>>From around the globe. It's the cube with digital coverage of IBM. Think 2021 brought to you by IBM. >>Hello everyone. Welcome back to the cubes. Ongoing virtual coverage of IBM. Think 2021. This is our second virtual think. And we're going to talk about what's on the minds of CTOs with a particular point of view from the EMEA region. I'm pleased to welcome rushy Parmer, who is an IBM fellow and vice-president of technology for AMEA that region. Hello Russia. Good to see you. >>Great to see you. So >>Let me start by, by asking, talk a little bit about the role of the CTO and why is it necessarily important to focus on the CTO role versus say some of the other technology practitioner roles? >>Yeah. You know, as you look at all the range of roles of the gut in the it department, the CTO is uniquely placed in looking forward at how technology and how digitization is going to make a difference in the business. But also at the same time, is there as the kind of thought leader for how they're going to really, um, reimagine the use of technology re-imagine automation, reimagining, how digitization helps them go to market different ways. So the CTO is a unique, a unique position from idea to impact. And in the past, we've kind of lost the CTO a little bit, but they're now reemerging as being the thought leader. That's only in driving digitization, going forward in our big clients. >>I, I would agree. I mean, it really has a deep understanding of that vision and can apply that vision to business success. So you obviously have a technical observation space and you also have some data, so maybe you could share with our audience how you inform yourself and your colleagues and IBM on, on what CTOs are thinking about and what they're worried about. >>Yeah. And so, so what we've done over the last four years now is gone out and interviewed CTOs. And can we do a very unstructured interviews? It's not, it's not a survey in the form of, uh, filling these, uh, these 10 questions and tell us yes or no. It reads a structured interview. We ask things like what's top of mind for you. What are the decisions you're making? Um, what's holding you back? What decisions do you think you shouldn't have made, or you wouldn't have liked to make? And, and it's that range of, um, of real input from the interview. So last year we interviewed a hundred CTOs. Um, this year we're actually doing a lot more, we're working with the IBM Institute of business value and we're gonna interview a lot more teachers, but for the material we're going to talk about today is really from those hundred CTO interviews. >>Yeah. And I think that, I mean, having done a lot of these myself, when you do those, we call them, you know, in depth interviews or ideas, you kind of have a structure and you do sort of follow that, but you learn so much and that maybe does inform those more structured interviews, uh, that, that, that you do down the road, you learn so much, but, but maybe you could summarize some of the concerns in the region what's on the minds of, of CTOs. Yeah. Yeah. The, >>The, the real decisions are being based around seven points, right? So the first one is we all know we're on a journey to the cloud. Um, but it's a hybrid multicloud. How do I think about the range of capabilities? I need to be able to unlock the latent potential of existing investments and the cloud-based capabilities we've got. So, so the, the hybrid cloud platform is, is, is one of the first and foundational pieces. The second challenge is that CTOs want to modernize their applications. And that modernization is a journey of, of moving towards microservices. That microservices journey has two parts. One is the business facing view, and that's what containers is all about choosing the right container platform. At the same time, they also want to use containers as a way of automation and management and reducing the effort and the infrastructure. So, so that's kind of two parts of that, that whole container journey. >>So Microsoft, this has really become the, the, the, the business developer view and containers become the operational view. At the same time, they wanna infuse new data to want to climb the AI ladder. They want to get the new, new insights from that data that plugs into those new workflows to get to those workflows. There's a decision around how do I isolate myself from some of the services of using that? And we've created a layer in the decisions around what called cloud services integration. So part service integration is, is kind of the, the modern day ESB as we might think about it. Um, but it's a way in which you choose which technology, which API I'm going to use from where, and then ultimately the CTOs are trying to build what are the new, um, uh, the new workflows, intelligent workflows. And they're really worried about how do I get the right level of automation that managing that issue between what becomes creepy and valuable, right. >>You know, there's some workflows that happen. You think, why the hell did that happen? Or I don't, that doesn't make sense. And, and, and it really sort of nerves the consumer, the user, whereas some which are wow, that's really cool. I really enjoyed that to try to get the intelligent workflows, right. Is a big concern. And then, um, on the two big, uh, parallel to that is how do we manage the systems operational automation, right from having the right data, the observability of all the infrastructure, recognizing they've got a spectrum of things from 30, 40, 50 year old systems to modern day cloud native systems, how to manage it, how to operationally automate that, keep that efficient, effective. And then of course, protecting from the perpetrator's rent business. A lot of people out there wanting to dig into the systems and, and, and, and draw all kinds of, um, you know, uh, data from their systems. So security, privacy, and making sure that align with the ethics and privacy of the business. So those are, those are the kind of range of issues, right? From the journey to cloud, through, to operational automation, through, through intelligent workflows, right. Into managing, protecting the services. >>That's interesting. Thank you for that. I mean, I remember, and you will, as well, some of the post wide thrust and sort of part of the modernization back then was during that they had budget to do that, but a lot of times organizations would make the mistake that they would, they're going to migrate off of a system that was working just fine. That was their sort of mental model of, of, of modernization. And it turned out to be disastrous in many cases. And so what, when I talk to CEOs, they talk about maybe, you know, I'd look at it as this, this abstraction layer. We want to protect what we have that works. Yes. Some stuff's going to go into the public cloud, but this hybrid connection that you talk about, and then we want control. And the way we're going to get control is we're going to use microservices to modernize and use modern API APIs. And so very, very sort of different thinking. And of course they want to avoid migration at all costs because it's so expensive and risky. I wonder if you could talk about, are there any patterns in terms of where people get started and the kinds of outcomes that they're working towards that they can measure? >>Yeah. And we kind of lump the, the learning from the work into three broad patterns, right. Um, one pattern is, is primarily around survival. They recognize that this journey, um, is, is very complex, that the pandemic has created tremendous challenges. Um, the market dynamics means that I've got to try and really be thoughtful in, in taking cost out and making sure they survive some of these issues and sort of the pattern is really around cost reduction. It may start with the hybrid cloud. It may start with in terms of workloads, but it's really about taking cost out of the systems. The second pattern is what we refer to as a simplification pattern. And this is about saying that we've got, we've got so much complexity because of technical debt, because of, you know, systems that we've half migrated in half done things with. Um, so how do I, how do I simplify my it landscape from applications through infrastructure to the data and make it more consistent and manageable and effective. >>And then the third one is that there are CTO saying, look, we've got a really pick that the time when we super scale something, we've got some things which we are unique and effective on. And I want to take that and really super scale that very quickly and make that consistent and really maximize the value of it. So that sort of pattern is really falling to those three categories of driving, driving cost reduction and survival simplification and modernization transformation. And then those that have got something which is unique and special and really super scaling up. >>Yeah. Right, right. Doubling down on those things that gave you unique, competitive advantage. Now, in this, in, in the studies that you've done over the years, you use this term ADP architectural decision points, and some of them are quite compelling. Maybe you could talk about some of those where there's some anxieties from the CTOs that, that you uncovered. >>Yeah. Yeah. The, the ADP's that we'll talk about the seven ATPs and it starts from the high rebuilt crowd through to, to intelligent workflows and so on. Um, and the ADP's themselves are really distilling the client's words in the client's, um, way of thinking about how they're going to drive those, those technologies. Um, and also how they're going to use those techniques to make a difference. But I think went through those interviews, um, what became the power is CTOs do have some anxieties as you refer to it. Um, and, and those anxiety, they couldn't necessarily put words on them and there were anxieties and like, are we thinking enough about the carbon footprint? Are we, are we being thoughtful in how we make sure we're reducing carbon footprint or reducing the environmental impact of the infrastructure you've got, we've got sprawling infrastructure, um, ripping out rare metals from the earth. >>Are we being thoughtful in how we reduce the, um, the amount of rare metals we have water consumption, uh, right through to is the code that we're producing efficient, secure and fit for, for the future? Um, are we being ethical in capturing the data for its right use, um, is the AI systems that we're building? Are they explainable? Are they ethical? Are they free from bias or are we kind of amplifying things that we shouldn't be able to find? So there was a whole bunch of those call anxieties and what we did along with the architectural decision report, um, a point after she decision report was, was identify what we call a set of responsibilities. And, and we've built a framework about around responsible computing, which is, uh, which is a basis for how you think through what your responsibilities are as a, as a CTO or as an it leader. Um, and we're right in the process of building out that, that kind of, um, responsible computing framework. >>Yeah, it's interesting. A lot of people may, may think about it. They think about the responsible computing and the sustainability, and they might think that's a, a one 80 from Milton Friedman economics, which said the job of business is to make profits. But in fact, responsible computing, there's a strong business case, uh, around it. It actually can help you reduce costs that can, can help you attract better employees because young people are passionate about this. I wonder if you could talk about how, how people can get involved with responsible computing in, in lean in. >>Yeah. So what we're about to publish is that he's actually a manifesto for responsible computing. So I think everybody, once we get that published, I'm hoping to do that in the next two to three months, we're working with a few clients, um, to there's actually three clients that have chosen, just click through your client's CTOs from the ones that we interviewed were very keen to collaborate with us in, in laying out that, um, that manifesto and the opportunity really is for anybody listening. If you, if you find this as a great value, please do come and reach out to me more than happy to collaborate with looking for more insights on this. Um, we've also had some, um, competitions. So in, in, in Mia, we've had a competition with, uh, with business partners looking for of how we can, um, really showcase examples or exemplars of being responsible computing provider, whether it's at the level of responsible data center, whether it's about responsible code data, use responsible systems, right through to responsible impact. And, you know, obviously a lot of our work around things like, um, your tech for good is, is tied directly to responsible impact. And of course, if you want to see what we IBM have been doing our responsible responsibility report, which we've been voluntarily publishing for the last 30 years, provides a tremendous set of insights on how we've done that over the years. And, and that's a, that's a great way for you to see how we've been doing things and see if that there are critical in your business. >>Yeah, so there's, so there's the, the re the ADP report is available. You can check it out on, on LinkedIn, um, go to go to Russia, LinkedIn profile, you'll find it. There's a blog post that talks about the next wave of digitization. Um, the learnings that you just talked about. So there's a lot of resources for, for people to get involved. I'll give you the last word rushy. >>Yeah. And th th this is, this is what I call job began. It's not job done. The whole ADP responsible computing is a digitization journey where we want to balance delivering business value and making a difference to the organization. But at the same time, being responsible, making sure that we're thoughtful of what's needed for the future. And we create impact that really matters. And, or we can feel proud that we've put a foundation for digitization, which will, which will serve the businesses for many years to come >>Love it, impact investing in your business and in the future. Russia, thanks so much for coming to the cube. Really appreciate it. Thank you. Okay. Keep it right there for more coverage from IBM. Think 2021. This is Dave Volante for the cube.

