 Hello and welcome. My name is Shannon Kemp and I'm the executive editor of Data Diversity. We'd like to thank you for joining this month's installment of the Monthly Data Diversity Webinar Series, CDO Vision. This series is designed to give you around education on data strategy topics in addition to our annual face-to-face CDO Vision event. We're already well underway planning for next year's event to be held in Atlanta, Georgia. In fact, we just sent out a call for presentations for that event. In the webinar series, John Lidley and Kelly O'Neill will be interviewing Andrew Sileski, senior vice president and global data officer at Charles Schwab. A couple of points to get us started. Due to the large number of people that attend these sessions, he will be muted during the webinar. For questions, we will be collecting them via the Q&A in the bottom right-hand corner of your screen. Or if you like to tweet, we encourage you to share highlights or questions via Twitter using hashtag CDO Vision. As always, we will send a follow-up email within two business days containing links to the slides. The recording of this session and additional information requested throughout the webinar. Now let me introduce our speakers for today. Well-known industry analyst John Lidley is a business technology thought leader and recognized authority in all aspects of enterprise information management with 30 years experience in planning, project management, improving IT organizations, and successful implementation of information systems. He is the president and chief delivery officer at First San Francisco Partners. Also joining us is Kelly O'Neill. Kelly is the founder and CEO of First San Francisco Partners. Having worked with the software and systems providers key to the formulation of enterprise information management, Kelly has played important roles in many of the groundbreaking initiatives that confirm the value of EIM to the enterprise. Recognizing an unmet need for clear guidance and advice on the intricacies of implementing EIM solutions, she founded First San Francisco Partners in early 2007. And joining us is guest speaker Andrew Sileski, Andrew Lee Schwab's global data function, which focuses on driving increased competitive advantages through improved data management. Key objectives include improving data access and availability, enabling speed to insight, and ensuring robust data governance. Prior to joining Schwab in 1995, Sileski was a senior engagement manager at the San Francisco Office of McKinsey & Company. Andrew also earned his bachelor's and master's degree in the industrial engineering from Stanford University. In addition, he earned his master's in business administration as an RJ scholar from the Stanford Graduate School of Business. He lives in San Rafael, California with his wife Christine and two children. And with that, I will turn it over to Kelly to get today's webinar started. Hello and welcome. Thank you, Shannon. Really appreciate it. So very excited to have Andrew on the call with John and I today. Just a couple of things to remind everyone of our upcoming webinars. Again, the first Thursday of every month we've got a Halloween special in October. And then we close out the year in November and December where we're really focusing on the strategy aspect as everybody's planning for their 2017 goals and budgets. We thought that the strategy approach would be really valuable for everyone. So today's agenda, we have a series of planned questions as we normally do with our interviewees. But the idea is to take a lot of questions from the participants to make sure that we are addressing those burning issues with our guest Andrew today. And so that you know what we all look like. Those of you who've joined before are familiar with John and my smiling faces. And so we're joined by Andrew. And now you can picture the face with the voice. All right. Well, let's go ahead and jump in if we're all ready. Starting off Andrew. So we've worked together for a gosh a year and a half now. Since you started your CDO journey. And as you got started and in your experience over the last couple of years, what are your top questions that you would coach other CDOs to focus on to be critical to the success of their path. Yeah. First, I just say Kelly and John, it's an honor to be on the call and have a broad participating group out there. Now good fun going through those bios and pictures. I thought it was the biggest. Absolutely it is Andrew your features. I appreciate that setup and you know, and part of my buy I should just share. I've been a 12 now a little over 20 years and had a long career as noted came here in 95 and have been in the global data office function. And really are effectively our first global data officer since about two years ago we just passed our two year anniversary so a long prior career to that that gives me some perspective on you know some of these questions. You know, and what I'll share is going through this to as I start the first response. Now, I would say almost every question needs to be responded to in a way that reflects the specific organization. There's no one set of answers that can be applied across an industry across, you know, all individuals aspiring are in this group. I think these responses need to be, you know, in many ways geared to the specific organization, the leadership team, the business challenges, how their position. So there's a uniqueness in each case. But, you know, if I had to say, you know, what are some of the top questions, it sort of breaks down into the why how and what. I mean, I think that one of the first questions a CDO should be asking to get a new CDO is, you know, why did we create this function? Why was there a need for this function? Why is this function needed given everything else that's going on within the organization? What's the unique mandate of this particular area? And really seek to understand that because there's the potential for, you know, a lot of overlap with legacy groups. And you know, you really want to carve out your own unique territory for a global data function. I think a key secondary question is now how is this function going to create business value? You know, you definitely don't want to be, you know, in this role, even though many do become very governance or regulatory focused or, you know, chasing technology for technology's sake. You know, I think it's critical for a data leader to be really a business champion. And what are the opportunities to better leverage data to create business value competitive differentiation? And you got to constantly be asking yourself, am I doing the activities that really are it creating business value? Or am I doing them for some other reason, some other mandate? And make sure, you know, that there is a close business value because at the end of the day, the group's going to be assessed, I believe, largely on business contribution. And then, you know, on the website, you know, something that's been helpful for us, you know, and again, we're still relatively immature with just two years. But I think one thing we've benefited from is, you know, teams should ask, you know, what communication framework can they create? Whether that's a vision statement or a set of initial projects that are going to be long in nature. You know, what communication framework can you create early on and then constantly reinforce? Because this role takes a lot of reinforcement across the enterprise for folks to get it. And if you have a framework that you can constantly be going back to, even though you might get sick of saying it over and over again, you