Resources and Toolkits

Video outlining best practices for states to improve their risk assessment and error detection processes, including model design, review sequencing, feature engineering, review process optimization, and quick wins

Resource to explore and compare state-by-state data on eligibility processing, payment accuracy, and policy options

Conversation sharing drivers and targeted interventions to reduce SNAP Payment Error Rates, drawing on six months of hands-on research with Arizona, North Carolina, and Maryland

Common policy missteps states may take in efforts to reduce SNAP payment error rates (PERs), such as adopting change reporting, imposing asset tests, or limiting discretionary exemptions, can have unintended effects of increasing error rates. Instead, states should make informed policy choices, such as adopting simplified reporting, waiving asset tests, allowing discretionary exemptions, and implementing…

Workshop examining how predictive analytics and risk scoring can improve SNAP implementation and evaluation, using Conneticut as a case study.

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.

A free resource that focuses on strategies that states can test immediately to reduce PER and lessen the burden on frontline eligibility workers

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.

Implementation-oriented framework to support states with adapting to community engagement/work requirements. Features overview of “look back” period and four-step compliance flow including: checking for automatic hardship, screening for exemptions, checking for participation, and allowing for requestable hardship.

Outlines cases in which generative AI can be appropriately deployed by grounding use in human-centered problem statements. Highlights practical application such as data extraction, summarization, and entity resolution to reduce caseworker burden while maintaining responsible oversight.

Key questions for states to consider during procurement of new technical systems to ensure proper evaluation of product solutions and their effectiveness.

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.

Blueprint on how work requirement policy impacts the process of SNAP application, determination, and maintained eligibility. Provides human-centered implementation recommendations such as focused support, ease of exemptions, discovery/comprehensive interview to capture compliance.