 Live from the campus of MIT in Cambridge, Massachusetts, it's theCUBE, covering the MIT Chief Data Officer and the Information Quality Symposium. Now, here are your hosts, Stu Miniman and Paul Gillan. Welcome back, this is Paul Gillan here with Stu Miniman at the MIT Chief Data Officer and Information Quality Symposium, wrapping up our second day of live streaming coverage. We're going to talk more about information value now. We have a distinguished guest, Jim Short, Dr. Jim Short, who is a research director for the Global Information Industry Center, University of California at San Diego and the Supercomputer Center, University of California at San Diego. Rejoining us, Steve Todd from EMC and the talk about data value, the value of putting in dollar value on data and we just were talking with Doug, Doug Laney from Gartner about that and I wonder, Jim, are you familiar with the work that Gartner is doing this area? Yes, very much so. Doug and I have spoken about that work over time and we're doing work that is complimentary to Doug's work at Gartner. He's looking at a certain set of characteristics around a topic area he calls Infonomics and we're looking at questions around monetization of data and particular strategies for how people value essentially the asset value of that data in different types of business transactions. How did you become involved, interested in this topic in the first place? I've been interested in the questions that companies have faced with growth and a natural outgrowth of studying data growth which is averaging about 50% a year in most large corporations is what is the value in that growth? How do companies extract that value? What are the formal processes they can use? We talk a lot about analytics, we talk about looking at characteristics of the most valued asset part of that growth. So it was really a question of what could we look at specifically that we look at common practices and new practices that companies were evolving to maximize that, the asset value. Now, Steve, you have been involved with this effort for about a year and a half. Now, what does EMC find of interest about this topic? I would say two years ago, 2014, as we were surveying our customers, we saw them indicating a desire to augment their product revenues with data revenues. And we wanted a strategy to figure out how do we help them to cross that bridge, to move from just selling products and getting one-time revenue to gathering data and making money off of it. And Jim at the San Diego Supercomputer Center was one of the few people, if any, that we knew in academia that was looking at this that could really help us to get a head start and understand whether this trend was real and he found it is. And now we're working on strategies that we think will help EMC customers become more data-centric and data savvy. Professor, one of the key things we've been talking about at this conference is some of the organizational challenges there. How does data value fit into that? What are some of the key stakeholders? Any guidance you give as to what you've seen so far or what the companies need to do to improve things? So, partly the reason that we're interested in the evolution of the CDO role is what responsibilities the CDO role will take in monetization of data, the definition of data as an asset to the corporation and where the communication about that asset value will rest in the company. So, there are many C-level executives with an interest in analytics, other forms of adding value to data which then you monetize and then bring to market in some fashion. So, it's a cooperative activity as well as a singular responsibility activity and we're interested in where that's gonna fall out. Want to participate in that discussion in management circles about where that is, particularly at a C-level executive environment. And I think the second aspect of that is where we see the evolution of this role as more companies shift with an interest in monetizing asset value. Are you helping companies innovate, figure out where the monetization opportunities are? I mean, often the biggest barrier is just coming up with the idea. Yeah, I think there's three, there's several different ways, but three main ways are asset productivity. So, if you're in a business that is having difficulties in performance, a lot of attention will be devoted to the productivity of the asset base of the current firm to get your performance up. Another, as Steve had mentioned, is that I have an existing product set. Some of those product sets can be information, you can add data to that product set, you can therefore expand the business scope of that product and the target market for that. And the third is new businesses would be the generation of new business built around a new data set of data strategies that the firm and those could be in partners with external firms, they could be within a single company, but in any event, that's what we've seen. Our work has suggested those three and I think there'll be some additional ones that are based around new kinds of technologies that are principally internet of things, which in principle, the stack for an IoT is not going to be in any specific company, it's going to be a broad base of companies that have to participate in some market fashion to bring that to value realization. So, I think it's those four that we've talked about. Are there any examples, either of you, of where companies have actually successfully done this, created the lines of business? Certainly, Jim, as part of his industry survey, has found some sensational examples of valuation in which data sets have been valued at a billion dollars. For example, Seizure's Palace Total Rewards customer loyalty database, as part of bankruptcy proceedings, was valued at a billion dollars. Tesco, when it wanted to spin off its Dunhumbi data science division in all the data of shopping patterns of 770 million customers, sold that for 900 million dollars. And so, those examples show use cases. Data sale, mergers and acquisitions, Microsoft's acquisition of LinkedIn, and LinkedIn's acquisition of Lynda.com the year before, was a billion dollar data acquisition. So, we're finding that there's some high profile data valuation business processes and customers, and most of them are struggling with how to understand, measure, manage valuation. And so, the industry is ripe for some education on best practices. When you speak to CEOs about this and define the opportunity, do you get a lot of excitement? Do you see lights going off, or do a lot of them just say, that's not our business, we're not in the data business? So, I think it's a mixture. I think the business case has to be built. There's inherent risks in expanding business scope around data, and a CEO's responsibilities are going to be to look at the characteristics of how the company expands. So, this is one of many opportunities companies have to expand their businesses. But yes, I think in general, in some specific targeted industries, healthcare, transportation, anyone who has a large asset base that they're looking to tie together on some kind of coordination system, or anyone who sees as part of their principal expansion of their business data partnerships. So, an example of that would be Ericsson, Inmersod, and Maritime Transportation. Anyone who's trying to expand that business scope, that's a CEO level consideration. So, in that sense, yes, that would be very much part of that discussion. So, one of the discussion points we've