4 Steps to Successful Data Governance Programs for Government

Getting started with data governance

Government agencies depend on data for all aspects of operations, from matching constituents with available resources and improving citizen services to streamlining day-to-day functions and capitalizing on funding opportunities. That’s why agencies on the path to data-driven digital transformation are exploring data governance solutions to:

• Discover critical data across siloed systems and agencies
• Understand data meaning, policies, and ownership
• Provide visibility into data quality rules, metrics, and lineage
• Monitor data usage, access, and changes

Unfortunately, when government agencies undertake traditional data governance initiatives, results frequently fall short of expectations. That’s because building data governance from the bottom up is difficult — particularly for agencies with siloed departments, outdated mainframe processes, and multiple incompatible databases.

The results too often are overly complex and focused too heavily on governance policies and enforcement. Government workers are asked to attend governance meetings, define terms, and change the way they work. Yet too often these workers don’t see the connection between data governance and how it makes an impact on meeting their own goals and responsibilities.

Data governance execution becomes bogged down in minutiae. It loses focus.

With no tangible improvement in insights, operations, costs, or constituent services — and no clear return on investment — leadership loses enthusiasm. Leadership may even consider defunding governance efforts, losing out on the benefits altogether.