ENGAGE18: Data Governance as a First Step to Transformation

Paul McInnis recaps his ENGAGE18 panel discussion on data management as an agent of change

Paul McInnis, Business Manager

“If an employee took a sledgehammer to their desk, you wouldn’t sit around and watch, would you?” This was a question posed by one of the ENGAGE18 panelists participating in the panel, “How Data Can Help Transform the Business”. The answer, quite obviously, is that no company would ever treat an asset like that. The point—as the panelist articulated—is that this is effectively how organizations are treating their data when they don’t promote governance or controls that instill data quality.

The discussion during the panel certainly touched upon how data management can fuel the business—from accelerating speed to market to creating back-office efficiencies or enabling new business insights. But the conversation largely focused on best practices to instill data governance, as this represents one of the greatest challenges for organizations undergoing change. The problem, which goes back to the question about the sledgehammer, is that while IT and performance measurement functions may recognize the value of robust data management, the rest of the organization often needs convincing.

This is changing, however. Every two years, Cutter Associates conducts a benchmarking survey of investment managers. Cutter’s most recent research showed that 78% of respondents believe their organization now views data as a strategic asset. In their 2011 research, not a single respondent thought that data served as a strategic asset or could offer any kind of competitive advantage. But while asset managers largely appreciate the value of their data today, the ROI still very much depends on how well they can govern their data to provide guardrails for the larger enterprise.

As we’ve discussed many times before, data—or more specifically, quality data—often provides the foundation for back-office transformations. Once a robust data management solution is in place that can deliver timely, fit-for-purpose data across the enterprise, organizations can then build out performance functions or leverage business intelligence tools, predictive analytics, or specialized reporting capabilities. But as data flows throughout the organization, it only becomes that much more critical that explicit protocols are being followed to avoid any degradation of data quality.

There are several significant challenges when it comes to both implementing and maintaining governance. And while the panel highlighted several considerations to affect a governance strategy, three principles in particular stood out, all of which are related:

Focus on the Enterprise

As one of the panelists noted, prior to their recent transformation, the organization never focused on the entire ecosystem or really understood precisely how the data was being used by other parts of the business. Moreover, he noted that it wasn’t that users necessarily needed new data, they just needed existing data to be useful. So by creating standards, defining the data and identifying the key processes applied across the enterprise, governance on its own can play a significant role in creating efficiencies and more functionality.

Eliminate Barriers

One of the factors driving organizational change is the need for more synchronization between functions. The same way agile development models in technology create cross-functional teams to instill efficiency and better coordination, investment organizations today are often seeking to break down the traditional walls that separate IT teams from business users. This is also why legacy system replacements are often accompanied by larger scale organizational transformations. Another panelist noted that their organization went so far as to co-locate their product teams across various business, IT and QA disciplines to engender collaboration and create an ongoing level of oversight.


All of this speaks to the need for communication. As one panelist described, the word “governance,” on its own often puts users in a defensive pose. But by creating a dialogue, providing transparency around the objectives and process, and re-positioning it as a call for institutionalized best practices, stakeholders will be more inclined to become part of the solution.

“If transformation is being driven by IT, you’re not going to get full ownership,” noted another panelist. “It must be an enabler; IT can’t drive the business or even define the problem, which is why there has to be an ongoing conversation.”

Of course, other factors are also in play. For instance, it’s typically a nonstarter if executives don’t provide top-down sponsorship. Equally important, if the data function is unable to meet the cadence required by the front office, there’s little that can stop portfolio managers, outside of a formal governance framework, from finding their own solutions.

But the reason so many organizations are finally recognizing the value of their data and taking steps through governance to improve data quality is because the need to effectively manage this information is only becoming more pronounced. Securities and instrument types are increasing in complexity. Industries, such as insurance, have also seen a division occur between those that utilize data to manage risk versus those that can’t. And as unstructured data becomes more prevalent, those who do not have a governance structure in place will be ill-equipped to benefit from these opportunities. With all of these forces illuminating the value of data, the times of allowing employees to take a sledgehammer to their data are in the past.

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