 Live from Boston, Massachusetts, it's theCUBE. Covering IBM Chief Data Officer Strategy Summit. Brought to you by IBM. Now here are your hosts, Dave Vellante and Stu Miniman. We're back, welcome to Boston everybody. This is the IBM Chief Data Officer Summit. This is theCUBE, the worldwide leader in live tech coverage. Inder Paul Bandari is here. He's the newly appointed Chief Data Officer at IBM. He's joined by Bob Pitchianos, the Senior Vice President of IBM's Analytics Group. Bob, great to see you again. Inder Paul, welcome to theCUBE. Thank you, great to be here. So good event, Bob, let's start with you. You guys have been on the Chief Data Officer kick for several years now. You're ahead of the curve. What are you trying to achieve at this event? Yeah, so Dave, thanks again for having us here and thanks for being here as well to help your audience share what we're doing here. We've always appreciated that, your commitment to helping the masses understand all the important pulses that are going on in the industry. What we're doing here is we're really moderating form between Chief Data Officers. And we started this really in the curve, as you said, 2014 where the conference was pretty small. There were some people who were actually examining the role, thinking about becoming a Chief Data Officer. We probably had a few formal Chief Data Officers. And we're talking about maybe 100 or so people who were participating in the very first one. Now you can see it's grown much larger. We have hundreds of people and we're doing it multiple times a year in multiple cities. But what we're really doing is we're bringing together a moderated form. And it's a privilege to be able to do this. This is not about selling anything to anybody. This is about exchanging ideas, understanding what are the challenges of the role, what are the opportunities, what's changing about the role, what's changing about the market and the landscape, what new risks might be on the horizon, what new opportunities might be on the horizon. And we really like to listen very closely to what's going on so we can maybe build better approaches to help them, whether that's through the services we provide or whether that's through the cloud capabilities we're offering or whether that's new products and services that need to be developed. And so it gives us a great understanding. And we're really fortunate to have our Chief Data Officer here, Indrapal, who's doing a great job in IBM and in helping us on our mission around really becoming a cognitive enterprise and making analytics and insight and data really be central to that transformation. So Dr. Mandari, new to the Chief Data Officer role, not new to IBM, you worked here and came back. I was first exposed to the role maybe four or five years ago at the MIT Chief Data Officer event. Okay, so you come in as a Chief Data Officer in December. Where do you start? So I've had the fortune of being in this role for a long time. I was one of the earliest. I created the role for healthcare in 2006. Then I've honed that role over three different Chief Data Officer appointments at healthcare companies and now I'm at IBM. So I do have, I do view the job as a craft. So it's a practitioner job and there's a craft to it. And to answer your question, there are five things that you have to do to get moving on the job. And three of those have to be done sequentially and two must be done in parallel with everything else. So the first thing is you've got to develop a data strategy. And a data strategy is focused around having an understanding of how the company monetizes or plans to monetize itself. What is the strategic monetization path of the company? Not so much how it monetizes data, but what is it trying to do? How is it going to make money in the future? So in the case of IBM, it's all around cognition. It's around enabling customers to become cognitive businesses. So my data strategy or our data strategy, I should say, is focused on enabling cognition, becoming a cognitive enterprise. And we've now realized that's in fact a prerequisite for cognition. So that's the data strategy piece and that's the very first thing that needs to be done. Because once you understand that, then you understand what data is critical for the company. So you don't boil the ocean. Instead, what you do is you begin to govern exactly what's necessary and make sure it's fit for purpose. And then you can also create trusted data sources around those critical data assets that are critical for the monetization strategy of the company. So those three have to go in sequence because if you don't do one, you can't do two adequately, you can't do three. And there are also significant pitfalls if you don't follow that sequence because you can end up boiling the ocean. And the other two activities that must be done concurrently, one is in terms of establishing deep partnerships with the other areas of the company, the key business units, the key functional units, because that's how you end up understanding what that data strategy ought to be. If you don't have that knowledge of the company by making that effort, that due diligence, then it's very difficult to get that data strategy right. So you've got to establish those partnerships. And then the fifth one is because this is a space where you do require very significant talent. You have to start developing that talent and that organizational capability right from day one. So, Bob, you said that data is the new middle manager. You can't have an effective middle manager unless you at least have some framework that was just described, is that fair? Yeah, absolutely. So when Interpol talks about that fourth initiative about the engagement with the business units and making sure that we're in alignment on how the company is monetizing its value to its clients, his involvement with our team goes way beyond how he thinks about what data it is that we're collecting and the products that we're offering and what we might understand about our customers or about the marketplace. His involvement goes also into how we're curating the right user experience for who we wanna empower with our products and offerings. Sometimes that's the role of the chief data officer. Sometimes that's the role of a data engineer. Sometimes it's the role of a data scientist. You mentioned data becoming the new middle