okay welcome back live in Las Vegas is the cube ibm's information on demand conferences q exclusive coverage SiliconANGLE will keep on here live I'm John furry the founder of silicon Hank I'm Joe mykos Dave vellante co-founder Wikibon org our next guest is a Fred Balboni global leader business analytics optimization IBM GBS global business services you know obviously big data is powering the world I mean just can demand for information and solutions is off the charts afraid welcome to the cube anything there's a services angle here where you know services matters because one in the channel partner is this good gross profit for helping customers implement solutions that they have demand for so you've 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 in the horizon in terms of on prem of Prem then you've got now see mobile devices bring your own device to work which is thrown off more data okay and then people want to be in all the different channels the social business so you know 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 a quick update and from from GBS i think that the to make this successful first of all it services is important it's the last mile you know that means the point you may it's the last mile and without without that you cannot ever deliver the value the 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 yet that's right but it's big 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 a hurdle we've got a jump on me articulate this to the businesses clients businesses think in terms of process you don't think in terms of data you know you don't go talk to a CIO 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 so that the processes but the data it's a tough thing so the first part the services is so crucial in this is being able to articulate the value of analytics and big data to a client in the businesses terms so it becomes a boardroom conversation kind of so that's 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 going to give me some quick wins here so it's kind of those timetable what kind of timetables mmmm back in the 80s 90s when client-server rolled out it was months and months yeah project management meetings roll out the Oracle systems roll out the big iron now I mean I'll see maybe shorter spurts little different hurdles what's the timetable only some of these horizons for these quick wins okay so project implementation I come on now let's let's know 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 going to 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 acceleration so you've got those code sets that are already there that you can add you can jump on top of I mean you can get these use cases up there in 6-8 weeks we have one we have an example a really large major company i'd rather not i'd rather not because it's not externally referenceable but a really a significant client that had on the order of more than more than 5 million discreet 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 twelve month project and by the way you know ten years ago that would have been a 18 to 24 month project yeah so I think that yeah we're moving much more rats the expectation now too I mean the customers realize that too right the absolute not but but there's one thing I want to talk about this it's still this is the one thing that if you'd asked me what's most important this speed thing allows you to go rapidly to places but you you better have a navigation roadmap on where you're going because if you're going to do all kinds of little code drops that's great but you want to make sure you're getting leverage so you're going somewhere so therefore there's a scale but this is where roadmapping 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 the client-server example you used because this kind of has a you know we've all been here right here we've all lived seen this movie before yeah if you if you don't in the build this roadmap another thing that happens do you remember when CIOs finally said okay I'm taking control this client servicing sure what do they end up with they ended up with all these departments of computing in the costs work going astronomical so if you've got a road map you can also address the issues of managed services because you don't the least thing you want to be is having all these data Mart's that are scattered everywhere because you get no economies you get no economies of it but a cloud would bring you you get Noah kind you get no economies and being able to do that and you end up having to have all these maintenance teams you know that maintenance and by the way analytics by its nature has constant maintenance little adjustments and changes you're getting new economies of that because they're all managed is discrete units so therefore there's a lot to be as you build this roadmap you've got to 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 thick I don't I don't I don't choose to question why I just accept it um i but i would say i which i would say customer's always right I just I just think the industry i thought that definitely but i think just the industries at a stage where you know we've always you know back in the old days of you know i'm going to show my age here but you know the procedure division in the data division oh my god looked at all and and and we you know the procedure division is where you actually did all the really and i think if the reason is we got understand the paradigm under which modern computing was created I don't to 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 reengineering 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 in 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 a decline saying hey you got to 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 biz erect what we do it two ways we do it two ways first of all let me not dress let me not dress monton up as lamb at the end of the day it's its data its 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 its customer that 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 in that way you can have an account because you're never going to drag a CEO into your fourth normal form data model so so therefore you've got to you've got to talk a language one number two you talk about 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 I if you can understand called detailed called 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 quick but if you follow I do so you talked 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 going to actually think about think about my customer base or my product base or whatever the lingua franca the business is still the businesses language it doesn't result of data but data can enrich the conversation in a way that can lead to new outcomes the data in rich's the conversation when you talk about the business outcomes that are created as the part of the use case well it's like a three third order differential equation but i go back i watch this yeah i just go say your tweet your epic soundbite machine just can't type fast enough on the crowd chat it's good for 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 you got people watching all right all right so so in terms of customers right give us a little bit peak of some of the customer responses when you when you open the kimono show them the road map you know the messaging around on IBM right now is pretty tight here at IOD last year was good this year is better you look really unified face to the customer when you show them the road map 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 is the emotion more of okay where do I jump in how do I jump in there doing it and this little shadow IT going on all over the place we know with Amazon out the area so so when you're in there you've got to have these are conversations what do they like and what's that 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 how can I get value from this and that in that and that's