Introduction

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.

Purpose

The primary purpose of this toolkit is to offer practical guidance to agencies on how to create a culture of evidence as a routine part of government operations. While the toolkit was developed with state Temporary Assistance for Needy Families (TANF) agencies in mind, many of the strategies may also be useful for individuals in a range of government agencies and other organizations, where the challenges – and potential for impact – are similar.

The material was sourced from interviews with practitioners who have successfully built sustainable data use into their everyday practices. This work was part of the TANF Data Innovation (TDI) project, launched by the Administration for Children and Families within the U.S. Department of Health and Human Services to strengthen agencies’ use of TANF, employment, and other administrative data.

Key Findings and Highlights

This toolkit presents two essential conditions for sustained data use. First, an agency must have a demand for data from decision-makers seeking data to inform their choices. And second, the agency needs the capacity to generate analyses—the people, data, and infrastructure necessary for data preparation and analysis. When both demand and capacity for data use are strong in an agency, the two are mutually reinforcing, encouraging more consistent practice and, ultimately, more evidence-based policymaking.

This toolkit offers concrete strategies on how to:

• Foster demand for data use
• Build staff capacity for analytics
• Build capacity through external partnerships
• Improve internal communication to support sustained data use
• Improve knowledge management and documentation about data use

It also includes a toolbox with guidance and fillable forms such as:

• A sustainable data use self-assessment
• Sample language for creating job descriptions for data analytics staff
• Sample interview questions for hiring data analytics staff
• Identifying the right training program for your needs
• A documentation checklist