Advanced analytics and AI are increasingly promoted as solutions to public-sector challenges. Experience from applied federal health programs shows that data quality, governance, and readiness still determine what analytic systems can reliably deliver.

Across public-sector health programs, analytic products are often technically sound but underutilized. Experience from implementation and evaluation work highlights how delivery structures, accountability, and timing shape whether data informs action.

Decision support is often equated with dashboards or reports. In practice, effective decision support aligns data, context, and timing to support real operational decisions under policy and resource constraints.

New tools and processes often fail to improve outcomes when workforce readiness is assumed rather than supported. Experience across public-sector health programs shows that workforce enablement is central to sustained program performance.