>>Mhm Yes. Hello and welcome back to the cubes coverage of red hat summit 2021 virtual. I'm john for your host of the cube we're here with Hillary Hunter, the VP and CTO and IBM fellow of IBM cloud at IBM. Hillary, Great to see you welcome back, You're no stranger to us in the cube your dentist few times. Thanks for coming on. >>Thanks so much for having me back. Great to talk more today >>I believe I B M is the premier sponsor for red hat summit this year. No, I mean I think they're somewhat interested in what's happening. >>Yeah, you know, somebody is such a great event for us because it brings together clients that, you know, we work together with red head on and gives us a chance to really talk about that overall journey to cloud and everything that we offer around cloud and cloud adoption um, and around redheads capabilities as well. So we look forward to the summit every year for sure. >>You know, the new IBM red hat relationship obviously pretty tight and successful seeing the early formations and customer attraction and just kind of the momentum, I'll never forget that Red hat something was in SAN Francisco. I sat down with Arvin at that time, uh, Red hat was not part of IBM and it was interesting. He was so tied into cloud native. It was almost as if he was dry running the acquisition, which he announced just moments later after that. But you can see the balance. The Ceo at IBM really totally sees the cloud. He sees that experience. He sees the customer impact. This has been an interesting year, especially with Covid and with the combination of red hat and IBM, this cloud priority for IT leaders is more important than ever before. What's your, what's your take on this? Because clearly you guys are all in on cloud, but not what people think, what's your, what's your view on this? >>Yeah. You know, from, from the perspective of those that are kind of data oriented IBM Institute for Business Value, did lots of studies over the last year, you know, saying that over 60% of leaders feel, you know, increased urgency to get to the cloud, um they're intending to accelerate their program to the cloud, but I think, you know, just even as consumers where each very conscious that our digital behaviors have changed a lot in the last year and we see that in our enterprise client base where um everything from, you know, a bank, we work that that that had to stand up their countries equivalent of the payroll protection program in a matter of weeks, which is just kind of unheard of to do something that robust that quickly or um, you know, retail obviously dealing with major changes, manufacturing, dealing with major changes and all consumers wanting to consume things on an app basis and such, not going into brick and mortar stores and such. And so everything has changed and months, I would say have sort of timeframes of months have been the norm instead of years for um, taking applications forward and modernizing them. And so this journey to cloud has compressed, It's accelerated. And as one client I spoke with said, uh, in the midst of last year, you know, it is existential that I get to cloud with urgency and I think That's been that has been the theme of 2020 and now also 2021. And so it is, it is the core technology for moving faster and dealing with all the change that we're all experiencing. >>That's just so right on point. But I got I want to ask you because this is the key trend enterprises are now realizing that cloud native architecture is based on open source specifically is a key architectural first principle now. >>Yeah. >>What's your, what, what would you say to the folks out there who were listening to this and watching this video, Who were out in the enterprise going, hey, that's a good call. I'm glad I did it. So I don't have any cognitive dissidence or I better get there faster. >>Yeah. You know, open source is such an important part of this conversation because I always say that open source moves at the rate and pays a global innovation, which is kind of a cute phrase that I really don't mean it in anyways, cute. It really is the case that the purpose of open sources for people globally to be contributing. And there's been innovation on everything from climate change to you know, musical applications to um things that are the fundamentals of major enterprise mission critical workloads that have happened is everyone is adopting cloud and open source faster. And so I think that, you know this choice to be on open source is a choice really, you know, to move at the pace of global innovation. It's a choice too um leverage capabilities that are portable and it's a choice to have flexibility in deployment because where everyone's I. T is deployed has also changed. And the balance of sort of where people need the cloud to kind of come to life and be has also changed as everyone's going through this period of significant change. >>That's awesome. IBM like Red has been a long supporter and has a history of supporting open source projects from Lenox to kubernetes. You guys, I think put a billion dollars in Lenox way back when it first started. Really power that movement. That's going back into the history books there. So how are you guys all collaborating today to advance the open source solutions for clients? >>Yeah, we remain very heavily invested in open source communities and invested in work jointly with Red Hat. Um you know, we enabled the technology known as um uh Rackham the short name for the Red Hat advanced cluster management software, um you know, in this last year, um and so, you know, provided that capability um to to become the basis of that that product. So we continue to, you know, move major projects into open source and we continue to encourage external innovators as well to create new capabilities. And open source are called for code initiatives for developers as an example, um have had specific programs around um uh social justice and racial issues. Um we have a new call for code out encouraging open source projects around climate change and sustainable agriculture and all those kind of topics and so everything from you know, topics with developers to core product portfolio for us. Um We have a very uh very firm commitment in an ongoing sustained contribution on an open source basis. >>I think that's important. Just to call out just to kind of take a little sidebar here. Um you guys really have a strong mission driven culture at IBM want to give you props for that. Just take a minute to say, Congratulations call for code incredible initiative. You guys do a great job. So congratulations on that. Appreciate. >>Thank you. Thank you. >>Um as a sponsor of Red Hat Summit this year, I am sponsoring the zone Read at um you have you have two sessions that you're hosting, Could you talk about what's going on? >>Yeah, the the two sessions, so one that I'm hosting is around um getting what we call 2.5 x value out of your cloud journey. Um and really looking at kind of how we're working with clients from the start of the journey of considering cloud through to actually deploying and managing environments and operating model on the cloud um and where we can extract greater value and then another session um that I'm doing with Roger Primo, our senior vice President for strategy at IBM We're talking about lessons and clouded option from the Fortune 500, so we're talking there about coca cola european bottling partners, about lumen technologies um and um also about wonderman Thompson, um and what they're doing with us with clouds, so kind of two sessions, kind of one talking a sort of a chalkboard style um A little bit of an informal conversation about what is value meaning cloud or what are we trying to get out of it together? Um And then a session with roger really kind of focused on enterprise use cases and real stories of cloud adoption. >>Alright so bottom line what's going to be in the sessions, why should I attend? What's the yeah >>so you know honest honestly I think that there's kind of this um there's this great hunger I would say in the industry right now to ascertain value um and in all I. T. Decision making, that's the key question right? Um not just go to the cloud because everyone's going to the cloud or not just adopt you know open source technologies because it's you know something that someone said to do, but what value are we going to get out of it? And then how do we have an intentional conversation about cloud architecture? How do we think about managing across environments in a consistent way? Um how do we think about extracting value in that journey of application, modernization, um and how do we structure and plan that in a way? Um that results in value to the business at the end of the day, because this notion of digital transformation is really what's underlying it. You want a different business outcome at the end of the day and the decisions that you take in your cloud journey picking. Um and open hybrid, multi cloud architecture leveraging technologies like IBM cloud satellite to have a consistent control plan across your environments, um leveraging particular programs that we have around security and compliance to accelerate the journey for regulated industries etcetera. Taking intentional decisions that are relevant to your industry that enable future flexibility and then enable a broad ecosystem of content, for example, through red hat marketplace, all the capabilities and content that deploy onto open shift, et cetera. Those are core foundational decisions that then unlock that value in the cloud journey and really result in a successful cloud experience and not just I kind of tried it and I did or didn't get out of it what I was expecting. So that's really what, you know, we talk about in these in these two sessions, um and walk through um in the second session than, you know, some client use cases of, of different levels and stages in that cloud journey, some really core enterprise capabilities and then Greenfield whitespace completely new capabilities and cloud can address that full spectrum. >>That's exciting not to get all nerdy for a second here, But you know, you bring up cloud architecture, hybrid cloud architecture and correct me if I'm wrong if you're going to address it because I think this is what I'm reporting and hearing in the industry against the killer problem everyone's trying to solve is you mentioned, um, data, you mentioned control playing for data, you mentioned security. These are like horizontally scalable operating model concepts. So if you think about an operating system, this is this is the architecture that becomes the cloud model hybrid model because it's not just public cloud cloud native or being born in the cloud. Like a startup. The integration of operating at scale is a distributed computing model. So you have an operating system concept with some systems engineering. Yeah, it sounds like a computer to me, right. It sounds like a mainframe. Sounds like something like that where you're thinking about not just software but operating model is, am I getting