manager. We think the citizen analyst is ushering in from their seat, but we also need to be able to, from an IT perspective, to help them eliminate the IT long tail and get transparency of the information. And sometimes it's the application developer. So we collaborate on a very frequent basis where when we think about offering new capabilities to those roles, well, what's the data implication of that? What's the governance implication of that? How do we make it a seamless experience? So as people start to move down the path of igniting all of the innovation across those roles, there's a continuum to the information they're using to be able to do that, how it's serving the enterprise, how it leads to that transformation to be a cognitive enterprise. And that's a very, very close collaboration. We're moving from, you said in your talk, the process era to what I just inserted to an insight era. Yeah. And I have a question around that. I'm not sure exactly how to formulate it, but maybe you can help. In the process era, technology was unknown. The process was very well-known, well-known, but technology was mysterious. We went to IBM and said, help. Today, it seems as though the process is unknown. The technology's pretty known. Look at what Uber, Airbnb are doing to grab in different technologies and putting them together, but the process is new. First of all, is that a reasonable observation? And if so, what does that mean for chief data officers? So, the process is new in the sense that in terms of making it a cognitive process, it's going to end up being new, right? So the Uberization that you've done it before. It's never been done before, right? In that sense. But it's different from process automation in the past. This is much more about knowledge, being able to scale knowledge, not just across one process, but across all the processes that make up a company. And so that goes also to the comment about data being the middle manager. I mean, if you've essentially got the ability to scale and manage knowledge, not just data, but knowledge in terms of the insights that the people who are working these processes are coming up in conjunction with these data and intelligent capabilities that are the hub, right? It's the intelligent system that's at the hub of this that's enabling all that. So that's really what leads to the so-called Uberization. Yeah, Dave, another important aspect of this is the process is dramatically different in the sense that it's ongoing. It's continuous, right? The process and your intimacy with Uber and the trust that you're developing in the brand doesn't start and stop with one transaction. It actually branches into many different things. So your expectations as that relationships evolve change. So what they need to understand about you, what they need to protect about you, how they need to protect you in their transformation, the richness of their service needs to continue to evolve. So how they perform that task and the abundance of information they have available to perform that task, but the difficulty of being able to really consume it and make use of it is a change. The other thing is it's a lot more conversational, right? So the process isn't a deterministic set of steps that someone at a desk can really formulate in a business rule or a static process. It's conversational, it changes. It needs to be disambiguated. It needs to introduce new information during the process of that disambiguation. And that really, really calls upon the capabilities of a cognitive system that is rich in its ability to understand and interact with natural language to potentially introduce other sources of rich information because you might take a picture about what you're experiencing. And all those things change that notion from process to the conversational element. So Dr. Madari, you've got an interesting role. Companies like IBM, I think about the IT, the CIO, the CDO. Not only do you have your internal role, but you're also a model for people going out there. You come to events like this, you're trying to help people in the role. You've been a CDO at some healthcare organizations. Can you tell us what's been different about being kind of the internal role of IBM? What kind of things? IBM, obviously a strong technology culture, but tell us a little bit of insights you've learned. What's anything surprised you in your time that you've been doing it? Oh, over the course of time that I've been doing the role across four different organizations. I guess specifically at IBM, what's different there? You know, IBM for one thing is the environment has tremendous scale. And if you're essentially talking about taking cognition to the enterprise, that gives us a tremendous test bed to try out all the capabilities that we're basically offering to our customers. And to hone that in the context of our own enterprise, you know, to build our own cognitive enterprise. And that's the journey that we're sharing with our customers and so forth. So that's different in, that wasn't the case in the previous roles that I had. And I think the other aspect that's different is the complexity of the organization. This is a large global organization that wasn't true of the previous roles as well. They were much more North America centric organizations. And so there's an aspect there that also then adds complexity to the role in terms of having to deal with different countries, different languages, different regulations. It just becomes much more complex. When you first became a CDO in 2006, you said? 2006, which was the same year as the federal rules of several procedure came out and emails became smoking guns. And then it was data viewed as a liability. And now it's completely viewed as an asset. But traditionally the CDO role was financial services and healthcare and government and highly regulated businesses. And it's clearly now seeping into new industries. What's driving that? Is it that value? Well, it is. I mean, it's, I think that understanding that, you know, there's a tremendous natural resource in the information and the data. But there is very much yin and yang around that notion of being responsible. I mean, one of the things that we're very proud of is the type of trust that we've established over a 105 year journey with our clients in the types of interactions we have with one another, the level of