>> Narrator: Live from Munich, Germany it's theCUBE, covering IBM, fast track your data. brought to you by IBM. >> Welcome back to Munich, Germany everybody. This is theCUBE, the leader in live tech coverage. We go out to the events, we extract the signal from the noise, and we're here at the IBM signature moment, Fast Track Your Data in Munich, where enterprise data governance is a huge theme. We're going to talk about that right now, I'm Dave Vellante with my co-host, Jim Kobielus. Sanjay Saxena is here, he's the senior Vice-President at Northern Trust. Sanjay, welcome to theCUBE, thanks for coming on. >> Thank you, thank you, thanks for having me. >> So, enterprise data governance is a huge theme here, we're going to get into that, but set up Northern Trust, your organization, and your role. >> So, I am the head for enterprise data governance for Northern Trust. It's an essential enterprise role across all the business units. I've been working with Northern Trust for the last three years to set up the program, and prior to this I worked with Bank of Montreal and other institutions doing similar things. >> So how is enterprise governance evolving? I mean, I go back to, sort of, 2006 for the federal rules of civil procedure when electronic, you know, records became admissible in courts, and that set off a whole chain reaction, and plugging the holes with email archiving, and it was just really scratching the surface. We've kind of evolved there, is governance a strategic imperative? Why is it a strategic imperative? And how is it evolving? >> Well, our program has significantly evolved over the past three years. Partly because of how the market conditions are, and what the regulators expect. We fundamentally started our program focused on regulations, risk and compliance, like most banks did. But now we are a very broad based program within the company. So not just a risk department or the finance department, but also the business units are asking for data governance and for quality. And we are in the asset management, asset servicing business. And a lot of our customers, we manage their data. So they are expecting this as stable stakes at this point in time. So we are realizing a lot of value of the data governance in the business units as well, in addition to the risk and compliance usage. >> So how has governance evolved? I mean I went back ten, eleven years which is like ancient history in these days. How has your, sort of, data governance strategy evolved, and where has it come from, and where are you now, and where are you going? >> So, about two to four years back there wasn't anything formal when it comes to governance, it was very specific to certain units of data, certain types of data. For example, most companies are very concerned about the pricing data. And that's where they would have governance. But it was never a broad based program. Nor was there an operating model around governance and organization, structure, teams of people, so over the past three or four years we've seen that evolution. So now I have a number of data stewards as part of my team, and within the business units, whose sole business is to do governance. We have formally establishing data governance principles and practices and policies. Years back, even three years back, you'd go to most organizations you wouldn't find any policies and practices of data governance. So those are two distinct ways that the governance has evolved in terms of the model. And also along with that has been an evolution of tools and technology and where IBM has heard this a lot. >> Generally the line of business people, you know, governance, compliance, even security, and it's changing but, generally if I hear those words as a business person, it's ugh, it's going to slow me down, it's going to cost me time, it's going to cost me money, bureaucracy overhead. How do you as a governance professional address that? Can you make governance a source of value? >> Right, so governance is a very abstract concept. Most people, most businesses, don't want they want to run away from anything close to governance, right? >> Dave: No accountability. >> No accountability, right? They want to be focused on their revenues, etc. So one way to make that, and what we've done is we've made it very tangible by showing them data quality in terms of metrics, in terms of dashboards, in terms of showing them cost of poor data quality, right? In terms of, for example, a simple example is, a customer names an address as being wrong, may not mean very much to a regulator, but it is really important from a business perspective for a relationship manager in our business. So what we've done is shown that to them and shown positive trending towards the mediation and tied it to the business outcomes. So I wouldn't say that we are there yet, it's a journey, but there's been a lot of evolution in the process, they are accepting my organization, they are accepting the roles, and they are accepting the work we're doing. And they want to be part of it. So that's how I see them evolve, I see this as a continuous evolvement even beyond that. And ultimately I see them using governance almost as a product. Right now it's, we provide a lot of data to our end consumers, to our asset management, to management companies, to fund administrators, and others, right? And data governance is an implicit component of that, right? We don't charge money for it, right? But in the world of the future I see that, depending on the tier of the customer, depending on the kind of data that we're supplying them, we can have different tiers of data quality and governance around that, and we could explicitly charge. So they're excited about that project, about that prospect, and they want to work with us on that. >> And you, do you have a chief data officer? >> Sanjay: Yes. >> Okay, so, is it a relatively new role? Or it's been around, I mean typically in your industry it's regulated and so you tend to have more propensity for CDOs, but has there been one for a while, or a couple years? >> Sanjay: It's been around for two years. >> Just two years? Okay. >> Sanjay: Yeah, two plus years, yes. >> Okay, so that chief data officer that emergent role, looks at things like data quality, looks at how to monetize data, tries to form relationships with the line of business, all those things. Companies generally are just starting to