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Asset Managers Continue to Struggle with Data Management, says Cutter Benchmarking Study

Investment managers increasingly recognize the value of their data, but the majority still struggle to manage it, according to the latest benchmarking study on data management by Cutter Associates.

Over two-thirds of the respondents said they see data as a strategic asset that provides competitive advantages. That compares to 45% of firms in 2013. In 2011, the unanimous answer was “no.”

Yet despite the change in attitude, the study found “most still need to establish data management processes that directly support high-level business goals.”

Slow progress

Less than half of the investment managers that participated have established a formal Enterprise Data Management (EDM) program. Among smaller managers the figure is even lower, with just a third of firms with less than US$100 billion in assets having such a program.

And although most of the study participants are working toward establishing a formal data governance framework, only one third have achieved that goal.

A major part of the problem, says the Cutter research, is the expanding volume and variety of data, “driven by increases in asset complexity, regulatory requirements, and demand for investment information from internal and external clients.” Growing data volumes have also increased the costs of maintaining it, at a time when investment managers are wrestling with internal budgetary pressures.

Get a head start

So how can firms make the leap in their data management capabilities that will enable them to extract greater value from their data, while improving efficiency and reducing costs?

Developing the necessary best practice data management and governance capabilities in-house to efficiently collect, normalize, store and distribute this deluge of data is neither cheap nor easy. But why go it alone?

The alternative is to leverage a professional managed data service. With the right partner, investment managers can reduce the total cost of ownership of their data, as well as significantly improve both data quality and responsiveness, leaving them free to focus on what they do best.

 

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