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What It Takes to Operationalize a Data Management Program

As the global financial industry faces lower margins, increasing competition and more regulation, one remedy that can help institutions effectively navigate these challenges is a successful data management program. Yet for many, that in and of itself is a daunting task.

Indeed, nearly half of the industry (43 percent) reported they are still in the process of making their data management programs operational, according to the 2015 Data Management Industry Benchmark conducted by the Enterprise Data Management Council, in partnership with Sapient Global Markets. While many buy-side, sell-side and insurance firms have at least initiated their data management programs (a giant undertaking for many organizations), they are encountering obstacles when taking the next step that can ultimately open the path to growth and revenue.

The most significant hurdle to achieve a fully operational program lies between the “developmental” stage (engagement with key stakeholders) and the “defined” stage (assignment and verification of requirements and responsibilities), what I refer to as “crossing the capability chasm.” Firms across the industry remain in the defined stage or somewhere in between because of the challenges associated with obtaining buy-in from key stakeholders that can establish a long-term program as a central business practice rather than simply a one-time project.

In fact, only 28 percent of data management programs have established sustainable funding. What’s more, just 7 percent of programs are being measured and only 7 percent have achieved harmonization, both of which could be improved by addressing the data management program’s value proposition and necessary collaboration within the various business units of an organization.

In The State of Data Management Programs, Industry Challenged to Make Programs Operational—I layout five key considerations for firms looking to cross the capability chasm and move toward a fully integrated and operational data management program. The five key considerations are based on the Benchmark findings, which surveyed buy-side, sell-side and insurance participants, and include:

  • Securing ongoing program funding
  • Measuring and communicating the program’s value
  • Establishing a clear methodology for data governance
  • Empowering the right people
  • Collaborating with IT, operations and business teams

Download the full-length paper for a detailed breakdown of these factors that can help guide firms as they build out an efficient and effective data management program that translates into new products, improved operations, innovative services, better customer experiences and ultimately greater growth and revenue.

Gavin Kaimowitz – Global Data Practice Lead
Gavin Kaimowitz is Sapient Global Markets’ Global Data Practice Lead across the capital and commodity sectors. Gavin is responsible for the collation and generation of best practices, thought leadership and strategy. He has a proven track record in the reference and market data domain of solution design, business case definition, strategic roadmap design and in building data management products.