understand, all right, how do I, how does data effect my monetization? Not so much how do I sell the data, but how does data help my cut costs or increase revenue? >> Yeah, well, or, yeah, related to that very much is, for example, do you compute a metric such as customer lifetime value that you would sacrifice if you don't, if your business doesn't consolidate multiple inconsistent customer data sets down to one canonical data set that you can use then to, high quality, that you can use to drive targeting marketing, and better engagement. Do you report like a CLV, customer lifetime value, as part of your overall governance strategy or thought about doing that? >> We've thought about doing that, and those metrics are evolving in our organization, but even a little bit more basic metrics around is your customer contactable, right? Do you have the right information about them? Or, for the share of the wallet, is it actually a better example? Like we have different investment products, and we have different products that we sell to our wealthy individuals. What portion of those, what is the average number of products that they have from us? And to be able to monitor, and measure it, across a meter of time, is a really important thing for businesses to do. >> Okay, let's, I see your button here, your badge here, it says IBM analytics, global elite, I think there was a little reception last night by the lake, and you know, all the execs took you guys out and wined and dined you and, you know, that's good. We saw that action going on. But so, what is that mean, a global elite? So that means you're a top-tier customer, what's your relationship with IBM, and how has that evolved? >> Right, so yeah, so North Interest buys a lot of stuff from IBM, lot of technology, tools, consulting, so we are, we are one of the top tier customers, and that's why we are part of the global elite program. And our relationship has really really evolved over time, especially in the governance base I'm talking about, and IBM has been a significant partner for us in terms of the initial strategy around governance, which we implemented and we are still on track to get that fully implemented. Equally important is the tools and technologies that they brought into the space. So most of the vendors provide segregated tools for different portions of data governance. You'll find some people good in lineators, good in meta data, glossary, etc. But IBM has an end to end suite, and we've been able to integrate that, we've been able to make it a single solution, single integrated solution, and that's really benefited us. So that's really been the contribution of IBM. >> And, okay, so can you talk more about the business impact about that single integrated solution? >> So the business impact is that today, unlike ever in the past, we have data quality dashboards. And this is, we are measuring data quality across thousands of data attributes on a monthly basis. We are publishing trends around data quality. We have that, we are also, for people, developers, for business people who are interested in where the data is coming from, we have lineage, we have an enterprise glossary. So it's a one stop solution across all of those. The business people are able to look at that, whether it's risk, finance, or business units, they're able to look at that on a monthly basis. We're able to provide implications of quality, we provide trending, so it is really taking us towards making us a data driven organization. >> Have you been a user, at least a beta-user of the governance catalog that IBM has announced today? What are your thoughts about that? >> Yes, so the information governance catalog we've been using that for the last three years. We have, as I said, about several thousand data elements in the information governance catalog. And what that does is, it creates that single vocabulary within the bank, and you cannot even imagine how difficult that is. Because for two business units to agree on the meaning of a term, it requires a lot of discussions and deliberations. But having a one simple repository that has all of the meta-data is one aspect of it. The second thing is, which has got implications in terms of data security and protection, that we are able to tag the data as sensitive data. For example, for GDPR, so we are using the same tool to be able to tag sensitive data elements and, as I said, the whole lineage, where does it reside, where does the data flow into, all of those things are very very easy and have been implemented in the IGC. >> Sanjay, what would you say is your biggest challenge as an enterprise data governance professional? >> Team management is still the biggest challenge, it is. As I said, it's a journey. And getting to every individual in the enterprise, for example, to start using this glossary that I just talked about. Or getting people to systematically look at data quality across the board. The other piece is the funding around data initiatives, right? So everyone's used to large transformation programs, but when I come up with a list of, here are the top ten data quality issues that need to be fixed, everybody looks over everybody else's shoulder I guess, and says, who's going to pay for it, right? And is this really our problem, or is this the problem of somebody else, right? So we get into a lot of those discussions, but it's a journey, as I said. >> Well, so you need executive support. To get executive support you have to demonstrate how it drives business values. So that's where it's, there's some carrot and stick involved. Well the stick is, well, we got to comply. We've heard a lot about GDRP and how that's going to, you know, cause pain. Okay, so that's the stick. The carrot is the data monetization, and the data value piece, connecting data quality to data value is that, you know, enticement, is it not. >> That's absolutely right, and the more and more we can show monetization of data, or even the fact that, because of that data governance or quality, we were able to acquire a new customer. It doesn't all need to be tangible is what I'm saying. But the more and more we can show monetization, the better off we'll be in terms of selling the program. >> Excellent. Well, Sanjay thanks very much for coming to theCUBE and sharing your experience, we really appreciate it. >> Sanjay: Thank you, thank you very much. >> You're welcome. (techno music)