Data Transforms Workforce Policy
Local and national leaders shared examples of how they are using data to improve workforce development during a national conference last week at Rutgers University in New Jersey.
The multi-day conference, sponsored by the Atlanta and Kansas City Federal Reserve Banks and the John J. Heldrich Center for Workforce Development at Rutgers, included two panels focused on data, research and evaluation.
A session titled “Intelligent Workforce Development Systems” that I moderated featured:
David Berman, New York City Center for Economic Opportunity (CEO), who discussed how his organization uses data to build all types of evidence about service effectiveness, ranging from performance outcomes to evaluations with randomized control trials. CEO’s dashboard tools allow its front-line staff to view the data they report in formats that help them better assist their clients.
Amanda Cage, Chicago Cook Workforce Partnership, who explained how Chicago is setting up an integrated data system to simplify data collection and reporting across workforce programs. Key lessons from developing the system include the need for: state and local champions of the project, common performance metrics for programs and funders, and a shared vision for the data system that takes into account the needs of front-line staff.
William Mabe, Heldrich Center, who suggested ways the workforce system can improve its use of data, including the refinement of analytic models that predict individuals’ service needs and more use of geospatial data. The Newark Workforce Investment Board looked at mapping of geographic data on occupational training participants and unemployment rates to guide its customer outreach strategies.
Another panel moderated by Demetra Nightingale, chief evaluation officer at the U.S. Department of Labor (DOL), explored ways that data can help policymakers and students make good decisions. Demetra noted a DOL clearinghouse on labor research and said the agency is working on multiple studies to determine how to effectively present data so students and workers choose high-quality training that leads to employment.