know, it really helps with the reinforcement to make sure everyone's getting a consistent story as understanding it. And the fact is in large organizations that I think most of us are all part of, you know, reinforcement is critical. Reinforcement of the same message is critical for it to sink in. So, you know, those are just some of the initial questions I think are most important. Great. And I think that to a certain extent they all tie together. And what I've seen you accomplish at Schwab is the way that you've tied together that vision that resonates both graphically and from a statement perspective back to business value and really tying together the purpose of your role, your organization's role, and the imperative around progressing Schwab business. So that's great. But still, because it's a new role and there's not a traditional sort of C-suite all the time, what are those challenges that you have had educating your peers who may not be as data savvy as other folks in the organization? Yeah. I mean, one thing we benefit from, you know, being on the Schwab, our headquarters is here in San Francisco. You know, we benefit by being surrounded by a lot of digital natives, you know, whether that's the Google's, Facebook's, you know, Uber's. So I didn't have a lot of challenge, you know, in making sure our C-suite understands the value of data. In fact, I think there's almost a paranoia that if we don't get focused in this area, you know, there's the chance, you know, we'll get Ubered in some way. And so I think, you know, there's no question there's an understanding of the growing importance of data, a recognition that Schwab hasn't really had discipline around data management. We've always been a data-driven firm. But, you know, Kelly, you and I joke, you know, I would say our history has been more data independence than one of data governance. People were allowed to do whatever they wanted with data, define it however they wanted, throw it into a flash report, send it to the CEO. I mean, they were Johnny on top of their business. And so, you know, we've always been data-driven. But we haven't thought of data as an enterprise asset as something that needs to be curated and cultivated and thought about new businesses that really can be data-enabled and data-driven. So I didn't have a challenge in that respect of, you know, getting their buy-in that this is an important area. I would say the key area that I've been focused on is just what the heck should we do. Yeah, being a data officer almost gives you the opportunity to do almost anything because data goes through everything. And you probably can make a case for a lot of different initiatives. And so the field is wide, you know, what are you going to do? And I think that's where our C-suite needed to be educated early on is, now, what is the unique purview of this group? What makes sense for this group to do? You know, of those activities, what are short-term in nature versus long-term in nature? How do we avoid doing what Rob does very well of chasing the bright, shiny and new? Now, how do we use this function to really address some long-standing issues that, you know, for better or for worse, are going to take some time and effort to make happen? And so that's really been the challenge, you know, getting alignment about what this function is uniquely positioned to do and making sure that there's broad-based agreement on that work plan because, you know, to tell the truth, it's going to take several years to come to fruition. It's not going to be cheap, and they're going to need to support it. Yeah, absolutely. I think that's great. We actually have had a question come in that I'd like to address right now because it's applicable to focus and how you allocate your time. So we have the question, has your organization been mandated to comply with BCBS 239? And what I would add to that is not just BCBS 239, but what other regulatory requirements are driving your activity and is it only regulatory that drives your activity? Yeah, great question, Kelly. So, you know, given we're in financial services, you know, there's clearly it's a highly regulated industry and, you know, so there needs to be a balancing act. You know, the way we approach it is, you know, we don't think it needs to be either or. I mean, what we're trying to do is drive business value and do it in a way that hopefully addresses the regulatory requirements along the way. So, you know, the regulatory requirements be them BCBS or, you know, cybersecurity requests from the Fed or other things that we have going on, that capital stress test, CCAR being a key area of focus, that they don't have to be derailers or distractions. You know, how can we use those efforts to actually advance some of our business objectives as well? So, you know, we definitely have a heavy responsibility and, you know, part of our function in global data is around data management, data governance. We work very closely with other functions across the enterprise, you know, our chief risk officer, you know, partners in finance. So it's very much a collaborative effort on things like BCBS 239. But I would say it's definitely not the sole focus. The focus of our function is around business value. And in the pursuit of business value, by virtue we're in a highly regulated industry, you've got to address the regulatory constraints as well. And so, you know, that's just part of the puzzle. Got it. Okay. I'm going to jump around a little bit. I know that we've put together some of these planned questions, but you've started to touch on the way that you interface with other groups in your organization. So I'd like to continue to pick up that thread a little bit and talk about kind of how Schwab is currently structured. I'm kind of jumping to bullet points or questions four and five in the sense that if you could address the way the scope of the chief data officer role, how you align with the other groups, be it analytics or the CIO, etc. Maybe just talk a little bit about that. What's working and what's been a challenge as well because I think this audience wants to hear, you know, when I'm in this role or now that I am in this role, how can I learn from people who have had, you know, two years more experience than I have? Yeah, Kelly, I just want to confirm you can hear me all right. I'm just having a little computer issue on my side. Can you hear me all right? That's fine. Yep. I won't worry about my computer. So, yeah, we, I would say there's so many folks asking about, you know, how do you structure a chief data officer function? Where should it report now what function should be part of it? And I think there's this quest to see, you know, is there a single model out there that can be applied, you know, to multiple industries, multiple organizations? And I would just say, as I said up front, that you've got to design in a way that's fit for purpose. You know, I don't think there's one model out there. You know, what Schwab does works for Schwab and our unique situation and objectives. It might not work for others. But, you know, the way, you know, we designed it is we really think about data management in Schwab as three groups that are sort of the triumvirate of data at Schwab. So, clearly have the global data function. The second function is essentially our centralized analytic function. We call analytics and business insight, but essentially a chief analytics officer leads that group. And we've done, you know, quite a good job of trying to centralize our analytic activities within that function. And then my third partner is my technology partner. That's