Establishing Data Governance, Step Three of the Data and Analytics Center of Excellence Approach
By the Data and Analytics Center of Excellence
The Office of Management and Budget has a demonstrated commitment to data governance across the federal government in The Federal Data Strategy 2020 Action Plan. This commitment to governance is fundamental to the use of data as a strategic asset. The Data and Analytics CoE (DA CoE) leverages industry expertise, and experience establishing data governance organizations at partner agencies to provide recommendations for executing data governance initiatives.
Develop a roadmap: Identifying relevant steps and determining an appropriate time frame for data governance maturity is required by the Evidence Based Policymaking Act and corresponding guidance. The 2020 Action Plan provides a Federal Data Strategy Playbook, which agencies may use to prioritize data governance and develop a roadmap. Included in the playbook are useful checklists, resources, and talking points to get agency-wide buy-in for their roadmap.
Create a resourcing plan: Chief Data Officer (CDO) responsibilities include data governance and lifecycle data management. Implementing the Evidence-Based Policymaking Act will require an empowered CDO with enough resources to manage their agency’s data assets. When considering the operationalization of the data governance, agencies must determine the combination of staffing, structure, and reporting that corresponds best with their resources, organization, and culture. The DA CoE can assist with data governance efforts by bridging technical expertise with agencies’ organizational expertise.
Determine governance approaches: Centralized governance approaches are usually favored by smaller organizations as it is simpler to have a single source of truth for data. Larger organizations have more difficulty with a fully centralized approach, as the same data assets can be interpreted differently across mission areas. Therefore, larger organizations lean toward decentralized approaches, utilizing local data management to create ‘sources of truth’ for data elements within a particular subset of the organization. Having multiple sources of truth with simple and transparent ways to reconcile differences provides the additional flexibility required by larger organizations.
Most data governance approaches utilize some combination of centralized or federated governance and management responsibilities. Agencies should aim for a strategy which provides the fewest possible interpretations for critical data elements, while providing enough robustness to use data elements across mission areas.
Establishing agency-wide data governance provides a baseline for data maturity assessments. The final part of this series will discuss the data maturity model and critical steps toward becoming a mature, data-driven agency.
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