had is how open mandates and government, you know, leveraging multiple data feeds, you know, impacts what's happening here. Is that fit into the discussion of data value, or is it in opposition to, you know, trying to get value out of our data? No, it's an important part of it, because a lot of companies are already using that. So, there's a lot of basic types of data, navigation data, GPS types of data, and so forth. A lot of the smart cities initiatives that people are speaking about are leveraging off of public data that's currently accessible. There is data partnerships, so if you look at Waze, for example, one of the things they're doing in the Connected Cities program is to tie up with public sources of data. So, this is, for certain kinds of businesses, this is an essential component of their business strategies. For others, it's something that they need to look at in the future. What's interesting about this is not just the current data sets, which you hear a lot about. Government is building different kinds of data sets, and they're making them available for different types of businesses. So, my recommendation in that space would be that in any business that has combination activity, business type of activity that combined with other kinds of data, public health data, data that looks at satellite types of resources for location data that's more precise than the current systems. Any of these kinds of systems, those are opportunities for private companies to take a look at partnerships with government. Talk about new sources of data. Brings to mind things like the industrial internet, internet of things. Steve, how do all this, the next boom of data that we're going to see play into your thinking? So, the boom means that we're going to have so much data streaming into a system that it'll be impossible to value it at rest, right? So, we believe that there's going to be a streaming analytic layer that is examining content as it comes in and making on-the-fly, valuation, you know, initial values, right? That a CDO or a CIO could look at right away to make decisions for the company. And I think that's the value of the use cases that Jim has brought to our attention, right? Jim's focus has been on what are the new business processes that are merging around data value? And my role is really what are the IT architecture changes that are going to need to happen to support these new business processes for data value? So, a use case there would be programmatic advertising. We're basically the advertising marketplaces being disrupted by essentially real-time ad placement and streaming media. So, if you're a media company, if you're an ad company, if you're a search-based company, like a Google that is positioning those ads in click-screen activity, you're going to be very interested in the real-time positioning of those ads. As you look at one topic we've been discussing here today is the role of the CDO, whether the CDO is in fact kind of a fixed or upper function, or whether it's endemic, it's intrinsic to the organization, big companies that are companies that are born with data, born on the web where data is at their core often don't need a CDO, it seems. What is your opinion on that? Does the CDO role eventually become extinct in organizations that truly become data-driven? Well, I think the proposition is, is that we think the CDO role is going to improve. So, an internet company that doesn't see the need for now doesn't mean that they're not going to see the need as they grow. So, as they expand their businesses away from the current internet business model and they expand into other businesses, which they're intending to do, the CDO role may be one that they look at with respect to the governance of different kinds of businesses where they need to manage a complicated data environment. In terms of the evolution of this role, there's several different C-level activities all associated with technology and data at this point. And there is certainly, we are going to approach a time, I think it's sooner than later, where some discussion in the C-suite has to be where these activities, responsibilities resolve. We heard a lot at this event at this conference about the need for coordination activities between different C-level executives and kind of the data chain. I think more of that has to happen. I think we're, so what I would look at is the more communication and the more activity of those companies is going to emerge the new kind of organizational arrangements for where this role will end up. So, I tend to look at companies that are in the information-intensive space because they are the guys that are going to have to resolve this sooner than later matter. Some of the most highly valued startups over the last three years, and I'm thinking of Lyft and Uber and Airbnb being some of the most pronounced examples of this, essentially all they have is data, right? That's the only asset they really have is data. Do you think that as a business model that is, do you think it will see an explosion of other companies with data at their core like that? Or are there just a few use cases where that really works? I think it'll be a general practice in business. I think you're going to see pretty much every business is going to have to have either the skill set or the knowledge of how to convert data into the business value of that data. Now, whether they use that internally as an asset type of activity, I can envision certain kinds of companies that would do that, would manage it as an internal asset and would use it in product spaces or in service spaces. But for many companies, I think they're, and increasingly we're part of our work is looking at those companies at the decision points they take, that in the introduction of new products, I mean, Immelt from GE is on record is stating that the company will be, by 2020, one of the top 10 software companies in the world. He makes that statement because the shift in how they sell products will increasingly become the services of those products with the information and the data that is generated by their environment. We're very interested in that and we're trying to track the development of that and look at the success of that in terms of what markets and what product lines they're introducing that strategy. And we think that's a general strategy, not specific to just GE, other companies. I would also argue that companies like Uber and Lyft, in addition to having the asset being data, is their ability to spin new revs of applications quickly in their agile development model. So we're seeing that there's a tie between the value of data and the ability for an organization to come up with a new function in their application, code it, test it, and deploy it. And as they shrink that cycle down, you see the value of data increasing because they're gathering new forms of data and getting that into their systems. We are, so we're out of time. I've been given the word, we can keep going on. I should point out, or note by the way, that Jim, in addition to all of the other things that you do, has been named the chair of the first West Coast CDO IQ Forum, which will be, I suppose, which will be in the February timeframe next year. Yes, yes. Great place to have it in winter, right? Oh, San Diego. I'm there, I'm there. I want to thank you very much for joining us. Fascinating topic. Steve, thanks again for being back with us. This is the queue. We will be back to wrap up the MIT CDO IQ Symposium in just a moment.