This toolkit provides individuals and organizations with guidance, drawn from learning and experience, on how to use administrative and other data to inform program improvements. It collects concrete strategies and practitioner-tested tools designed to advance these efforts. These materials were developed in pilot projects with local Temporary Assistance for Needy Families (TANF) agencies as part of the TANF Data Collaborative (TDC).
In 2017, the Administration for Children and Families (ACF) under the U.S. Department of Health and Human Services began the TANF Data Innovation (TDI) project. Its goal was to expand TANF agencies use of TANF administrative and employment data to improve program services and outcomes for families with low incomes. This report focuses on the TANF Data Collaborative (TDC) component of the TDI. TDC provided technical assistance (TA) and learning opportunities to two groups: all TANF agencies serving families on or eligible for TANF, and a select few agencies chosen for the TDC Pilot Initiative.
This brief describes TDI’s efforts to transform federal TANF and employment data into an integrated resource for program management and evidence building. This challenging project required the resolution of multiple technical, legal, and data security issues. Lessons learned may be useful for audiences interested in unlocking the potential of administrative data, including members of federal and state agencies, researchers, and advocates of evidence-informed policymaking.
The Temporary Assistance for Needy Families (TANF) Data Collaborative Pilot Initiative is a component of the TANF Data Innovation project. The 30-month pilot offered technical assistance and training to support cross-disciplinary teams of staff at eight state and county TANF programs in the routine use of TANF and other administrative data to inform policy and practice.
The Temporary Assistance for Needy Families (TANF) Data Collaborative Pilot Initiative is a component of the TANF Data Innovation project. The 30-month pilot offered technical assistance and training to support cross-disciplinary teams of staff at eight state and county TANF programs in the routine use of TANF and other administrative data to inform policy and practice.
The Temporary Assistance for Needy Families (TANF) Data Collaborative Pilot Initiative is a component of the TANF Data Innovation project. The 30-month pilot offered technical assistance and training to support cross-disciplinary teams of staff at eight state and county TANF programs in the routine use of TANF and other administrative data to inform policy and practice.
This brief describes the TANF Data Collaborative (TDC), an innovative approach to increasing data analytics capacity at state Temporary Assistance for Needy Families (TANF) agencies.
This toolkit offers strategies and tools to help agencies build the culture and infrastructure needed to apply data analysis routinely, effectively, and accurately – referred to in this publication as “sustainable data use.” It covers a variety of subjects – from staffing and technology to collaboration and funding – that can impact the longevity of analytics work in the public sector.
The Temporary Assistance for Needy Families (TANF) Data Collaborative Pilot Initiative is a component of the TANF Data Innovation project. The 30-month pilot offered technical assistance and training to support cross-disciplinary teams of staff at eight state and county TANF programs in the routine use of TANF and other administrative data to inform policy and practice.
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.
