>> Announcer: Live from Las Vegas, it's theCUBE, covering InterConnect 2017. Brought to you by IBM. >> Okay, welcome back, everyone. We're live here at the Mandalay Bay in Las Vegas for the wrap-up of IBM InterConnect 2017. I'm John Furrier. My co-host this week, my partner in crime, co-CEO, co-founder of SiliconANGLE Media Inc. with myself, Dave Vellante. Dave, it's been a great week. I just feel like I have been Watsonized and Blockchained and cloud all week. As we wrap up InterConnect, I want to get your thoughts on IBM, the cloud business, the big data marketplace, some of the things that we're seeing at the 100 of events we go to. We've got our events coming up, we're going to be in Munich next month, we got DockerCon, but a lot of developer events coming up, but in general, we get to see the landscape, in some cases, that others don't see. Let's talk about that, so before we get into the landscape, let's about IBM, IBM's prospects. This show, just quick stat, almost double the online traffic we're seeing on IBMGO than World of Watson, which was the biggest show we've ever done with theCUBE that we've seen. So, an interest, it's a data point. Unpack the data, you can see that there's a lot of global interest in what IBM is doing right now with the cloud and with Watson, and certainly with Blockchain you add another disruptive enabler potentially to what will either be a brilliant IBM strategy or a complete crash and burn. I think this is an IBM go big or go home moment with Ginni Rometty. I love her messaging, I love her three pillars, enterprise strong, data first, cognitive to the core. That is solid messaging, all three pillars. To me, it's clear. IBM is at a reinvention moment, it's all coming together, but it's a go big or go home moment for them. >> Well, you know, John, I mean, Ginni when she took over, sorry, she was running strategy before she became CEO, I mean, IBM had a choice, they could go double down on infrastructure and go knock it out with Dell and EMC and HP, or they could go up the value chain. And my ongoing joke is Dell bought EMC, IBM buys some other company, and that to me underscores the differentiation in thinking. Oracle, I think, is a little different, but Oracle and IBM are somewhat similar, I think you'd agree, in that they've got a big SaaS portfolio, they're trying to vertically integrate, they're trying to drive high value margin businesses. The difference is IBM's much more services oriented than, say, an Oracle, and that's still, as I say, a big challenge for IBM. But I'm more, I'm a bull on IBM. >> Why is that? >> I think the strategy is, number one, they're relevant. We talked for years about how we weren't that excited about Microsoft because they weren't relevant. Satya Nadella came in, all of a sudden, they're relevant again. I think IBM is highly relevant in the minds of CEOs, CIOs, CCOs, CDOs, all the C-suite, IBM is super relevant there, just as are Accenture and Ernie Young and all the big SIs. But IBM's got tons of products beneath it, number one. Number two, despite the fact that, you called it out several years ago, they bought software for 2.4 billion, it was a bare metal hosting company, alright, but IBM's turning that into >> Bluemix. >> a cloud business with Bluemix, right. And they're building, bringing in acquisitions like Cleversafe, like Aspera, like Ustream, and others, where they're bringing services that are differentiated. You can only get Watson on IBM's cloud, you can only get IBM's Blockchain on IBM's cloud, so they're bringing in value-added services, and there's only one place you can get them, and I think that's a viable strategy that's going to throw off a lot of cash, and it's going to lead to success. >> And by the way, they're also continuing to invest in open source. So, again, that's-- >> That's the other piece. I wanted to talk to you, and this is your wheelhouse. IBM's open source mojo is not just lip service, alright. They have deep-rooted DNA in open source and their strategy around it, and they've proven that they can monetize open source. What's their model, I mean, explain the model because I think it's instructive. >> I mean, open source, there's a lot of different models. Red Hat-- >> For IBM, I mean. >> IBM's model of open source is very clear. If you look at what they've done with just Blockchain as a great example, they have mobilized their company, and they did it with Bluemix as well with the cloud, once they said, "We want to get in the cloud game," once, "We want to do Blockchain," they go open source at the core, then they get their entire brain trust workin' on it. It's not just a hand wave, some division, they're kind of reorganizing on the fly, they're kind of agile organization, which some may read as chaotic, but to me, I think that's just good management practice in this day and age. They get an open source project, and they drive that home, and they have people contributing and giving that to the community, and then adding value on top and differentiating. It's just classic 101, create some value, and create some differentiation with your products, and by the way, if you don't want to use our products, build your own, or hey, use the open source code. That's pretty much an over-simplified version of open source. >> But Blockchain's a great example of this, right? So, they see the leverage in open source project, they put all these resources in, and they say, okay, now let's build our product on top of that, let's get the open source community leverage and this is, let me ask you this, does IBM, so several years ago when IBM announced Bluemix, you were pretty critical. >> John: I was very critical. >> IBM has to win the developer audience or it's cooked in this game. >> That's what I said. >> How is it done, how would you grade them? >> I think they're doing very well. I think IBM is, again, to use your word, they're not putting lip service in it. So, I was joking with Meg Swanson last night, I saw Adam Gunther when they interviewed on theCUBE, and I was critical. I didn't say that their cloud was bad, I was just saying it's just not as, just got a lot of work to do, Amazon's kickin' ass, which we now know that happened, right. But they've done well. They've done well, they've ran hard, they've gone the table stakes on the enterprise. I still think they got some more work to do, we can analyze, I'm putting out my cloud ratings matrix, I'm going to put IBM on that list, I have Google and Amazon done. I'm going to add Microsoft Azure and IBM onto the mix in the comparison matrix. But IBM has done good with the developers. They've just invested 10 million in this announcement, and they're ramping up. I wouldn't say they're throwing just money at it, they got people, so I would give them, I'd give them a B-plus, A-minus score because they're hustlin', they're doing it. Are they totally blowing it out of the water? No, I don't think they're pushing hard enough there. I think they could give it some more gas, I think they could do more with it, personally thinking. But you know, Dr. Angel Diaz was on earlier today. They're going at their own pace. >> But you agree they're in the game. >> Oh, totally. >> Making good progress. >> They're totally, IBM is totally in the cloud game, and they don't get a lot of credit for it. Either does Oracle, by the way. Somehow, people seem to talk about Azure and Google. Google is so far behind, in my opinion, they're not even close. I think it's Amazon, Azure, IBM and Oracle and Google all kind of in that-- >> Juxtapose Oracle's developer cred, even though it owns Java, with IBM's. How would you compare the two? >> Very similar, I think. Different approaches, but again, to your point, IBM's relevant, Oracle's relevant. We had this question about VMware when they did the deal with AWS. They have customers and they have cash, so they're not going anywhere. It's not like IBM's a sinking ship. It's not like Oracle's a sinking ship. Now, that being said, there's a huge shift in the business, and I would say in that scenario, Google is in a very good position, so I've been very critical on Google only because they're trying to be acting like they're an enterprise flag. They're not, I mean, Google's got great tech, TensorFlow, machine learning. Google has great cloud tech, but in that game, they're up in the number one, two spot. But in the enterprise side, they're not close. They're workin' on that. So, that's my critique of Google. Microsoft has got the DNA for the enterprise, so Microsoft and Oracle to me are more similar than comparing IBM and Oracle. I'd say IBM is a lot more like Google and Amazon, kind of in-between, but Oracle and Microsoft look the same to me. Big install base, highly differentiated, stacks aren't perfect, but it looks good on paper, and they're gettin' business. And Oracle's earnings, by the way, were very explosive due to the cloud growth. >> Another question I like to ask sometimes is, okay, what would you have done differently if you had a choice? Like when Gerstner was running IBM, he chose to consolidate the company, essentially, not consolidate, but focus on services, one throat to choke, single-faced IBM. Great customer service and build the services business, buy-in, PWC, et cetera, that was the key. What could you have done differently that could've said, well-- >> John: For IBM? >> Yeah, at the time, you could have said, "We're spin out different product groups. "We're going to be the best at microprocessors, "or disk drives, or database, or software." >> I think IBM moved too slow. >> That's a historical example. Given what IBM's doing today, what would you have done differently if you were Ginni Rometty five or six years ago? >> I would've done what they're doing now three years ago. We were, when we started working with them with CUBE, IOD events, and Pulse. >> Dave: Information on Demand. >> You had a lot of silence. I think, if I had to go back and get a mulligan, if I was Ginni Rometty, I would've moved faster. >> Dave: Done that faster. >> Hindsight's 20-20 on that, but it wasn't that clear. But again, it's the big aircraft carrier, it can only move so fast. I think what they're doing now is good strategy, and they're price strong, data force, cognitive to the core is a good strategy. Now, cognitive is words for AI, and that's their word, cognitive 'cause of Watson, but essentially, machine learning and AI is going to be a big pillar there, and then, the data first is more of an architectural component that's very good. But in general, Dave, the cloud is, this is what's going on in my find. It's so obvious to me. The big data marketplace that was we defined by Cloudera and Hadoop and Hortonworks just never panned out. It morphed into a bigger picture, and so, Hadoop is part of, now, a bigger ecosystem. Cloud was growing very fast. Those two worlds are coming together and growing very rapidly independent with big data, with machine learning, AI, and IOT. They're coming together. The intersection of the big data and the cloud. >> Cloud-mapping data. That was Yuri Burton from 2005. >> But it's coming together really fast, and the IOT is the real business driver. I know there's not a lot of stuff shipping yet in the sim stuff out there, but merging IOT into IT into business process and into developer mindset, whether it's an Indiegogo up to full-on developers is the accelerant that's going to fuel the AI value. To me, that's the intersection point of big data and cloud, and that is the home run, that's the holy grail, and that's going to be disrupting some preexisting decisions by big vendors who made bets, and I'm talkin' about bets made in the past five years, not like bets made 20 years ago or 10 years ago. I think the IOT is going to really shape the game. The other thing I worry about now, in my opinion, is a lot of AI-washing. People say, "Oh, AI." You see people on the stage, "Oh, we did this with AI." There's no AI, it's augmented intelligence, which is basically predictive analytics. You know, true AI is not yet here, it's a little bit hyped up, not that I mind that. I think that the machine learning is the real meat on the bone right now, I think that's the core enabler. Machine learning is by far the most important trend in the computer science world today as it relates to integrating that capability into cloud native, microservices, and overall application. >> I agree, I mean, AI is still a heavy lift, but to me, the key, I go back to something you were saying, is developers. That's the lever that's going to give you the ability to move large mountains. If you don't have that developer community, and you don't have open source chops, you're going to struggle a little bit. You're going to be either in a swim lane like Oracle with its database and its red stack, and maybe you can break out of that, but I'm not sure it wants to. Or you're going to be stuck in infrastructure lane. >> Yeah, but the developers are driving all the action right now. My point about machine learning, if you look at the shows just recently, and certainly we have the history of the past year, machine learning is the sexiest trend in every show. Last show was Google Next, machine learning with TensorFlow, both open source. Machine learning's not new, it's just now accelerating the developer. The developers want to move faster, and I think things like machine learning, things like cognitive that IBM puts out there, are great catalysts. That's going to be a big thing we're going to watch, obviously, we have a big developer community at SiliconANGLE, so something to watch. >> What's next? We've got a chief data scientist summit next week in Silicon Valley, we're going to be at the-- >> Let's look at my Friday show this week. Every Friday I do the Silicon Valley Friday show with me and guests, we got that goin' on, so always check that out on soundcloud.com/johnfurrier, or check out my Facebook feed, facebook.com/johnfurrier. But in terms of CUBE events, we've got DataWorks in Munich on April 2nd, DockerCon in Austin, Oracle Marketing Sum Experience, Red Hat, Dell EMC World, Service Now, Open Stack, Big Data in London. >> It's going to be a busy spring. >> Lot of stuff going on. Great stuff. >> Deb, we'll see you in July. >> In bumper sticker, Dave, this show, encapsulate your thoughts. >> Well, I think it's all about cloud, data, and cognitive coming together in a way that allows business value and differentiation through the end customer. That's what this show is about to me. It's not about infrastructure, cloud and infrastructure, that's kind of table stakes. It's all about differentiation up the stack, creating, enabling new business models. >> My encapsulation is the enterprise strong, data first, cognitive to the core message that Ginni said, that translates into IBM's shoring up their base products and putting an innovation strategy around Blockchain and soon to be cognitive computing at a whole 'nother level, and I think they're going to have a real innovation strategy and continue to use what they did with Watson, the winning formula. Put something out there that's a guiding principle and draft the company behind it. I think that, to me, is my big walk away, and I think Blockchain will potentially level, has game-changing capabilities, and if that plays out like Watson's playing out, then IBM could be in great shape on both shoring up the base in cloud and their business and having an innovation strategy that extends them out. That to me is the reason why I'm bullish on them. So, great show, Dave Vellante. Thanks to the guys, thanks for everyone watching. That's it for us here in theCUBE. I'm John Furrier, Dave Vellante wrapping up IBM InterConnect 2017. Thanks for watching, stay with us, and follow us at theCUBE on Twitter and siliconangle.tv on the web. Thanks for watching. (electronic keyboard music)

