Private capital data operations are demanding more political science than engineering

Data isn't just an IT issue, it's a business priority. Adam Davis, global data practice lead at Reformis, explains how to make the entire firm see it that way.

Adam Davis

Financial leaders may not say it during interviews with the financial press, but there is a deep concern about the pace of technological change in sectors ranging from consumer banking to wealth management.

More than 70 percent of financial services CEOs say the speed of change in technology concerns them, according to a PwC survey. And for good reason. The consultancy estimated that 22 percent of companies in asset and wealth management were at risk of disruption heading toward 2021. Innovators in the market like Harmonate CEO Kevin Walkup have pointed out that “we’re headed for a period of radical required transparency.”

For those of us working in fund management who see the need for greater investment in data systems, these statistics should feel like an opportunity. It’s time for funds to truly start managing data as an asset.

Uncertainty among execs presents a need for concrete solutions and a strategic plan. Most executives at financial firms already realize that big data is a business imperative, but don’t necessarily know what that means operationally.

That’s where tech-savvy and future-oriented members of the team need to step forward. Once you’re in the boardroom, here are some tips on how to convince the C-suite to begin building a future for your firm’s data.

Define the destination 

Just like architects settle on a blueprint before construction begins, fund managers need to agree on their goals before building the proverbial foundation to optimize data management. So what does a data-mature investment firm look like?

Whereas many firms currently have data stored and managed in different departments, with limited ability to share information across the organization, forward-thinking funds are trying to consolidate data in a central depository where it can be accessed by whoever needs it. Consolidation streamlines information sharing and avoids redundant work cleaning and compiling data.

Most data-mature firms also have a centralized data management team, or data stewards, spread across the organization. Either way, these team members understand the data on a very deep level, allowing them to check for quality and redundancy across departments and troubleshoot or train others should special needs or problems arise.

Once executives can envision the house, they will be more likely to dig the foundation.

Present concrete proposals

Look at your organization for specific places where a data-centered approach can solve problems or create efficiencies. Move the conversation about data from abstractions to actionable items.

Assess examples of where existing systems broke down – clients complaining about delays in reporting or a regulatory hiccup caused by faulty data – and show how more effective data management would fix it.

What tasks are high-value accountants performing that could be automated? What tasks are being performed by multiple departments because data isn’t being shared? What jobs and tasks can machine learning perform better than humans, allowing humans to focus on higher-value work?

Companies will eventually need to take a more holistic inventory of their data requirements. But identifying specific pain points provides a good starting place.

Let the business team lead

It’s a mistake to approach data as an IT issue. It must be a business priority. This means members of the business and operations teams should be making the case for increased investment in data systems.

Bad data management can damage client relationships, mislead your own analysts and cause regulatory compliance headaches. Plus, there’s a tremendous opportunity cost in humans expending too many resources on work, especially rote work, that can be easily automated.

It’s true that the exponential increase in incoming data in the future will entail new costs. But the alternative is unacceptable. If firms don’t start building systems that can digest and disseminate lessons from the increasingly large volume of information available for analysis, they’ll face more than a tech problem. Within a few years, their inaction could cause their entire operations to fail.

Create milestones along the way

For firms just starting their data journey, it could take years to integrate centralized data systems and retrain or hire personnel to run their data operation at an enterprise scale.

So how do you keep up the momentum once everyone buys into the same vision? More specifically, how do you make sure data remains a business priority in the months and years ahead as companies implement plans to harness their data?

It’s important to celebrate milestones along the way to track progress and as a sort of evolving proof of concept. Report back to the board on how much accuracy has improved, how many hours have been saved, and how client satisfaction has gone up.

And let CEOs and COOs use the technology. Let them see how much easier they can realize the goals they manage and govern data properly in easy-to-use interfaces accessible across their organizations.

Executives will need to treat their data as an asset eventually, whether or not they want to do so. They might need convincing to begin earlier rather than when it’s too late. Now is the time for them to see the light.

Adam Davis is global data practice lead at Reformis, a data management consultancy for private funds and allocators