that right? Because this is like fundamental. >>Yeah, it's so fundamental. And I think it's a great analogy, right? I think it's um you know, everyone has kind of, their different description of what cloud is, what constitutes cloud and all that kind of thing, but I think it's great to think of it as a system, it's a system for computing and what we're trying to do with cloud, what we're trying to do with kubernetes is to orchestrate a bunch of, you know, computing in a consistent way, as, you know, other functions within a single server do. Um What we're trying to do with open shift is, you know, to enable um clients to consume things in a consistent way across many different environments. Again, that's the same sort of function um conceptually as, you know, an operating system or something like that is supposed to provide is to have a platform fundamentally, I think the word platform is important, right? Have a platform that's consistent across many environments and enables people to be productive in all those environments where they need to be doing their computing. >>We were talking before we came on camera about cloud history and we were kind of riffing back and forth around, oh yeah, five years ago or six years ago was all the conversations go to the cloud now, it's like serious conscience around the maturity of cloud and how to operate that scale in the cloud, which is complex, it's complex system and you have complexity around system complexity and novelty complexity, so you have kind of all these new things happening. So I want to ask you because you're an IBM fellow and you're on the cloud side at IBM with all this red hat goodness you've got going on, Can you give us a preview of the maturity model that you see the IBM season, that red hats doing so that these architectures can be consistent across the platforms, because you've got def sec ops, you've got all these new things, you've got security and data at scale, it's not that obviously it's not easy, but it has to be easier. What's what's the preview of the maturity model? >>Yeah, you know, it really is about kind of a one plus one equals three conversation because red hats approach to provide a consistent platform across different environments in terms of Lennox and Kubernetes and the open shift platform um enables that first conversation about consistency and maturity um in many cases comes from consistency, being able to have standards and consistency and deployment across different environments leads to efficiency. Um But then IBM odds on that, you know, a set of conversations also around data governance, um consistency of data, cataloguing data management across environments, machine learning and ai right bringing in A. I. For I. T. Operations, helping you be more efficient to diagnose problems in the IT environment, other things like that. And then, you know, in addition, you know, automation ultimately right when we're talking about F. R. I. T. Ops, but also automation which begins down at the open shift level, you know with use of answerable and other things like that and extends them up into automation and monitoring of the environment and the workloads and other things like that. And so it really is a set of unlocking value through increasing amounts of insight, consistency across environments, layering that up into the data layer. Um And then overall being able to do that, you know efficiently um and and in a consistent way across the different environments, you know, where cloud needs to be deployed in order to be most effective, >>You know, David Hunt and I always talk about IBM and all the years we've been covering with the Cube, I mean we've pretty much been to every IBM events since the Cube was founded and we're on our 11th year now watching the progression, you guys have so much expertise in so many different verticals, just a history and the expertise and the knowledge and the people. They're so smart. Um I have to ask you how you evolved your portfolio with the cloud now um as it's gone through, as we are in the 2021 having these mature conversations around, you know, full integration, large scale enterprise deployments, Critical Mission Mission Critical Applications, critical infrastructure, data, cybersecurity, global scale. How are you evolve your portfolio to better support your clients in this new environment? >>Yeah, there's a lot in there and you hit a lot of the keywords already. Thank you. But but I think that you know um we have oriented our portfolio is such that all of our systems support Red hat um and open shift, um our cloud, we have redhead open shift as a managed service and kubernetes is at the core of what we're doing as a cloud provider and achieving our own operational efficiencies um from the perspective of our software portfolio, our core products are delivered in the form of what we refer to as cloud packs on open shift and therefore deploy across all these different environments where open shift is supported, um products available through Red hat marketplace, you know, which facilitates the billing and purchasing an acquisition and installation of anything within the red hat ecosystem. And I think, you know, for us this is also then become also a journey about operational efficiency. We're working with many of our clients is we're kind of chatting about before about their cloud operating model, about their transformation um and ultimately in many cases about consumption of cloud as a service. Um and so um as we, you know, extend our own cloud capabilities, you know, out into other environment through distributed cloud program, what we refer to as as IBM cloud satellite, you know, that enables consistent and secure deployment of cloud um into any environment um where someone needs, you know, cloud to be operated. Um And that operating model conversation with our clients, you know, has to do with their own open shift environments that has to do with their software from IBM, it has to do their cloud services. And we're really ultimately looking to partner with clients to find efficiency in each stage of that journey and application modernization in deployment and then in getting consistency across all their environments, leveraging everything from uh the red hat, you know, ACM capabilities for cluster management up through a i for beauty shops and automation and use of a common console across services. And so it's an exciting time because we've been able to align our portfolio, get consistency and delivery of the red half capabilities across our full portfolio and then enable clients to progress to really efficient consumption of cloud. >>That's awesome. Great stuff there. I got to ask you the question that's on probably your customers minds. They say, okay, Hillary, you got me sold me on this. I get what's going on, I just gotta go faster. How do I advance my hybrid cloud model faster? What are you gonna do for me? What do you have within the red hat world and IBM world? How are you gonna make me go faster? That's in high quality way? >>Yeah. You know, we often like to start with an assessment of the application landscape because you move faster by moving strategically, right? So assessing applications and the opportunity to move most quickly into a cloud model, um, what to containerized first, what to invest in lift and shift perspective, etcetera. So we we help people look at um what is strategic to move and where the return on investment will be the greatest. We help them also with migrations, Right? So we can help jump in with additional skills and establish a cloud center of competency and other things like that. That can help them move faster as well as move faster with us. And I think ultimately choosing the right portfolio for what is defined as cloud is so important, having uh, an open based architecture and cloud deployment choice is so important so that you don't get stuck in where you made some of your initial decisions. And so I think those are kind of the three core components to how we're helping our clients move as quickly as possible and at the rate and pace that the current climate frankly demands of everyone. >>You know, I was joking with a friend the other night about databases and how generations you have an argument about what is it database, what's it used for. And then when you kind of get to that argument, all agree. Then a new database comes along and then it's for different functions. Just the growth in the internet and computing. Same with cloud, you kind of see a parallel thing where it's like debate, what is cloud? Why does he even exist? People have different definitions. That was, you know, I mean a decade or so ago. And then now we're at almost another point where it's again another read definition of, okay, what's next for cloud? It's almost like an inflection point here again. So with that I got to ask you as a fellow and IBM VP and Cto, what is the IBM cloud because if I'm going to have a discussion with IBM at the center of it, what does it mean to me? That's what people would like to know. How do you respond to that? >>Yeah. You know, I think two things I think number one to the, to the question of accelerating people's journeys to the cloud, we are very focused within the IBM cloud business um on our industry specific programs on our work with our traditional enterprise client base and regulated industries, things like what we're doing in cloud for financial services, where we're taking cloud, um and not just doing some sort of marketing but doing technology, which contextualize is cloud to tackle the difficult problems of those industries. So financial services, telco uh et cetera. And so I think that's really about next generation cloud, right? Not cloud, just for oh, I'm consuming some sauce, and so it's going to be in the cloud. Um but SAS and I SV capabilities and an organization's own capabilities delivered in a way appropriate to their industry in in a way that enables them to consume cloud faster. And I think along those lines then kind of second thing of, you know, whereas cloud headed the conversation in the industry around confidential computing, I think is increasingly important. Um It's an area that we've invested now for several generations of technology capability, confidential computing means being able to operate even in a cloud environment where there are others around um but still have complete privacy and authority over what you're doing. And that extra degree of protection is so important right now. It's such a critical conversation um with all of our clients. Obviously those in things like, you know, digital assets, custody or healthcare records or other things like that are very concerned and focused about data privacy and protection. And these technologies are obvious to them in many cases that yes, they should take that extra step and leverage confidential computing and additional data protection. But really confidential computing we're seeing growing as a topic zero trust other models like that because everyone wants to know that not only are they moving