okay we're back here live at the IBM iod information on demand conference hashtag IBM iod this is the cube so looking the anglo Mookie bonds flagship program we go out for the events extracting from the noise i'm john furrier might join my co-host Davey lonte and we'd love to have analysts in here and in this case former analyst James Cole Beatles welcome to back to the cube thank you very much John thank you Dave pleasure see you again finger of being at IOD you're a thought leader you are an influencer you work at IBM so you you're out there the front lines doing some great work so thank you very much tell us explains the folks out there not about the show because we've had some people coming in last year you were private in but what does this fit what is this vector in context to what's relevant the market obviously big data and analytics is the hottest thing on the planet right now and you got social business now emerging categorically here but it has a couple different flavors to it right within IBM's context yeah but the messaging is simple right you got analytics that drives value outcomes social business is the preferred way of people going to operate their businesses engagement and all that is great stuff new channels marketing eccentric cetera explain to them how I OD is fitting into these megatrends into mega trends I think the hottest trends why our customers caring about what's going on here is a lot of a lot of activity around customers what is what does IOD fit into that a bigger picture yeah well you know the world has changed the world culture has changed radically and really in the last decade or so none is everywhere in the world everything is now online and digital increasingly it's streaming in terms of culture look what's happening to Hollywood is being deconstructed by the netflixs of the world you know movies and TV and music and everything is delivered online now all engagement more more engagements with your employer with your you know with merchants with your family everywhere is online things like streaming media so if you look at how the world culture has changed I yesterday I spoke here on a topic that's near and dear to my heart called big media it's the support of the ascendance of streaming media and not just the area as I laid out but in education like MOOCs distance learning we use it internally at IBM for our think fridays and Ginni Rometty and the executive team you know every Friday its cloud or its big data or whatever you know we need all need to get up to speed on the world culture has changed now analytics is fundamental to that whole proposition in terms of world culture analytics driving gagement analytics in terms of you know in a business context analytics a 360-degree view and you have data warehouses and the master data and you have predictive models to drive segmentation and target marketing and all that good stuff you know that's been in business for a long time that those set of practices they have become prevalent in most industries now not just in say retailing you know the Amazons of the world they're pervasive across all industries big data is fundamental to that you know engagement model its social social in the sense that social is one of many channels through which business is engaged with through which many people engage the social is assumed assuming a degree of importance in the fabric of modern life that goes beyond simple you know engagement with you know brands and whatnot social is how people create is how they declare who they are it's their identity and so social in your personal life we all know about Facebook and Twitter and everything else and YouTube but social has revolutionized enterprise cultures everywhere you know we use social internally of course we use our own Lotus connections most large and even many mid-sized firms now use social for interactions among employees or throughout their Val you chain so social business is about all of that it's the b2c it's the b2b it's the e2e and employ to employ all these different models of engagement they all demand a number of things obviously the social platform they demand the data of various sorts structured unstructured in shared repositories or cubes or Mars or whatnot they it demands the the big data platforms not only at respite in motion the streaming media to make it all happen in real time so at IOD if you see what the themes are this year and really it's been a building for several years cloud everything social is running in the cloud now more and more not just public Claus but Federation's of public and private clouds it's it's all about cognitive computing which is a relatively new term in the Sun sets achieved a certain amount of vogue in the last year or so which is really fundamentally as an evolutionary trend it's basically a I for the 21st century but leveraging unstructured data and and machine learning and so forth and predictive analytics and you know well the whole world learn what metadata was with the whole NSA yeah comments no it's like me and then just to wrap it up in memory real-time blu acceleration you know you need real-time you need streaming you need collaboration and social you know peer-to-peer user-generated content all of that to make this new world culture really take off and IBM provides all that we recognize that that's where the world's going we've been orienting reorienting all of our solutions around these models cloud social increasingly going forward and you know we provide solutions that enable our customers in all industries to go there and big data is fundamental to all of that as we say we're computer science meets social science that's always been Silicon angles kind of masthead view but to unpack what you just said from the market relevance you mentioned Netflix we saw Amazon coming out their own movie they're going to go direct with their own programming so so but that speaks to the direct business model of the web was originally pioneered as hey direct business model cut the middleman out but now that dimension has been explored so that kind of what you're saying there so that's cool the end user pieces interesting image is social so what's your take on the end user orientation what's the expectation because you got social you got a trash you got in motion you got learning machines providing great recommendations got the Watson kind of yeah reasoning for people so personalization recommendation engines the sea change attention time currency big days of all those buzzwords all right what is the expectation for users in the future right now we're moving into this new world where I can self serve myself monologue based the information from the web now it's all coming at everyone real time the alarms are going off as Jeff Jonas says what is that prefer user experience the direct business model people get that I think the business to see that but now the end users are now at the center of the value proposition how do what's the role of the user now they're participating in the media there are also consumers of the media yeah and they now have different devices so what's the sources of data so fundamentally yeah the role of the consumers expectations now is always everything is always on everything is always online everything is all digital everything is all real time and streaming everything is all self-service everything is all available in the palm of my hand and then the back-end infrastructure the cross-channel infrastructure users don't care about individual socials they really don't they don't really fundamentally care about Facebook or Twitter or whatever you have they just care that what their experience is seamless as they move from one channel to another they're not perceived as channels anymore they're simply perceived as places or communities that overlap too in a dizzying array of socials thus social is where we all live and thus social increasingly is mobile increasingly mobile is you know the user expects that the handoff from my smartphone to my tablet to my laptop to my digital TV sentence and so forth that it all happens through the magic of infrastructure that it's being taken care of and they don't have to worry about that handoff it all it's all part of one seamless experience yeah they always just say the search business it's the it's the it's the intersection of contextual and behavioral yeah and now you take that online behaviors community contextual is context to what people are interested at any given time yeah it's so many longtail distributions at any given time so do you see the the new media companies that the new brands that might emerge mean there's all the talk about Marissa Mayer kind of turning over yahoo and yeah she some say putting lipstick on a pig but but but is that they're just an old older branch trying to be cool but is that what users want just like media but just user experience me like we're small media but we got big ideas but the thing is the outcomes right small frying big blues go figure are the outcomes still the same company still want to drive sales for their business sell a product provide great value you just want to find great content and find people I mean the same concept of the old web search find out and run sumit give any vision on how that environment will evolve for a user like is it going to be pushed at me do you see it a new portal developing is mmm Facebook's kind of a walled garden humble don't care about that what's your take on that the future vision of a user experience online user experience online future vision in many ways I think let's talk about Internet of Things because that keeps coming more and more into the discussion it's it's not so much that the user wants a seamless experience across channel cross device all that but a big part of that experience is the user knows that increasingly they'll have some confidence that whatever environments physical environments there in our being obviously there's privacy implications that surveillance here are being monitored and tracked and optimized to meet their requirements to some degree in other words environmental monitoring internet of things in your smart home you want to configure so you smart home so that every room that you walk into is as you as you're moving there even before you get there has already been optimized to your needs that ideally there should prediction Oh Jim's walking into the bathroom so turn the light on and also start to heat up the water because it's ten o'clock at night Jim's usually takes his bath around this time you sort of want that experience to be handled by the internet of things like nest these new tools like nest oh yeah yeah so essentially then it's my user experience is not just me interacting with devices but me simply moving through environments that are continuously optimized to my knees and needs of my family you know the whole notion of autonomous vehicles your vehicle if it's your personal vehicle then you want to always autumn optimize the experience in terms of like you know the heat setting and and the entertainment justement saan the you know the media center and they're always to be tailored to your specific needs at any point in time but also let's say you take a zipcar you rent a zipcar and you've got an ID with that company or any of the other companies that provide those on-demand rental car services ideally in this scenario that whatever vehicle you you rent through them for a few hours or so when you enter it it becomes your vehicle is completely customized to your needs because you're a loyal customer of that firm and they've got your profile information this is just a hypothetical I'm not speaking to anything that I actually know about what they're doing but fundamentally you know ideally any on-demand vehicle or conveyance or other item that you you lease in this new economy is personalized to your needs while you're using it and then as it were depersonalized when you check it back in so the next person can have it personalized to their use as long as they need it that's the vision of a big part of the vision of customer experience management personalization not just of your personal devices but personalization of almost any device or environment in which you are operating so that's one kanodia wants this question no I would ask one more question on that on the user experience came on Twitter from a big data alex says while you're on the subject which a my Alex I don't great great friend of the cube but thanks for the tweet today we don't have our crowd shado-pan we can get the chat going there but why not talk about AR and I've been in reality I mean honestly Internet of Things is now not the palm of your hand it could be on your wrist or on your clothing the wearables on the glasses and just gave out three invites to google glass so this is again another edition augmented reality is software paradigm as well what is that what is it what does that fit into that what's your take on augmented reality augmented reality ok so augmented reality is that which I don't use myself I've just simply seen it demonstrated and plenty of places so augmented reality is all about layers of additional information overlaid on whatever visual video view or image view that you happen to be carrying with you or have available to you while you're walking around in your normal life so right now conceivably if this is an AR a setting that I would environment or enabled device I would be able to see for example that ok who's in this room in the sense that who is declared that they are in this area of Mandalay Bay right now and why specifically are they doing to the extent that they allow that information to be seen and o of these people here which of these people if any might be the person I'm going to be speaking with it for 30 so that if they happen to be in this environment i can see that i can see that they're to some degree they may have indicated status waiting for james could be a list to get done with the Wikibon people oh that's kind of cool so I'd see that overlay and I walk to other parts of the Convention Center I might also see overlays as I walk around like oh there's a course down as several rooms down that I actually put in my schedule it's going to start in about five minutes I'll just duck you into there because it reminds me through the overlay that's the whole notion of personalization of the environment in which you're walking around in real time dynamically and contextual in alignment with your needs or with your requirements are in alignment also with these whatever data those environment managers wish to share to anybody who's subscribing in that contact so that's a context-aware that theme have been talking about here on textual essentially it's a public space that's personalized to your needs in the sense that you have a personalized view in a dynamically update okay that sounds like crowd chat Oh are we running a trip crouched at right now crouch at San overlay so just as lovely overlay so look to the minute social network yeah tailored to the needs of the group yep that adds value on top of that data yeah so James I gotta get your take on something so we had Merv on yesterday great Adrian with my great Buy analyst day and he was on last week at Big Data NYC you know we did our own little vent there Don coincident with hadoop world so Murph said well we're just entering the trough of disillusionment for big data yeah you love those Gartner you know I love medications tools I mean they are genius and I get him but he said that's a good thing because it goes left to right so we're making progress here ok right but I'm getting nervous the internet of things I love the concept we don't we don't work on industrial internet and you know a smarter planet it's in there so I love it but I'm getting nervous here's why I look back at a lot of the promises that were made in the BI days 360-degree other business predictive analytics a lot of things that are now talking about in the hood sort of Hadoop big data movement that we're actually fulfilling with this new wave that the old wave really wasn't able to fill because the cousin sort of distracted doing sarbanes-oxley and reporting in and balanced scorecards so so I'm nervous he's old school now it when he when he referenced is something that was hot in the mid part of the two thousand decade okay go ahead okay we had a guy on today talking about balance core would you know we're just talking about crowd chat that's the hottest day in 2013 like five years or hurt anybody mentions sarbanes-oxley so what kind of saved that whole business Roy thank you and Ron but so heavy right so what I'm nervous about as we as I've seen a number of waves over the years where the the vendor community promises a vision great vision great marketing and then all of a sudden something hotter comes along like Internet of Things and says don't know this is really it so my question to you is will help us it'll help me in my mind you know close that dissonance gap is are these two initiatives the sort of big data analytics for everybody putting analytics in the hands of business users yeah or is that sort of complementary to the internet of thing his internet of things just the new big trillion dollar market that everybody's going to go after and forget about all those promises about analytics everywhere help me sure Jay through that my job is to clarify confusion hey um you know if you look at the convergence of various call them paradigms there's a lot of big data analytics is one of them right now clearly there's cloud clearly their social there's big data analytics in mobile and there's something called Internet of Things so some some talk about smack smac social mobile analytic a que a big data cloud if you add IOT of there it's smack yet I don't think it works or smash yet but fundamentally if you think about Internet of Things it's it's all about machines or automated devices of various sorts probes and you know your smartphone and whatever I know servers or even you know the autonomous vehicles those are things that do things and you know they might be sources of data they would are they might be consumers of data they might conceivably even be intermediaries or brokers or routers or data what I'm getting at is that if you look at big data analytics I always think of it as a pipeline all data it's like data sources and data consumers and then there's all these databases and other functions that operate between them to move data and analytics and insight from one end to the other of the pipe in a conceptual way think of the internet of things as well a new category of sources of data these devices whether they be probes or monitors or your smart phones and new consumers and they all those same things are probably going to be many of them consumers of data and there's message passing among them and then the data that they passed might be passed in real time through streaming like InfoSphere streams it might be cached or stored and various intermediate databases and various analytics performed on them so think of you know I like to think of the internet of persons places and things persons that's human endpoints consumers and and sources of data that's all of us that's social places that's geospatial you know you think about it the Internet of geospatial you know geo spatial coordinates of of data and analytics and then there's things there's you know automated endpoints or you know hardware even Nana from macro to nano devices so it's just a new range of sources and and consumers of data and new types of analytics that are performed in new functions that can be performed and outcomes enable when you as it were stack in and out of things with social with claw with mobile new possibilities in terms of optimization in real time it throughout the you know the smarter planet if you think about the smarter planet vision it's all about interconnected instrumented and intelligent instrumented you know instrumentation that traditionally it suggests hardware instrumentation that's what probes our sensors and actuators that's the Internet of Things it's a fundamental infrastructure within smarter planet I'd love that thank you for clarifying i could write a blog post out of that and i think i'm very well made so um now i want to follow up and bring it back to the users I know snack and I thought you were going to say a story no smack MapReduce analytics and query or sell smack on the cube so so I want bring it back to the users so we had a great conversation yesterday actually last week I'll be met it was on off you know ah be met and he said look why are there any any you know where all the big data apps he said you need three things to for big data apps you need domain expertise you need algorithms which are free and you need data scientists like oh we'll never get there all right oh so rules really free while there are that was this argument yeah it means a source if people charge him