deliver the value. The really interesting challenge that every executive faces is you need to be able to, we can easily get our head around big data technology. And I shouldn't trivialize that, but you can go and understand the technology, what's possible in big data. You can also get your head around analytics and the analytics algorithms and the kind of insights that can be drawn from that. The real challenge is how do you articulate what's kind of possible to a client? Because many of the use cases are very niche. And so clients often say, yeah, that's right, but it's possibly bigger than that. Yeah, that's right. It's possibly bigger than that. The other issue or the other challenge to get, we've got to, hurdle, we've got to jump in and articulate this to the businesses. Clients, businesses, think in terms of process. They don't think in terms of data. You don't go talk to a CEO and say, you know, tell us what's the key attributes of your customer. And they don't think that way. They can talk to you about servicing a customer or selling to a customer or managing customer complaints to the processes, but the data, it's a tough thing. So the first part of the services is so crucial in this is being able to articulate the value of analytics and big data to a client in the business's terms. So it becomes a boardroom conversation. So that gets the program started. And then quickly being able to fill in with use cases because clients don't want this to be, they don't want to start from a blank sheet of paper and they don't, like, you know, give me some quick wins here. So it's kind of those things. What kind of timetables? I remember back in the 80s, 90s when client server rolled out. It was months and months, you know, project management meetings, roll out the Oracle systems, roll out the big iron. Now, I mean, obviously, you may be shorter spurts, little different hurdles. What's the timetable on some of these horizons for these quick wins? Okay, so, you know, project implementations. Like tomorrow or the day. But no, let's, no, it's, it's, I think that, that we're measuring project implementations in weeks. I think cloud-based technology allows us to provision environments on the order of a couple of weeks. And that used to be on the order of five to six months. So I think that's gonna, that accelerates everything. And that also allows you to do a lot of, a lot more speed to value, get applications or analytics use cases up there much more rapidly. One, two, as you start to build these portfolio of use cases. And if they're built on acceleration tools, I mean, accelerates, so you've got those code sets that are already there that you can, you can jump on top of. I mean, you can get these use cases up there in six, eight weeks. I mean, we have one, we have one example. A really, a large major company, and I'd rather not, I'd rather not, because it's not externally referenceable, but really a significant client that had on the order of more than, more than five million discrete customers. And doing detailed customer analytics on their customer base against their products. And we were able to get that baby up and running in three and a half months. Now that two to three years ago, traditional logic would have told you that was a nine to 12 month project. And by the way, 10 years ago, that would have been a 18 to 24 month project. So I think that, yeah, we're moving much more rapidly. That's the expectation now too. I mean, the customer's realized that too, right? Absolutely, no, but there's one thing I want to talk about this. It's still, this is the one thing that, if you'd ask me what's most important. The speed thing allows you to go rapidly to places, but you better have a navigation roadmap on where you're going. Because if you're gonna do all kinds of little code drops, that's great, but you wanna make sure you're getting leverage so you're going somewhere. So therefore, this is where road mapping becomes really, really important for every, the technology side of the business. You have to have a technology roadmap. The other thing that's really important out of this is if you don't, let's use a client server example you used, because this kind of has a, we've all been here, right? We've all lived, we've seen this movie before. If you don't build this roadmap, another thing that happens, do you remember when CIOs finally said, okay, I'm taking control of this client server thing? Sure. What did they end up with? They ended up with all these departments of computing and the costs were going astronomical. So if you've got a roadmap, you can also address the issues of managed services because you don't. The least thing you wanna be is having all these data marts that are scattered everywhere because you get no economies, you get no economies that a cloud would bring you, you get no economies of being able to do that, and you end up having to have all these maintenance teams, app maintenance, and by the way, analytics by its nature has constant app maintenance, little adjustments and changes. You're getting no economies of that because they're all managed as discrete units. So therefore, there's a lot to be as you build this roadmap, you've gotta think about the managed services environment as well. So Fred, you talked about earlier, clients don't think in terms of data, they think in terms of their business process. Is that a blind spot for clients? Because there are some companies, Google, for