Michigan’s Office of Child Support (OCS) plays a crucial role in helping to ensure children receive the financial support they need even when their parents are not together.
The OCS wanted to address a key challenge: that as many as one in five child support cases kept getting "stuck" in pre-obligation, the first step in obtaining an obligation to pay child support.
As a result, too many children were waiting to receive support, and the OCS was at risk of not meeting federal child support guidelines for the percentage of open cases for which obligation is established.
Reflecting Michigan’s strategic goal of using analytics to improve child support services and outcomes for families, the OCS decided to test predictive analytics as a tool for understanding—and reversing—that trend.