for algorithms big trouble was this point I think okay sure so and then we had a discussion yesterday about how in the early days of the automobile industry you know the forecast was this is problematic the gap to adoption is just aren't enough chauffeurs know the premise that we were putting forth in the discussion yesterday I don't know who that was with was that with Judith it was good was that look we've got to figure out a way to get analytics in the hands of the business user we can't have to go through a data scientist or some business analyst no that's not going to work and we'll never get adoption so what what's going to bridge that gap is it is it the things you talked about before all these you know cool solutions that you guys are developing the project neo that you announce today visualization yeah there's another piece of that what puts it in the hands of guys like me that I can actually use the data in new and productive ways yeah well self-service business intelligence and visualization tools that are embedded in the very experience of using apps for example on your smartphone democratization of data science down to all of us you need the right tools you need you need the tools that the new generation of people like my children's generation just adopt and they work in there just a tune from from the cradle to working with data and visualizations and creating visual you know analytics of various sorts though they may not perceive it as being analytics they miss may perceive it as working with shapes and patterns and stuff yeah you would stop yeah so playing around you know in a sandbox i love that terminology data scientists working you know sandboxes which is data that's martes that they build to do regression analysis and segmentation and decision trees and all you know all that good stuff you know the fact is your sandbox can conceivably be completely on your handheld device with all the visualizations built-in you're simply doing searches and queries you know you're asking natural language questions you're looking at the responses you're changing your queries you're changing your visualizations and so forth to see if anything pops out at you as being significant playing around it you know it's as simple a matter that that these kinds of tools such as IBM you know cognos and so forth enable everybody to become as it worried a data scientist without having to you know become a maquette their profession it's just a part of the fabric of living in modern society where data surrounds us people are going to start playing with data and they're going to start teaching themselves all these capabilities in the same way that when they invented automobiles and you know wasn't Henry 42 invented them it was in like the late 1800s by engineers in Europe and America you know it's like we didn't all become auto mechanics you know there are trained auto mechanics but I think most human beings in the modern world know that there's a thing called an automobile that has an engine that needs gasoline and oil and occasionally needs to be brought to a professional mechanic for a repair and so forth we have many of us have a rough idea of something called a carburetor blah blah blah you know in the same way that when computers came up after world war two and then gradually invaded our lives through PCs and everything we all didn't become computer scientist but most of us have an idea of what a hard disk is most of it no most of us know something about something called software and things are called operating systems in the same way now in this new world most of us will become big data analytics geeks practical into the extent that will learn enough of the basic terms of art and the relationships among the various components to live our lives and when the stuff breaks down we call the likes of IBM to come and fix it or better yet they just buy our products and they just work magically all the time without fail conversing and comfortable with the concepts to the point which you can leverage them and what about visualization where does that fit visualization visualization is where the rubber meets the road of analytics is it's where human beings how human beings extract meaning insight fundamentally maybe that's like yeah you extracted inside a lots of different ways you do searches and so forth but to play around it to actually see you know a heat map or a geospatial map or or or you know a pie chart or whatever you see things with your eyes that you may not have realized we're there and if you can play around and play with different visualizations against the same data set things will pop out that you know the statistical model just seek the raw output of a data mining our predictive model or statistical analysis those patterns may not suggest themselves and rows of numbers that would pop out to an average human being or to a data scientist they need the visualizations to see things that you know because in other words when you think about analytics it's all about the algorithms that are drilling through the data to find those patterns but it's also about the visualizations the algorithms and you need the visualizations and of course you need the data to really enable human beings of all levels of expertise to find meaning and fundamentally visualizations are a lingua franca between non-expert human beings and expert eamon beings between data scientists visualizations are a lingua franca Hey look what I saw what do you think you know that's the whole promise of tools like concert for example we demonstrated this this morning it's a collaborative environment as sharing of visualizations and data sets and so forth among business analysts and the normal knowledge worker you know it with it you know like what do you see here's what I see what do you think I don't see that here's another visualization what do you see there oh yeah I think I see what you mean and here's my annotation about what I have broader context I've you know here's what I oh this is great that's the whole notion of humans deriving insight we derive it in socials we derive it in teams of that some Dave might be adept at seeing things that Jim is just absolutely blind to or you know Nancy might see things that both of us are applying to but we're all looking at the same pictures and we're all working with the same data part art yeah it's all so let's talk about some plumbing conversations you know one of the things that we noticed we were at the splunk conference this year's blown came out of nowhere taking log files making them manageable saving time for people so the thing that comes out of the splunk conversation is that it's just so easy to use that their customer testimonials are overwhelmingly positive around the area hey I just dumped my data into this the splunk box and it grid good stuffs happening I can search it it can give me insight save me time so that's the kind of ease of use so so how does IBM getting to that scenario because you guys have some good products we've got on the platform side but you also have some older products legacy Lotus other environments collaborative software that's all coming together in converging so how do we get to that environment where it's just that he just dumped your data in and let it do its magic well Odin go that's the very proposition that we provide with our puresystems puredata systems portfolio tree data system and big insights right for Hadoop so forth big in size you know we have an appliance now yeah we have pdh so that's the whole create load and go scenario that because Bob pidgeotto unless wretched and others demonstrated on the main stage yesterday and today so we did we do that and we are simple and straight being easy to use and so forth that's our value prop that's the whole value prop of an appliance you know simple you don't need a ton of expertise we pre build all the expert in a expertise patterns that you can use to derive quick value from this deployment we provide industry solution accelerates from machine data analytics on top of big insights to do the kinds of things you're talking about with splunk offerings so fundamentally you know that's scenario we all we and we're you know we have many fine competitors we offer that capability now in terms of the broader context you're describing we're a well-established provider of solutions we go back more than a hundred years we have many different product portfolios we have lots and lots of customers who would invested in IBM for a long time they might have our older products our newer products in various combinations we support the older generations we strive to migrate our customers to the newer releases when they're ready we don't force them to migrate so we make very we're very careful in our row maps to provide them with a migration path and to make it worth their while to upgrade when the time comes to the newer feature ok so I got it don't change gears to the to the shiny new toy conversation which is you know you know we love that in Silicon Valley what's a shiny new toy there's always an emerging markets when you have see changes like this where there's a whole the new whole new wave comes in creates new wealth old gets destructed new tags over whatever the conversation goes but I got to ask you okay well Elsa to the IBM landscape that you that you're over overlooking with big data and under the under the hood with cloud etc there's always that one thing that kind of breaks out as the leader the leading toy a shiny object that that people gravitate to as as I'm honest I won't say lost later because you got you know it's not not about giving away free it's it's the product that goes well we this is the lead horse you know and in this game right yeah so what is that what is the IBM thing right now that you're doubling down on is it blu acceleration is it incites is it point2 with a few highlights right now that's really cutting through the new the new the new soil of yeah we're developing our own rip off version of google glass thank you know I'm saying it's always I mean I'm gonna say shiny too but there's always that sexy product well I want that I want L customers name I want that product which leads more you know how she lifts for other products is there one is there a few you can talk about that you've noticed anecdotally is going to be specific data but just observational a shiny toy for the consumer market or for the business business business mark okay yeah yeah is it Watson is Watson the draw is it what's the headline looking for the lead lead dog here what's the attack there's always one an emerging market well you can put your the spot here well you could say that the funny thing is the whole notion of a shiny new toy implies something tangible when the world is gone more and more intangible in the cloud so we are moving our entire portfolio beginning links the big data analytics solutions into the cloud cloud first development going forward our other core principles for the pure data systems portfolio and the light for the shiny the shiny new thing the new cons could be shiny new concept or new paradigm yeah but the shiny new thing is the cloud the cloud is something pervasive and the cloud is something that it really multi form factors that's not very sexy but customers want flexibility you know they want to acquire the same functionality either as a licensed software package and running on commodity hardware we offer that for our big data analytics offerings or as an appliance and one sort or another that specialized particular occurrence or as a SAS cloud offering or as a capability that they can deploy in a virtualization layer on top of IBM or non-ibm hardware or they want the abilities you can mix and match those various deployment form factors so in many ways the whole notion of multi form factor flexibility is the shiny new thing it's the hybrid model for deployment of these capabilities on Prem in the cloud combination thereof that's not terribly sexy because it's totally it's totally abstract but it's totally real I mean demand wise people can see them that drives my business because when you go to the cloud I mean that's where you can really begin to scale seriously beyond the petabytes the whole notion of big media it will exist entirely in the cloud big media I like to think is the next sexy thing because streaming is coming into every aspect of human existence where stream computing a lot of people who focus on Big Data think of volume as being like big headline oh god we'd go to petabytes and exabytes and all that yeah it's important some really fixate on variety all these disparate sources of data and now we have all the sensor data and that's very important we have all the social media and everything all those new sources that's extremely important but look at the velocity everybody is expecting real-time instantaneous continuous streaming you know everything we do all of our entertainment all of our education surveillance you know everything is completely streaming I think ubiquitous streaming to every device and everybody themselves continue to continuing to stream their very lives everywhere all the time is the sexy new thing Dave and I talk about running data we coined that term running data what four years ago so I got to get you got to get kind of a thought leader they're watching us and we're watching streaming data right now from these said these are your guys are streaming this is big media give us some wanna get your thought leader perspective here some thought leader mojo around um the hashtag data economy you know you need now you're moving into a conversation with c-level folks and they said James tell me what the hell is this data economy thing right so what is the data economy in your words kind of like I mean I'll say it's a mindset I'll everything else what's your take on that we've been discussing that internally and externally at IBM we're trying to get our heads around what that means here's my take as one IBM are one thought Leigh right by the way the trick of being a thought leader is just to let your own thoughts lead you where they will turn around where all my followers yeah hopefully they want to lead you to far astray where you're out in the wilderness too long that's an important type of people are talking about because people are trying to put the definition around at economy can you actually have a business construct around yeah data here is my taken on the layers of the meaning of data economy it's monetizing your data the whole notion of monetization of your data data becomes a product that you generate internally or that you source from externally but you repackage it up and then resell with value add the whole notion of data monetization and you know implies a marketplace for data based products you know when I say data I'm using it in the broader context of it could be streaming media as the kind of one is a very valuable category of you know data like you know whatever kollywood provides so there's a whole notion of monetizing your data or providing a marketplace for others to monetize their data and you take a transaction fee from that or it also means in more of a traditional big data or data warehousing bi sense it means that you drive superior outcomes for your your own business from your own data you know through the usual method of better decision if better decisions on trustworthy data and the like so if you look at data monetization in terms of those layers including the marketplace including you know data-driven okay in many ways the whole notion of a data economy hinges on everybody's realization now that the chief resource for betterment of humanity one of the chief resources going forward for us to get smarter as a species on this planet is to continue to harness the data that we ourselves generate you know people stop what data is being the new oil what oil was there before we ever evolved but data wasn't there before we we landed on earth or before we evolved we generate that so it's our own exhaust your own exhaust that's actually a renewable resource data exhaust from data from exhausted gold that's what we say data is the data exhaust it's good if you can harness it and put it together as Jeff Jones says the puzzle piece is the picture the big picture at the smarter picture the smarter planet so on the final question I want to wrap up here to our next guest but what's going on with you these days talk about what's up with you you know you're very active on Facebook will you give a good following I'll be coming up what's happening you know I'll make sure I said big birthday for you on your Facebook page what's going on in your life I'll see you're working at IBM one of the things are interesting what's on your mind these days when you're at leisure are you hanging out you think what are you thinking about the most what are you doing with your you know things with your family's cherith let's see what's going on well I hang out at home with my wife and drink beer and listen to music and tweet about it everybody knows that stuff kind of beer do you drink whatever is on sale I'm not going to say where we buy it but it's a very nice place that whose initials are TJ but fundamentally you know my my mind is an open book because I evangelize I put my thoughts and my work thoughts and love my personal thoughts out there on socials I lived completely ons but I completely unsocial I self-edit but fundamentally the thought leadership I produce that the blogs and whatnot I produce all the time I put them out there for general discussion and I get a lot of good sort of feedback the world and including from inside of IBM I just try to stretch people's minds what's going on with me I'm just enjoying what I'm doing for a living now people save Jim you're with IBM why aren't you an analyst I'm still doing very analyst style work in in a vendor context I'm a thought leader I was a thought leader as I try to be being a thought leader is like being a humorist it's like it's a statement of your ambition not your outcome or your results yeah you can write jokes too you're blue in the face but if nobody laughs then you're not a successful comedian likewise i can write thought leadership pieces till I'm blue in the face but if nobody responds that I'm not leaving anybody anywhere i'm just going around in circles so my my ambition and every single day is to say