example, that does think in terms of data. In your view, should clients increasingly be thinking in data terms, or does our industry have to evolve to make the data map to business process? I actually, I kind of just take it as a fix. I don't choose to question why, I just accept it. But I would say. Customer's always right. Well, I just think the industry, definitely. But I think just the industry's at a stage where, we've always, back in the old days of, I'm gonna show my age here, but the procedure division and the data division. Oh my God, I hooked that old. And the procedure division is where you actually did all the really, and I think the other reason is, we gotta understand the paradigm under which modern computing was created. I don't wanna be like, we go into history lesson, but the paradigm under which modern computing was created was that we use computers to automate tasks. So we've always taken this procedural approach, which went, then we went to process re-engineering, and that became a boardroom conversation. So just, I think we've conditioned, over the last 40 years, businesses to think about using technology to gain business efficiency, they've always thought in terms of process. So that's why this data element, yeah, companies like Google founded on analytics, clearly have got a whole different headset and a different way to approach these, which gives them a built in bias when they address the problems they've got in their businesses. Sure. But you don't come into clients saying, hey, you gotta rethink the way in which you look at data. You come in and say, let's figure out how we can exploit data in your business. Correct, we do it two ways. We do it two ways. First of all, let me not dress, let me not dress mutton up as lamb. At the end of the day, it's data. It's data, okay? Now the question is how you articulate that. And it's twofold. We tend to, I like to use a metaphor to describe the data. So if it's customer, the metaphor we've been using recently is DNA, DNA strands to be able. So you use a metaphor that there's a language that the business can relate to and you can create a common language very easy. One, and that way you can have a, because you're never gonna drag a CEO into your fourth normal form data model. So therefore you've got to talk a language. One, number two, you talk about it as a collection of use cases. So you use use cases as a vehicle to have the process conversation. And because with the use case you also can talk business outcomes, benefits, and you can tell kind of a story. You don't have to drag them through the details of the process, but you can tell them a story, whether it's, you know, if you can understand call detailed data records and the affinities, you can understand the social networks and therefore you can reduce churn within your telco customer base. As an example, it was a bit quick, but if you follow what I mean. Oh, yeah, I do. So you talk to them about its little use cases and they begin to understand, wow, what's possible. And then you talk about their data as a DNA chain and they get, I got it. I actually need to get the DNA chain if I'm gonna actually think about my customer base or my product base or whatever. Yeah, the lingua franca of the business is still the business's language. It doesn't change as a result of data, but data can enrich the conversation in a way that can lead to new outcomes. The data enriches the conversation when you talk about the business outcomes that are created as the part of the use case. Well, that's like a three, third order differential equation. I'm gonna go back and watch this video. Yeah, I was gonna say, you're a tweet, you're an epic soundbite machine. I just can't type fast enough on the crowd chat. It's good for Twitter viewing. Yeah, I've just opened a Twitter account. Please look me up, I'm looking for friends. I promise to start posting. We got people watching, all right. All right, so in terms of customers, right, give us a little bit peak of some of the customer responses when you open the Kimono, show them the roadmap. The messaging around IBM right now is pretty tight here at IOD, last year was good. This year it's better, real unified. Face to the customer. When you show them the roadmap, what's the feeling they get it? They feel like, okay, I got some trust, IBM's got some track record history. Do they, is the emotion more of, okay, where do I jump in, how do I jump in? They're doing it and there's little shadow IT going on all over the place we know with Amazon out of the area. So when you're in there, you've got to have these hard conversations. What are they like and what's the level of response you get from CIOs and then also the folks in the trenches? So there's always a question, which there's a couple of questions. First of all is how can I get value from this? And that's a, I'm tightly coupled to my existing transaction processing, which is kind of like, if you will, I'll call that turbocharged BI. And which is where so many people have come from, is this turbocharged BI environment. And listen, that's an important part of your reporting business. You need to do that to keep the wheels on. The question is as you move to this notion of analytics giving you great insight, then you've got to say, okay, I need to go from turbocharged BI to really augmented components. So clients, I'd say there's a large group of people that are right now moving from turbocharged BI