essentially my delivery and operations partner. Leads a group that's called global data technology and completely aligned with global data in terms of delivering, you know, capabilities, platforms and operating those, you know, for enterprise purposes. So it's really these three groups. And, you know, some might say, well, that's a data organization that doesn't have analytics. But, you know, the benefit of that is it allows quite a bit of focus. I view it as I have the luxury to focus on things like, you know, data governance, to focus on our platform strategy, to focus on self-service, to focus on master data management, to focus on big data technology. You know, I don't have to worry about my business partners and did they get their daily reporting this morning. You know, that's what my analytics partner needs to worry about. I can focus on, you know, curating our data, you know, making sure our data is accessible and available. We're driving speed to insight and we're meeting our requirements to have a robust data environment. So I report into our chief marketing officer. I think, you know, as given Gartner data, that puts me in the 2% club. I think only 2% of chief data officers report into a CMO. But at Schwab it works great because I'm, you know, in somewhat of a, I refer to it the Switzerland on the business side because our marketing organization has a very broad footprint. It's not just a classic marketing function. It has analytics. It has a few other key areas that support the enterprise. So it keeps me with one foot on the business side. I've got a partner on technology and it works well at Schwab. Excellent. So when we were planning for this call, John, you had some questions around kind of the C in the CDO. And what does that mean? Yeah. Well, I get a lot of questions in our practice. Well, CDO has to report to the CEO. And why is that? And we just heard that, oh, it doesn't have to, right? And I think it comes down to this, what does the chief, the C mean? There is just an analogy that the CDO is the top data job. But there is a difference. There is a difference between someone being over some data management things and then having a level of corporate level accountability. And I was just wondering how could you speak to the differences in your perception? I mean, you have peers that are CDOs and top data jobs as well. And how did your organization kind of reconcile what is the accountability type areas and what are the other aspects like you don't have analytics reporting. How did that decision, how was that arrived at? Yeah. So let me address first the question reporting to the CEO. So, to me, it depends very much on the relationships the individual has within the organization and how the organization functions. For bare force, I've been a 12, 20 years and I have a very broad set of relationships. Our current CEO I have reported to in prior jobs. Our CEO is incredibly approachable, incredibly supportive as the rest of our C suite is around our global data initiatives. So I never feel like I lack sort of that connection when needed. I update our CEO pretty frequently. I'm scheduled to meet with him to do a particularly big data review with him shortly. So he's engaged and, you know, in some organizations it might, you know, if you're a new CDO new to the organization. I mean, I think those situations are the most challenging where you don't have the breadth of relationships and you might need that tie to the CEO to give you leverage in establishing those relationships. But from where I stand, and again, just my situation in the way Schwab operates, which, you know, even though we're the largest publicly traded financial services firm in terms of assets, you know, in many ways we operate still like that small entrepreneurial firm that Chuck started 40 years ago. So it's very easy to access leadership at Schwab. Now, one of our key leadership traits that we try to cultivate is all around collaboration. So people are very approachable. And, you know, again, being with marketing, given particularly our CMO is such a data oriented CMO, such a champion of data and analytics, really viewing that as the future of marketing, as well as the future of the firm, you know, I sort of feel like I get the best of both worlds, you know, an incredibly strong partner, you know, as well as access to the rest of our C suite. Now, one of the ways we coordinate across our C suite is our senior governing group, what we call Global Data Subcommittee, and we meet with them quarterly, includes basically all the revenue heads, you know, across Schwab, the vast majority of our executive committee. So they are very engaged, you know, at that level too. So again, I don't think I suffer from, you know, lack of access or influence given where I report. Okay, what about authorities? The implication of a CDO is authority across the data access across the whole organization is, is that even though you report up to somebody in marketing, which isn't, which is, you know, fairly functionally defined, it seems, to some people, there is an authority there. Could you expand on that a little bit because this is where, you know, we'll get into lively discussions with other folks as to, you know, you can't possibly have the authority, but I'm not hearing it. Can you expand on that? Yeah, and maybe, you know, benefit at Schwab unlike, you know, other organizations talking with other peers and situations they find themselves in. You know, Schwab doesn't suffer from, you know, any organization trying to protect their data. I don't have any, you know, of the Schwab business group saying, you know, this is my data, you know, get out of my backyard. You know, again, maybe it's, you know, by virtue of being based in San Francisco and, you know, understanding the value of bringing together our data, making our data more integrated, improving the quality of our data, improving our understanding of our data. You know, people are eager to see us take on initiatives such as master data management. So, you know, I think I've been empowered, you know, by our executive committee to, you know, to charge off on a set of activities that effectively we designed almost two years ago. We fortunately benefited, I think, from a fairly good initial strategy piece of work up front that put in motion series of, you know, four core work streams that we've stuck true to. And the reinforcement of those, the progress along the way that individuals are able to see, you know, is really, you know, building momentum. So, I don't face a lot of resistance. And, you know, and again, maybe that's just the orientation. I do think we feel, you know, the team here feels very lucky. And I don't know what you do if you're in an organization where you just don't have executive leadership or executive support. That's very challenging. I think you got to address that challenge up front. Now, we have a team that's leaning in and it's more a question of can you just go faster with what you're trying to accomplish. And, you know, our challenge is, you know, how do you balance quick wins versus, you know, foundational improvements that take more time. And I would say I try to make sure I'm not over-rotating to quick wins. I try to do a few things, a little bit of eye candy, some new data, you know, explorations that will provide value to the business. So there's a little bit of that. But, you know, 90% of what we're doing is trying to address some of the foundational issues that have been created over Schwab's 40-year legacy that if we don't do it, no one's going to do it. And so, you got to keep that focus and rallying