at least one thing that might stretch somebody's box a little bit wider yeah yeah I think I think IBM smart they've been in social for a while the content markings about you know marketing to individuals yeah with credibility so I love analysts I love all my buds like like Merv and everybody else and I'm you know sort of a similar cat but you know there's a role for X analysts inside of solution providers and we have any number John Hegarty we have we have Brian Hill another X forest to write you know it's it's a you know it's a big industry but it's a small industry we have smart people on both sides of the equation solution provider and influencer my line um under people 99 seats and you know I I suck up to my superiors at IBM i suck up to any analyst who says nice things about me and hosts be on their show and i was going out of my life i'm just a big suck up well we like we like to have been looking forward to doing some crowd chats with you our new crouch an application with you guys lock you into that immediately it's a thought leader haven that the Crouch as as it turns out Dave what's your take on the analyst role at IBM just do a little analysis of the analyst at IBM which you're taken well I think it's under situation I think that the role that they that IBM's put James in is precisely the way in which corporations vendors should use former analysts they should give you a wide latitude a platform and and not try to filter you you know and you're good like that and so guess what I do the usual marketing stuff to the traditional but I do the new generation of thought leadership marketing and there's a role for both of those to me marketing have said this is if I said it was I said a hundred times marketing should be a source of value to people and it's so easy to make marketing a source of value by writing great content or producing great content so yeah that's my take on a jonathan your your marketing is a great explainer you explain the value to the market and thereby hopefully for your company generate demand hopefully in the direction of your cut your customers buying your things but that's what analysts the influencers should be explainers it's you know probably Dave I mean has influenced as influences that we are with with a qu here's my take on it when you have social media of direct full transparency there's no you can't head fake anyone anymore that all those days are gone so analyst bloggers people who are head faking a journalist's head faking the house the audiences will find out everything so to me it's like it's the metaphor of when someone knocks on your door your house and you open it up and they want to sell you something you shut the door in their face when you come in there and they say hey I want to hang out I got you know I got some free beer and a big-screen TV you want to watch some football maybe you invite him in the living room so the idea of communities and direct marketing's about when if you let them into your living room yeah you're not selling right you are creating value see what i do i drop smart i try to drop smart ideas into every conversational contacts throughout socials and also at events like i od so you know a big part of what I do is I thought leadership marketer is not just right you know you're clever blogs and all that but I simply participate in all the relevant conversations where I want I want ideas to be introduced and oh by they want way I definitely want people to be aware that I am an IBM employee and my company's provides really good products and services and support you know that's really a chief role of an evangelist in a high-tech slider that's one of the reasons why we started crouched at because the hashtag get so difficult to go deep into so creates crowd chatter let's go deeper and have a conversation and add some value to it you know it's you thinking about earned media as parents been kicked around but in communities the endorsement of trust earning a position whether you work at IBM people don't care a he works at IBM or whatever if you're creating value and you maybe have some free beer you get an entry but you win on your own merits you know I'm saying at the end of the day the content is the own merits and I think that's the open source paradigm that is hitting the content business which is community marketing if your pain-in-the-ass think you're going to get bounced out right out of the community or if you're selling something you're on so you guys do a great job really am i awesome you thank you James I really love what you add to the iod experience here with this corner and all the interviews is great great material well thanks for having us here really appreciate it I learned a lot it's been great you guys are great to work with very professional the products got great great-looking luqman portfolio hidden all hitting all the buttons there so hitting all the Gulf box so this is the cube we'll be right back with our last interview coming up shortly with Jeff Jonas he's got some surprises for us so we'll we'll see what he brings brings to his a game apparently he told me last night is bring his a-game to the cube so I'm a huge Jeff Jonas fan he's a rock star we love them on the cube iza teka athlete like yourself we write back with our next guest after this short break

>>Okay. We're back live here at the cube in Las Vegas for IBM. Information on demand. I'm John furrier with Dave Volante a joined the crowd chat on crowd chat.net and we're here with less wretched than general manager of business analytics at IBM. Welcome to the cube. Thanks. I know you've got short time. And for the folks that are going about 10 minutes, we're going to just jump right into it. So obviously business analytics and social business, big data analytics and social business driving the market of the data economy. And under the hood you've got cloud and mobile apps and connected devices. So, so the number one thing that comes up is we need more data scientists and we've got to get the data in the hands of users. So, um, talk a little about your vision there and what's going on here around that rent concept. Yeah, I think it's key here as we talk about imagining the future and leveraging big data analytics, we talk about infusing a culture of analytics everywhere in the organization. >>So the key about that is to really create solutions that are fast, that are easier and that are frankly smarter throughout the organization. So how would, how does visualization play into that last one? If you could talk about that a little bit. Because as a business user, you know, you guys are describing the keynotes today, right? Somebody put up the spreadsheet like, ah, how can you make it easier for people to consume? Yeah, you want to have more rapid insight to action. This is all about whether it's predictive capabilities or we think about, you know, when you look at organizations today, you think about descriptive analytics, what's going on and then you diagnose it, why is it going on? You look at the future with predictive analytics and then even look at prescriptive analytics with things like looking at next best action and then even cognitive capabilities. >>What we really want to do here is make it a lot easier for users to not only visualize and explore, but to then see the patterns in the data to guide them. And what we're trying to do here is really change the whole analytic experience. How they make decisions, how information is presented in a much easier way. Let's talk about the difference in, in verticals. A lot of people have a conversations around business strategy and also the solutions they put out. We're horizontal, we're vertical. Something, a very vertical approach. Even at a technical level with the stack or organization, you guys have a play in all the verticals. Um, and the verticals have different outcome objectives yet. So that means different analytics. How do you guys deal with that? I mean it's an opportunity certainly, but I mean from a technology and then solutions standpoint. >>Yeah, I think a, the key here is we focus on number one, taking advantage of all data, whether it's structured or unstructured, whether it's in motion at rest. And then we want to deliver, as I mentioned previously, all analytic capability from descriptive all the way to cognitive and then all solutions. That's where you get then into the verticals. So telcos are looking at customer churn. Insurance companies are looking at broad banks are looking at risk. Public sector organizations are looking at reducing cycle time and then medical institutions really collaborative care, uh, with, with the patient. So what we try to do here is take that capability that we've got all data, all analytics, all solutions, then apply it, pinpoint it. So for example, predictive maintenance and quality for industrial sector customers. So what you see here is we've announced a solution that converges that capability again, makes it faster, it makes it easier, makes it smarter to deploy. >>I talked with this, uh, EVP CIO stat oil, and she told me that, you know, they had their data in a silo for the exploration side of the business, but when they opened up new data sets that had nothing to do with their business, like ocean data, right? It amazing, amazing transformation and improvements in their business. That's two different datasets. How do you guys enable customers to do that? One, do you, do you do that? And these verticals have to kind of go outside their kind of data competency? Yeah. Okay. Can you talk a little bit about that? So really here when you think about analytics and you think about social, mobile cloud, we're looking at systems of engagement, we're looking at presenting information to people on the frontline that could come from many heterogeneous data sources. So what we want to do is be able to bring that together. We have solutions that actually do that and then bring it together for that user, for that particular problem. >>Let's, what does your business look like? I mean, you're running this to the, the IBM analytics business analytics group. What's in the business analytics group? >>Yeah, it's a pretty big business. Um, I actually came into IBM from Cognos, so that was business intelligence. That was about six years ago. I was the col Cognos. So business intelligence is the first piece. Second piece is performance management capability. So this is financial performance management, sales performance management and disclosure management. And then you've got predictive analytics. So you get into statistics, you get into modeling, you get into, uh, kind of approaching some of the cognitive capabilities. And finally, risk management. This is financial market, credit risk, governance, risk compliance. So it's a pretty big business. We focus on customer related areas, operational areas, finance and risk. And then of course with our big data rather than we focused on this overall big data and analytics opportunity. It's a global business. It's a, something that's very important to IBM. And it's a, it's really, when you think about big data analytics, about 15 cents on every it, the >>dollar being spent. So you're there, the Cognos acquisition, I mean you could, you could argue with it one of two of the major acquisitions that IBM has. That's probably one of the two most important that and PWC, right? I mean it's really transformative. Did you, when you were at Cognos, did you ever imagine, could you even listen to the future as to what has become of this sort of big data meme? I mean it's always been sort of the vision 360 degree view of the customer and all that stuff, but the, just the amount of data, is that something that you guys actually envisioned and you're now seeing through? >>Yeah, no, I think we had, um, you know, it really is gotten to be much bigger than I would have ever dreamed of. You know, and this is the whole theme of this conference, right? It's think big, deliver big, wind big. At the same time we did have a view of where this thing would evolve to, we always talked about this whole all analytic capability and being able to present that to the user, being able to exploit the data that's out there in all the different shapes and forms. But it really has grown pervasively. We talk about, first of all imagining it, you know, you've got the four V's of big data, volume, variety, velocity, veracity, but we talk about having the vision and the value. That's the fifth and sixth really imagining the future, being able to realize it with a big data and analytics architecture and then frankly being able to trust it in terms of security, privacy and risk. >>Yeah, you guys have, Cognos was a nice exit. Was it 5 billion was the, who was the exit when an IBM purchased Cognos was most of that? It was a five, $5 billion firm from an IBM. Yeah. So, so you don't, do you think you undersold? No, no. But you know, the reality is is you, you, you, you never would have been able to see that vision through as an independent company. I mean the resources that you're required, whether it's the services, the hardware piece, the other big data analytics pieces would have been very hard for an independent company. I think to compete with that. We were talking earlier about the little different parts of the big data ecosystem. You know, you got a little doop specialists, you know, you got guys who have tried to, you know, remain independent, still doing okay. But yeah, IBM's got a lot of capabilities there. You've mentioned in your keynote project Neo, what is, what is project Neo? >>Yeah. Neo is our next generation data discovery capability. And again, in the spirit of being faster, easier, smarter, what we're trying to do is make this visualization capability as well as the learning capability available to all knowledge workers, not just modelers. So you don't need to do sophisticated modeling. It'll come back and guide you through in a very natural language kind of way. And it's, we're really trying to change how the whole analytic experience happens. And underneath Neo it takes advantage of some of the other capabilities. We talked today about blue, blue acceleration and then our analytic catalyst capability, which really puts kind of the stats and modeling in a box and brings it to that user. So we're very excited. We're going to be showing that today, uh, in our, in our main tent session. So it should be a know 3:00 PM it's at 3:00 PM yeah. >>At three 30 actually. So that's, so next generation discovery that's on across all datasets. Yes. And with analytics, uh, visualization built in for knowledge workers, you mean like a data scientist or like a worker on the front lines. So the iPhone, what, I mean, like a worker, this would be any knowledge worker, but then we're also with analytics trying to make it more pervasive. We'll embed it in a business process, for example, like a next best action or things like that. So you're going to have analytics going to the masses, embedded in a business process, but then here this is all about really looking at in a descriptive way what different things you want to see in your business in a very self service oriented way. Awesome. Awesome. What do you, what are you hearing from customers? You're out in the field, you run into big business of IBM that has a lot of legacy customers with computing platforms and paradigms that have been old-school. >>I'm going to say old school and a lot of new school rollouts and deployments. What are the top things are customers are asking for and when you want to go out, if you the dial up the top three, you know, floated to the top. What are the top three? I think that the number one thing that clients want here is outcomes. Business outcomes very quickly, right? They also want help on their journeys, right? As they look to evolve their analytic cultures, they look to evolve their platforms. They really want us to be able to go on that journey with them, help them understand their maturity, help them understand where they should be going and really help them prioritize the key actions they can take to drive the outcomes. And then it's really a, once you start, you focused on the priorities, then it's really helping them implement those. >>So we really look to, you know, our partner ecosystem as well as our services organization to help them drive those outcomes quicker. So a lot of activity you'd call the market robust at this point, very robust against 15 cents on every it dollars. It's a huge opportunity. It's a very exciting, a certain political business. Your Tim is 15 cents at every it dollar. The big data analytics component of it spent. Yeah, I mean served with service catalog, self-service with instrumentation of essentially value chains. I mean everything is now instrumented for the first time in history of business. I mean you think about it. Yeah. From oil exploration to hiring. So really appreciate your insight. A final question is what, what do you, what should people walk away with who aren't on site here, who are watching a, about what's happening here at IOD? There's so much happening. >>You know, we're talking, I think there's a lot of announcements. First of all, taking advantage of all data, whether it's insights stream. So we've got all data announcements, all analytic announcements, new solution announcements. But as we've looked out and we talked to many of our clients over the last couple of months, what do they need help with to be successful here? Because this is really all about outperforming. It's about continuously transforming in your business. They, they really want help imagining the future. So let's infuse that analytic culture everywhere in the business. Let's really, um, realize the value here. So evolve our platform and architecture and then really do it in a trusting way to drive the outcomes less. Thanks so much for your time. I know you're really busy. You've got a lot of, uh, business to do, customers to talk to a and speeches to give. Appreciate your time taking on the cube business outcomes fastest. What people want the most, help on this journey and collaborative way and implement it, scale it up. So, uh, that's, that's the future of business, social, social, business, business analytics and data. And onto the hood, the engine of innovation, cloud and mobile, social. This, the cube. We write back with our next guest after the short break, >>the cube.