you know a I'm tightly coupled to my existing transaction processing which is kind of like if you will call that turbocharged bi and and which is 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 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 there's a large group of people that are right now moving from turbocharged bi to the notion advanced use cases so there's this some disco a large discussion right now how do I show me do use cases by which i can I can rapidly that would be advanced how to linux up the calling advance limit well no we have well 60 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 uses accelerators I mean we call them wink we call them assets and we just them up as accelerators but their code fragments that we bring to a client as the basis that we put on top of the 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 non idealities it's like literally being best practices in the form of technology to the customers well you're on an IBM thing I mean dare I called an application no I wouldn't dare call it an application we're not in that business but the point is is that it is it's starting to feel like an application because it's really moving down these unreal integrated solution is really where we going it's an accelerant this code correct so it's leverage the economies of scale is every success breeds that's exactly it more and then on top of that we would have that just don't 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 round risk and fraud around customers I mean 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 the parts they want to buy something and so fine here's a package solution let's go buy something um and then last but not least 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 they and we didn't talk about it much in the main 10 or any better 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 kinds with IBM Research so this is about client says I've got this problem i think it's unachievable i cannot solve this problem you know help me map in my oil exploration like things that are considered big problems big problems let's let's apply this group that does patent factory you know that IBM is but 15 years in a row let's apply those people to my our problems and we have 60 we have 16 so we do about 15 to 20 a year so it's not like we like we're not cranking these out like I'm 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 to know why IBM that was said IBM Research was the first answer that's right he gave we talked to him about that on the cube you know in his is insane me as a customer and we you know we always love to hear from customers I mean you know the splunk conference just had was just last week as an emerging startup because probably well aware of those guys they have customers that just say just glowing reports you get to the same same set of customers you know he is someone of high-caliber at the command and control in his healthcare mission and he's automating himself he it's and essentially creating this new data model that allows it to be pushed down to be listen you've got to do this and I'll tell you why you remember the the governance discussion is it was well I'm most excited about is the governance discussion five to eight years ago was an arcane discussion available 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 number the validity and the heritage of the numbers and in this place 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 that you can now start to trust these systems of record but let's talk about data quality data quality but it's also the governess in the death of mindset is much broader iteration right how we said the first you know that folks from the nonprofit said you want to go on the record but he's basically saying I'll say basically when you put stuff out when you package and then bring it out it still might have some flaws in the data quality but it's the iteration is transformational but once that's in market saying that's changing he things prepare pre-packaging data and then bringing it in is not the better approach but I want to ask you about the your what you just said about this governance conversation that is date the core of this debate around the data economy what is the data economy in your mind given what you do the history that you've lived through we've seen those movies now the cutting edge new wave that will create new well for new ways change from transform business all that stuff's great but what is the data conn what does that mean to business executives that they're focusing on outcomes is 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 and problem was I got to take 200 million dollars out of my advertising spend budget two hundred million dollars out of my advertising spend was he's a retailer end and the problem is is out of my 600 million dollar advertising budget the problem I have is 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 to minimize my risk just spread it around how do i how do I manage the 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 system 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 parts of the model which is we understood the trending in 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 in certain media types they could like doubled their spin and they wouldn't got want any lift in the advertised in their in their sales what we did was we got 200 million out of their budget and increase they got 300 million incremental sales that Christmas season because we help them get really smart about the play let me tell you I tell us privately i maked media buyers look at me like like I'm like a pariah yeah but but it is actually really you know 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 in these simple correlations and from that simple correlation you can instantly go and your business you can get the lift listen I can get five percent I IBM get five percent ten percent lift in some small segment business I've got the volume that's going to make a significant difference to my share one small piece of data could open up a window kind of had with Jodie Foster we would contact words like one piece of data opens up a ton of new data I mean that totally is leverage and it changes the game for that customer and and that to me is that is the guts of the data economy identifying those correlations and and what we're finding is our most recent study we just released it here the thing the IB the IBM Institute for business value big data and analytics study w IBM com it's the Institute for bit I bv study on big data just released and said 75 percent 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 are all on machines it's really about it's an ardent science its 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 got to take action on the insight you know it's not enough to know if I could predict for you who's going to win tonight's basketball game you still got to place the bet you still have to take action on the inside 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 trust the technology and it's until you take that leap of faith remember when the Indiana Jones movie when he liked the leap of faith and you've got to like to step out and take that leap of faith once you take that leap of faith in you suddenly have trust in the data so that's that trust to mention and that's a human thing that's not a that's that's not a that's an organizational thing that is 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's and put on my car when 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 ok we're here live in Las Vegas we're going to take about that bet that was going to win the games and I will be the sports book later this is the cube live in Las Vegas for information on demand hashtag IBM iod this tequila right back with our next guest if the short break exclusive coverage from information on demand ibm's premier conference we write back the q