towards that objective. Thanks. The aspect of nobody has, you know, this is mine's keep away is so, so, so important that that's the key. Back to you, Kelly. I think I'm cool for now. Yeah, no, I think I'd like to, again, pick up a question from the Q&A group because you started down a path of managing, you know, quick wins, eye candy, along with some of these strategic more platform-based initiatives. And the question that came in is what innovations or improvements have been implemented in the data world that have provided monetized value to your organization? So this could be a quick win monetization. This could be where you're headed from a platform perspective to enable monetization. What have you seen from an innovation perspective? Yeah, that's a great question. Now, I struggle a lot on, you know, are we being innovative? Is the secret sauce of a data organization around innovation or is it just around execution? Because, you know, I compare notes with, you know, other CDOs as much as I can. And I find that, you know, this being a very collaborative group because I think we're all trying to figure it out together. And that's, you know, demonstrated by the participation on the call. I mean, we're, I think we're all trying to figure out this new area and charting the course. And, you know, when I step back and I look at what we're working on, you know, again, big data technology, master data management, better usage of our integrated, you know, our enterprise data warehouse, data governance, data management. I mean, those topic areas in themselves aren't that dissimilar from what 80% of other CDOs are chasing. I bet if you have 8 out of 10 CDOs, if they showed their reference architecture for big data technology, they would all look very much the same. So I don't know if the innovation is coming from the initiatives themselves. I think it's going to be coming more from the execution of those initiatives. And what does that enable for your specific business? So maybe I'll give one quick example of something we're working on. You know, that's partially enabled through big data technology, but you know, can be done without it is. You know, Schwab, you know, has a sort of unique data opportunity because of our large retail client base. The fact that we have performance information, you know, for all of our retail clients and it's not self-reported performance. It's actual daily calculated performance, you know, excluding cash flows. Just like you would look at a mutual fund or ETF, we're able to look at our clients and say who's a top performer and who's not a top performer. And what are they doing to drive their performance? And so one of the things we're looking to create is really a peer comparison tool so that if you want to look at any peer group, you define it. What's your benchmark? Who are you trying to aspire to look like and create a benchmark that is much more personal than say what most people use, which is a standard index, like the S&P 500, which isn't necessarily the right index that, you know, someone who's 30 years old or 60 years old should be using. You know, we can create a peer group that, you know, is customized to you. What's the top decile done year to date, past month, past five years? And what should you do to look more like that? So that's sort of an opportunity to better leverage the data we sit on today. It can be advanced more with integration of third-party data. But really, I would say our innovations we're trying to focus on are how do we better utilize first-party data? Now, how do we use the data that Schwab uniquely sits on in a way that's value-add that's going to have a high barrier for someone else to copy? And those are the innovations we're looking at. So, you know, in some cases, those are turning into some of the eye candy. I mentioned some of the shorter-term initiatives that are going to be enabled through these longer-term foundational efforts that we're going to make. You know, an example being a Schwab, you know, we have what we call, you know, 40 separate client masters across the organization. You know, effectively, we don't have a client master because we have 40 examples of them that are often in conflict. We've got to address that through master data management, and that's going to fuel other data innovations similar to the peer comparison I mentioned. Kelly, I don't know if that helps. I think that helps a lot, and I think one of the kind of opportunities but also challenges is this push, pull as far as these innovations go. In the sense that are you as the global data group pushing these innovations, or is the business pulling you along, and how do you manage that? How do you engage with their projects, if you will, or their programs to make sure that there's a data awareness, or are you pushing the data awareness into their strategies? Yeah, that's a great question. You know, when I took on this job, I was hopeful that it would be more pulled and pushed. You know, I was hoping, you know, business leaders would be banging down on my door saying, you know, here are data opportunities we need to pursue, and here's how I want to create value. You know, here's an analogy to something else that we potentially could apply at Schwab, and I got to say, you know, as we probably see in all of our organizations, our business leaders, they're busy. They've got a lot of things they're working on, and they might not have the time to really think through these data opportunities. So it's become a little bit more push than I had anticipated. You know, I would say, you know, I benefit by being able to engage with our business leaders, you know, fairly frequently to share ideas and to brainstorm. And, you know, I've got a couple meetings, you know, with our two largest business units upcoming in the next couple weeks with their leadership teams to sort of explore some new opportunities. So it has been a little bit more push than pull. But to your point about, you know, other projects, I mean, one thing I think we've done a good job at is just creating more data awareness across the firm. And so now what we're, you know, being, you know, invited to do is as large projects are being pursued that have large data components. You know, they're recognizing global data needs to be at the table from the beginning that we need to have strong data governance to enable these projects. We've got to avoid, you know, the errors of the past. How do we leverage, you know, our new big data technology capabilities for a particular project? So we have more projects that are bringing us in very early on because there's an awareness that we need to treat the data right from the beginning. It's just much harder to remediate on the back end. And, you know, so, you know, that's an element of being pulled, you know, versus having to push all the time. And that goes back to I think some of your comments in the beginning where some of the initial priorities of a CDO are is to our gosh, my grammar is terrible to look at that communication framework, because if you've got that communication framework and you are able to engage across a large organization like Schwab, people become aware of what you're doing. And so it doesn't become entirely push and it doesn't become entirely pull. It is, like you said, truly a collaborative environment. So I just want to emphasize that kind of communication piece that you talked about in the beginning and bring it full circle. Yeah. I mean, it's critical in a larger organization because you're competing for mindshare. I mean, there's so much else going on. Now, how does it sink in, you know, what this