okay we're back here live at IBM iod this is the cube our flagship program about the advances in there from the noise i'm john furrier the founders look at an angle enjoy my co-host David on to the co-founder Wikibon or go to SiliconANGLE calm for the reference point in tech innovation Kotobuki bun or for free research research analysts they're putting out free content and of course you always come by the Cuban see where we are in the events wouldn't be at Amazon Web Services event with all the events extracted sniffle noise and share that with you our next guest is Tom de Klerk CIO of superior group welcome to the queue thank you Dave you and I'd love to talk about CEOs because you know maybe we get the real scoop on things so first why you here at IBM iod let's get that out of the way to talk about some of the things you doing here and what you're seeing here sure so we something with the company three years we're a staffing organization why I'm here I was actually here last year and we've implemented three major systems in the last three years one was SI p and embrace the ERP system second being IBM connections and the third being IBM cognos and so over the course of the three years you know trying to roll off these projects so I'm here to to learn more about you know the capabilities of cognos and the biggest one for me is that with cognos and SI p SI p when they bought their in iowa city i'm sorry when IBM bought cognos it was 881 they had a report pack specifically for SI p customers so when they went to 10 1 and 10 2 they didn't offer that product so there they just started developing a year ago I sat down with some senior executives if the IBM organization and said you guys are losing an opportunity here customers that have an implementation of SI p and trying to get information out other than using SI piece product business analytics so they over the course of the year have been developing a rapport pack that they can offer the customers so we were part of the beta testing program for IBM and so that's I'm here to actually talk to some other people and understand something listen to you see how they impact on product development that's good well yeah there's there's the continuous improvements even I'm even on the well you look at the report pack now it's still in my mind and I fed this feedback back night there's it's a do list oh absolutely but that's not any type of a rollout of any product you can expect that so tell us a little bit more about superior group you guys your staffing company would yes we're a we're a company that's headquartered in Buffalo New York and we started back in nineteen fifty-seven it's a privately held company we have a total of 400 staff employees and roughly anywhere from seven to nine thousand contract employees so we provide workforce solutions as well as outsourcing and primarily in three areas people process as well as the outsourcing project outsourcing so on the people side it's your traditional recruiting for staff augmentation executive Research recruiting as well as direct placement and then on the process ID we offer managed services program we also offer vendor managed services independent independent contractor compliance and then on the outsourced and we have IT outsourcing HR outsourcing so that's pretty much our companies make up and tell we were talking off-camera about sort of the role the CIO and you'd like to everybody would like to be more strategic if they had time but a lot of the cios especially mid-sized organizations she doesn't don't have as many you know people to to be able to sit back and do some of those more strategic things but so a lot of CIOs talk about transforming their organization you've kind of transformed it with three huge projects in the past what would you say this was two years yes sir yeah the solicitors perspective SI p was started in july of 2010 and then started last year with the IBM connections and the Cognos reporting okay so but still over sure yeah let me that's that's some major disruptions to talk about how you manage that so it was extremely challenging especially given the number of resources that we have were a mid-sized company and when I came from a manufacturing organization spent 15 years working for manufacture Murray so going from that vertical into professional services vertical I was used to used to having a lot of IT resources to be able to support an organization so you highly leveraged the contractors and consultants both with sa fie they're implementing partner as well as an IBM it was critical for us to leverage IBM's knowledge and their skill set in order to be successful in rolling out our products so the SI p rollout was was the most complicated i'm sonia to me by far by far it took yeah we rolled out ECC six-point lead us with the full suite payroll sore we provide pay Rowling's one of our services so HCM which is human capital management the sales and distribution material management so a lot of the fundamental components of sa p we rolled out so it was it was quite a an interesting experience that was that core yes he went capital measurement or success factors no ms core we've looked at successfactors about it about a year ago and it just doesn't fit quite fit at this point in time as they start to develop in the product becomes a little more mature that may be a better fit for our organization and connections what was the driver behind bringing them in and talk about that a little bit sure so for us connections we did some analysis early this year breaking in january went a project strategy where we looked and discussed with some of our internal associates and interviewed about 30 staff employees and one of the only two fundamental things that came back out of that analysis was one we don't communicate properly our business goals throughout our organization so we're headquartered in Buffalo but we have over 50 locations worldwide so we have a lot of connect you know offices remotely and people that aren't sitting at our headquarters and that was another concern of feedback that was brought back to us was that we don't have the ability or the people with the remote offices felt like they weren't part of the the whole process or communicating properly with a corporate headquarters so we felt that this was the perfect platform to allow us to enable them so we did quite a bit of research we have a director of marketing and mobile strategy that went through a complete analysis and we looked at the SharePoint product but what's nice about the this product as opposed to the SharePoint is the the look and feel of you know like a linkedin the Twitter and that social media aspect of it so it really leveraged us leverage for us an opportunity to to collaborate and to reach out to these locations so the objectives were collaboration better communication so how is that being used how widely is it being used how did it change things it's really curious as to the outcome so actually it wasn't very positive outcome in it you know as you roll out of when you take a company you actually do a transformation into a social media type organization it's never in my opinion ever done it's a continuous process so we're still evolving as we go along I think the key is to be a front is that have the right adoption strategy so last year in january i attended the IBM connect down in florida and i actually participated an event with some senior execs with sandy sandy carter from IBM who heads up that part of the organization the social media and so it really it was about adoption strategy it's keith really not only is it just to implement it that's an IT thing and that's pretty straightforward but i've seen in the past it's always the challenge of not only just implementing the technology but then it's it's adopting and getting your users to use that and so because it had that look and feel that a lot of the people are familiar with you and your facebooks and that it's X have been extremely successful in rolling that out now that said we still think there's additional opportunities and we're looking at doing some enhancements social dashboarding looking at executive blogs a big value at four ization it's just when we roll it out not just internally to our staff employees but rolling it out to our contractors so we have anywhere between seven to nine thousand contractors working for superior and so they'll be working in our business there's a high turnover rate yoko and we'll place someone at a company but maybe work there for a month two months a week and that when they leave that now which goes away with them so we're really targeting our value add to be able to roll this out to even to our contract employee so when they go work on site they start to collaborate share information and invent that they do leave we still harvest that information that's bi-directional too I mean they're a representation of your company even though they are transient but so you can communicate to them like you say executive blogs what the what the corporate messaging is policies whatever it is that they can take it to as representing you essentially as an extension of your workforce and as you say you get knowledge back right oh absolutely and so one of the key values that we places that when we did that analysis I said earlier is that we didn't feel like there was a communication so now with the social media platform in place now we have people that are in our bangalore office can communicate and feel like they're in touch with our corporate headquarters and also their co-workers that are saying it on-site facilities that our customers so it really is improved that collaboration and communication it's really brought the organization together did you ever think at one point we just used you know publicly available social tools Facebook or LinkedIn just start a blog yet we and our organization has done that we have the Twitter count the facebook account but this was an opportunity for us to develop it and Taylor more customized it more for hours or specific names you've integrated those public network lots of little works right you if you go to our website you'll see the links and connections right into that yeah so functionally it's obviously a more rich environment connections right so why don't we talk about that a little bit what sort of what additional value did that bring to you is paying for it well sure is you how to justify it what value did you get there several areas that we feel it brought value one is you can it's a platform that can accessed anywhere so you don't have to be on our internal network to be able to access and collaborate and communicate right so that was a huge value add for our organization allows us to connect and stay stay together it empowered our users to be able to contribute openly be able to collaborate to be able to innovate and be able to take calculated risks from IT standpoint we see a reduction in email I don't have the actual numbers to tell you what percentage reduction an email but I'm pushing very strongly that we have an opportunity to use and leverage connections instead of sending emails traditionally you know people send an email check this where with connections you put the hosts the content or you put the files upload the files in there and they'll send a notification so you're not plugging you know plugging up your email system with additional data so yeah there's a Productivity aspect of that absolutely I think oh god I was Christian and the other thing is that you know the time to market for solutions has definitely reduced and even the the increase in efficiency so I know we spent some time looking at like this ed brillz book on opting in and then there's his situation identifies in the book is the traditional product manager they find him in manufacturing is really moving more towards a social product manager leveraging the IBM connections or for superior we took an opportunity to do that so I got to ask you about the social software Dave and I've been tracking jive all these other companies amor the facebook for the enterprise is kind of what they've been calling it but the feedback we've been hearing from CIOs was that I just favorited I signed something is it's in the social media team is running it that other team and so we were talking about the metaphor that the social media teams are a lot like the web teams in the 90s oh yeah we need a website yeah the kids are doing it right like the new guys the young guys are putting a web pages searchable it grew obviously it's relevant the websites grew and became big business e-commerce social media is the same way it's like everyone can see that it's real they know it's gonna be important it's not a lot of budget associating there's not a lot of personnel so the issue is is that they get implemented these say if they get sold these software packages and then they got to implement it kind of like communities yet this other stuff happening twitter facebook linkedin events live streaming so a lot of other social activations going on so so i want to get your take on as a CIO do you look at get involved in levels like that on the app's side is those apps decisions made with that in mind of like the personnel costs and and and the actual to run it and i've got some guys just for the hey i bought that i don't use anymore why it's just too much hassle right so there's a hassle factor what do you take what's your to my taste first of all I'm very big on when i get an asset or acquire an asset as best you realizing that asset you know and i came to this organization i saw several situations where assets were purchased to your point and just sitting idle because maybe it was a head take additional initiative to implement that so in our situation i work very closely with a gentleman that really did most of the work and doing all the research and its name is Franco he handles our he's a director of digital mobile strategy and so he went out and did all the work for us came back and sat down with myself and our president reviewed what makes the most sense I came from a manufacturing facilities it utilized the SharePoint so I was big at SharePoint so I was kind of was pushing in that direction but when I actually sat down with him i we went through really the true value adds what we can gain from that it was really a no-brainer for us do you ever have a situation where you put you put your fist down so hey you know what we just got to abandon that right now let's cut our losses move on in physics for example is another use case where same same situation I won't name the vendor was an IBM it was another one where hey want to do some new things we don't the staff the guys making us drive this engine until we get an roi out of in other words they were like we're going to ride this Pony until either collapses or ROI comes out of it when in reality they just driving down a cul-de-sac yeah so at some point in an emerging market like we're in agile is the option to abandon right you got to know and to cut the cord right oh absolutely and I'm not you know I'm not in a position where I'd say absolutely one band if it made sense it's right it's got to be a business decision well altima tlie position has always been it's got to work with the business and let the business drive and not i.t i.t is there to enable the business so we can provide our input and on the day they let them make the decisions now we didn't talk about the Cognos implementation any kind of depth so tell me tell me what you're doing with with cognos we talked a little bit about the essay p extension but how are you using cognos so primarily we have as i mentioned before part of our businesses and the managed services programs we offer MSPs which we have a tool called work nexus which is our vendor management solution involves our MSP they our customers will use this tool for recruiting for looking at time clocks looking at the proving timesheets invoicing and so forth so we have some pretty strict requirements of pulling that information now in providing reports to our customers we use our platform developed on it's based on abdominal environment so we in order to give them the reports we create what's called ad-hoc reports out of Domino very limited capabilities so that was our first target area was to use cognos to provide more enrich type dashboards active type reports for our customers we're just about completed with that part of the project the next is really to pulp reports out of sa p and so the standard reports that that i have with that IBM has provided is really more in the SD area as well as in the MM area so for our organization we're so heavily on payroll and people we really need to have report start in that area so and the next year i'm trying to work with a partner local partner in our area LPA systems to help develop more reports tailored towards SI p to provide workers compensation but i need to run a report that pulls out the work of compensation to do an essay p is so much more costly than to do it out of out of the Cognos so that's our goal in the next year's really to pull more reports using cognos out of sa p okay um what if we could talk a little bit about cloud which you're sort of stance on that you know some cio say no way others say yes others get you know shadow I t he coming to the cloud what's the state of cloud from an infrastructure standpoint and even a SAS you organization sure so we're currently in the process actually I'm looking at our organization and a traditional IT become a cost center so I'm trying to actually move it into a profit Center by offering services so we're targeting in the Buffalo area anyways small companies we're offering hosting cloud-based service whether it be private or rather be a public cloud services I'm not opposed at all to using a cloud-based solution in fact I'm on my essay p side for my dr site i'm doing just that i have a contract with a where the company is providing me a a cloud-based solution for my dr ok so but so you use it for disaster recovery are you doing any sort of Production apps in the cloud or would you ever consider doing that or no because we would consider i'm not sure if i consider this company because our information is very this very controlled we fall under the ssae 16 because we house that we host data that has in the HIPAA regulations all the different regulations so we have people social security number in that so to offer that in the cloud not to say that's not secure but we have much better control and we have an infrastructure in our organization that has enough bandwidth has enough cooling all the normal environmental that you have for data center so right now for us it makes more sense for us but in three to five years from now maybe even sooner that will probably look at possibly what's the cost differentiation between doing it in house having the resources to a versus offering what about test endeavor you do any tested dev stuff oh yes we have in our SP environment have a traditional three-tier landscape so we've got a dev quality in the production all of which is housed inside the decision actually to have that to have that done was before I joined the company so we the decision was made at say in May of 2010 I joined in July had I been before and I really would have pushed to have that hosted somewhere else because my opinion for an organization mostly like ours we don't have the technical expertise to be able to you know the basis capabilities the architecture the hardware all that type of stuff so I think that's a better fit for most people in do an essay p implementations of looking at that may be the first second or third year if you trust me we don't have that experience if you're new to an essay p type environment no no no no use case for it right no using Bitcoin at all no you have a from Association last night about Bitcoin still look at the next to look crazy were down yeah PayPal's looking at is that in the news it's not mainstream enterprises yeah we loved we loved talking to see iOS housley Wikibon community we have a lot of CIOs with a lot of CEOs in our network and you know this is challenging opportunity but the days the good days are ahead i mean we're seeing huge investment opportunity growth new top line drivers that are changing the business where the CIO is kind of CEO like dealing with all the normal cost side but really drop driving profits so so i got to get the question before we end the segment is cost center versus profit center and you guys mentioned you guys are down pnl profit center right how does that change the game mindset wise and how you execute and what you can adopt and how fast well obviously the owners of the organization love the fact that we're offering that as a as an opportunity to generate some additional revenue i'm assuming you took the facilities equation out of your pnl yeah right what was it so good before i joined the organization write that down at her i keep track of that for sure okay go ahead but before join the our organization i joke jokingly say this we had more bandwidth in some banks I mean we really had the the infrastructure in place I fully redone it and so forth so we had long-term contracts so I've got five-year contracts with services with companies that I have to keep otherwise you can pay the penalty and get out but so we said you know why not leverage and we did a virtualization project when I first joined we recovered over fifty percent of our data center space so I have all this empty space I've all this band was sitting here I've got all the redundancies in the environment to be able to support that why not go after a small company i'm not going to be able to compete you know with the bigger companies and that but we're targeting some of the local companies and we're doing quite successful yeah why not that's great yeah awesome okay we're here live at the iod conference this is the cube we'll be right back with our next guest after this short break stay with us the q

