Association for Public Policy Analysis & Management

As human service agencies strive to provide evidence for decision-making around policies, programs, and practices, many face significant barriers in data access and use. Two initiatives, the Family Self-Sufficiency Data Center (FSSDC) and the TANF Data Innovation (TDI) project, both funded by the U.S. Department of Health and Human Services’ Administration for Children and Families, Office of Planning, Research and Evaluation, aim to address these barriers and improve data usage at the state agency level.

Since 2013, the FSSDC has supported states’ efforts to better use data, both internally and in partnership with external researchers. The goal has been to increase the amount and quality of data available to understand family self-sufficiency. Over the past 5 years, the FSSDC has achieved this mission through data support and technical assistance; outreach and collaboration; and collaborative research projects. The FSSDC works directly with agencies and researchers— one-on-one and in cohorts that facilitate peer learning—to assess data quality, restructure data, examine caseload dynamics, and explore policy questions of interest. The FSSDC also generates publicly-available resources, including data models and code that can be used on data at the state level, and has worked with states to implement these tools.

A needs assessment conducted in 2014 provided the initial foundation for engagement with states. Findings revealed that agencies’ data use is determined not only by what they hope to know but, perhaps more importantly, by their ability to access and analyze the necessary data. Common challenges include legal restrictions to data sharing, staff and system capacities, data quality concerns, and barriers to accessing longitudinal and linked data needed to address important questions. Subsequent work with states has confirmed the realities of these challenges shared by many states, and also shed light on divergent experiences across states. States are differently situated on many dimensions of data use capability, which shapes the solutions they need.

In order to substantially improve data usage in TANF agencies across the US, we need to determine efficient and scalable ways to reach agencies with assistance targeted to meet their needs. A first step is gathering comprehensive, multi-dimensional information about state capacities, capabilities, and current data use to determine each TANF agency’s data readiness and to identify the assistance that would most benefit them. Through the TDI project, we will build upon what we learned in 2014 with an expanded national needs assessment. Data will include a 50-state survey, supplemented by key stakeholder interviews, a review of published literature, and examination of publicly-available information such as reports, legislative testimony, and budget information from government and related websites. From our work in 2014, we hypothesize that we will be able to identify clustered patterns in agencies’ strengths and gaps in readiness to work with data. This will allow us to develop targeted technical assistance that takes advantage of what states do well, while addressing the things that hinder deeper engagement with data. These insights will inform the dissemination of new innovations specifically targeted to state needs.