intimacy that we have in their business and a very foundational way that we serve them. And so we can never, ever do anything to compromise that. So the focus on really providing the ability to do the necessary governance and to do the necessary data provenance in lineage and cybersecurity while not stifling innovation and being able to push into the next horizon. Inderpal mentioned the fact that IBM in and of itself, we think of ourselves as a laboratory, a laboratory for cognitive innovation, a laboratory for design innovation, which is so necessary in the digital era. And I think we've done a really good job in those spaces, but we're constantly pushing the envelope. A good example of that is blockchain, I had a technology that sometimes people think about in nefarious circumstances about what it meant to the ability to launch a silk road or something of that nature. We looked at the innovation, understanding quite a lot about it, being one of the core innovators around it, and saw great promise in being able to transform the way people thought about clearing multi-party transactions and applied it to our own IBM credit organization to think about a very transparent hyper ledger. We could bring those multiple parties together. People could have transparency in the transactions, have a great deal of access into that space. And in a very, very rapid amount of time, we're able to take our very sizable IBM credit organization and implement that hyper ledger also while thinking about the data regulation, the data governance implications. I think that's a really good example. That's absolutely right. I mean, I think Bob mentioned the example about the IBM credit organization, but there are implications far beyond that. There are applications far beyond that. In the data space, it affords us now the opportunity to bring together identity management, the profiles that people create from data, the security aspects, and essentially combine all of these aspects into what will then really become a trusted source of data. I don't mean internally, but trusted by the consumers of the data, the subjects of the data, because you'll be able to do that much in a way that's absolutely appropriate, not just fit for business purpose, but also very, very respectful of the consent and those aspects, the privacy aspects of data. So blockchain really is a critical technology. Hyper ledger is a great example. We were at IBM Edge this week. You're going to be at World of Watson. We will be at World of Watson. We had the CEO of Everledger on and they basically brought a million diamonds and bringing transparency to the diamond industry. It's fraught with fraud and theft and counterfeiting. Helping preserve the integrity of the industry and eliminating the blood diamonds and they, right? It's fascinating to see how this Bitcoin, when so many people disparage it as a currency, but not just a currency. You guys, IBM saw that early on and obviously participated in the open source. You know the old saying, follow the money. This is like follow the data. So if I understand it correctly, your job as CDO is to sort of supercharge the business lines with the data strategy and then Bob, your job is the line of business managers to supercharge your customers' businesses with the data strategy. Is that right? Is that the right value chain? I think you nailed it. Yep. One of the things people are struggling with these days is if they can get their own data in house, then they've also got to deal with third party data, industry data, everything like that. IBM's role in that data chain is really interesting. You talked this morning about kind of the weather channel and kind of the data play there. Yeah. What's IBM's role in there going forward? It's one of the most exciting things, I think, about how we've evolved our strategy. And we're very fortunate to have Ginny at the helm who really understands that transformational landscape and how partnerships really change the ability to innovate for the companies we serve. And it was very obvious in understanding our clients' problems that while they had a wealth of information that they were dealing with internally, there was great promise in being able to introduce these outside signals, if you will, insights from other sources of data. Sometimes I called them vectors of information that could really transform the way they were thinking about solving their customer problems. So why wouldn't you ever want to understand that customer's sentiment about your brand or about the product or service? And as a consequence of that, capabilities that are there on Twitter or WeChat or Line are essential to that depending on where your brand is operating. Your brand's probably operating in a multinational space anyway, so you have to listen to all those signals and they're all in multiple language. And sentiment is very, very bespoke. It's a different language. So you have to apply sophisticated machine learning. We've invented new algorithms to understand how to glean the signal out of all that white noise. You use the weather example as well. We think about the economic impact of climate, atmosphere, weather on business. And it's profound. We have a trillion dollars in each calendar year that are lost information, lost assets, lost opportunity, misplaced inventory, undelivered inventory. And we think we can do a better job of helping our clients take the weather excuses out of business in a variety of different industries. And so we've focused our initiatives on that information, integration, governance, understanding, new analytics to introduce those outside signals directly in the heart and wanna place it on the desk of the Chief Data Officer or those who are innovating around information and data. My joke last Columbus Day was, Dell's buying EMC, IBM's buying the weather company. What does that say? My question is, Interpol, when M&A happens, and Bob, when you go out and purchase companies that are data-driven, what role does the Chief Data Officer play in both M&A, pre and post? So, you know, I think the, one of the, there've been a, I'm just gonna touch on a couple of points that Bob made, and I'll address your question directly as well. In terms of the role of the Chief Data Officer, I think you'd given me that question before and how that's evolved. The one very interesting thing that's happening