Pragmatic Data Transformation: Addressing Your Data Needs Without Disrupting Your Business

October 17, 2019
As data use cases increase, the need to service data in an efficient, scalable, and flexible way will only escalate.

Asset managers and financial institutions say data management is one of their top three most pressing challenges. Meanwhile, 66 percent of asset managers view data management as the area of their business that most calls for total disruption.1 But there are as many “solutions” out there as problems to solve. Solutions are available to facilitate investment decisions, open insights through analytics, manage risk and regulatory compliance, provide oversight of vendors, measure performance — the sky is the limit. Well, actually, data is the limit. Specifically access to high quality, well-organized, ready-to-consume data.

For asset managers, looking at a “total disruption” and overhaul of their data ecosystem is daunting. It’s often said that data should be treated as an asset — you hear it all the time — but revamping an operating model can be capital and headcount intensive. Rather than taking on this scope, some asset managers are turning to asset servicers for data solutions. This makes sense: assets servicers have domain expertise about what the data means, they typically originate the data, and know how to surface the data that matters. This deep understanding of the data, as well as their clients’ business model, puts asset servicers in a good position to develop trustworthy data solutions that can help. It’s no wonder that data related capabilities and services are now as much a part of the buying decision and commercial relationship as traditional core services such as custody and fund servicing.

With all of that said, there’s no silver bullet that can solve a large-scale data restructuring. The key to unlocking the power of data lies in what we call pragmatic transformation—meaningful, incremental, iterative adjustments that build to a holistic solution.

Here are three ways our clients are addressing data needs without the total disruption of a wholesale overhaul.

Case Study 1:

Rightsize your data footprint

Client A was in the midst of a productivity exercise and wanted to assess if they were receiving reports from their various service providers that could be decommissioned. Our investigation into their request produced clear opportunities for efficiency gains.

Our findings:

  • The client was receiving hundreds of reports each month, a result of years of specific requests across business areas and providers
  • 50% of the reports were customized
  • All of the reports were transmitted via email instead of standard, automated channels
  • Multiple versions of the same report were being sent to different functions across the client
  • 25% of the reports were going to third party service providers, some of whom were no longer responsible for the function that originally required them to have access to the data

Our process:

Through a series of workshops, we worked with Client A to rationalize their reports. We then produced streamlined data inventories focused on: email, FTPs, portals, SWIFT messages, and third-party data feeds in/out.

These projects, more often than not, started with relatively simple questions:

  • Where does data overlap?
  • What reports are customized?
  • Where are different departments getting the same data feeds?
  • Where is the manual intervention required?
  • How much data is going out the door?
  • Are all data recipients valid?

The result?

After data inventories and workshops, our clients are seeing enhanced levels of control, efficiency, and oversight. While the work is ongoing, we see clients making progress in these areas:

  • Decommissioning obsolete reports: cutting cost and driving efficiency
  • Gaining control of their data – confirming data recipients
  • Rightsizing the data footprint for more intuitive decision making, thereby reducing costs
  • Streamlining how data is received
  • Decrease risk by ensuring all flows were going to authorized users

Case Study 2:

Trim the Fat: Streamline your custom reporting

Client B has historically required their service providers to customize all reporting to follow the client’s own proprietary standards. Client B wanted their inbound reports to include internal transaction codes related to cash and share postings to make it easier for their systems to consume inbound data.

Our findings:

Over time, the impact of Client B’s approach was that their providers had hard coded reporting specifically for Client B. Later, when Client B approached their providers about upgrading reporting in support of an internal platform upgrade, they found the providers were not in a position to send the data without rebuilding all the existing data feeds which impacted the timing of the initiative.

This is a theme we see with many clients who want reporting their way which can include data column order, FX currency translations, specific timing rules, and myriad other small custom coding or manual intervention.

Our process:

BBH is working with clients like Client B to resource all the reporting they receive to standardized models and use an advanced translation engine to support any client-specific terminology required in out-bound reporting flows. Using standard data models and configuration tools allows the client to have more flexibility to consume data in a manner that optimizes Client B’s workflow, without modifying the source data and limiting the ability to use data for multiple purposes.

The result?

  • Client B is gaining greater control of report delivery through standardization and is able to calibrate the frequency of reports to its intended workflow
  • Client B sees their data as they like but doesn’t have to pay for each manual upload

Case Study 3:

Clean up your multi-provider mess

Client C was rolling out a new risk management platform but was having trouble getting data into the application.

  • The platform required the client’s full holding portfolio to be uploaded daily to run the risk analysis, but Client C’s portfolio had been allocated to over a dozen different sub-advisors
  • While the sub-advisors were willing and able to provide position holdings data to Client C, Client C found themselves on the receiving end of over a dozen separate position files that needed to be formatted, normalized, and aggregated, at a cost of many hours of manual work, just to prepare the data for upload

Our process:

BBH is working with Client C to introduce Infomediary Data Services as a solution to solve its data aggregation challenges. The Infomediary platform will sit in between the client and their service providers to automatically receive sub-advisor files and transform the data into an aggregated, normalized, and ready-to-use standard data set. As their business evolves, Infomediary makes it easy to plug and play any new service providers into the same infrastructure.

The result?

Client B will recognize:

  • Efficiency and cost savings
  • Ready-to-use data set for analytics and research without preparation or manual intervention
  • Freedom to easily add or subtract a new service provider

Bottom Line

Small steps can yield meaningful results. As data use cases increase, the need to service data in an efficient, scalable, and flexible way will only escalate. From a consolidated supply chain to efficient insight interpretation, and from standardized reporting to strategic decision-making support, the right data servicing partner can equip asset managers with the necessary tools to grow without a complete overhaul.

Next time you hear someone mention that data is an asset, ask yourself whether your operating model and relationship with your service providers supports the comment.

Case studies are for illustrative purposes and may not be representative of the experience of other clients and are no guarantee of future success.

1 Reinventing Operations in Asset Management, Accenture, 2019

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