A modernized public benefits system would better serve program participants, administrators, policy makers, and taxpayers. This paper proposes a set of principles both define the desired future state and outline the values that shape decision making along the way. Practices describe the processes needed to achieve modernization.
Oklahoma Human Services (OKDHS) modernized their service delivery by reducing their real estate footprint, designing trauma-informed and user-friendly spaces, and expanding an embedded worker program to improve accessibility and client experience. Through their "Service First" strategy, OKDHS aims to create more equitable and compassionate interactions, reaching vulnerable populations while addressing high occupancy costs.
This nine-minute video, produced after the completion of the TANF Data Collaborative (TDC) Pilot, features staff members from the California, Colorado, Minnesota, and Virginia TANF agencies reflecting on their challenges, accomplishments, and general experiences during the pilot. In particular, they describe their research questions and discuss building data capacity, integrating datasets, networking with other states, increasing collaboration between state and county agencies, learning new technical skills, and the benefits of being able to draw from diverse skillsets, all within the context of the TDC Pilot.
This toolkit is designed to assist state and local TANF agencies in accessing, linking, and analyzing employment data from unemployment insurance (UI) systems. The toolkit provides practical guidance on using UI wage data for program monitoring, reporting, and evaluation, and it may be valuable for other human services agencies and policymakers interested in improving workforce outcomes. The report highlights four key sections, covering the purpose of the toolkit, challenges in accessing UI wage data, methods for linking data sources, and instructions for preparing data for analysis. Additionally, an accompanying GitHub repository offers open-source code and resources for data processing and analysis. This toolkit serves as a starting point for TANF leaders who want to access and analyze UI wage data and offers the essential building blocks you will need to get started on your data analysis journey.
On May 19, 2023, the Digital Benefits Network published a new, open dataset documenting authentication and identity proofing requirements across online SNAP, WIC, TANF, Medicaid, child care (CCAP) applications, and unemployment insurance applications. This page includes data and observations about authentication and identity proofing steps specifically for online applications that include TANF.
On May 19, 2023, the Digital Benefits Network published a new, open dataset documenting authentication and identity proofing requirements across online SNAP, WIC, TANF, Medicaid, child care (CCAP) applications, and unemployment insurance applications.
This GitHub repository includes resources that users of the UI wage data toolkit may find helpful. It covers a variety of topics, including equity, data security, programming, and data QC tips. It also serves as a place for our team to continue to post information that the TANF Data Collaborative (TDC) pilot sites found useful during our partnerships with them.
Policymakers, program administrators, federal leaders, researchers, and advocates are increasingly focused on using administrative data to build evidence for improving government programs. Achieving this goal requires accessible data sources and the capacity to use them, yet stakeholders have little information about the baseline level of state capacity in these areas. How does one measure concepts such as “effective data use” and “analytic capacity?” This brief reports findings from a pioneering and comprehensive needs assessment that examined the capacity of Temporary Assistance for Needy Families (TANF) programs in 54 U.S. states and territories to analyze data used for program improvement, monitoring, and evidence-building. The needs assessment provides a foundation for technical assistance and continued improvement for the TANF program and may also provide valuable insights and frameworks for other state-administered human services programs.
Government agencies at all levels collect administrative data in the course of their day-to-day operations. While such information has been used to determine effectiveness through program evaluations for many years, program administrators view it increasingly as a valuable resource that can also be used to improve program performance. For example, administrative data from employment and public benefits programs such as Temporary Assistance for Needy Families (TANF) can offer insights into families’ unmet needs and ways to improve services.
Temporary Assistance for Needy Families (TANF) leaders, policymakers, and researchers all recognize the need for TANF agencies to use the data they collect to better understand how well their programs are working and how to improve them, given the impact on the families they serve. It is often difficult, however, for agencies already stretched to capacity to prioritize and execute data use and analytics. State TANF leaders are seeking roadmaps for how to transform their organizations and become data-driven.
This expansive toolkit provides guidance, real world examples, and resources to help TANF and child support programs engage the families they serve in improving service delivery, policy, and program operations.
