Transcript: Data, Transformation, and the Future of Pension Funds

Air Date: May 15, 2023 | 12:00 PM, EDT

Caroline: Good afternoon everyone, and thanks for joining us. I'd like to welcome you to this week's Monday Minute Live Chat hosted by the Canadian Leadership Congress. The topic today is Data Transformation and the Future of Pension Funds. Here to address the topic are Darcie James Maxwell, who is Head of Canadian Operations, Data and Platform Solutions with BNY Mellon. Darcie is also a member of the CIBC Mellon leadership team. We have Tristan Robinson who is Vice President Finance Platform, Capital Markets with OMERS. Welcome Darcie, and Tristan.

Tristan: Thank you.

Caroline: All right. Well, look, I want to learn a little bit about both of your backgrounds with regard to this topic, and how you are addressing it within your organizations or with your clients. I'm going to start with you, Tristan.

Tristan: Thanks so much, Caroline. Really happy to be here, and talk about this subject. I'm a big fan of transformation. I've had the privilege of leading several in my career, and data is something I'm very passionate about. In my current role at OMERS, I lead several platforms, so our trading platform, portfolio servicing platform, and data and performance platforms.

Part of my role is helping to chart out what our strategic roadmap is going to look like to modernize our platforms, and deliver new capabilities to my partners in capital markets, risk and corporate finance. We have a long road ahead as we build that roadmap. In prior roles, I have, as I mentioned, supported various transformation programs, technology-enabled programs, but data was at the heart of what we were trying to accomplish, and solve for. Really happy to engage in this topic.

Caroline: Great, Darcie.

Darcie: Sure. It's actually really a pleasure to be here. Obviously, I've worked with you before Caroline, but Tristan and I even did a transformation project once before at a client. I've been working with clients across Canada, and other regions for more than 20 years on some form of a data initiative. So, looking at how they maximize the use of that data, and then be technology-enabled to be able to distribute that, and really leverage the value-add that it brings.

In my current role as a member of the CIBC Mellon leadership team, and also representing BNY Mellon in the Canadian space is really all about how do we make sure that our clients are taking advantage of the data that we provide as an asset servicing partner. Also, how do they integrate that with the data needs that they have within their organization, so that they can effectively aggregate, distribute, make sure that there's a valid governance process in place to truly take advantage of what their either external clients or internal stakeholders do require.

Caroline: That's great. We can get into a little bit about that process in today's discussion. First though, I want to turn to the term transformation because you might agree, it's become a bit of a buzzword. It's used a lot. I'm wondering, Darcie, if you can give us a definition of transformation through your eyes.

Darcie: Absolutely. I would agree with you that everyone talks, "We're doing some type of a transformation." I equate it to making change. Recognizing that there may be deficiencies in your operating model, your technology processes, or even the talent that you manage. How do you adjust them to be future-proof for where the organization is going? Any bits, and pieces of that will constitute some form of a transformation for an organization. It's very much a large change management process to, how do I look at whatever technology legacy stack that I have, all of those things. Then really define that, and what's the problem I need to solve.

Many of the clients that I engage with start off with a conversation around transformation saying, "My front office is looking for risk models that I can't support," or, "I need to introduce additional instruments that I cannot support." That then starts a conversation that goes into those three key areas, either operational process or technology, and then that becomes the framework for a transformation exercise. I know, Tristan, you look at it from a different perspective than I do, so probably you need to add to that.

Tristan: Well, I think it's fundamentally changing the capabilities that you deliver as an organization. I couldn't agree with you more in the sense that it covers not only your technology. I think that's an element of it, but it's your people, your processes. It's adding new capabilities or enhancing capabilities in an organization. What I've found just in looking at transformations, one of the successes I've had is taking a business architecture lens to the problem. What are our strategic objectives? What capabilities do we want to enable with the work that we're doing? Then help to understand that gap.

That really crystallizes for organizations, where to invest in, and what to develop. Totally agree with you. It's a people, processes, technology problem. It's holistically how do we deliver a specific capability to the organization? That's a bit of where I see firms can really value or develop values by looking at it holistically across their architecture.

Caroline: Darcie, I want to pick up this topic with you again. You talked earlier about the conversations around transformation with your clients, and I'd like to get a sense of what that challenge looks like. We've heard a little bit about how you help people, but how are clients experiencing this challenge?