okay we're back here live at IBM information on demand this is the cube our flagship program would go out to the advanced extracted signal from the noise this is SiliconANGLE and booking bonds production exclusive coverage of information on demand we have a crowd chatting on right now go to crouch at net / IBM iod this is a chat web app mobile version coming so I saw the complaints earlier be part of the conversation to log in and share your opinion with us ask questions a lot of folks on there right now great engagements with all that all the comments go to the public timeline of LinkedIn or Twitter wherever you sign in on to the hashtag IBM iod we'll be watching that I'm John Furyk gentleman my coach Dave vellante and we have Marsha Connor on who's the principle of sense of I grew she's also an author and she writes about the topic welcome to the queue thank you glad to be here so what is social business I mean you know we love we love talking about social business but it's kind of like you had this term web 2.0 which is everyone argued about you had big data which everyone kind of argued about which actually Israel 30 it's a real market social business which is kind of an elusive term what the hell does it mean is that Twitter or Facebook is it social media consultants is the real value there since this is the kind of question that everyone's talking about and we're talking about so what's your take on that >> my take is very simple for way too many years decades when people go to work they have to leave their personality their heart their cares their relationships in the car or in the subway or however they got to work that day and social business is really the first opportunity we have to be human beings at work we're allowed to actually talk about the things we care about to be able to bring our interests and our passions into the conversation to be real trustworthy people and what happens as a result of that is that for the first time ever there is an acceleration in the workplace because people can actually be their full selves it seems so simple only because the the backlash or the way that we have worked for so long has been so strong and so overpowering that we almost equates not being human with what business is so the idea of social and business being together it seems a little off we assume that business is human is inhuman but the idea of bringing them together is a huge step in the right direction and it opens up the possibility of actually doing great things >> there should be some anti social >> Jeff chick just say we maybe software in commenting about it's almost too social right now people need to kind of bring that personality to work so it's very interesting day what's your take on this I mean you're an analyst you look at the market is social business really mean what's your take on that yeah I think it slowly rabbids to me it's just it's second nature right i mean i remember the conversations not that long ago it's probably 2006-2007 what's the ROI on social media and do we really want to apply it to business and then so what happened was people just did it right and when they did it they said this surely works and we're getting productivity gains and people are happier and it's just a sort of a natural progression of what we're doing in our everyday lives so I just think to me the real opportunity is now okay what's the future what can you do with all this data were collecting and how can you actually affect you know changes within organizations and feedback to people and power them in different ways so that's kind of you know what I think about it I mean does that make sense to you >> it does actually I take the almost opposite view though it's not that they're in fighting with one another but the idea is that we need to figure out what we need to remove not add so it's not that we have all this new data and we can actually be doing more stuff but the question becomes for me and their organizations that I work with this what can we remove what are the policies that the nonsense that happens in work every single day that shouldn't be there is only there because we don't have a better way a more trustworthy more human way of actually working together so it's incredibly liberating or incredibly open from our perspective simply because it's it's less >> processes you haven't evolved to adopt >> so you're saying the business ooh the permeation of social networking within organizations that's not true for >> all organizations right i mean when >> they're starting with a green field the >> business processes are very social right >> about 70 people though and all of a sudden somebody says we need an HR department we need that the number was 50 >> 70 actually well especially for organizations that have aspirations of growing very very large and they get to this point where they believe that they have to put these things in place because there's this expectation that business means heavy process organized codified and I'm not saying that there aren't some benefits of actually having some order amid the chaos there's absolutely benefit there but we need to be thinking about what is needed at human scale versus what is the building or the organization itself need to be maintained to keep going >> saying if they take a small startup that >> so you're very social they've got social tools in place as they grow your day they muck it up just that what you see >> that is what I'm saying one of my clients a number of years ago I pulled me well actually I overheard this and then I had a conversation with him off line he pulled me aside who said you know what you really do is you make work not suck and he said it so candidly and it's a leader in a very large corporation I thought to myself wait a minute I had never really thought about it that way but for the large part that's people in the organization's feel like the amount of time that each of us spend on actually just maintaining the organization it's time that we could be using for far better things and so if we can start moving away from that maintaining of the organizational rigor we can actually start using that in those ingenious skills back to what we're doing >> example i was using about the use of the >> so the startup of the green sheet of paper the better example is the big company that you're sort of overlaying these social processes on top of how are you helping them sort of break the old habits maybe >> talk about what they should be doing >> yeah well the most specific thing I do is I very rigorously scalpel like actually organizations tell me of going in and identify one of the things keeping people from being able to do work that they were hired to do when's the last time you hired an idiot when I >> asked that question >> question we were just talking about I >> I won't answer that >> I ask that question actually very often is sometimes actually just speaking to a very large group and somebody always gonna raise their hand there's time the story and that's a little uncomfortable at times but the reality is we hire the best and brightest people that we know we try to find great people but something happens about two and a half weeks in all of a sudden they just get stupid right all of a sudden they can't do whatever it is >> very social they don't blame yourselves someone else I didn't I didn't improve that guy but let's not over though but some finish the story here because you're basically saying we inject stupidity into the system it's generally >> Yes we inject the stupidity in but we put them in cages in large part we ask people to say leave a large part of who they are what they're capable of doing somewhere else and so what happens is the longer you work for an organization the more likely you are to be incredibly invested in your community you either work at the Boy Scouts or or you you know you lead a program inside of your community to do better food services a well we have we find consistently is the more you feel like you've been stuffed into a desk drawer the more likely you are to still bring those capabilities to some other part of your life that's just ridiculous don't get me wrong I'm a big fan of people doing great things in our communities but it's really sad to me to understand that we can't bring those same capabilities that same ingenuity into the workplace where people were hired to actually share those gifts >> okay so so but so you go with the scalpel okay oh let me tell you a policy manual how do you not cut to the bone sami do you absolutely there are you not cut into muscle well such an example yeah that would help us I'd say most organizations have no idea where that muscle on that bone is it i mean that's actually a great question so so it at a more abstract level let me just say that there's i have been handed paper-based read notebooks from some of the world's largest organizations where you are going page by page by page of the policies the procedures and sometimes those are handed out in the new employee orientation other times that they're just assumed where people have to actually to start learning from you know social learning from the people around them as to what's the appropriate thing or what's an inappropriate thing to be doing and if you start actually looking at those you discover time and again that those policies those guidelines this what is establishing the culture are largely based on one person doing something really stupid and that person probably especially given a social business world probably wouldn't have done it a second time in this new environment but in this particular case they did that and all of a sudden we had to actually like in a community after a wreck now a stop sign are you had to you know put up a light because you hate had the lawyers be involved in this there's an incredibly yeah covering your ass you're overreacting simply because we haven't had better processes in the past one of the things we know for example of social tools is that when somebody says something stupid their co-workers almost always rise up and say that's not right anymore that's incorrect or here's a better way to do it the only thing worse than people saying dumb things work is people believing dumb things work and with these tools we all of a sudden have the opportunity to correct those things where people do smart things again so from a scalpel like perspective it's looking at what are the underpinnings of our work what are the things that are controlling how we work not only just the processes but the behaviors that are there and to actually look through them systematically and to remove everything that's there then the next step is really talking with people and being able to prove to them that when they work in different sorts of ways that they will be treated in different sorts of ways and frankly that becomes a harder exercise the larger the corporation >> chat from grant case how does an >> so question from our crowd organization start that journey especially in a firm like financial services where that might already be part of the culture >> is always part of the culture you advances in financial services I work with a very large business the business ensure for example and what we found is that when they start introducing social tools into the workplace they weren't so worried that people are going to say dumb things they were more worried that their employees were like cats under the stairs that nobody would say anything because they were so terrified of what would happen as a result of them saying that and so we had to do is are introducing into the culture of that organization processes that would say we care about what you think we had a woman for example say that when we went to her and we've been told that she would not participate in something like this when we went to her she said you know I've been putting in my desk drawers literally for over 20 years all the cool things I've wanted to do in this organization and you're telling me i can now blog about those things or i can actually put them in a micro and and we said yes and says well i really don't believe you so it wasn't even mad saying we can do it but well I get in trouble you know I get in trouble and I not even get troubled by the big police but just well I get you know looks from my peers and so we actually started giving her examples of some of her peers and some of her colleagues who were doing different sorts of things in her being able to build trust that this was a workable system >> does crowdsourcing just Twitter does a success of Facebook and LinkedIn the social networks nicely the rise of the hashtag which has become a great waited for people to dial into folksonomies of groups or active conversations does that change and give people more of a it removed some dissidents if you will about okay it's okay to be public does that change the game a little bit on social software is it validated or just a scare people further into the into their caves we see on crowd chatter there's more anonymous viewers that happy boo actually sign in it has become kind of like an arena we mentioned sometimes it's like gladiator the thought leaders battling it out for you know we seen this on forums right higher see chat rooms you know so people just want to watch yeah >> so what you're what you've done though is reduce this down to one personality type and the reality is that we have have extroverts and introverts in our workplace we have people who are comfortable talking in public and those who aren't and so the simple introduction of online tools brings to our workplaces a way for people who are uncomfortable sharing to do that with a little bit more anonymity and to have a lot more comfort and being able to do that they may not want actually look people in the eye when they say these things but it doesn't mean they don't have valuable things to say I was asked by a journalist a number of years ago if I believe that the introduction of social tools would all of a sudden mean the end of meetings in the workplace and I said absolutely not but what you're now going to hear is the voice of people who never spoke up at meetings and to actually have a well-rounded workforce you need to have the voice of all those brilliant people you hired >> wait a moment yes I think I said all the forecast for cars was limited because they didn't people think enough chauffeurs to drive them you know nobody will buy them still is gonna bite it's a big barrier small market it's not enough show first is a wreck yeah >> but if we can actually provide a venue for everybody to be able to contribute at work one that's either in person or online we're just opening up the possibility of who could >> okay so what's the craziest thing you've seen both on two spectrums with social business successful crazy and crazy good meaning kind of like Anna Steve Jobs craziness way to a crazy fail you have to name names he just can talk about the use cases I mean by that or you can talk about the names if you want to the appoint people out crazy good wow they really levered all the aspects of the data they they were innovative just or lucky or two they put a lot of money into it and it could failed miserably yeah okay I think I can come up with two I'm not so sure and the crazy like in woohoo were in Vegas kind of crazy example though give me a few minutes wrapping up with that one okay though I will say that in a large financial services organization that the Vice President of Human Resources i actually have photos of her going around to every single cube on her floor and taking person and taking photos of each employee for their personal profiles because people are so terrified of actually even doing taking that step that she walked around the floor of her building and took pictures of every single person and that may not see a saying some crazy in Las Vegas sense but it was pretty radical for her to be doing that but it showed her commitment to be able to do this so let me give you a different example electronics firm we're going through I'm so a large global not going to name names but you can probably actually make some guesses we're going through some horrible financial problems and it was just a right around the time they introduced social business tools into their workforce and when they did that the the pretty much the person who is supporting that initiative would send out emails to move people toward working in a social way at he would send out emails that would be fairly scandalous actually and they would say things like it's about to get on the press that we were about to lose dot dot dot at all his email would say and then there was a link that they had to actually go into the social system to be able to learn the rest of the things he not only had a blast actually eliminating the whole lot of link faded the entire over a hundred thousand personal work for that's good pageviews assassin twitter / ma been going on to in a matter of days they had pretty much converted the entire organization to be using these tools and as a result of that they believe that they actually didn't have all the problems they would have had had they not done this because for the first time ever people weren't just sitting behind their desks and being terrified for their lives going back to your crowdsource point they were there together and they actually could talk about what's going on they created what we call rumor central which is a practice that I bring into many organizations they actually had a group within the organization that anybody could ask anything they could actually ask the question what is the rumor you know they could say here's the rumor I've heard how accurate is it and then somebody in the organization would actually be there to answer that and be able to correct that and be able to fix that and it was a beautiful example of how that works >> from the crowd chat along the line of >> we had a question coming question we just had to run the people extroverts and introverts so the question is what is the value of a lurker in social business is there one well if it's a person kind of hanging around question was that that's a great question oh yeah >> I thought you're muttering under your breath like a lurker okay the problem with workers he said she's yelling in the cheap seats what we know about lurkers is that traditionally they are people who wouldn't raise their voice in a meeting that they are also somebody who is just going to you know sit and listen but what happens is it that person then goes to the restroom or goes to the cafeteria or actually even on the bus that night or in their community and they talk about what they've learned so the idea of measuring people as lurkers or participants is a very shallow way of looking at it because it only means that the value is in the conversation of their having at that time or that they didn't comment or they didn't contribute that that is what provides value it's a skewed perspective on engagement it's a cute perspective of what brings value to the organization if they can be listening which is a truly an untapped skill and most of our workforces that they can be listening and then they can actually be thinking also a crazy idea and actually then be able to figure out what they are doing and then be able to do that all the value there but I'm I actually am a little bit weary sometimes when I see the people who are commenting all the time >> it's like lurker so in social context if you can see the participation if someone's just just online with an online button