data functions about, when people should be bringing you in and, you know, keeping the message really simple and then repeat, repeat, repeat. So it's really required to get your foot in the door. And then you got to deal with all the change management challenges, you know, are unique to that specific, you know, issue that you'll be, you know, hopefully presented with. But to just get your foot in the door, you know, the message got to be simple and it's got to be repeated. Absolutely. Yeah, you know, another question came in that I think is actually a quite interesting question. And this is actually a challenge that is occurring in a lot of firms that I'd love your perspective and just your comment on. So the question is, if you're doing the CDO role without the title, do you try to build it in your company? Or are you better off moving to a company that already recognizes that role as a title? Yeah, that's a tough question to tell you the truth. Yeah, I get called to help by a number of folks that are trying to get sort of recognized for what they're doing, you know, and advancing the cause. I mean, I will say, you know, from the Forrester and Gartner folks, I mean, Kelly, you and John, you see this detail. I mean, it was, you know, this is a new role. I mean, it wasn't that long ago, people were just saying, what the heck is this role? Why would I want this role? I mean, it seems in many organizations that question has changed to not, do you need this role? The question is, why wouldn't you have this role? So I think more organizations are feeling the pressure and maybe a little paranoia, depending on their competitive set, that heck of others are doing this. You know, I better get with the program or the bus might leave me behind. So, you know, hopefully that's, you know, there's positive momentum to, you know, identify new CDOs for organizations that don't yet have them. But I would say, God, if you're in an organization where they just, I mean, you might want to ask the question, well, why aren't they identifying a CDO? Is it viewed that that role already exists within an existing role? So it's not an issue that they don't view the importance of data. It's more that they feel that those responsibilities are already covered just with a different title. If it's a situation where there just isn't senior level appreciation for the importance of data, you know, that's a different challenge. I mean, you know, that can be an uphill battle for a very long time because if you're not able to get resources, at least, you know, the way Schwab works, if you're not able to get funding, you're not going to make any progress with their project priorities. You can only go out with the tin cup so far. You know, you're going to need money to make this happen. I mean, this is fundamental change and it's really not a project. I mean, it really is a mindset. If the organization just doesn't have that mindset, I'd say you've got to think twice about, is it ever going to get there? Yeah, absolutely. I think that's, Ann, I'd like to just expand on that a little bit. One of the questions that we had planned for is, so what sort of support structures do need to exist within a company in order to support the role of a CDO? So one of the things that you mentioned is awareness. So data awareness and the importance of data. Are there organizational support structures? Are there other sorts of support structures that you think that the company needs to step up to in order to make this role successful? Yeah, I think that is unique to each organization. You know, so what are the gaps? Do you have a PMO structure or not? How effective is that? I mean, when I think about that question for Schwab, what's most critical, and we've talked about these areas. You know, first is senior level engagement, empowerment, belief. You've got to have that C-suite support, I believe. I mean, to me, that just clears the streets. And then secondly, you need funding. Now, when I was asked to take on this role, I was in a very different role at Schwab. I was leading our branch network across the country, 300 plus retail branches, very large organization. I was asked to step into this role. And, you know, my first question was, well, you know, sounds great, but are you going to fund it? And, you know, two years ago, you know, wasn't necessarily the best of, you know, financial climate for Schwab, a lot of competition for resources. And, you know, the first three months were really a test of, you know, is this going to get funded? Are we serious about it? And, you know, fortunately, it's been well supported. Now, the CFO, who's a strong supporter of this area and our CEO and others, you know, stood behind what they committed to and the funding has now progressed from where we were initially to where we are today. So you've got to have executive level support. If you have executive level support and, you know, with that comes funding support. You know, I think all the other support groups that you need, you know, whether that's technology, legal compliance, you know, whatever it might be, you know, will follow. The funding's really just kind of putting the money where the mouth is sort of thing and walking the talk. And I do think that that is a critical component because we've seen organizations that talk about it. You know, yes, data is an asset. We need to better protect our data. We need to understand our data. It's critical to progressing our understanding of our customers, et cetera. But then when the funding cycle comes around, it is like walking around with a tin cup. And I do think that sometimes there is that fundamental disconnect that is you're able to connect sometimes and progress. But if there isn't a desire to have that understanding, like you said, sometimes it can just be pushing a boulder uphill. Each organization's got to decide, you know, how do you, if you don't have that senior level of engagement or, you know, maybe engagement but not alignment. Now, how do you get it? You know, I mentioned when we first kicked off, you know, creating this function, we actually, you know, worked with a consulting group that has a very, you know, strong relationship with Schwab. And, you know, we didn't want to recreate the wheel, so we wanted to really take advantage of best practices out there and really understand what was the right approach for Schwab. And I say I went out to our executive committee members and I didn't, you know, suggest to anyone they had to participate. I asked who wanted to participate. And fortunately, I had 80% of our executive committee that said I wanted to be part of that vision setting process. And so they were involved from the beginning and helping chart the path. And I think that has helped quite a bit because then when I go for funding, you know, and we're in the third year now if some of those activities are approaching the third year. They know why we're doing it. And, you know, we're part of creating that roadmap. So, but, you know, this area can only get so far on existing what we would call fundamental operating expense. You've got to be investing project money and investment for the future. I mean, these changes don't happen without investments in technology and process and in people. So, and it doesn't come cheap. Yeah, that's right. Well, we have had another question that not sure if this is considered confidential information, but because we've brought it up two or three times. I think we've kind of begged the question, what is the simple message that you repeat again and again across Schwab? So, can you share that with the audience? I think it's I