faster because they're moving to cloud, but they're doing so in a way that is without any compromise in their total security, um and their data protection on behalf of their clients. So it's exciting times. >>So it's so exciting just to think about the possibilities because trust more than ever now, we're on a global society, whether it's cyber security or personal interactions to data signing off on code, what's the mutability of it? I mean, it's a complete interplay of all the fun things of uh of the technology kind of coming together. >>Absolutely, yeah. There is so much coming together and confidential computing and realizing it has been a decade long journey for us. Right? We brought our first products actually into cloud in 2019, but its hardware, it's software, it services. It's a lot of different things coming together. Um but we've been able to bring them together, bring them together at enterprise scale able to run entire databases and large workloads and you know um pharmaceutical record system for Germany and customer records for daimler and um you know what we're doing with banks globally etcetera and so you know it's it's wonderful to see all of that work from our research division and our developers and our cloud teams kind of come together and come to fruition and and really be real and be product sizable. So it's it's very exciting times and it's it's a conversation that I think I encourage everyone to learn a little bit more about confidential computing. >>Hillary hunter. Thank you for coming on the cube. Vice President CTO and IBM fellow which is a big distinction at IBM. Congratulations and thanks for coming on the Cuban sharing your insight. Always a pleasure to have you on an expert always. Great conversation. Thanks for coming on. >>Thanks so much for having me. It was a pleasure. >>Okay, so cubes coverage of red Hat Summit 21 of course, IBM think is right around the corner as well. So that's gonna be another great event as well. I'm john Feehery, a host of the cube bringing all the action. Thanks for watching. Yeah.

>>from >>Around the globe, it's the cube with digital coverage of IBM think 2020 >>one brought to you by IBM. Hello everyone and welcome back to the cubes ongoing virtual coverage of IBM think 2021 this is our second virtual think and we're going to talk about what's on the minds of C. T. O. S with a particular point of view from the EMEA region. I'm pleased to welcome rasheed Parmer, who is an IBM fellow and vice president of technology for Armenia that region. Hello rashid, Good to see you. >>Hey David, great to see you. >>So let me start by by asking talk a little bit about the role of the C. T. O. And why is it necessarily important to focus on the C. T. O. Role versus say some of the other technology practitioner roles? >>Yeah. You know, you know, they as you look at all the range of roles of the got in in the I. T. Department, the CTO is uniquely placed in looking forward how technology and how digitization is gonna make a difference in the business but also at the same time is there as the kind of thought leader for how they're going to really you re imagine the use of technology reimagine automation, reimagining, how digitalization helps them go to market different ways. So the CTO is a unique unique position from idea to impact. And in the past we've kind of lost the C. T. A little bit but they're now re emerging as being the thought leader that's owning and driving digitalization going forward in our big plants. >>Yeah I agree. And it really has a deep understanding of that vision and can apply that vision to business success. So you obviously have a technical observation space and you also have some data so maybe you could share with our audience how you inform yourself and your colleagues and IBM on on what C. T. O. S. Are thinking about and what they're worried about. >>Yeah. So what we've done over the last four years now is gone out and interviewed Cdos and we do a very unstructured interviews. It's not it's not a survey in the form of uh you know, filling these uh these 10 questions and tell us yes or no. It really is a structured interviews. We asked things like what's top of mind for you, what are the decisions you're making? What's holding you back? What decisions do you think you shouldn't have made or you wouldn't have liked to make? And it's that range of a real input from the the interview. So last year we interviewed 100 CTO s um this year we're actually doing a lot more. We're working with the IBM Institute Business Value and we're gonna interview a lot more teachers but but the material we're gonna talk about today is is really from those 100 CTO interviews. >>Yeah. And I think that having done a lot of these myself, when you do those, we call them, you know in depth interviews, our I. D. S. You kind of have a structure and you sort of follow that but you learn so much and that it maybe does inform those more structured interviews that you do down the road. You learn so much, but maybe you could summarize some of the concerns in the region. What's on the minds of Ceos? >>Yeah. And you know, the the real decisions are made based around seven points. Right? So the first one is we all know, we're on a journey to the cloud but it's a hybrid multi cloud. How do I think about the range of capabilities and need to be able to unlock the latent potential of existing investments and the cloud based capabilities of God. So, so the hybrid cloud platform is one of the the first and foundational pieces. The second challenge is the C e O s want to modernize their applications and that modernization is a journey of moving towards microservices. That microservices journey has two parts. One is the business facing view and that's what containers is all about, choosing the right container platform at the same time. They also want to use containers as a way of automation and management and reducing the effort in the infrastructure. So, so that's kind of two parts of the whole container journey. So Microsoft, this has really become the business developer view and containers become the operational view At the same time. They want infused new data, they want to climb the ladder, they want to get the new new insights from that data that plugs into those new workflows to get to those workflows. There's a decision around how do I isolate myself from some of the services of using that? And we created a layer in the decisions around what's called cloud services integration. So cloud services integration is kind of the modern day E S B as we might think about it, but it's a way in which you choose which technology, which a P I is. I'm going to use from where and then ultimately, the CTS are trying to build what are the new, the new workflows, intelligent workflows and they're really worried about how do I get the right level of automation that managing that issue between what becomes creepy and valuable, Right? You know, the some workflows that happen, you think, why the hell did that happen? Right. That doesn't make sense. And and and and it really sort of nerves. The consumer, the user where some which are, wow, that's really cool. I really enjoyed that. To try to get the intelligent workflows right is a big concern. And then on the two big perils of that is how do we manage the system, the operational automation right from having the right data observe ability of all the infrastructure, recognizing they've got a spectrum of things from 30 40 50 year old systems to modern day cloud native systems, how to manage how operationally automate that keep that efficient, effective. And then of course protecting from the perpetrators, right? Business, a lot of people out there wanting to begin to the systems and, and, and and draw all kinds of, you know, a data from their system. So security, privacy and making sure that align with the ethics and privacy of the business. So those are those are the kind of range of issues right from the journey to cloud, through to operational automation, through through intelligent workflows, right into manage and protecting the services. >>It's interesting. Thank you for that. I mean I remember and you will as well some of the post Y two K you know, thrust and part part of the modernization back then was during that they had budget to do that. But a lot of times organizations would make the mistake that they would they're going to migrate off of a system that was working just fine. That was there sort of mental model of of modernization. And it turned out to be disastrous in many cases. And so when I talk to Ceos they talk about maybe, you know, I'd look at it is this this abstraction layer we want to protect what we have that works. Yes. Some stuff is going to go into the public cloud, but this hybrid connection that you talk about and then we want control and the way we're gonna get control is we're gonna use microservices to modernize and use modern A. P. I. S. And so very very sort of different thinking. And of course they want to avoid migration at all costs because it's so expensive and risky. I wonder if you could talk about, are there any patterns in terms of where people get started and the kinds of outcomes that they're working towards that they can measure? >>Yeah, we we kind of lumped the learning from the work into three broad patterns, right? Um one pattern is primarily around survival. They recognize that this journey is very complex. The pandemic has created tremendous challenges. The market dynamics means they've got to try and really be thoughtful in in taking cost out and making sure they survive some of these issues. And so the pattern is really around cost reduction. It may start with a hybrid cloud, it may start with intelligent workflows but it's really about taking costs out of the systems. The second pattern is what is referred to as a simplification pattern and this is about saying but we've got we've got so much complexity because of technical debt because of you know systems that we've half migrated and half done things with. So how do I how do I simplify my I. T. Landscape from applications through infrastructure for data and make it more consistent, manageable and and effective. And then the 3rd 1 is their city is saying look we've got a really pick the time when we super scale something, we've got something which we are unique and effective on and I want to take that and really super scale that very quickly and make that consistent and really maximize value of it so that the pattern is really fall into three categories of driving, driving, cost reduction and survival, simplification and modernisation transformation. And then those that have got something which is unique and special and really super scaring up. >>Yeah. Right, right, doubling down on those things. That unique competitive advantage in the, in the studies that you've done over the years. You use this term ADP architectural decision points and some of them are quite compelling. Maybe you could talk about some of those. Were there some anxieties from the cdos that you