to the notion of advanced use cases. So there's some, a large discussion right now of how do I show me use cases by which I can rapidly. So that would be advanced out of Linux, is what people call advanced out of Linux? No, we have, well, 60 use cases, industry-based use cases that we as a services business put together. On top of that, we have about seven or eight key code fragments that we use as accelerators. I mean, we call them, I think we call them assets and we just them up as accelerators, but they're code fragments that we bring to a client as the basis that we put on top of the blue stack of technology to actually get them a speed to value, because we really want to be able to get clients up and running within this notion of 1,980 days. It's like literally being best practices in the form of technology to the customers. Well, I mean, you're on an IBM thing. I mean, dare I call it an application? No, I wouldn't dare call it an application because we're not in that business. But the point is, is that it's starting to feel like an application because it's really moving down these integrated solution is really where we go. So the accelerators code, correct. So it's leverage. The economy of scale is every success breeds. That's exactly it. And then on top of that, we would have, just throw a few other things that we do to accelerate these things. We actually have five, what we call signature solutions, which is services, software together with a piece of services code coming together to solve a problem. We've got that around risk and fraud, around customers. I mean, so some specific, very narrow things. If somebody wants to, you know, because often IT departments, they want to buy something. They want to buy something. They don't want to go down a project. They want to buy something and so fine. Here's a prepackage solution. Let's go buy something. And then last but not least, the one thing we haven't talked much about, but I always like to throw this out there because I think this is one of the things that, and we didn't talk about it much in the maintain or any of our sessions, but let's not forget about IBM research. I'm really proud to report to you now since we started this category. We've done 61st of a kind with IBM research. So this is about, client says, I've got this problem. I think it's unachievable. I cannot solve this problem. Help me map in my oil exploration. Like things that are considered- These are big problems. Big problems. Let's apply this group that does patent factory, you know, that IBM is, 15 years in a row. Let's apply those people to our problems. And we have 60, so we do about 15 to 20 a year. So it's not like we're not cranking these out like on hundreds of thousands of licenses. But it's where basically our services business, our software business and IBM research go work on solving a client specific problem. You heard Tim Buckman this morning when he was asked, you know, why IBM? He said IBM research was the first answer. That's right. He gave, we talked to him about that on theCUBE. Yeah, I mean, and his insight, I mean, he's a customer. And you know, we always love to hear from customers. I mean, you know, the Splunk conference just had, it was just last week, it was an emerging startup. You guys are probably well aware of those guys. They have customers that just say, just glowing reports. You guys have the same set of customers. You know, he is someone of high caliber at the command and control and his health care mission. And he's automating himself. And essentially creating this new data model that allows it to be pushed down through the organization. Listen, you've got to do this and I'll tell you why. You remember the, the governance discussion is, well, I'm most excited about it. The governance discussion five to eight years ago was an arcane discussion of data modelers. And like, what do we do? The governance discussion is quickly moving into the language of our business people. And the reason is because they're beginning to, do you remember the days of accounting systems? When they say, we want our accounting department to focus on analyzing the numbers and not collecting and forming the numbers. Well, we're here again. And if you've got good data governance, you can focus on creating the insights and determining what actions you want from the insights as opposed to questioning the numbers and questioning the validity and the heritage of the numbers. The validity and the heritage of the numbers and this plays everywhere. Yep, financial services companies are the most stressed about it because the validity and heritage is required when you want to prove a compliance to a federal statute. Yes, but it means everywhere. If you're a consumer packaged goods company and you don't believe that sales are down in a certain market or a certain chain store, first thing they do is they start challenging the numbers. If you have good governance, you can now start to, you can now start to trust these systems of record. Let's, let's drill down. We're talking about data quality, data quality, but it's also the, the governance and the definitions. It's a mindset of, it's, we talked about iteration, right? We said the first, you know, the folks from the non-profits said, he didn't want to go on the record, but he's basically saying, I'll say it. Basically when you put stuff out, when you package it, then bring it out, it still might have some flaws in the data