Darcie: Oh, sure. Like I said, and similar to Tristan's comment, it starts off with a business problem that is usually where a client will reach out. What we're seeing quite commonly is some of the sets that clients are really focused on is, I'll take for example, ESG data, where they have a need to be able to add those particular metrics to their performance attribution, or their risk analysis, or some other integrated reporting. ESG is essentially a large dataset problem. It's looking at multiple data sources, different definitions of those data. The people who may be consuming it may not understand the data sources, how do they actually store it someplace? How do they compute with it?

Then how do they then distribute that out to their stakeholders? That sometimes is one of the triggers that we get. We have a client that says, "I want to maximize my use of ESG data." Other common problems we find is, we hear about quite recently especially is alternatives, or derivative instruments, OTCs, all of those lovely creative things that are coming out and into the market. Well, they also pose either a technology or an operations challenge, and also sometimes a people challenge because you may not have the resources that understand those instruments, what do they look like from evaluation perspective, how do you generate performance or attribution on those things, how do we evaluate?

That may also mean that my legacy accounting technology may not be able to even be able to book a transaction of that particular instrument type. That then generates another problem statement that the client then has that doesn't look at, "If I'm going to make a change to accommodate for this business problem, how do I make sure that I'm looking at their step back?" Then I look at it holistically and say, "Where is the organization going?"

We're going to be going into these instrument categories, these regional categories, investment styles, analytic styles, quantitative analysis, and then start to work with what's the data that that is going to need? Then start to work backwards in terms of the technology needs, processes, or even talent that understand these pieces. That's usually the kickoff that I've been seeing a lot from the clients that we've been engaging with, in terms of how do they start the conversation around transformation.

Caroline: Tristan, what specific business problems were you looking to address through transformation?

Tristan: Each organization that I've worked with that has been on this journey is tackling a different issue. In some cases, it's just a lot of technical debt, and legacy architecture that's been built up over many years of growth, and acquisitions. It's really the driver is of an efficiency play at that point. There's other scenarios where it's really the quality of insights, and analytics that you can build off of your data that's really driving the desire to move to a more data-centric organization, and transform your internal capabilities.

I think there's in all of those different scenarios, be it you're looking to increase your efficiency as an organization, or you're looking to really improve your capabilities say as part of the investment management process, develop new decision support functionalities as an example. Regardless of it I've found out, at least in my experience, data's really at the heart of what needs to get corrected in order to fix that challenge. I think regardless of the industry, and again, I've worked on transformation programs in banking asset management, and now on the asset owner side, there is a common theme about some of the constraints organizations face in terms of their technical debt, and some of the legacy architecture, and data integrations that really restrict organization's ability to develop new capabilities and operate efficiently.

Really not an easy problem to solve for, it does mean fundamentally changing the way you think about data, and managing your data as an organization, and maturing those data management and data governance capabilities as almost a first step. Here at OMERS we see a tremendous opportunity in front of us to modernize our own stack of applications, and our functions. We're excited to start that journey as well.

Darcie: If you don't mind, Caroline, I'm going to add one thing to Tristan's. You said a word that really resonated with me, and reminded me about the point, which is data quality, and the build. In many cases, when clients come to us with these challenges, it starts off with, "Do I need to buy a platform? Do I need to build a platform? Do I need to build a data warehouse?" I think the answers that we would've given 10 years ago, even five years ago, that has really drastically changed.

Clients are looking at the expense pressures, "I got to solve this problem, but I don't have capacity to do a multi-year runway project that's going to unplug every system and come in with a new one." That's not necessarily the way that clients can look at it anymore. I would say even the term of how we will think about transformation has changed over the last couple of years because the approach has to be, how do I get time to market, and how quickly quality, as you mentioned Tristan, and then on top of that really expense reduction. They have to be able to absorb it effectively into the organization. It's just one thing I wanted to add to that.

Caroline: That's a really good point because when we talk about replacing legacy technology, you have to make that decision as to whether to build or buy, outsource. Tristan, how do you make that decision?

Tristan: It's a really interesting question. I think it starts with understanding, and really coming to terms with what your core capabilities are as an organization. What business do you want to be in? What value do you deliver? I think if you're looking at your peers and the service offerings that are out there, you start to really understand that, "Well, maybe a lot of these functions, even though we've been doing something in a particular way historically, maybe this is a commodity function that we can look at delivering that function in a more efficient or alternative way by leveraging as service providers."

It is a bit of an existential question that I think every organization will go through. What's really interesting, particularly in the asset management and asset owner space, is that the operating models have been evolving so rapidly in the last 10, 15 years. While 15 years ago, the standard might be an on-prem solution for many of our applications, operational teams supporting them, we've seen and proven that there are several different models out there that are interesting. We're going to take our time going through those, answering some of those questions here at OMERS, but it is encouraging.

