The Value of Predictive Analytics and Machine Learning to Predict Social Service Milestones

Social services programs are increasingly looking for ways to forecast which participants are likely to reach major milestones so they can tailor services and allocate resources. In recent years, some programs have explored advanced predictive modeling approaches that harness potentially millions of data points and may incorporate machine learning: a variety of algorithms that determine relationships between prediction measures and the outcome. While there is potential for social service programs to use advanced models, MDRC’s Center for Data Insights (CDI) has found that such methods are not always better at making reliable predictions and come with trade-offs. This post outlines CDI’s approach to predictive analytics, using illustrations from two studies: Career Pathways, a workforce training program, and Child First, a home visiting program.