uncovered? >>Yeah. You know, the, the NDP s talk about the 70 Gps and it starts from the higher ability crowd through to two intelligent workflows and so on. And the NDP s themselves are really distilling the client's words and the clients way of thinking about how they're going to drive those, those technologies, um and also how they're going to use those techniques to make a difference. But if we went through those interviews, what became apparent is, see us do have some anxieties as you refer to, and those anxieties, they couldn't necessarily put words on them and their anxieties. Like, are we thinking enough about the carbon footprint? Are we are we being thoughtful in how we make sure we're reducing carbon footprint or reducing the environmental impact of the infrastructure? You've got, we've got sprawling infrastructure um ripping out rare metals from the earth. Are we being thoughtful in how we reduce the amount of rare metals we have water consumption right through to is the code that we're producing efficient, secure and and fit for for the future. Are we being ethical in capturing the data for its right use? Um Is the ai systems that we're building? Are they explainable? Are they ethical? Are they free from bias or are we kind of amplifying things that we shouldn't be amplifying? So there was a whole bunch of those call anxieties and what we did along with the architectural decision report. A point after decision report was was identify what we call a set of responsibilities. And and we've built a framework about around responsible computing which is which is a basis for how you think through what your responsibilities are as a as a Ceo are as an I. T. Leader. And we're right in the process of building out that that kind of responsible computing framework. >>You know it's interesting a lot of people may may think about they think about the responsible computing and and and the sustainability and they might think that's a 1 80 from Milton Friedman Economics, which is the job of businesses to make profits. But in fact responsible computing, there's a strong business case around it. It actually can help you reduce costs that can help you attract better employees. Because young people are passionate about this. I wonder if you could talk about how how people can get involved with responsible computing and lean in. >>Yeah, so what we're about to publish it is actually manifesto for responsible computing. So I think everybody wants to get that published. I'm hoping to do that in the next two or three months. We're working with a few clients. So there's actually three clients that have chosen through your client cts from the ones that we interviewed were very keen to collaborate with us in laying out that that manifesto and the opportunity really is from anybody listening. If if you if you find this of great value, please do come and reach out to me more than happy to collaborate. We're looking for more insights on this. We've also had some competitions. So in in in a media we've had a competition with business partners, looking for ideas of how we can really showcase examples or exemplars of being responsible computing provider, whether it's at the level of responsible data center, whether it's about responsible code data, use Responsible systems right through the responsible impact. And obviously a lot of our work around things like your tech for good is tied directly to responsible impact. And of course, if you want to see what we have never been doing are responsible responsibility report, which we've been voluntarily publishing for the last 30 years, provides a tremendous set of insights on how we've done that over the years. And and that's a that's a great way for you to see how we've been doing things and see if there are people in your business. >>Yeah. So there's so there's the, the ADP report is available. You can check it out on on linkedin. Um, go to, go to Russia linked in profile, you'll find it. There's a blog post that talks about the next wave of, of digitization, uh, you know, the learnings that you just talked about. So there's a lot of resources for for people to get involved. I'll give you the last word. >>Yeah. And look, this is this is what I call job big and it's not job done that the whole ADP responsible computing is a digitization journey where we want to balance delivering business value and making a difference to the organization, but at the same time being responsible in making sure that we're thoughtful what's needed for the future and we create impact that really matters. And we can feel proud that we've put a foundation for digitization which will which will serve the businesses for many years to come, >>love it, impact investing in your business and in the future. Russia, thanks so much for coming on the cube. Really appreciate it. >>A pleasure. Thank you. >>Okay, keep it right there for more coverage from IBM think 2021 this is Dave Volonte for the Cube. Yeah, yeah.

(pulsating music) >> Live from Fisherman's Wharf in San Francisco, it's theCUBE! Covering IBM Chief Data Officer Strategy Summit, Spring 2017. Brought to you by IBM. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at Fisherman's Wharf in San Francisco at the IBM Chief Data Officer Strategy Summit, Spring 2017. It's a mouthful, it's a great event, and it's one of many CDO summits that IBM's putting in around the country, and soon around the world. So check it out. We're happy to be here and really talk to some of the thought leaders about getting into the nitty gritty detail of strategy and execution. So we're excited to be joined by our next guest, Rebecca Shockley. She's an Analytics Global Research Leader for the IBM Institute for Business Value. Welcome, Rebecca. I didn't know about the IBM Institute for Business Value. >> Thank you. >> Absolutely. And Priya V. She said Priya V's good, so you can see the whole name on the bottom, but Priya V. is the CTO of Cognitive/IOT/Watson Health at IBM. Welcome, Priya. >> Thank you. >> So first off, just impressions of the conference? It's been going on all day today. You've got 170 or some-odd CDO's here sharing best practices, listening to the sessions. Any surprising takeaways coming out of any of the sessions you've been at so far? >> On a daily basis I live and breathe data. That's what I help our customers to get better at it, and today is the day where we get to talk about how can we adopt something which is emerging in that space? We talk about data governance, what we need to look at in that space, and cognitive as being the fabric that we are integrating into this data governance actually. It's a great day, and I'm happy to talk to over, like you said, 170 CDO's representing different verticals. >> Excellent. And Rebecca, you do a lot of core research that feeds a lot of the statistics that we've seen on the keynote slides, this and that. And one of the interesting things we talked about off air, was really you guys are coming up with a playbook which is really to help CDO's basically execute and be successful CDO's. Can you tell us about the playbook? >> Well, the playbook was born out of a Gartner statistic that came out I guess two or three years ago that said by 2016 you'll have 90% of organizations will have a CDO and 50% of them will fail. And we didn't think that was very optimistic. >> Jeff: 90% will have them and 50% will fail? >> Yes, and so I can tell you that based on our survey of 6,000 global executives last fall, the number is at 41% in 2016. And I'm hoping that the playbook kept them from being a failure. So what we did with the playbook is basically laid out the six key questions that an organization needs to think about as they're either putting in a CDO office or revamping their CDO offices. Because Gartner wasn't completely unfounded in thinking a lot of CDO offices weren't doing well when they made that prediction. Because it is very difficult to put in place, mostly because of culture change, right? It's a very different kind of way to think. So, but we're certainly not seeing the turnover we were in the early years of CDO's or hopefully the failure rate that Gartner predicted. >> So what are the top two or three of those six that they need to be thinking about? >> So they need to think about their objectives. And one of the things that we found was that when we look at CDO's, there's three different categories that you can really put them in. A data integrator, so is the CDO primarily focused on getting the data together, getting the quality of the data, really bringing the organization up to speed. The next thing that most organizations look at is being a business optimizer. So can they use that data to optimize their internal processes or their external relationships? And then the third category is market innovator. Can they use that data to really innovate, bring in new business models, new data monetization strategies, things like that. The biggest problem we found is that CDO's that we surveyed, and we surveyed 800 CDO's, we're seeing that they're being assessed on all three of those things, and it's hard to do all three at once, largely because if you're still having to focus on getting your data in a place where you can start doing real science against it you're probably not going to be full-time market innovator either. You can't be full-time in two different places. That's not to say as a data integrator you can't bring in data scientists, do some skunk works on some of the early work, find... and we've seen organizations really, like Bank Itau down in Brazil, really in that early stages still come up with some very innovative things to do, but that's more of a one-off, right. If you're being judged on all three of those, that I think is where the failure rate comes in. >> But it sounds like those are kind of sequential, but you can't operate them sequentially cause in theory you never finish the first phase, right? >> You never finish, you're always keeping up with the data. But for some organizations, they really need to, they're still operating with very dirty, very siloed data that you really can't bring together for analytics. Now once you're able to look at that data, you can be doing the other two, optimizing and innovating, at the same time. But your primary focus has to be on getting the data straight. Once you've got a functioning data ecosystem, then the level of attention that you have to put there is going to go down, and you can start working on, focusing on innovation and optimization more as your full-time role. But no, data integrator never goes away completely. >> And cleanser. Then, that's a great strategy. Then, as you said, then the rubber's got to hit the road. And Priya, that's where you play in, the execution point. Like you say, you like to get your hands dirty with the CDO's. So what are you seeing from your point of view? In terms of actually executing, finding early wins, easy paths to success, you know, how to get those early wins basically, right? To validate what you're doing. That's right. Like you said, it's