I think, starting with what your core capabilities are, what your competitive advantage is as an organization is the first question. Are we in the business of generating alpha? Absolutely. That's something that we want to continue to invest in, and make sure that we've got those functions operating effectively. Do we want to be in the custody business? No, we've already outsourced that piece.

I think there's lots of other capabilities that we could take a look at in the future, but each organization's going to look at those questions differently. I think as long as you're asking the right questions, understanding what service offerings are out there in the marketplace, and getting the advisory support, and help to see what's been successful at other organizations, then you can start to form a view of what that looks like for your own organization.

Darcie: I think the one thing I would add is, we've been using the word the continuum of services in the last couple of years because what we see is that clients need a hybrid mix. It's either I'm going to a technology play, or I'm going to do a full outsource play, or I do a bit of a mixed bag in terms of the managed services. You look at all the components that I add to Tristan's point, it's going to drive benefit and value-add, and maybe that's the secret sauce that you want to keep as close in-house as possible.

Those things that are commodities, whether it's the overnight batch processing, looking at data integration, those things can be partnered with somebody else who can do it as scale, but you have a fixed cost that you can then protect and manage with that. We're seeing that hybrid approach of partnering in those areas that are truly, "Let somebody else worry about that. I don't want to invest in the skillsets or the overhead or the governance, I just want to manage that process, have somebody be accountable for it, and then I can focus on what is truly value-add."

That's really the question we're seeing that clients need to ask themselves is what actually is the truly value-add activity that I want to be able to retain and manage in as much as possible? I'll give you an example of that, where in some cases we look at performance data, it's a calculation process. The rate of return is fairly consistent regardless of industry. You may have nuances to attribution, the analytics that you want to derive from it, and some of the risk metrics that you might want to do to drive that.

Those pieces or components of performance that you can say, "Have somebody else take care of that, and give me the output so that I can enrich that information based on what my stakeholders want to be able to see." We're seeing that to actually to that level of componentizing different functions to say, "What do I really want to keep, and where do I want to spend all my time and resources?"

Caroline: It sounds really important to take those steps to really make sense or have or organize the data so that it really does provide value and drive solutions. Tristan, on the data side, when we're talking about organizing data, and ensuring that it is valuable for your teams and can be used, how are you making sense of how to order the data that you have?

Tristan: That's a great question. I think and again, I've seen this in a variety of organizations where you've got a legacy architecture, technical debt solutions that have been built on top of each other, data lineage becomes quite a challenge. Understanding your data assets, understanding how those data assets are maintained, are fed, understanding the quality of that data, these are all capabilities in, and of themselves. The way that I look at ensuring your data assets deliver value or can deliver value in the future as you continue to evolve and change is ensuring that you've got a strong data governance framework in place, ensuring that you measure the quality of your data.

If you can't measure it, then you can't fix it. Ensuring that you're very clear on the data lineage, so the hops and jumps data takes in order to get from point A to point B. Again, in a lot of organizations, these are quite complicated processes and workflows. It means really interrogating and researching really legacy processes, and how data's transformed along that path. It starts with maturing your data management, and your data governance capabilities. That's where if you're taking a data first or a data-centric strategy or approach to your transformation programs, that really has to be the beginning of where you start.

Caroline: Darcie, a data-centric operating model, is that what you're driving to?

Darcie: One of my favorite terms, quite frankly. [laughs] I always think of it as it's a mindset shift, and that treating data as an asset, and recognizing that value that it does have to what you do as an organization. Once you have that adjustment, then you really start to think about, "How do I govern it." That's just Tristan's point. Where is it going? Who's using what? How do you make sure that there's not duplications, not being replicated in multiple places? Where do you know it's coming from source? Where is it going from an end target? There's also the cost aspect of it. Many clients are leveraging third parties, say benchmark data, other analytics information, all those have licensing associated with it. You really have to think of all types of data as some type of an asset that needs to have some controls, and before you actually do distribute it. Also, I think the key piece to it is understanding that the stakeholder analysis as to who's using it. We see quite frequently clients are generating data warehouses full of data. Then when they start to see who's actually using it, the people are actually creating their own Excel spreadsheet somewhere else because it's a totally other different data set, and they didn't even know maybe that something's there, and available.

We use a lot of discussions with clients that talk about what's the stakeholder analysis, what's the quality controls that are in place, what does the data catalog look like? Do you even know what data you have available for others to be able to use? Then to distribute that, but again, it really comes down to that mindset that data is an asset and it should be treated as such.