think it'd be great for them to hear it. Yeah. Kelly, it's fine. You know, we're trying to figure out how to take that to the next version. So, we're kind of doing some enhancement of that. But it was a little bit in the intro. I mean, we do talk about, you know, global data is, you know, our vision is to drive competitive advantage through data. Now, there's a lot of functions across the firm that are trying to do that as well. So, what's our unique contribution to that vision? And we really say there's three things that we're trying to do. We are trying to make data more accessible and available. I mean, getting data at Schwab is, you know, too difficult. I've seen it for 20 years. We joke it's tribal knowledge. It's, you know, there's no data directory. There's no data owners. I mean, initially, that's what, you know, what I came into. Yeah. So, access and availability is job one. Second is, you know, we are all about speed to insight. I mean, data on its own, we all know, you know, provides no value unless it's driving insight. And, you know, unfortunately at Schwab, when I, you know, our history is, you know, a lot of ETL processing, you know, pulling data from all around the organization to get, bring it together for analytics rather than bringing our analytics to the data. And that's because of the way we organize our data or have organized our data. So, you know, we have initiatives to drive speed to insight and get to really streaming data and streaming insight. And then last but not least is the sound and robust data environment because we recognize we're in a regulated industry. We recognize, you know, almost every regulatory inquiry at the stage asks about data governance. We could be having a capital planning discussion, a cybersecurity discussion, a capital stress test discussion, and the regulators all want to know about data governance. And, you know, so that has to be part of our puzzle. But again, doing it in a way that's delivering business value is the way we try to accomplish it. So again, you know, those are the three legs and, you know, that is driving what we call our core four. We have four foundational investments that we're pursuing and we reinforce those as well. And one of the things that I think has resonated within your organization is that your leveraging data for competitive advantage speaks very well to Schwab's culture. You're within the marketing organization. You're a highly competitive culture. It really does resonate almost viscerally with that organization. And then when you drill down into those three categories of access and availability, speed to insight, and a robust foundation, that creates a way where you're tying in immediately to those organizations that you work with quite closely, like the analytics and business insight, like your IT organization and your data technology organization. So I think that the meaning behind those, I would say kind of four short messages, you know, your overall vision and then the three supporting statements are really meaningful. So it's not just that you've created this, you know, vision statement. It's the meaning behind it that I think has resonated with the rest of the organization. And the way, you know, that we created that, and I think this is replicated, you know, can be replicated in any organization, is you've got to start from your pain points. You know, because everyone in the organization hopefully can align against what the pain points are. And some of the pain points, I think, you know, are probably shared very broadly. I mean, the stats that, you know, most analytic folks spend 70 to 80% of their time finding and organizing data versus doing analytics. I think we've all seen that, and that's a pretty common problem. But there's probably some unique pain points to specific industries. And if you can sort of get those identified and get people nodding their heads around those and then structure your messages or response to those pain points, it's hard for people not to, you know, want to join on board. Rilke, as part of the getting data easier to get to, are you dealing with any of the data integration challenges there at, how is that within your charter? Yes, so definitely, you know, integrating data repositories, you know, getting to master sources. Yes, I mean, you know, we're, you know, we're responsible for, you know, our data management strategy and overseeing the execution of that data management strategy. So that is a platform strategy. That's a data governance strategy. You know, there's many legs to that, but data integration and, you know, confirming authorized sources and then you get into, you know, the metadata for those sources and quality standards for those sources and the structure to govern that, you know, all part of global data. Another question that we've had that is, I think, also, John, up your alley as well, is we've had a question around how do you figure out the value of the data. So to me, there's two aspects of that, Andrew, and I love your perspective on this. One is the core value of the data. My data provides value in X monetization way, and then there's the value that is created by usage of the data. So two different viewpoints. Have you gone down that path? And if so, maybe comment on how you've done it and what the outcome has been. Yeah, maybe this is partly what you're referring to. Maybe not. I mean, I know there's, you know, there's a growing body of wisdom of, you know, should data be on the balance sheet? Is there a way? Exactly. Yep, that's it. How do you want data? You know, we have not gone to that view yet or that stage of maturity or evolution. You know, for us, you know, data, the value of data is in the use of the data. And as you know well, and John know well, I mean, not all data is created equally. So, you know, we, you know, are very focused on understanding our critical data elements, you know, not all data has the same quality needs. No, it's based on, you know, the use of the data. So, you know, we're all about, in some ways, disaggregating our data landscape and really understanding what's most important and then ensuring that the governance that's put in place, you know, is appropriate. You know, given the value we're trying to extract or the use of that data. But, you know, again, you know, we're not having much discussion about, you know, for now, putting data on the balance sheet. Got it. Okay. Another question that's come in that is similar to one of the questions on the slide is, what experience is useful in this role? So, I'd like to get your perspective from two sides. What was your background that enabled you to be successful and why were you tapped for this role? And then if you were to coach others, what experience do you think they would need? Another question asked specifically about things like software development operations or database management. Yep, yep. So, I'm a little weary of answering this question because, you know, with two years in, I don't think we can declare success yet at Schwab. I think we've had a good initial run, but the jury's going to still be out. And so, you know, take it with a grain of salt because I think we're still proving our success. And I also say it's sort of where I kicked off, you know, I don't think there's one profile. There's not one organization structure. There's not one set of capabilities. I mean, it really is about the organization, you know, that you're going to be part of. And what's that data organization intended to do? You know, what are the issues it's trying to address? What's its unique mandate? I think that's going to bias what are