become a universal fact that data governance and things, everything around consolidating data and the value of insights we get off it, that's been established fact. Now CDO's and the rest of the organization, the CIO's and the CTO's, have this mandate to start executing on them. And how do we go about it? That's part of my job at IBM as well. As a CTO, I work with our customers to identify where are the dominant business value? Where are those things which is completely data-driven? Maybe it is cognitive forecasting, or your business requirement could be how can I maximize 40% of my service channel? Which in the end of the day could be a cognitive-enabled data-driven virtual assistant, which is automating and bringing a TCO of huge incredible value. Those are some of the key execution elements we are trying to bring. But like we said, yes, we have to bring in the data, we have to hire the right talent, and we have to have a strategy. All those great things happen. But I always start with a problem, a problem which actually anchors everything together. A problem is a business problem which demonstrates key business values, so we actually know what we are trying to solve, and work backwards in terms of what is the data element to it, what are the technologies and toolkits that we can put on top of it, and who are the right people that we can involve in parallel with the strategy that we have already established. So that's the way we've been going about. We have seen phenomenal successes, huge results, which has been transformative in nature and not just these 170 CDO's. I mean, we want to make sure every one of our customers is able to take advantage of that. >> But it's not just the CDO, it's the entire business. So the IBM Institute on Business Value looks at an enormous amount of research, or does an enormous amount of research and looks at a lot of different issues. So for example, your CDO report is phenomenal, I think you do one for the CMO, a number of different chief officers. How are other functions or other roles within business starting to acculturate to this notion of data as a driver of new behaviors? And then we can talk about, what are some of those new behaviors? The degree to which the leadership is ready to drive that? >> I think the executive suite is really starting to embrace data much more than it has in the past. Primarily because of the digitization of everything, right. Before, the amount of data that you had was somewhat limited. Often it was internal data, and the quality was suspect. As we started digitizing all the business processes and being able to bring in an enormous amount of external data, I think organizationally executives are getting much more comfortable with the ability to use that data to further their goals within the organization. >> So in general, the chief groups are starting to look at data as a way of doing things differently. >> Absolutely. >> And how is that translating into then doing things differently? >> Yeah, so I was just at the session where we talked about how organizations and business units are even coming together because of data governance and the data itself. Because they are having federated units where a certain part of business is enabled and having new insights because we are actually doing these things. And new businesses like monetizing data is something which is happening now. Data as a service. Actually having data as a platform where people can build new applications. I mean the whole new segment of people as data engineers, full stack developers, and data scientists actually. I mean, they are incubated and they end up building lots of new applications which has never been part of a typical business unit. So these are the cultural and the business changes we are starting to see in many organizations actually. Some of them are leading the way because they just did it without knowing actually that's the way they should be doing it. But that's how it influences many organizations. >> I think you were looking for kind of an example as well, so in the keynote this morning one of the gentlemen was talking about working with their CFO, their risk and compliance office, and were able to take the ability to identify a threat within their ecosystem from two days down to three milliseconds. So that's what can happen once you really start being able to utilize the data that's available to an organization much more effectively, is that kind of quantum leap change in being able to understand what's happening in the marketplace, bing able to understand what's happening with consumers or customers or clients, whichever flavor you have, and we see that throughout the organization. So it's not just the CFO, but the CMO, and being able to do much more targeted, much more focused on the consumer side or the client customer side, that's better for me, right. And the marketing teams are seeing 30, 40% increase in their ability to execute campaigns because they're more data-driven now. >> So has the bit flipped where the business units are now coming to the CDO's office and pounding on the door, saying "I need my team"? As opposed to trying to coerce that you no longer use intuition? >> So it depends upon where you are, where the company is. Because what we call that is the snowball effect. It's one of the reasons you have to have the governance in place and get things going kind of in parallel. Because what we see is that most organizations go in skeptically. They're used to running on their gut instinct. That's how they got their jobs mostly, right? They had good instincts, they made good decisions, they got promoted. And so making that transition to being a data-driven organization can be very difficult. What we find though, is that once one section, one segment, one flavor, one good campaign happens, as soon as those results start to mount up in the organization, you start to see a snowball effect. And what I was hearing particularly last year when I was talking to CDO's was that it had taken them so long to get started, but now they had so much demand coming from the business that they want to look at this, and they want to look at that, and they want to look at the other thing, because once you have results, everybody else in the organization wants those same kind of results. >> Just to add to that, data is not anymore viewed as a commodity. If you have seen valuable organizations who know what their asset is, it's not just a commodity. So the parity of... >> Peter: Or even a liability is what it used to be, right? >> Exactly. >> Peter: It's expensive to hold it and store it, and keep track of it. >> Exactly. So the parity of this is very different right now. So people are talking about, how can I take advantage of the intelligence? So business units, they don't come and pound the door rather they are trying to see what data that I can have, or what intelligence that I can have to make my business different shade, or I can value add something more. That's a type of... So I feel based on the experiences that we work with our customers, it's bringing organizations together. And for certain times, yes sometimes the smartness and the best practices come in place that how we can avoid some of the common mistakes that we do, in terms of replicating 800 times or not knowing who else is using. So some of the tools and techniques help us to master those things. It is bringing organizations and leveraging the intelligence that what you find might be useful to her, and what she finds might be useful. Or what we all don't know, that we go figure it out where we can get it. >> So what's the next step in the journey to increase the democratization of the utilization of that data? Because obviously Chief Data Officers, there aren't that many of them, their teams are relatively small. >> Well, 41% of businesses, so there's a large number of them out there. >> Yeah, but these are huge companies with a whole bunch of business units that have tremendous opportunity to optimize around things that they haven't done yet. So how do we continue to kind of move this democratization of both the access and the tools and the utilization of the insights that they're all sitting on? >> I have some bolder expectations on this, because data and the way in which data becomes an asset, not anymore a liability, actually folds up many of the layers of applications that we have. I used to come from an enterprise background in the past. We had layers of application programming which just used data as one single layer. In terms of opportunities for this, there is a lot more deserving silos and deserving layers of IT in a typical organization. When we build data-driven applications, this is all going to change. It's fascinating. This role is in the front and center of everything actually, around data-driven. And you also heard enough about cognitive computing these days, because it is the key ingredient for cognitive computing. We talked about full ease of cognitive computing. It has to start first learning, and data is the first step in terms of learning. And then it goes into process re-engineering, and then you reinvent things and you disrupt things and you bring new experiences or humanize your solution. So it's on a great trajectory. It's going tochange the way we do things. It's going to give new and unexpected things both from a consumer point and from an enterprise point as well. It'll bring effects like consumerization of enterprises and what-not. So I have bolder and broader expectations out of this fascinating data world. >> I think one of the things that made people hesitant before was an unfamiliarity with thinking about using data, say a CSR on the front line using data instead of the scripts he or she had been given, or their own experience. And I think what we're seeing now is A, everybody's personal life is much more digital than it was before, therefore everybody's somewhat more comfortable with interacting. And B, once you start to see those results and they realize that they can move from having to crunch numbers and do all the background work once we can automate that through robotic process automation or cognitive process automation, and let them focus on the more interesting, higher value parts of their job, we've seen that greatly impact the culture change. The culture change question comes whether people are thinking they're going to lose their job because of the data, or whether it's going to let them do more interesting things with their jobs. And I think hopefully we're getting past that "it's me or it" stage, into the, how can I use data to augment the work that I'm doing, and get more personal satisfaction, if not business satisfaction, out of the work that I'm doing. Hopefully getting rid of some of the mundane. >> I think there's also going to be a lot of software that's created that's going to be created in different ways and have different impacts. The reality is, we're creating data incredibly fast. We know that is has enormous value. People are not going to change that