Introduction
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.
The TDC Pilot Initiative used a unique TA approach that focused on “learning by doing” to help state and county TANF staff members expand their data analytics knowledge and skills. Eight pilot agency teams were selected to participate in the 30-month pilot, which ran from February 2020 ‒July 2022. Each pilot agency team conceived of and conducted a data analytics project, supported by the TDI team through monthly webinars, annual cross-pilot conferences, regular meetings with coaches, and intensive training.
Purpose
U.S. states, tribes, and territories regularly send the administrative data they collect from human services programs to federal agencies to meet compliance requirements. Administrative data, however, can be leveraged beyond reporting to gain a deeper understanding of program operations, participation, and performance.
The learning by doing method developed in the TDC Pilot Initiative and examined in this report may be useful to researchers and staff members in a wide range of public sector agencies looking for a portable approach to support the use of administrative data for learning and program improvement. While TDI focused specifically on the TANF program, the design and delivery of training and TA is relevant for any agency seeking to use its administrative data to answer key questions and improve services. This pilot initiative offers a real-world model for federal agencies, policymakers, foundations, and other funders interested in investing in approaches to improve data analytics capacity among state agencies.
Key Findings and Highlights
The TDC Pilot Initiative demonstrated that learning through training and TA as part of doing a data analytics project can lead to sustained, expanded data use. The eight pilot agency teams were successful in expanding their routine use, integration, and analysis of TANF and employment data beyond the usual reporting requirements.
This report shares the insights gained by the TDI team from the TDC Pilot Initiative. It describes the policy context and origin of the initiative and offers lessons on how to design and implement a sustainable approach to data use. It also highlights insights learned by the TDI team and the pilot agency teams during and after the pilot. Among those insights:
Pilot Design
- Deliberately hardwire sustainability objectives into the training and TA so that teams continue to use the skills, knowledge, and practices they have learned.
- Clearly establish an equity lens from the very beginning and maintain an ongoing focus throughout a project.
- Build efforts to capture and maintain the attention of participants into the TA, so they engage enough in the project to absorb what they have learned.
Pilot Implementation
- It takes more than staff technical skills. Building agency data analytics capacity also requires developing strong communication and collaboration practices across units, such as forming cross-disciplinary teams that meet regularly, creating a shared vocabulary, and leveraging each staff member’s knowledge and expertise.
- Flexibility is important. Any team taking on a data analytics project should be prepared to pivot in response to such things as new information, shifting leadership priorities, and staff turnover.
- Engage all types of learners. Working across teams within an agency requires balancing customization and consistency throughout the project for staff members who have a wide range of skills and competencies. Tactics used by the TDI team to differentiate learning included organizing group discussions by staff role, adding new learning modes, and inviting other experts to offer guidance and instruction.
Methods
The content presented in this report originates from interviews and surveys conducted with staff from the eight participating pilot agencies. This data was gathered during and after the implementation of the TDC Pilot Initiative. In addition, progress reports and notes from discussions within the TDI team and with ACF also served as important qualitative resources.