the skills that you're going to want in the leader. You know, at Schwab, you know, given we're a highly collaborative culture, I think, you know, what I've benefited from is being part of the business. You know, having come from the business side, you know, I mentioned I ran Schwab's branches. I spent six years running Schwab.com. I did a couple different startups here on the business side, including our first fee-based advised offering. So, you know, I've been the business guy. And I think I also benefit from being an ex-strategy guy. I spent seven years at McKinsey prior to Schwab. And so I come from, you know, that side of being able to take what was a, you know, was a de novo group with, you know, sort of a desire but no clear necessarily vision of what really it should do at Schwab. And now having that clean sheet of paper can be challenging. And so I think I benefited from the strategy side and then the business connection side. You know, in some groups, you know, being the technologist may be important. I think it's important for this leader to be definitely technology aware, to be technology experienced. You know, having six years on Schwab.com and rewriting our client site, four million lines of code, I think gives me a little bit of technology chops. But I am not a coder. I'm not a DBA. And, you know, but I can partner effectively with those folks that are. So, you know, in Schwab's culture, given there's so many different technologies I'm trying to bring to bear, I don't think I could be an expert in all of them. You know, I need to be able to work with folks, you know, with different disciplines, whether they're data modelers or whether they're experts in master data management or in Hadoop technology or whatever it might be. So I think there needs to be that aptitude and collaborative spirit, you know, in the particular leader. So, again, I don't think there's one size fits all, you know, for me at Schwab, you know, having those relationships and the understanding of the business and, you know, ability to hopefully think about what could be innovative uses of data. Having been on the business side, you know, is definitely a nice benefit. Yeah, I think that you can talk specifically about why this is important with credibility to your C-suite peers. You know, you felt the pain, right? For sure. John, are there any other questions that you wanted to raise before we finish up the planned questions here? One more came through and this is a little bit, I think someone has a concern about their data management environment specifically. And it was around streaming intelligence or I would, you know, maybe a really low latency type of things now. You don't have in your area, I recollect, the analytics, et cetera, but are you assisting in that area? Is that something that crosses your radar? Yeah, so we're enabling the platform to be able to ingest data, you know, streaming data as part of our, you know, big data technology or big data initiative. So we're enabling that capability and working very closely with our analytic partners in terms of what use cases are they trying to apply more of a streaming capability to make sure our platforms can support it. So, you know, we're the owners of, you know, our integrated data warehouse. You know, we're the owners of our Hadoop clusters so that, again, you know, moving from a batch environment to more of a streaming environment and understanding what are the use cases you're trying to deliver against. You know, we're sort of sitting at the middle of technology doing it and our analytic partners that are going to use it to make sure it's constructed in the right way. Yeah, that's a really neat way that a couple of things you said, you don't have the analytics, but you're really, really integral to being involved with that. And in addition, what you said earlier about data integration and the fact that you are speaking at an enterprise level and enabling your peers in analytics and NBI, et cetera. Really speaks strongly to the fact that I think, and maybe you could comment on this a bit more, that it's not so much where you report to. It's what your charter is. It's what your authority is. And it's how you can work with your peers there. Yeah, no, I mean, John, I completely agree with that. I've often said, you know, the organizational model, you know, the chart, organizational chart shouldn't really matter if you have the right relationships and you have the right charter. You can work in any structure. And so I think that is most important. I spent a lot of time with my chief analytics partner and also my delivery partner. The three of us meet frequently, communicate daily, and that's critical. And I think what works well on the analytics side is my analytics partner wants to do analytics. I mean, he wants to be out of the data business. I mean, you know, unfortunately, his folks get pulled into data quite a bit, you know, for their own specific use cases or others want them to support their self service. You know, as we all know, we see analytic groups that really aren't doing analytics. They're basically data provisioning for other BI functions. You know, he doesn't want to do that. And, you know, hasn't had the capacity to address the root causes of why that is so cumbersome. And that's really what the data organization is doing is, you know, this idea of making data accessible and available. It's not just for my hardcore, you know, data science users. You know, it's for that casual BI user, you know, as well. And, you know, so the fact that there's almost a clear demarcation of where analytics begins, where data ends, you know, and how our technology group fits into supporting both of us. So, you know, just, you know, there's sort of clear marching orders. And I wouldn't suggest there aren't points at which there might be friendly fire or, you know, questions about should I run with this or should you. There's always going to be those types of examples. But, you know, fortunately we've got the relationships where we just tee it up and say, who's best positioned to go after this? Where's the natural home? And we jointly agree. So, again, relationship building, collaboration, you know, it's what makes it happen. Very good. Thanks. So, along the same lines, the questions come in around what skill set has served you best. And so you've talked about your capability to develop relationships, your capability to work collaboratively. What, if you were to say not necessarily experience, but your innate skill, what would you say has best served you in this role? Yeah, I'm thinking about that one, Kelly. I mean, maybe I would point to, you know, some of the achievements. You had another question about, you know, what are some of the achievements and what are the skills that have enabled those achievements. So, you know, I think you have to have a skill around building a team. You know, I came into this role, as I mentioned, you know, it was me and my assistant at the beginning. You know, I left 2,000 people behind in our branch network and started a Novo function and heck, I've done that before at Schwab and sometimes it feels a little uncomfortable. And now we scale the team of over 20 folks and, you know, being able to figure out the right talent, how you organize it, convince people they should come on board, heavy mix of external talent as well as internal talent. So you've got to be a talent magnet in some ways to, you know, particularly with a new group. Why would I want to take on the risk to join this group? You've got to miss people. And then you've got to be good at, you know, structuring, you