you don't even know if they're listening right so I think that's I think that's the key point if they're listening and they're active that's an interesting data point so like one things that Dave and I look at and lurkers is are they in context to the conversation and are they active so getting that active data is interesting in context to what's being measured so if we look at a cluster of a crowd like a crowdsource crouched at hey if someone's actively talking they're in in the in context >> I still think that's an extroverted way of looking at it I still think it's a way of saying that that engagement is only by hearing or seeing their voice so let me give you the example so I work with a large an organization the intelligence community I'll leave it at that and one of the things that they track is where people actually look online and as a result of that they're actually able to follow the thread from the first thing that they looked at what do they look at next and they have and are able to establish breadcrumbs as to what someone looked at first and then what they looked at next and then what they did after that and what happened is along that whole continuum somebody eventually at some point in time will do sort of the equivalent of a like or they'll add a comment somewhere along that path but then if you go in and you were looking at that first document and you then get to see sort of like amazon recommends other books you can then say other people who looked at this document looked at these things next now that first person may have not commented for a very long time if ever but the value to the other people in that organization by understanding the other amazing and wonderful and helpful or not helpful things they saw afterwards brought incredible value to the organization and that was a a passive way of actually sharing and helping and narrowing down and helping people make better decisions but it was by no means the level of active engagements that so often we are looking at as the only measure of value in the organization Marcia we got cut on time here our next guest but amazing conversation folks go see her blog guys awesome thanks for the comment we'd go another hour okay but they'll give you the final word what is just share with the folks out there your view of the future next couple years what's going to come around the corner connect the dots what do you see happening is going to be an implosion the kind of Biggs is going to be more growth what's going to happen what do you think is going to how is this industry industry how is social business going to shape up >> well I'm if we're talking about the next few years I think that we are all in for a big wake-up call not only are we starting to see the structures and the systems around us failing from my government and economy all sorts of different ways a perspective but if we look at epochs of history this happens consistently and we're about the end of this particular epoch and I say that not as a doom and gloom er at all but to say that I believe for the first time we have the tools and technologies to be able to do something significant to be actually be able to rewrite how organizations work what work means how human beings get to interact to be able to make change in the world that has been cordoned off for way too long and so as these systems the systems that aren't workings are falling away we have the opportunity to actually be able to lean in to be able to live in and to be able to say I want to be a human being 24 hours a day I don't want to be a number or a chess pawn any longer and i am going to actually make a difference in the work i do and i'm going to do that throughout my day every day so i'm i'm incredibly excited about the prospect of what we can do it requires us all to actually look inside figure out who we are figure out what we want to do and actually be able to go do that social destruction of old with new new >> humanization of the crowd and waves of innovations we always say tave you don't get out in front of you become driftwood and there will be some destruction in business models we love it this is social business this is the cube exclusive coverage from information on demand ibm's conference here in Las Vegas is the cube we write back with our next guest right thank you the cube

okay we're back live here inside the cube rounding out day one of exclusive coverage of IBM information on demand I'm John further the founder SiliconANGLE enjoy my co-host Davey lonte we're here in heat you saw who's the vice president I said that speaks that you know I think you always get promoted you've been on the cube so many times you doing so well it's all your reason tatian was so amazing I always liked SVP the cute good things happen that's exactly why i be MVP is a big deal unlike some of the starters where everyone gets EVP all these other titles but welcome back thank you so the storytelling has been phenomenal here although murs a little bit critical some of the presentations earlier from gardner but the stories higher your IBM just from last year take us through what's changed from iod last year to this year the story has gotten tighter yes comprehensive give us the quick okay quick view um okay here's the point of view here's the point of view first you got to invest in a platform which we've all talked about and i will tell you it's not just us saying it i would say other vendors are now copying what we're saying cuz if you went to strata yes which you were there we were there probably heard some of the messages that's right why everybody wants to be a platform okay one two elevated risk uncertainty governance I think privacy privacy security risk this is what people are talking about they want to invest in a more why because you know what the decisions matter they want to make bigger beds they want to do more things around customer experience they want to improve products they want to improve pricing the third area is really a cultural statement like applying analytics in the organization because the people and the skills I would say the culture conversation is happening a lot more this year than it was a year ago not just at IOD but in the industry so I think what you're seeing here at IOD is actually a reflection of what the conversations are happening so our organizations culturally ready for this I mean you guys are going to say yes and everybody comes on says oh yes we're seeing it all over the place but are they really ready it depends I think some are some are absolutely ready some are not and probably the best examples are and it really depends on the industry so I'll give you a few examples so in the government area I think people see the power of applying things like real-time contextual insight leveraging stream computing why because national security matters a lot of fraudulent activity because that's measurable you can drive revenue or savings healthcare people know that a lot of decision-making is being made without a comprehensive view of the analytics and the data now the other area that's interesting is most people like to talk about text analytics unstructured data a lot of social media data but the bulk of the data that's actually being used currently in terms of big data analytics is really transactional data why because that's what's maintained in most operational systems where health systems so you're going to see a lot more data warehouse augmentation use cases leverage you can do on the front end or the back end you're going to see kind of more in terms of comprehensive view of the customer right augmenting like an existing customer loyalty or segmentation data with additional let's say activity data that they're interacting with and that was the usta kind of demo showing social data cell phone metadata is that considered transactional you know it is well call me to record right CDR call detail records well the real time is important to you mentioned the US open just for folks out there was a demo on stage when you guys open data yeah at all the trend sentiment data the social data but that's people's thoughts right so you can see what people are doing now that's big yeah you know what's amazing about that just one second which is what we were doing was we were predicting it based on the past but then we were modifying it based on real time activity and conversation so let's say something hot happened and all of a sudden it was interesting when Brian told me this he was like oh yeah Serena's average Twitter score was like 2,200 twit tweets a day and then if some activity were to happen let's say I don't know she didn't he wrote she had got into a romance or let's say she decided to launch a new product then all of a sudden you'd see an accused spike rate in activity social activity that would then predict how they wanted to operate that environment that's amazing and you know we you know we love daily seen our our crowd spots be finder we have the new crowd chat one and this idea of connecting consumers is loose data it's ephemeral data it's transient data but it's now capture will so people can have a have fun into tennis tournament and then it's over they go back home to work you still have that metadata we do that's very kind of its transient and ephemeral that's value so you know Merv was saying also that your groups doing a lot of value creation let's talk about that for a second business outcomes what do you what's the top conversation when you walk into a customer that says hey you know here's point a point B B's my outcome mm-hmm one of those conversations like I mean what are they what are some of the outcomes you just talked to use case you tell customers but like what did some of the exact you know what I'll tell you one use case so and this was actually in the healthcare hotel you won healthcare use case in one financial services use case both conversations happened actually in the last two weeks so in the healthcare use case there's already let's say a model that's happening for this particular hospital now they have a workflow process typically in a workflow process you you're applying capabilities where you've modeled out your steps right you do a before be before see and you automate this leveraging BPM type capabilities in a data context you don't actually start necessarily with knowing what the workflow is you kind of let the data determine what the workflow should be so in the this was in an ICU arena historically if you wanted to decide who was the healthiest of the patients in the ICU because you had another trauma coming in there was a workflow that said you had to go check the nurses the patient's profile and say who gets kicked out of what bed or moved because they're most likely to be in a healthy state that's a predefined workflow but if you're applying streams for example all the sudden you could have real-time visibility without necessarily a nurse calling a doctor who that calls the local staff who then calls the cleaning crew rate you could actually have a dashboard that says with eighty percent confidence beds2 and ate those patients because of the following conditions could be the ones that you are proactive in and saying oh you know what not only can they be released but we have this degree of confidence around them being because of the days that it's coming obvious information that changes then potentially you know the way your kind of setting your rules and policies around your workflow another example which was really a government use case was think about in government security so in security scenarios and national security state there is you never quite know exactly what people are intended to do other than you know they're intending something bad right and they're intentionally trying not to be found so human trafficking it's an ugly topic but I want to bring it up for a second here what you're doing is you're actually looking at data compositions and and different patterns and resolving entities and based on that that will dictate kind of potentially a whole new flow or a treatment or remediation or activity or savior which is not the predefined workflow it's you're letting the data actually all of a sudden connect to other data points that then you're arriving at the insight to take the action where is completely different I wanna go back to sleep RFI course not healthcare examples yeah so where are we today is that something that's actually being implemented is that something they sort of a proof of concept well that's actually being done at it's being done in a couple different hospitals one of which is actually in hospital in Canada and then we're also leveraging streams in the emory university intensive Timothy Buckman on you did earlier oh yeah the ICU of the future right absolutely brilliant trafficking example brings up you know Ashley that's the underbelly of the world in society but like data condition to Jeff Jonas been on the queue as you know many times and he talks with his puzzle pieces in a way that the data is traveling on a network a network that's distributed essentially that's network computing I mean estate management so look at network management you can look at patterns right so so that's an interesting example so that begs the next question what is the craziest most interesting use case you seen oh my gosh okay now i got i think about oh yes and you can talk about and i can talk about that creates business value or society value oh you know I okay um for you are putting me on the spot the craziest one so 3 we could be great could be g-rated don't you know they go to 2k yeah you know what I participated three weeks ago tiaa-cref actually hosted a fraud summit where it was all investigators like they were doing crime investigation so more than sixty percent of the guys in the room carried weapons because they were Security Intelligence they were pleased they were DA's they repented I was not packing anyway and there was about so 60-plus percent were those right and then only about thirty percent in the room were what i would consider the data scientists in the room like these are the guys are trying to decide which claims are not true or false so forth there were at least like three or four use cases in that discussion that came out they were unbelievable so one is in the fraud area in particular and in crime they're luring the data there what does luring the data they're taking location-based data for geographic region they're putting crime data on top of that right historical like drug rings and even like datasets in miami-dade county the DA told me they were doing things where rather than looking at people that are doing the drugs they they realize people that had possession of a drug typically purchased within a certain location and they had these abandoned properties and were able to identify entire rings based on that another one this is also semi drug-related is in the energy utility space there was in the middle part of the United States houses in Nice urban areas where they were completely torn apart on the interior and build into marijuana houses and so of course they're utilizing high levels of gas and electricity in order to maintain the water fertilization everything else well what happens is it drives peaks in the way that the energy utility looks on a given day pattern so based on that they're able to detect how inappropriate activities are happening and whether it's a single opportunistic type activity whether it's saying this was doing laundry or irrigating the Erie hey we well you know what's interesting about electricity to is especially someone's using electricity but no one's like using any of the gas you're like home but no one's cooking you know something's a little long but it was fascinating i mean really fascinating there were like several other crime scenarios in terms of speed i actually did not know the US Postal Service is like the longest running federal institution that actually tracked like mail fraud and one of the use cases i'm sure jeff has talked about here on the cube is probably a moneygram use case but we talked about that we talked I mean it the stories were unreal because I was spending time with forensic scientists as well as forensic investigators and that's a completely do we're getting we're getting the few minutes need for a platform to handle all this diversity so that's the security risk the governance everything you gotta go cuz your star for the analyst me I can't watch this conversation one final question one of the best yet as we get drugs in there we got other things packing guns guns and drugs you in traffic you know tobacco if you go / news / tobacco well write the knowledge worker all right final question for I know you gotta go this big data applications were you know the guys in the mailroom the guys work for the post office are now unable to actually do this kind of high-level kind of date basically data science yeah if you will or being an analyst so that what I want you to share the folks your vision of the definition of the knowledge worker overused word that's been kicked around for the PC generates but now with handheld with analytical real-time with streaming all this stuff happening at the edge how is it going to change that the knowledge work or the person in the trenches it could be person the cubicle the person on the go the mobile sales person or anyone you know I some people feel threatened when they hear that you're going to apply data and analytics everywhere because you're it implies that you're automating things but that's actually not the value the real value is the insight so that you can double down on the decisions you want to make so if you're more confident you're going to take bigger bets right and decision-making historically has been I think reserved for a very elite few and what we're talking about now is a democratization of that insight and with that comes a lot of empowerment a lot empowerment for everyone and you don't have to be a data scientist be able to be able to make decisions and inform decisions if anything you know actually Tim Buckman I had a good conversation about them as a professional you know what I if I was a physician I'd want to work at the hospital that has the advanced capabilities why because it allows me as a professional physician to then be able to do what I was trained to do not to detect and have to pay attention to all these alarms going off you know I want to work at the institutions and organizations that are investing appropriately because it pushes the caliber of the work I get to do so I think it just changes the dynamics for everyone tim was like a high-priced logistics manager you want to work with people want to work with leaders and now we're in a modern era this new wave is upon us who care and they want to improve and this is about continuing to improve Dave and I always talk about the open source world that those principles are going mainstream to every aspect of business collaboration openness transparency not controlled absolutely absolutely Indy thanks so much for coming in the queue and know you're busy think of your time we are here live in the cube getting all the signal from the noise and some good commentary at the end a one we have one more guest ray way right up next stay tuned right back the queue

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