rapidly. New types of algorithms are coming on, but many of the algorithms are algorithms we've had for years, so in many respects it's how we render all of that in some of the new software that's not driven by process but driven by data. >> And the beauty of it is this software will be invisible. It will be self-healing, regeneratable software. >> Invisible to some, but very very highly visible to others. I think that's one of the big challenges that IT organizations face, and businesses face. Is how do they think through that new software? So you talked about today, or historically, you talked about your application stack, where you have stacks which would have some little view of the data, and in many respects we need to free that data up, remove it out of the application so we can do new things with it. So how is that process going to either be facilitated, or impeded by the fact that in so many organizations, data is regarded as a commodity, something that's disposable. Do we need to become more explicit in articulating or talking about what it means to think of data as an asset, as something that's valuable? What do you think? >> Yeah, so in the typical application world, when we start, if you really look at it, data comes at the very end of it. Because people start designing what is going to be their mockups, where are they going to integrate with what sources, am I talking to the bank as an API, et cetera. So the data representation comes at the very end. In the current generation of applications, the cognitive applications that we are building, first we start with the data. We understand what are we working on, and we start applying, taking advantage of machines and all these algorithms which existed like you said, many many decades ago. And we take advantage of machines to automate them to get the intelligence, and then we write applications. So you see the order has changed actually. It's a complete reversal. Yes we had typical three-tier, four-tier architecture. But the order of how we perceive and understand the problem is different. But we are very confident. We are trying to maximize 40% of your sales. We are trying to create digital connected dashboards for your CFO where the entire board can make decisions on the fly. So we know the business outcome, but we are starting with the data. So the fundamental change in how software is built, and all these modules of software which you are talking about, why I mentioned invisible, is some are generatable. The AI and cognitive is advanced in such a way that some are generatable. If it understands the data underlying, it can generate what it should do with the data. That's what we are teaching. That's what ontology and all this is about. So that's why I said it's limitless, it's pretty bold, and it's going to change the way we have done things in the past. And like she said, it's only going to complement humans, because we are always better decision-makers, but we need so much of cognitive capability to aid and supplement our decision-making. So that's going to be the way that we run our businesses. >> All right. Priya's painting a pretty picture. I like it. You know, some people see only the dark side. That's clearly the bright side. That's a terrific story, so thank you. So Priya and Rebecca, thanks for taking a few minutes. Hope you enjoy the rest of the show, surrounded by all this big brain power. And I appreciate you stopping by. >> Thanks so much. >> Thank you. >> All right. Jeff Frick and Peter Burris. You're watching theCUBE from the IBM Chief Data Officers Summit, Spring 2017. We'll be right back after this short break. Thanks for watching. (drums pound) (hands clap rhythmically) >> [Computerized Voice] You really crushed it. (quiet synthesizer music) >> My name is Dave Vellante, and I'm a long-time industry analyst. I was at IDC for a number of years and ran the company's largest and most profitable business. I focused on a lot of areas, infrastructure, software, organizations, the CIO community. Cut my teeth there.

>> Announcer: Live, from Las Vegas, it's The Cube covering Interconnect, 2017. Brought to you by, IBM. >> Hey welcome back everybody, live here in Las Vegas at the Mandalay Bay IMB Interconnect 2017, it's The Cube's exclusive coverage, I'm Jon Furrier, my co-host Dave Vellante, our next guest is Ramesh Gopinath who's the VP of Block Chain Solutions and Research, welcome to The Cube. >> Thank you. >> Block chain front and center, super exciting, it's been trending pretty much throughout the conference, really is an amazing story, big props from the CEO and (mumbles) and a variety of the executives. Watching is instrumental in the future of business, we had Don Tapscott on yesterday really talking about the revolution of what this is all about and he's the author of the book, The Blockchain Revolution, but if blockchain is a game changer shift to how the business will be operating in the future, so just to level step, just give us the one on one blochchain, versus bitcoin, and why IBM is going in this direction and where it came from. >> So blockchain is all about increasing a trust in business transactions. This is something we recognize about a couple of years ago when a small team of us started playing around with, you know, the technology behind bitcoin, right. And we look at it and said hey look, here's an opportunity for the first time for companies to share some information in a secure fashion with each other and, in addition, run some workflows or business processes on top. That was an eye opener for us, it immediately told us this could have applications in all industries, right. And so what do we do first? So we said let's play around with this a little bit. We looked at existing technologies out there for blockchain and to pick the platform you tried a few use cases and realize, oh my god, there is a whole lot to be done to get a blockchain for business, right. And that's how we started this journey, almost a year and a half, two years ago. And we decided to explore that. >> And the key distinction Ramesh, and we know from just highlighting it here for the folks, is bitcoin is a currency that has a blockchain, so it's powering bitcoin. You're talking about something more fundamental for business which is using the blockchain technology for businesses and what bitcoin is to blockchain, business is to blockchain from your standpoint. >> That's right, and also I think the blockchain is really, the inspiration for it comes from bitcoin perhaps, that's a good way of thinking about it. But today for example, the hyperledger version one that was announced earlier this week at this conference is dramatically different from the underlying blockchain and bitcoin in other platforms out there, right. Because it's really built primarily based on requirements that we have gathered by working with hundreds of clients in financial services and supply chain, in public sector, et cetera, and realizing what levels of confidentiality, what levels of privacy, what level of permissioning, you know, who participates in the transaction. All of that is what has led to, what we call the (mumbles)- >> John: Okay somebody's got a question. >> John: I got a follow up on that, but go ahead. >> Uh, just one more point on this but you can follow up on my point. Give us the status of blockchain today for IBM. Lay out the solution because you move from research now to the exclusions group, you have customer action going on, sales motions, solutions motions. What is the architecture, what does it look like, what is the solution today from a blockchain standpoint? >> So, just, you asked what are you doing at a high level, essentially we have three broad, big investments. One is everything to do with you know, opensource in a hyperledger project, I mentioned that. Then there is you package that into a platform, IBM blockchain, high security business network, that was also announced earlier this week. And the third layer is again what you asked about solutions. What we have been doing over the last year, year plus is, in fact, it's an interesting journey, we started out with what I call blockchain tourism, there were a whole bunch of POC's if you want to call it that, starting with financial services initially, but in gradually other areas, like supply chain, in healthcare, et cetera. Towards the middle of 2016 we saw a transition, at least on the financial service side people were started to talk about, hey now I understand this technology and what it's capable of, let's talk about production deployments, right now I'll give you a few examples as we go along. >> Dave: So, I want to go back if I can a little bit and just get somewhat didactic for a moment. My understanding is there's three attributes, I'm sure there are many more of blockchain which are really relevant, and especially as it relates to the security if I may, it's distributed obviously, and it's been said it's virtually unhackable unless 50% of the stakeholders agree to collude, and then there's no need for a trusted third party so it reduces the threat space. Are those sort of accurate statements and when somebody says, well it's virtually unhackable, you know you tweet that and somebody says, well everything's hackable, help us understand sort of those fundaments of blockchain and why they're relevant. >> That's right, so the way I think about it is a blockchain is a trusted database. Now why is it trusted? There are three properties, I'll get to it, kind of overlaps with what you mentioned. The first one is, any transaction you do onto the database, anything that goes in it basically is done in a nonreputiable fashion. If I do something I can't say, "I didn't do that," so that helps. What goes in, you know you have that property. The second piece is, whatever goes in goes in through a vetting process, we will call it the consensus. There is some sort of a chat between parties before something goes in. Therefore, I can't unilaterally do something onto the blockchain, right, I can't, somebody else vetted what I did, that increases trust. And the third piece is, once it gets in there it cannot be tampered with. We say it's immutable sometimes, and what is that based on? There's a whole lot of topographic math behind it, but at a high level there are two aspects to it. One is, there are multiple copies. So if I change something, if I hack into mine, I'm inconsistent with what others have, so that's one. The second is, the transactions are chained together, blocks of transactions are chained together where a fingerprint of one block is put into the next. What that means is, if I tamper with the block say 15, a long blockchain, all transactions after that are invalid, I have to do a lot of work to fix it, so it's very very hard to tamper with. Of course, as with security, there's no such thing as nothing that is hackable, right, so collusions et cetera, potentially can happen. But the key is, significant increase in the level of trust is the way I would put it. >> Dave: Great, okay, and so now if we can get into