know, a game plan and being able to sell that. So, you know, I think that's where the strategic side can help folks is, you know, what is the game plan? What's that roadmap? You know, why should people be making that investment? Why is that important to the business? Why should you get the money and versus someone else? And so, you know, having a little bit of sales skill that is fact-based, I think is critical in all this. And then I think it's just got to be a communicator. You know, saying, as we said before, until you're blue in the face, you might be saying the same message, you know, but across the board, I do a lot of speaking with groups. I'll speak with any group. You know, no, invitation gets turned down to spread the message of global data. And, you know, so, again, being a communicator, being an effective salesperson, and being that talent magnet, I mean, I think those are some of the skills that are important, particularly if you're a new group. That is really great advice. Real quick, I popped up here, somehow we've scored an echo here somehow. Someone just sent in something on the chat, and that was data standards and policies. Real quick, are you setting them and give us an example? Yes. So when I came into this function, we had no data governance policy. I don't even think we knew what a data governance policy was. You know, there were no defined standards to put against that. So, you know, we actually started some pilot work early on and the tail end of last year actually approved a formal data governance policy that supports standards. And that's the foundation we're using to roll out our operating model for data governance. You know, if I look back last year and Kelly knows as well, you know, taking, you know, having no data governance really activities at the firm. I'm most proud of the fact that we staffed a team, largely of external talent because Schwab didn't have it. So staffing was key. We put in place a tool set. So we had no data quality tool. We had no metadata tool. We had no workflow or data, data glossary tools. So three new tools that were added enterprise wide capabilities. And last but not least was getting approval of our data governance policy, you know, our standards and really what we call our operating model. So that was all part of the first year of data governance and, you know, now we're, you know, aggressively operationalizing that. So yes, that's been part of our part of our chart. Awesome. Awesome. Back to you, Kim. Great. Okay. Last question from the audience and then we'll wrap up with our lessons learned because that's always a good one. So any comments on data lakes, aka data swamp and any lessons learned around the direction of and use of big data? Yeah. I mean, I wouldn't want to say I'm an authority on big data. I mean, we're still, I'd say, advancing our maturity on big data. I mean, Schwab's had a couple of pilot efforts now for a couple of years that were fit for purpose clusters that were spun up. You know, where we are right now is we're, you know, creating what we call a big data hub, part of our big data environment. We try to avoid using the lake or swamp, you know, terms. Yeah. And it's all about creating one, you know, one environment, a multi-tenant environment. So that really can be, you know, where we can support multiple use cases, one point of ingestion for all data at 12, you know, that then gets published out to other potential repositories as needed. So we're in the construction mode of our big data environment. We've got some early use cases that we want to deploy that against. So we're very focused. We're not just building the technology. We know where we want to use it. And we've got partners that are, you know, chomping at the bit to get started. And yeah, I definitely think there's a role for big data technology. I mean, no question. Now, like any technology, you've got to be careful with how you deploy it. Now, just putting it in place without clarity of how you want to use it is probably a recipe for problems. And so that's why we've been very conscious of being thoughtful about our use cases, making sure the environment we're creating is appropriate for not just those use cases, but, you know, our vision for where we're trying to go longer term. And, you know, I think it's hard to imagine, you know, a data organization three to five years down the road with not a pretty strong, you know, strong emphasis on what I call the suite of big data technologies. It's not just to do, but it's everything that hangs off of the ecosystem of big data technology. And, you know, I often say, you know, internally everyone thinks we created global data because of the growth of data. And, you know, we've all seen and Internet of Things. I mean, in many ways, you know, our organizations have been enabled not just by just the growth of data. It's the technology that's enabling us to capture and, you know, analyze that data. And so you got to figure out a way to use it, but don't go in and do it just because, you know, everyone else is doing it. You got to understand why you're using it in your organization and drive towards those use cases. Yeah, absolutely. Would that tie into your final comments around two or three lessons learned? Yeah, lesson. Yeah, I mean, in some ways, you know, tying back to some of the comments at the beginning, I think the approach and structure that people use, you know, needs to be, you know, the catchphrase fit for purpose. It's got to be designed for your organization, your objectives. So, you know, don't just take a model that you see is working somewhere else and assume it's going to work for you. You know, be very thoughtful and make it fit for purpose. That would be one. Second, you know, back to my comment that you can almost justify doing anything because you're a data leader. You know, you got to learn to say no. I had an example of that this morning, which is a longer discussion, but, you know, a group that could have become part of global data. And it really wasn't the perfect fit and finding an appropriate way to say no. I mean, in a lot of cases, you want to keep on the responsibilities and be able to show more value, but those can be distractions. So, you know, just demand data to create a lot of opportunities, be selective. And then the last thing we emphasized is develop a story that can stand a test of time. You know, that can be that evergreen story. If you're constantly changing your story, people are going to get lost. And so, you know, try to be broad. Maybe it's not, you know, too differentiated, but, you know, it's going to come through in the execution. And again, tie that story back to your pain points because people feel the data pain points and they want someone to fix them. Fantastic. All right, Andrew, this has been such a pleasure. Thank you so much. Back to you, Shannon. Thank you, Kelly. And John for leading another great webinar. And, Andrew, thank you so much for joining us for this great discussion. We just love it. And as always, thanks to our attendees for being so engaged in everything we do and for asking such great questions. We really just love the engagement there. As Kelly just switched the screen, the next webinar in the series is October 6th on data governance and enterprise information management. Take the scary stuff out of your program. I've been waiting all year to do that. Thank you again to everybody. And I just reminder, I'll get the follow-up email out within two business days with links to the slides, the recording, and all that good stuff. So I hope everyone has a great day. And thank you. Thank you. Bye-bye.