Are You Ready to Move on From Your Legacy Portfolio Management System?

Eagle’s Darcie James-Maxwell looks back on her experience both using and then helping clients to replace investment systems, as she discusses how legacy-system replacement can be a catalyst for efficiency and growth in our latest Q&A.

Q. It’s been roughly a year since you were named the Head of Eagle’s Operations in Canada. What was your initial focus when you transitioned into this role and what have been some of the biggest challenges you’ve encountered?

That’s a good question. When I transitioned from overseeing the relationship management team in Canada to overall accountability of our Canadian business, my number one focus has remained our clients. I have spent the last year meeting with clients to ensure that we have a clear understanding of their business goals and objectives—after all, it’s paramount that Eagle continues to meet their business requirements. I also spent a fair amount of time looking at the wider landscape in Canada, where the market is on the verge of significant change. There are a number of legacy platforms that appear to be nearing end of life, which is causing several clients to think about their multi-year roadmaps.

Q. You began your career as a performance analyst and as a user of the kind of solutions that Eagle and its peers provide. You also spent a significant amount of time at a competitor before coming to Eagle in 2005. Given this perspective, how have you seen the industry and marketplace evolve?

I began my career as a Performance Analyst with Frank Russell Canada and then moved to the technology side and worked at what used to be called Financial Models Company (and their flagship system “Pacer”), which was acquired and rolled into SS&C Technologies. This is actually where a number of us at Eagle Canada started their career, including Mal [Cullen], Eagle’s CEO.

In terms of the evolution, 20 years ago I was working through the challenges most firms faced dealing with inherent poor data quality and unwieldy processes in attempting to ensure that we had accurate rates of returns for analysis. Today, data quality is still at the core of supporting investment decisions and one of the primary reasons clients choose Eagle. Technology has also advanced significantly over the years to support data management processes and governance programs.

Before joining Eagle, I was part of the team that implemented and supported what are considered today to be legacy platforms. I can very clearly recall the time and resources required to decompose something like an incorrect rate of return, where the root cause was often due to the upstream inputs or data sources. Something as basic as figuring out if someone forgot to apply the month end price override on  their transaction entry could result in hours of work. It was an excruciating process because it could derail your entire morning or even your day as you tried to diagnose the issue. I find it kind of remarkable that analysts still encounter these types of challenges here in 2017. It speaks to the need for organizations to take manual processes out of the equation.

As far as how the marketplace has evolved, it’s reflective of what is happening across all industries: Automation is taking over and creating new efficiencies that were largely unheard of ten years ago. Data is key to automation. It requires pristine, validated data with access to transparency that traces data lineage from source to consumption. This is precisely why data centricity is so critical, whether it’s supporting an accounting book of record, performance measurement solutions, or simply supporting data governance in this era of heightened regulatory oversight. All strategies should start by answering the question: How do we ensure timely and accurate data for consumption across the organization?

Q. One of the biggest industry developments facing back- and middle-office professionals in Canada is the ongoing transition away from legacy systems that have been in place for two or even three decades. What kind of impact will this have in the near term?

Well, for long-tenured professionals who have been utilizing the same system their entire career this probably seems somewhat overwhelming. That being said, it presents a tremendous opportunity to upgrade platforms, improve processes and adopt far-more efficient operational workflows without processes running in batch. Think about it: What proportion of operational workflows today consists of data investigation after all the batch files are complete? When users can capture data discrepancies earlier in the process, not only does it save time and resources, but it allows the analysts to focus exclusively on the errors. And looking beyond the efficiencies, the biggest benefit of exception-based processing is that it allows organizations to significantly reduce their operational risk.

So to address the question more directly, the near-term impact of unwinding a legacy platform is that organizations still dependent on the system will have to gain a better understanding of what manual or custom solutions they have developed over the years. The medium- and long-term impact, though, is that these organizations will become more efficient, less exposed to operational risk, and better prepared for a landscape in which their data strategy will either facilitate or bottleneck growth.

Q. So what would be your advice for clients that have relied on legacy portfolio management systems for the past 30 years?

I’m going to sound like a broken record, but it really is all about the data. First and foremost, organizations shouldn’t begin a legacy-system replacement initiative until they’ve developed a comprehensive data strategy. It can be one of most the overlooked components of back-office transformation projects, but it’s critically important.

A key pillar within the data strategy should be the Investment Book of Record (IBOR). This has become a prerequisite to meet the ever-increasing demands for data, whether it’s to support investment decisions, operations, compliance needs, client reporting or anything else. Moreover, this ever-expanding set of use cases for data also speaks to the need for flexibility. When data sets had one or two downstream users, you could get away with hierarchical class schemes and attribute-based structures—today, your ability to slice and dice the data to meet all the disparate organizational needs depends on whether you can define your data breakdowns based on specific demands and whether business users can easily make changes as needed.

Developing a data strategy is not unlike a home renovation in that once you open the up walls you’ll discover all sorts of new problems you weren’t aware of. Consider the time and resources most organizations have put into building and managing custom databases or spreadsheets. We’ll often be called on to solve a discrete data management issue, but in the process, we’ll discover a gnarled tangle of inter-dependencies that are resource-intensive, degrade data quality and expose the organization to significant operational risks.

We have helped clients execute a number of legacy system conversions in recent years. In the process, we’ve found that it’s not uncommon for us to discover that the extract files that go into end products like client statements, monthly fact sheets and other ad hoc needs are being pulled directly from the portfolio management system database. In these cases we have to effectively collapse and rebuild these systems around a well-defined data management solution, but these are the types of issues that you’ll find when you “open up the walls.”

Q. So how does all of this come together for asset managers and investment firms looking to unwind their legacy systems?

Well, it all goes back to the point I made in the beginning about data centricity. Accounting is effectively an operational process that supports a firm’s books of record, regulatory reporting, an IBOR, a performance book of record (or PBOR) and information delivery. All of these functions run on data inputs, which is why we traditionally think of Accounting as the end state—not the first step—in moving away from a legacy accounting platform.

At Eagle, when we first started initiating conversions for our Canadian clients, we started with data management and performance deployments and then added accounting processing. This approach allows clients to leverage the investments they’ve already made in their systems to achieve a fully integrated operational workflow faster. Other Canadian clients have worked with Eagle for data-centric deployments that have allowed them to graduate from legacy processes altogether. This perspective is crucial in unwinding legacy systems because we understand what’s behind the walls. We’re also well-versed around the complexities of managing data from other systems, such as dealing with the nuances of local Canadian systems, and we know where to seek out all of the inter-dependencies that may not be obvious to those less familiar with the technology or the Canadian market.

It’s truly the end of an era for some and that change may appear daunting—but the key is ensuring you have the right partner to guide you through the process.

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