Resources and Toolkits

Technical resource for modeling SNAP payment errors including code, data, methods, and detailed findings

Paper exploring how uncapped benefit calculations in payment error predictive models can help create space for more “buffer” and create inclusion or exclusion criteria for better targeted reviews and greater predictive power.

An interactive cross-state analysis tool demonstrating how removing the $58 SNAP QC tolerance threshold could increase payment error rates and related state costs.

An interactive dashboard that enables users to explore and monitor key metrics of the Supplemental Nutrition Assistance Program (SNAP) Quality Control (QC) system.

Guidance on state policy chocies that tend to increase SNAP payment error rates include requiring change reporting or monthly reporting, imposing asset tests, and limiting discretionary exemptions. In contrast, states can reduce errors by simplifying reporting requirements, using BBCE, applying exemptions, and using one-month lookbacks to minimize reassessments and ensure coverage for eligible populations.

An interactive dashboard that enables users to explore and monitor key metrics of the Supplemental Nutrition Assistance Program (SNAP) Quality Control (QC) system.

Resource Hub including data visualization tools, modeling tips, and lessons gathered from States to support the work of QC data modeling nationwide.

Workshop to foster collaboration and share modeling practices among state agencies in response to HR1’s new SNAP PER cost share requirements. Gathering encompassed convened a group of nearly 40 research and data analytics staff from across 15 states involved in SNAP QC data modeling.

Guide on how state agencies can develop legible and flexible metrics to assess implementation of new work requirements, outlining how to build, capture, and effectively utilize metrics to monitor impact for operational awareness and decisionmaking.

Repository of resources for state administrators to support the implementation of work requirement policies through overview of implications and recommendations of smart system designs and processes.

Key strategies to improve accuracy and efficiency of SNAP program delivery, including evaluating intervention impacts independently, developing strong proxy metrics, watching for unintended consequences, strategically reviewing most error-prone case elements and actions, leveraging new technology for caseworkers, and improving client communication and outreach.

Outlines four proactive strategies to design resilient and adaptable technical systems including feature flags, modularity, configurability, and phased approaches.