Tristan: Just maybe if I could just add to that, the stakeholder usage is an interesting one as well because there's what you know of your reporting and analytics requirements today, but then there's the future. There's always a greater demand for regulatory reporting changes or deeper insights. It's not always easy to design assets for all of those future use cases. If you take an approach of capturing your data, and understanding your data at a real atomic level, then it at least gives you a better chance at meeting what the future needs of the organization, and those data assets will be.

It's a bit of work to really understand those data requirements, and capture data at that form. I think if an organization's on that path, it'll at least give you a better chance of meeting those future needs that you're not even aware of now.

Caroline: Organizations are also on a path at various stages in terms of their use of the cloud. I wonder where this fits within overall cloud usage. Should it be cloud-enabled or cloud-first in terms of the approach? I'd love to get your thoughts, Darcie.

Darcie: Sure. If you think of data management as a framework, it's been around for a long time. What's different I think of the opportunities that are different is cloud. Cloud provides a couple of different things that the storage capabilities, the cloud computing capabilities that brings a whole new dimension to how you manage data. When an organization's trying to define a data-centric operating model, they want to be able to consider, "Am I going to start off in the cloud on whatever I'm building out new, and leverage those tools natively that are built in the cloud?"

They've got those built in if you look at some of the various providers that are out there, or are they going to be looking at taking their existing processes, and moving it to the cloud to be able to just have from an infrastructure management perspective. It's two different considerations. When we think about data management, really it's about how do you take advantage of unlocking the cloud computing? That can do large and large data sets, and they can also manage unstructured data sets in a much more effective way than your traditional say, oracle relational database or something along those lines.

Caroline: Tristan, did you want to add to that?

Tristan: Yes, absolutely. We're very excited here at OMERS to leverage, just use it, cloud as a cloud, and the service offerings around cloud. We're well underway on our journey here looking at some of the analytic capabilities that have been unlocked by cloud technology, it's an exciting time. Ideally, we'd want partners that can enable our growth in a sustainable way, and I think cloud's a fundamental part of that story.

If a service provider doesn't have the ability to scale, compute or storage because they're not natively designed to leverage what cloud has to offer as a capability, that's obviously going to factor into our decisions. These are massive innovations in our space. Certainly, as you're picking your partners, you want to make sure that they're set up to leverage them.

Caroline: That's really key. What are some of the consistent challenges or pitfalls you're seeing in the process we've been talking about, Darcie?

Darcie: I think the first pitfall is where do you start? I think sometimes organizations struggle with what's the starting point? Where, I think the incorrect way to do it or challenging way to do that is if you start with technology decisions, "I need to buy X," and instead of starting with, "What are my users' needs? What is the business problem that I'm trying to solve?" That allows you to be able to define the technology to support whatever that business challenge is. I put that in the way of saying, there's some clients who'll say, "Well, I need to buy a cloud platform, I need to buy a cloud platform." What are you going to do with the cloud platform? What problem is it going to solve? If you start with, "I have a business problem that says I need to be able to amalgamate ESG data with my risk analytics together, how do I do that?"

Then that actually defines the business problem with the vendor, defines your scope, your use cases that you want to be able to go after, and then you can then decide what technology will enable that to be solved. That's one of the most common challenges that we do see. The second one I do think is that there needs to be some level of planning that goes into a data management initiative. We use a lot of buzzwords in the industry, data-centric, data transformation, data management, data governance, really need to understand how is that going to be executed in your organization?

As you transform, how do you maintain the day-to-day activities? You have to think about those two things as you go along. It's not just a matter of the change happening overnight, it's how do I also slowly, gradually absorb change while maintaining my deliverables to my stakeholders? Some of those are probably the top two that I see as some of the challenges that we encounter with clients.

Caroline: For sure. Tristan, I'd love your thoughts on any factors or considerations you'd like to put out there for people listening today when it comes to implementing a data-centric operating model. We've been talking about that a lot here today.

Tristan: Sure. Thank you. I couldn't agree more with Darcie's context around it really starts with what you're trying to accomplish. What are the outcomes you're trying to achieve? One of the other pieces that I think doesn't get enough attention generally is just the change that any transformation program like this, what it means to the people in your organizations. Going through a transformation program or moving towards a data-centric organization means an entire shift in the way organizations work within each other, how teams interact, the skills that are needed in order to be successful.