sort of how people are specifically applying this technology, you guys started with the hyperledger, you know, open project, but can we get more specific in terms of how say organizations are actually deploying blockchain? >> Ramesh: So we are still running a blockchain in productions since September 6th, right, so it's been only four months. In fact that blockchain is more than a half a million blocks today, so let me tell you what that solution is so you get a sense of, and it's very prototypical in terms of, you know, all solutions that I've dealt with so far across industries. The use case is a following, so you have a buyer, you have a seller and you have a financer, that's IBM. We basically finance, shotgun financing of, think of it as channel financing or inventory finance. What happens typically is, the buyer basically orders something and the seller essentially gets approval from us to say, okay, yeah we can basically send it to the buyer. A few days go by, IBM has already paid the seller basically, just like credit cards (mumbles) consumers. A month later basically we go in, say hey look, guys, time for you to pay up and they say, look, we didn't even receive the goods. So this entire process, what I just described you can think of as a workflow where these three parties are sending messages back and forth. The way we do it in a blockchain is, this entire workflow is captured as a sequence of transactions that are registered on the blockchain. Now how does this help us? Take the example I gave, proof of delivery. If when the logistics company delivers it at the buyer's site, it's recorded on the blockchain. There is no need for a dispute. And typically disputes, basically puts a lot of capital, you know, it holds up a lot of capital right. Capital inefficiency is the problem we're after. In fact, after six months of deployment I can tell you essentially a significant improvement in terms of the time savings as well as elimination of disputes. >> John: That's a great efficiency. Who's buying, who's actually implementing it customers-wise. Can you name names? >> Ramesh: Yeah, so, examples are the, let me give you a few in financial services. So we are working with Salus Bank which does, you now, five trillion dollars worth of foreign transactions every day. They are building a netting engine called Salusnet a solution called Salusnet, and we're working with them on that. Another example is the work that we are doing with Northern Trust, where basically they have a private equity administration blockchain. In fact, it's a very interesting one because it also involves the regulator as a part of the blockchain, so that's a second example. A third one is the one we announced in January with the Depository, Trading and Clearing Corporation DTCC, and that one is for credit debitors, life cycle management, in fact all the examples if you notice, there is a life cycle like I gave in that example earlier of buying till all your goods are delivered, payment is made, those life cycles, those processes are captured as trusted processes on a trusted data store. That's basically blockchain for you, right, that's financial services. Maybe I'll touch upon two more examples to complete the story. Supply chain. I walk into a store and buy some sliced mangos at Walmart, is it safe to eat? To answer that question you need to know the provinence. Which farm in Mexico did it come from, who all touched it, who washed it, who processed it, et cetera, all the way till it got to the store. That sort of information sharing does not happen today in the supply chain. We believe with the block chain that is possible, that allow us to get a good sense of where things came from, making consumers more comfortable. Similar story can deal with pharma too. I pop a pill, I want to be sure that it's safe to have. In fact, as you know the World Health Organization says in Africa, every year a hundred thousand kids die of counterfeit malaria drugs alone, right, so imagine if you could capture these sorts of supply chain flows on a blockchain you could make dramatic improvements. >> Dave: Diamonds provenience is another one, and it's not just blood diamonds. >> Ramesh: I'm more excited by the providence of food and pharma, but diamonds- >> But there's tons of fraud in the diamond supply chain. >> Ramesh: Absolutely. >> And that's really where they're, you know- >> John: Well this brings up the whole business model disruptions, so, what are you guys seeing for the kids of conversations? Because you're getting at the business model impact significantly one, you're reducing costs of transactional costs for new measurement systems, aka blockchain, and you have all the methodology behind it, but everything from music to art to content, I mean, payments, this is like a game changer. >> Absolutely, and I think from the point of view, you know, in all of the use cases I've seen, the sort of value to the ecosystem is clean and obvious, and so you can immediately say, aha, this is going to happen overnight. But the reality is basically, it's a complex ecosystem play though. So, for example, in the supply chain use case, food safety, you need to have the farmers, the entire value chain involved, participating in some fashion on the blockchain. That is not easy to do. So there is, how do you sort of set up ecosystems is a key part of- >> John: What's your strategy there? I'm going to ask Marie when she comes on, but what's the strategy with ecosystem? Because you want to jump start this, you got to prime the pump big time. >> Ramesh: Absolutely, so there are many ways to solve this, but one approach we have taken so far, and it's obvious in all the sort of partnerships that we're working on. Take for example food safety. One way to start with it is to start with a big retailer, like a Walmart. They bring in the suppliers, and the suppliers bring in the farmers. Take the case of what we are doing in container shipping. So basically, movement of containers from point A to point B, we're trying to completely digitize that process, this is a project that we're doing with Maersk. Why Maersk? They are 20% of the container shipping market, right? But in all of these cases I got to be very clear, we are not building a solution for Maersk or for Walmart. We're really building something for the industry, because food safety, you want to solve it for the industry. Just by helping Walmart along. >> John: That's why the open source thing is critical here. >> That's right. >> John: And the update on that, it's all open source on which components, or is it all open source? >> Ramesh: So the open source is all about at the platform layer. The solution itself, you know not everything in the solution is going to be open source. But the key point I was trying to make is that you go off the sort of significant anchor tenants in the ecosystem that draws others into the picture, but that's still not enough, you need to make sure there are economic incentives for others to join in. >> John: So to put it together, tie it together, the ecosystem strategy is, take an industry scope and try the rising tides floats all boats kind of approach. So adoption's critical. >> Absolutely correct, absolutely correct, and I think again I can use food safety to make that point. Think about it, right? So there is, let's say, a spinach problem, we had it in 2006. So you find a problem, you trace it back to a source. Let's say Walmart is the store in which somebody bought it and it was traced from there. That's not good enough. From the source it went to many other retailers. So you need to be able to track down and pull all of them off the shelves. Therefore you have to go for an industry solution. >> John: I can imagine the healthcare thing would be even more impactful too, I mean, financial services pretty obvious, transactional stuff there, but healthcare, so many different variations of supply chain and transactions. >> Ramesh: Absolutely, so in a way, the way I think about it is in a financial service everybody had a hunch this could be big, but supply chain, we've come a really long way, I think this is going to be the space which will have the most destruction, and its interesting considering when we started my first conversation with folks, whether it be a Walmart or Maersk, first question is, "what is blockchain?" We've come a long way in the last say eight, nine months. >> John: You guys get so excited where you're kind of pinching yourselves because you can get kind of euphoric about some of the disruption impact. It's just mind blowing to think when you're talking about food, the food industry and healthcare. You got to get tampered down a little bit in some realism, is there that IBM excitement internally share some color internally within IBM the excitement, and then you got to be getting realistic, a lot of the clients rolling it out to kind of got to walk before they can run. >> Ramesh: Yeah, so, the way I would state it is if you had asked me a year ago do you expect to be in the shape we are in today, I would have said no way. I've been shocked at the pace at which this has been moving both from the point of view of the technology itself, maturing of the technology, and in fact when we say blockchain is here now, so that's at the technology layer level, but in terms of use cases, think about it, there are a number of financial services institutions that are talking about production deployments late this year, early next year. In fact, when we did our own IBM Institute for Business Values survey, came back with fully 15% of those who were surveyed, there were like 400-odd banks plus capital market institutions are going to be in production by end of this year. When I heard that in September I still didn't believe it, but I am beginning to believe it now. >> Well it's interesting I think, the cultural shift is that technologists from computer scientists to practitioners that are technologists, they get it. They can see what blockchain does, so I think as people get more and more momentum, that's the fly wheel that you guys are open for and it's happening. >> That's right, in fact I'm also a techie at heart, but in terms of conversation (mumbles) I never talk about technology anymore because the thing is, there are only two concepts in blockchain. It's trusted data across companies, trusted business process. Everything else is detail. >> John: Got it, Ramesh, thanks so much for sharing, great conversation, formerly with IBM research, now Vice-President of Blockchain Solutions at IBM, great to interview, great insight, blockchain revolution is here, check out our interview yesterday with Dom Tapscott yesterday on YouTube, The Blockchain Revolution, his book really kind of lays out some of the big disruptive game changers. This is The Cube, doing our share of blockchain right now, bringing content in blocks and chunks, not yet blockchain enabled. I'm John Furrier, Dave Vellante, be back with more after this short break. (synthesized music)

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