Smarter, Better, Faster: The Potential for Predictive Analytics and Rapid-Cycle Evaluation to Improve Program Development and Outcomes

Jun 19, 2014
Authors
Scott Cody and Andrew Asher
  • Agency departments with planning and oversight responsibilities should encourage program staff to conduct a thorough needs assessment.
  • Federal agencies should invest in in data quality and data linkage, as well as measures to support and promote innovation among agency staff. 

Predictive modeling and rapid-cycle evaluation— both individually and together—hold significant promise to improve programs in an increasingly fast-paced policy and political environment. 

The authors propose that social service agencies take two actions. First, agency departments with planning and oversight responsibilities should encourage the staff of individual programs to conduct a thorough needs assessment. This assessment should identify where predictive analytics and rapid-cycle evaluation can be used to improve service delivery and program management. The assessment should also evaluate whether the benefits of adopting these tools outweigh the costs, resulting in a recommendation of whether and how these tools should be deployed. Second, federal agencies should take broad steps to promote the use of predictive analytics and rapid-cycle evaluation across multiple programs. These steps include investments in data quality and data linkage, as well as measures to support and promote innovation among agency staff.