Embedding change management practices and really understanding the capabilities that you need your people to bring to the table, I think is extremely important. Change management shouldn't just be an implementation phase activity either. It's not just training and communications on a release, it's really fundamentally changing, and reskilling, and reengineering how teams interact with each other. I think that change management lens to any transformation program, data-centric transformation or otherwise is extremely important.

Darcie: If you don't mind, I'm going to add to that because that is absolutely so correct, Tristan. We have really recommended strongly with our clients to include in any program a work stream, they're actually called the operational readiness. That operational readiness incorporates what's the change to people, processes that needs to be prepared, and not only prepared to go live, but prepared to maintain and operationally run whatever we've done and as we go forward. That has to be a critical component to understand that how are people going to accept this change after it's done?

Are they going to be able to care and feed it, and be able to be comfortable in that new operating model? Definitely, absolutely agree with you on the change management that we've really, really strongly recommended clients have an operational readiness work stream with any transformation program and a particular sign-off process too so that all stakeholder groups are saying, "Yes, I'm operationally ready to adopt this as well."

Caroline: Great. A bigger picture question I'd like to ask is, why are we at this moment of transformation? Where do you see us in a few years down the road? I'm going to ask that of you, Darcie.

Darcie: It's a good question. I think every other week that the answer is going to change actually because I think that we're just really starting to figure out how do we take advantage of some of the technology and tools, whether it be AI, cloud computing, all of these different things that are available. On the other side, I think the investment industry is also changing and evolving in terms of the markets and the processes, things like that. Within those two, we're moving both quickly. I see that we're going to be having the same conversation around transformation in five years from now. The difference will be there's that word, we need to go from one level to the next level in terms of the level of data, the level of analytics. The speed is going to become so much more, where we think of an end of day set of data might be sufficient at the moment.

Then we want to be able to have start of day, "Okay that's good," but you know what? People are going to be looking for that same level of an analytics and drive of information throughout the day. How are we going to get to those things? Faster access to information I think, is going to be the next hurdle once people can at least catch up to what the data needs that are out right now.

Caroline: Tristan.

Tristan: I think we are at a crossroads, particularly from a technology standpoint in terms of the capabilities that cloud, and all the innovations around cloud, and service offerings around cloud are delivering to us. If you look at a traditional on-premise type of shop with lots of technical debt, there's a lot that needs to happen, even just to get to the starting line of any digital transformation, or to move to a data-centric approach. I do think that a lot of these innovations and how service providers are taking them and developing new solutions, leveraging that technology, it's really changing how we operate or can operate.

I do think that's a catalyst. I think from an operational and business context perspective, we will be asking this question every year. The question might change subtly from year to year, but there's always going to be an increase in analytic demands. There's always going to be changing regulatory context. There's always going to be real business changes in terms of growth and M&A, or divestiture, or otherwise. All of those change points or drivers lead to firms taking a look at their business architecture, their operating model and we'll have to start thinking about, "Well, what do I do about this situation? Where do I go from here?"

Caroline: Tristan, if you had one piece of advice for your peers listening today what would it be?

Tristan: I think it's people look at transformation programs as really daunting exercises. I think they take a lot out of you, they can be very costly. It's a significant impact to your teams and your people. I would say, pick your partners and your advisors wisely. I think that's one of the first recommendations. Really do your due diligence. You want to make sure that you're getting the guidance that you can trust.

If I can add another, it's because these transformations tend to be longer-term change programs, having the organizational buy-in at all levels is incredibly important. Making sure that incentives are tied to success and that from the top of the organization to the staff level, everybody understands why we're doing this and what the mission looks like, I think that's probably one of the keys to sustaining momentum on these programs.

Caroline: Darcie, key takeaway.

Darcie: The one thing I would take away is that transformation can be incremental. We think of the objective, then the strategy, and the long-term target can be a long-term or in a longer duration, but the change itself can be done in incremental small stages. We're really trying to actually get our clients to think about that differently, and because to your point, Tristan, we hear the word transformation program, they think ,"Oh my gosh, it's going to be multi-year. I'm going to retire before it's done. It's going to be exhausting."

What we realize now is that one, given the tools, the changes in what our partners are being able to do, whether it's your asset service provider, your technology providers, what they can do to accelerate and move quicker has been much different than when there was a couple of years ago. I also think is we try to break things into what change can I absorb into a three-month period, so that it's we're seeing continual success and be as agile as possible because as you can build success, it builds momentum. It keeps that motivation going as much as possible throughout it. That's really definitely the way that I can while you might want a long-term vision, think about short incremental deliverables.

Tristan: Couldn't agree more.