now with what IBM is doing is that previously the Chief Data Officer role, at least with regard to the data, not so much the strategy, but the data itself was internal focused. You know, you kind of worried about the data you had in-house or the data you were bringing in. Now you've got to worry as much about the exogenous data. And because, you know, so that's one way that that role has changed considerably and is changing and evolving, and it's creating new opportunities for us. The other is, again in the past, the Chief Data Officer role was around creating a warehouse for analytics and separated out from the operational processes. That's changing too, because now we've got to transform these processes themselves. So that's another expanded role. To come back to acquisitions, M&A, I mean, I view that as essentially another process that a company has. And so the Chief Data Officer role is pretty key in terms of enabling that, both in terms of data, but also in terms of giving guidance and advice if, for instance, the acquisition is in that realm itself, then we'd be more closely involved. But if it's beyond that, in terms of being able to get the right data to that process, as well as then once you've acquired the company in being able to integrate back the critical data assets, those are the key aspects of the role. So you've got, I mean, at the simplest level, you've got data sources and all the things associated with that, and then you've got your algorithms and your machine learning, and we're moving beyond sort of Hadoop to cut costs into this new era. But so how do companies adjudicate, and I guess you've got to do both, you've got to get new data sources and you've got to improve this continuous process, Bob, that you talked about. How do you guide your customers as to where they put their resources? No, and that's really, Dave, as you're touching on it again, that's really the benefit of this sort of a forum and this sort of a conference. It's sharing the best practices of how the top experts in the world are really wrestling with that and identifying, I think, you know, Interpol's framework, what do you do sequentially to build the disciplines, to build the solid core and foundation, to make the connections that align with the business strategy, and then what do you do concurrently along that model to continue to iterate and how do you manage and make sure your stakeholders understand what's being done, what they need to continue to do to evolve the innovation, and you know, come join us here and we'll go through that in detail, but you know, Interpol did a great job of sharing his framework of success in the other room, other CDOs are doing that now. Yeah, I just wanted to quickly add to Bob's comment. The framework that I described, right, it has a check and balance built into it because if you are all about governance, then the CDO role becomes very defensive in nature. It's all about making sure you're within the guardrails and so forth, but you're not really moving forward in a strategic way to help the company and that's why, you know, setting it up by driving it from the strategy down just makes it easier to strike that balance. That's clerical and more about innovation. We talked about the D in CDO today, meaning data, but really I think about it as being a great crucible for disruption and innovation. Chief Disruption Officer. I call it the Chief Disruption Officer, so if you- And digital is data, so there's that piece of it as well. We have to go, I don't want to go, but so one last question for each of you. So Inderpal, thinking about, and you just kind of just touched on it, not just playing defense, you know, thinking more offense. This role, where do you want to take it? What are your sort of midterm, longterm goals with this role? It's the specific role at IBM or the just in general, the specific role. Well, I think in the case of IBM, we have the data strategy pretty well defined now. It's all about being able to enable a cognitive enterprise. And so in my mind in two to three years, we'll have completely established how that ought to be done as a prescription, and we'll also have our clients essentially sharing in that journey so that they can go off and create cognitive enterprises themselves. So that's pretty well set. I have a pretty short window two to three years to make that happen. And I think it's doable and I think it'll be just a tremendous transformation. Well, we're excited to be watching and documenting that. Now, Bob, I have to ask you, we're all the Watson coming up new name for new conference. We're trying to get Pepper on, we're trying to get Ginny on. Let's see, what should we expect? Maybe it could as well look like. Oh, look, I mean, I think this year we're sort of blowing the roof off. And literally, we're getting so big that we had to move the venue. It is very much still in its core that multiple practitioner, that multiple industry event that you experienced with insight. So whether or not you're thinking about this and the auspices of managing your traditional environments and what you need to do to bring them into the future and how you tie these things together, that's there for you. All those great industry tracks around the product agendas and what's coming out are there. But the level of inspiration and involvement around this cognitive innovation space is going to be front and center. We're joined by Ginny Rometti herself, who's going to be a very special keynote. We have, I think, an unprecedented lineup of industry leaders who are going to come and talk about disruption and about disruption in the cognitive era. And then, as always, the most valuable thing is the journeys that our clients and our partners are sharing with us about how we're leading this inflection point and transformation in the industry. So I'm very much excited to see you there. And I hope that your audience joins us as well. Great. Well, Indapald, congratulations on the new role. Thank you. I got a couple good blog posts out of your comments today. So I really appreciate that. And Bob, always a pleasure. Thanks so much for having us here. Really appreciate it. Thanks for having us. All right, keep right there, everybody. This is theCUBE. We'll be back. This is the IBM Chief Data Officer Summit. We're live from Boston. We're back. My name is Dave Vellante and I'm a long.