okay welcome back to IBM's information on demand live in Las Vegas this is the cube SiliconANGLE movie bonds flagship program we go out to the events it's check the student from the noise talk to the thought leaders get all the data share that with you and you go to SiliconANGLE com or Wikibon or to get all the footage and we're if you want to participate with us we're rolling out our new innovative crowd activated innovation application called crowd chat go to crouch at net / IBM iod just login with your twitter handle or your linkedin and participate and share your voice is going to be on the record transcript of the cube conversations I'm John furrier with silicon items with my co-host hi buddy I'm Dave vellante Wikibon dork thanks for watching aren't you Oh bhambri is here she's the vice president of big data and analytics at IBM many time cube guests as you welcome back good to see you again thank you so we were both down at New York City last week for the hadoop world really amazing to see how that industry has evolved I mean you guys I've said the number of times today and I said this to you before you superglued your your big data or your analytics business to the Big Data meme and really created a new category I don't know if that was by design or you know or not but it certainly happened suddenly by design well congratulations then because because I think that you know again even a year a year and a half ago those two terms big data and analytics were sort of separate now it's really considered as one right yeah yeah I think because initially as people our businesses started getting really flooded with big data right dealing with the large volumes dealing with structured semi-structured or unstructured data they were looking at that you know how do you store and manage this data in a cost-effective manner but you know if you're just only storing this data that's useless and now obviously it's people realize that they need and there is insights from this data that has to be gleaned and there's technology that is available to do that so so customers are moving very quickly to that it's not just about cost savings in terms of handling this data but getting insights from it so so big data and analytics you know is becoming it's it's becoming synonymous heroes interesting to me on Jules is you know just following this business it's all it's like there's a zillion different nails out there and and and everybody has a hammer and they're hitting the nail with their unique camera but I've it's like IBM as a lot of different hammers so we could talk about that a little bit you've got a very diverse portfolio you don't try to force one particular solution on the client you it sort of an it's the Pens sort of answer we could talk about that a little bit yeah sure so in the context of big data when we look at just let's start with transactional data right that continues to be the number one source where there is very valuable insights to be gleaned from it so the volumes are growing that you know we have retailers that are handling now 2.5 million transactions per hour a telco industry handling 10 billion call data detailed records every day so when you look at that level that volume of transactions obviously you need to be you need engines that can handle that that can process analyze and gain insights from this that you can get you can do ad hoc analytics on this run queries and get information out of this at the same speed at which this data is getting generated so you know we we announced the blu acceleration rate witches are in memory columnstore which gives you the power to handle these kinds of volumes and be able to really query and get value out of this very quickly so but now when you look at you know you go beyond the structured data or beyond transactional data there is semi structured unstructured data that's where which is still data at rest is where you know we have big insights which leverages Apache Hadoop open source but we've built lots of capabilities on top of that where we get we give the customers the best of open source plus at the same time the ability to analyze this data so you know we have text analytics capabilities we provide machine learning algorithms we have provided integration with that that customers can do predictive modeling on this data using SPSS using open source languages like our and in terms of visualization they can visualize this data using cognos they can visualize this data using MicroStrategy so we are giving customers like you said it's not just you know there's one hammer and they have to use that for every nail the other aspect has been around real time and we heard that a lot at strada right in the like I've been going to start us since the beginning and those that time even though we were talking about real time but nobody else true nobody was talking nobody was back in the hadoop world days ago one big bats job yeah so in real time is now the hotbed of the conversation a journalist storm he's new technologies coming out with him with yarn has done it's been interesting yeah you seen the same thing yeah so so and and of course you know we have a very mature technology in that space you know InfoSphere streams for a real-time analytics has been around for a long time it was you know developed initially for the US government and so we've been you know in the space for more than anybody else and we have deployments in the telco space where you know these tens of billions of call detail records are being processed analyzed in real time and you know these telcos are using it to predict customer churn to prevent customer churn gaining all kinds of insights and extremely high you know very low latency so so it's good to see that you know other companies are recognizing the need for it and are you know bringing other offerings out in this space yes every time before somebody says oh I want to go you know low latency and I want to use spark you say okay no problem we could do that and streets is interesting because if I understand it you're basically acting on the data producing analytics prior to persisting the data on in memory it's all in memory and but yet at the same time is it of my question is is it evolving where you now can blend that sort of real-time yeah activity with maybe some some batch data and and talk about how that's evolving yeah absolutely so so streams is for for you know where as data is coming in it can be processed filtered patterns can be seen in streams of data by correlating connecting different streams of data and based on a certain events occurring actions can be taken now it is possible that you know all of this data doesn't need to be persisted but there may be some aspects or some attributes of this data that need to be persisted you could persist this data in a database that is use it as a way to populate your warehouse you could persist it in a Hadoop based offering like BigInsights where you can you know bring in other kinds of data and enrich the data it's it's like data loans from data and a different picture emerges Jeff Jonas's puzzle right so that's that that's very valid and so so when we look at the real time it is about taking action in real time but there is data that can be persisted from that in both the warehouse as well as on something like the insides are too I want to throw a term at you and see what what what this means to you we actually doing some crowd chats with with IBM on this topic data economy was going to SS you have no date economy what does the data economy mean to you what our customers you know doing with the data economy yes okay so so my take on this is that there are there are two aspects of this one is that the cost of storing the data and analyzing the data processing the data has gone down substantially the but the value in this data because you can now process analyze petabytes of this data you can bring in not just structured but semi-structured and unstructured data you can glean information from different types of data and a different picture emerges so the value that is in this data has gone up substantially I previously a lot of this data was probably discarded people without people knowing that there is useful information in this so to the business the value in the data has gone up what they can do with this data in terms of making business decisions in terms of you know making their customers and consumers more satisfied giving them the right products and services and how they can monetize that data has gone up but the cost of storing and analyzing and processing has gone down rich which i think is fantastic right so it's a huge win win for businesses it's a huge win win for the consumers because they are getting now products and services from you know the businesses which they were not before so that that to me is the economy of data so this is why I John I think IBM is really going to kill it in this in this business because they've got such a huge portfolio they've got if you look at where I OD has evolved data management information management data governance all the stuff on privacy these were all cost items before people looked at him on I gotta deal with all this data and now it's there's been a bit flip uh-huh IBM is just in this wonderful position to take advantage of it of course Ginny's trying to turn that you know the the battleship and try to get everybody aligned but the moons and stars are aligning and really there's a there's a tailwind yeah we have a question on domains where we have a question on Twitter from Jim Lundy analyst former Gartner analyst says own firm now shout out to Jim Jim thanks for for watching as always I know you're a cube cube alum and also avid watcher and now now a loyal member of the crowd chat community the question is blu acceleration is helps drive more data into actionable analytics and dashboards mm-hmm can I BM drive new more new deals with it I've sued so can you expound it answers yes yes yes and can you elaborate on that for Jim yeah I you know with blu acceleration you know we have had customers that have evaluated blue and against sa bihana and have found that what blue can provide is is they ahead of what SI p hana can provide so we have a number of accounts where you know people are going with the performance the throughput you know what blue provides is is very unique and it's very head of what anybody else has in the market in solving SI p including SI p and and you know it's ultimately its value to the business right and that's what we are trying to do that how do we let our customers the right technology so that they can deal with all of this data get their arms around it get value from this data quickly that's that's really of a sense here wonderful part of Jim's question is yes the driving new deals for sure a new product new deals me to drive new footprints is that maybe what he's asking right in other words you traditional IBM accounts are doing doing deals are you able to drive new footprints yeah yeah we you know there are there are customers that you know I'm not gonna take any names here but which have come to us which are new to IBM right so it's a it's that to us and that's happening that new business that's Nate new business and that's happening with us for all our big data offerings because you know the richness that is there in the portfolio it's not that we have like you were saying Dave it's not that we have one hammer and we are going to use it for every nail that is out there you know as people are looking at blue big insights for her to streams for real time and with all this comes the whole lifecycle management and governance right so security privacy all those things don't don't go away so all the stuff that was relevant for the relational data now we are able to bring that to big data very quickly and which is I think of huge value to customers and as people are moving very quickly in this big data space there's nobody else who can just bring all of these assets together from and and you know provide an integrated platform what use cases to Jim's point I don't you know I know you don't want to name names but can you name you how about some use cases that that these customers are using with blue like but use cases and they solving so you know I from from a use case a standpoint it is really like you know people are seeing performance which is you know 30 32 times faster than what they had seen when they were not using and in-memory columnstore you know so eight to twenty five thirty two times per men's gains is is you know something that is huge and is getting more and more people attracted to this so let's take an industry take financial services for example so the big the big ones in financial services are a risk people want to know you know are they credit risk yeah there's obviously marketing serving up serving up ads a fraud detection you would think is another one that in more real time are these these you know these will be the segments and of course you know retail where again you know there is like i was saying right that the number of transactions that are being handled is is growing phenomenally i gave one example which was around 2.5 million transactions per hour which was unheard of before and the information that has to be gleaned from it which is you know to leverage this for demand forecasting to leverage this for gaining insights in terms of giving the customers the right kind of coupons to make sure that those coupons are getting you know are being used so it was you know before the world used to be you get the coupons in your email in your mail then the world changed to that you get coupons after you've done the transaction now where we are seeing customers is that when a customer walks in the store that's where they get the coupons based on which i layer in so it's a combination of the transactional data the location data right and we are able to bring all of this together so so it's blue combined with you know what things like streams and big insights can do that makes the use cases even more powerful and unique so I like this new format of the crowd chatting emily is a one hour crowd chat where it's kind of like thought leaders just going to pounding away but this is more like reddit AMA but much better question coming in from grant case is one of the themes to you is one of the themes we've heard about in Makino was the lack of analytical talent what is going on to contribute more value for an organization skilling up the work for or implementing better software tools for knowledge workers so in terms so skills is definitely an issue that has been a been a challenge in the in the industry with and it got pretty compound with big data and the new technology is coming in from the standpoint of you know what we are doing for the data scientists which is you know the people who are leveraging data to to gain new insights to explore and and and discover what other attributes they should be adding to their predictive models to improve the accuracy of those models so there is there's a very rich set of tools which are used for exploration and discovery so we have which is both from you know Cognos has such such such capabilities we have such capabilities with our data Explorer absolutely basically tooling for the predictive on the modeling sister right now the efforts them on the modeling and for the predictive and descriptive analytics right I mean there's a lot of when you look at that Windows petabytes of data before people even get to predictive there's a lot of value to be gleaned from descriptive analytics and being able to do it at scale at petabytes of data was difficult before and and now that's possible with extra excellent visualization right so that it's it's taking things too that it the analytics is becoming interactive it's not just that you know you you you are able to do this in real time ask the questions get the right answers because the the models running on petabytes of data and the results coming from that is now possible so so interactive analytics is where this is going so another question is Jim was asking i was one of ibm's going around doing blue accelerator upgrades with all its existing clients loan origination is a no brainer upgrade I don't even know that was the kind of follow-up that I had asked is that new accounts is a new footprint or is it just sort of you it is spending existing it's it's boat it's boat what is the characteristic of a company that is successfully or characteristics of a company that is successfully leveraging data yeah so companies are thinking about now that you know their existing edw which is that enterprise data warehouse needs to be expanded so you know before if they were only dealing with warehouses which one handling just structure data they are augmenting that so this is from a technology standpoint right there augmenting that and building their logical data warehouse which takes care of not just the structure data but also semi-structured and unstructured data are bringing augmenting the warehouses with Hadoop based offerings like big insights with real-time offerings like streams so that from an IT standpoint they are ready to deal with all kinds of data and be able to analyze and gain information from all kinds of data now from the standpoint of you know how do you start the Big Data journey it the platform that at least you know we provide is a plug-and-play so there are different starting points for for businesses they may have started with warehouses they bring in a poly structured store with big inside / Hadoop they are building social profiles from social and public data which was not being done before matching that with the enterprise data which may be in CRM systems master data management systems inside the enterprise and which creates quadrants of comparisons and they are gaining more insights about the customer based on master data management based on social profiles that they are building so so this is one big trend that we are seeing you know to take this journey they have to you know take smaller smaller bites digests that get value out of it and you know eat it in chunks rather than try to you know eat the whole pie in one chunk so a lot of companies starting with exploration proof of concepts implementing certain use cases in four to six weeks getting value and then continuing to add more and more data sources and more and more applications so there are those who would say those existing edw so many people man some people would say they should be retired you would disagree with that no no I yeah I I think we very much need that experience and expertise businesses need that experience and expertise because it's not an either/or it's not that that goes away and there comes a different kind of a warehouse it's an evolution right but there's a tension there though wouldn't you say there's an organizational tension between the sort of newbies and the existing you know edw crowd i would say that maybe you know three years ago that was there was a little bit of that but there is i mean i talked to a lot of customers and there is i don't see that anymore so people are people are you know they they understand they know what's happening they are moving with the times and they know that this evolution is where the market is going where the business is going and where the technology you know they're going to be made obsolete if they don't embrace it right yeah yeah so so as we get on time I want to ask you a personal question what's going on with you these days with within IBM asli you're in a hot area you are at just in New York last week tell us what's going on in your life these days I mean things going well I mean what things you're looking at what are you paying attention to what's on your radar when you wake up and get to work before you get to work what's what are you thinking about what's the big picture so so obviously you know big data has been really fascinating right lots of lots of different kinds of applications in different industries so working with the customers in telco and healthcare banking financial sector has been very educational right so a lot of learning and that's very exciting and what's on my radar is we are obviously now seeing that we've done a lot of work in terms of helping customers develop and their Big Data Platform on-premise now we are seeing more and more a trend where people want to put this on the cloud so that's something that we have now a lot of I mean it's not like we haven't paid attention to the cloud but you know in the in the coming months you are going to see more from us are where you know how do we build cus how do we help customers build both private and and and public cloud offerings are and and you know where they can provide analytics as a service two different lines of business by setting up the clouds soso cloud is certainly on my mind software acquisition that was a hole in the portfolio and that filled it you guys got to drive that so so both software and then of course OpenStack right from an infrastructure standpoint for what's happening in the open source so we are you know leveraging both of those and like I said you'll hear more about that OpenStack is key as I say for you guys because you have you have street cred when it comes to open source I mean what you did in Linux and made a you know great business out of that so everybody will point it you know whether it's Oracle or IBM and HP say oh they just want to sell us our stack you've got to demonstrate and that you're open and OpenStack it's great way to do that and other initiatives as well so like I say that's a V excited about that yeah yeah okay I sure well thanks very much for coming on the cube it's always a pleasure to thank you see you yeah same here great having you back thank you very much okay we'll be right back live here inside the cube here and IV IBM information on demand hashtag IBM iod go to crouch at net / IBM iod and join the conversation where we're going to have a on the record crowd chat conversation with the folks out the who aren't here on-site or on-site Worth's we're here alive in Las Vegas I'm Java with Dave on to write back the q