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Keeping data governance interesting


Data governance – the process by which banks ensure that the data they manage and ultimately include in their financial statements is accurate and trustworthy – has become increasingly critical as financial services institutions face immense regulatory scrutiny to prove the trustworthiness of those financial statements. As the Basel Committee on Banking Supervision and other sources have reported, poor data governance played a significant role in the global financial crisis that began in 2007 as bank Information and Technology (IT) and data systems fell short in managing financial risk.

Data governance isn’t new to banks; it just isn’t sustainable for many as a long-term value proposition. What’s going wrong?

First, data governance efforts tend to be a cyclical phenomenon. They get established based on an urgent need, typically brought up by audit or compliance, but quickly lose steam once that need has been satisfied. Responsibility is shifted to lower level employees who are already juggling demanding schedules.

A typical data governance program involves establishing councils, boards, task forces and working groups to assist with defining, managing the quality of and certifying data the bank originates and reports on. Adding these responsibilities and recurring meetings to everyone’s already busy schedules often pushes data governance into a back seat behind pressing production or operational priorities. Meetings are skipped, progress is often delayed and business value is most definitely not realized as the entire effort fades away.

Breaking this cycle demands a new approach geared towards employee engagement and interest. Meetings and committees need to be replaced with collaboration and “gamification” – using game thinking and mechanicsin this business context to engage users for solutions. For example, implement crowdsourcing methods where employees define, rank and approve data definitions online. Ask them to recommend and score the quality and accuracy of information sources. Let them nominate and rank subject matter experts. Give them an incentive to properly provide and correct issues in applications and reports and define methods for tracking down the source of issues as well.

Finally, highlight those individuals who excel at materially improving the organization’s understanding of its data issues and find creative long-term solutions for any problems discovered.  

Mr. Kalderon is NewVantage Partners’ practice leader for Big Data and Analytics at Boston-based NewVantage Partners. He can be reached at [email protected].