quality, but it's the iteration that's the transformation of it, once it's in market, saying that's changing. He thinks prepackaging data and then bringing it in is not the better approach. But I want to ask you about the, what you just said about this governance conversation, that is data, the core of this debate around the data economy. What is the data economy in your mind? Given what you, the history that you've lived through, we've seen those movies now, the cutting edge, new wave that will create new wealth and new ways, change from transform business, all that stuff's great. But what is the data economy? What does that mean to business executives that they're focusing on outcomes? Is it, is it changing data governance? Is it changing the value chains? Is it changing? What's your thoughts on that? The data economy is about discovering those points of leverage that, that the data tells you that your instincts don't. The data tells you that your instincts don't. One of my favorite stories, three years ago, four years ago, we were called in and clients said, this is my problem. The going in problem was I gotta take $200 million out of my advertising spend budget. $200 million out of my advertising spend budget is a retailer. And the problem is, is out of my $600 million advertising budget. The problem I have is, I also have all kinds of interesting theories and models that my agencies have told me. I'm not quite sure, do I just take 200 off the board, across the board, do I take 200 off of the board? To minimize my risk, I'll just spread it around. How do I manage this process? And what we actually did was we built a super, super set of sophisticated analytics which tied to their transaction systems but also tied to their social media systems. So we also understood, and what we did was we were able to understand which customer cohorts responded to which media types. Then we added one more part to the model which is we understood the trending and the cost of free-to-air, cable, radio, internet, all the different media types. And as we looked at the cost models of them and we understood which customer cohorts responded to which media types, we suddenly realized that they were super saturated. I mean, certain media types, they could double their spend and they wouldn't get any lift in their sales. What we did was we got 200 million out of their budget and they got 300 million incremental sales that Christmas season because we helped them get really smart about the, now let me tell you, I tell this privately, media buyers look at me like I'm like a pariah, but it has actually really started to rethink. Now there's just a really great example because I think we've all can relate to that but that's the data economy where you find these veins of gold and these simple correlations and from that simple correlation you can instantly go and your business, you can get the lift. Listen, I can get 5%, I-I-B-M, get 5%, 10% lift in some small segment of my business, I've got the volume, that's gonna make a significant difference to my share. Yeah, one small piece of data could open up a window kind of that Jody Foster would contact where it's like one piece of data opens up a ton of window up of new data. I mean that totally is leverage. Change is the game for that customer. And that to me is the guts of the data economy, identifying those correlations and what we're finding is our most recent study, we just released it here at the thing, the IBM Institute for Business Value, Big Data and Analytics Study, IBM.com, it's the Institute for IBVE study on Big Data, just released and it said 75% of all companies that are outperforming their peers have said Big Data, Analytics is one of the key reasons. And the human component not to put our all on machines, it's really about, it's an art and a science. It's a mix of both the math and the human piece. Well, you know, there's this notion of not only do you create the insight, but you've gotta take action on the insight. You know, it's not enough to know if I actually could predict for you who's gonna win tonight's basketball game. You still gotta place the bet. You still have to take action on the insight. And so therefore, this notion of action to insight is all about trust. Trust in the insight, trust in the data and trust in the technology that the business trusts the technology. And it's until you take that leap of faith. Remember one of the Indiana Jones movie when he like the leap of faith and you've gotta like step out and take that leap of faith. Once you take that leap of faith and you suddenly have trust in the data. So that's that trust dimension. And that's a human thing. That's not a, that's not a, that's an organizational thing. That is not, not a lot of technology in that one. Okay Fred, we gotta wrap up. I'll give you the final word for the folks out there. Quickly put a bumper sticker on IOD this year. So put on my car and I drive home. What's that bumper sticker say for this year? It's not all about the technology but it starts with the technology. Okay, we're here live in Las Vegas. We're going to take up on that bet for those who's going to win the game tonight. We'll be in the sports book later. This is theCUBE live in Las Vegas for information on demand, hashtag IBM IOD. This is theCUBE. We'll be right back with our next guest after this short break. Exclusive coverage from information on demand IBM's premier conference. We'll be right back.