Department of Labor’s New Enterprise Data Strategy

Published: June 22, 2022

Federal Market AnalysisInformation TechnologyDOL

Earlier this year, the Department of Labor (DOL) released a new enterprise data strategy to provide capabilities that strengthen data operations, improve data management, and use data to inform program administration and decision-making.

Released in the spring of this year, the 14-page plan will guide agency data efforts over the next three years.  

During the introduction of the plan, Labor Deputy Secretary Julie Su states, “Data is truly one of the superpowers of the Department of Labor. That superpower allows us to move the needle on critical goals for American workers [in the areas of job quality and equity].”

The purpose of the data strategy is to:

  • Clearly articulate enterprise goals for data and the expected value of improved operations
  • Appropriately prioritize the importance of data in major lines of business including IT, budget, performance management, goal setting, training, and personnel management
  • Align local data management decisions to enterprise goals, methods, and standards
  • Integrate strategic goals for data into existing planning, administration, budget, and management systems

DOL’s Evidence Act Officials are quoted in the report as collectively stating, “Increasingly, our success in accomplishing the department’s mission is dependent on recognizing the essential role data has in understanding the populations we serve, the current and emerging challenges those populations face, and providing an objective basis for efficiently and effectively targeting our resources and efforts to those most in need. Data are central to assessing the state of workers and the workforce, the impacts of Department of Labor programs, and providing transparency into our actions and the impacts that result. This Enterprise Data Strategy brings a more central focus to the need for quality, consistency, and availability of data to inform and influence how DOL carries out its mission.”

The plan goes on to define stakeholders who play a role in improving DOL data including program staff and leadership; external governmental, public and private entities; American workers; DOL’s CIO; DOL’s senior leadership; and DOL’s data governance body.

The strategy uses the commonly accepted FAIR Data Principles (Findable, Accessible, Interoperable, and Reusable) to support the reusability of digital assets. The FAIR principles as defined in DOL’s strategy are as follows:

  • Making data findable
  • Making data accessible
  • Making data interoperable
  • Making data reusable

DOL’s data strategy also lists the following five strategic goals

  1. Data Should be Considered “Open” by Default
  2. Data Should Be Comprehensible  
  3. Data Should Be Fit for Purpose
  4. Data Should Be Readily Available in Consistent and Predictable Ways
  5. Data Should Be a Departmental Strategic Asset

Using these foundational principles and goals, DOL’s data strategy is meant to guide decision-making, project planning, and data governance, and incrementally improve the state of data in the department. 

DOL plans to operationalize the strategy at the agency and department level through:  

  • Organizational and culture change
  • Strengthened governance
  • Developing, recruiting, and maintaining data talent
  • Integrating data as a priority into existing management systems
  • Expanding analytical capabilities to leverage data to inform planning and administration

The strategy concludes with details on several ongoing efforts that illustrate the department’s commitment to making progress towards the principles and goals identified in the strategy. These actions include:

  • First-ever open data Request for Information (RFI) to be released
  • Further develop workforce scorecards and dashboards
  • Combine and improve enforcement data for public consumption
  • Working across stakeholders to modernize the Labor Market Information (LMI) System

Federal contractors may find opportunities to assist DOL and its agencies with implementing the data strategy through products and services that address data governance, collection, management, curation, harmonization, standardization, storage, retrieval, analysis, and security.