Leveraging Data as a Strategic Asset Part I: Access, Use, and Augmentation
In late June, the Department of Commerce created an opportunity to share input on the Federal Data Strategy by requesting comments on the Cross-Agency Priority goal of Leveraging Data as a Strategic Asset. The Department of Commerce specifically requested comments on best practices related to the four pillars of the federal data strategy:
- Enterprise Data Governance
- Access, Use, and Augmentation
- Decision-Making and Accountability
- Commercialization, Innovation, and Public Use.
Given that data is a critical component of Third Sector’s work in outcomes-oriented contracting, we were happy to share perspective from our experience (which is available in full here). In this two-part blog series, we’ll explore how two of the Federal Data Strategy pillars can accelerate improved outcomes in social services. Part I shares some of our thinking on challenges and solutions to encourage access, use, and augmentation of federal data. Part II focuses on how federal data can improve decision-making and accountability.
The federal government possesses one of the greatest untapped resources in our nation: administrative data. Substantive changes to access, use, and augmentation of administrative data would unleash tremendous value by improving outcomes for millions of people who use local, state, and federal services.
The second pillar of the federal data strategy focuses on Access, Use and Augmentation. Specifically, this pillar considers what practices the Federal Government should study further as it develops policies and practices to enable interested parties to effectively and efficiently access and use data assets, such as:
- Making data available more quickly and in more useful formats;
- Maximizing the amount of non-sensitive data shared with the public;
- Leveraging new technologies and best practices to increase access to sensitive or restricted data while protecting privacy, security, confidentiality, and the interests of data providers.
Data, often from sensitive domains such as incarceration, health, or children and families, is critical to the work we do at Third Sector. There are clear opportunities to expand outcomes-oriented government by creating easier access to federal data while still protecting the privacy of those receiving services. A concrete example is how easier access to federal data could have changed our work in Massachusetts with Governor Baker’s Learn To Earn Initiative.
Local agencies often collect similar types of data in different ways, and have their own processes to access data held locally, making it difficult to transfer successful project models to new jurisdictions. Third Sector’s work could be more easily scaled if we could instead turn to standardized federal data metrics and processes to reduce barriers to outcomes-oriented policy and access federal data indicative of social sector outcomes.
Another obstacle to effective use of federal data is the variation in formats of data use agreements (DUAs), even between federal agencies. Applicants are often required to re-start at the bottom of the learning curve for each new dataset they need to access, even though the substantive requirements are more or less the same. If the federal government created a common standard request approach with agency-specific appendices, it would be considerably easier to navigate and would permit more productive use of federal data.
Third Sector has also found that even though non-sensitive data lacks the privacy concerns that can complicate data access and use, non-sensitive federal data is still underutilized at all levels of government. In addition to these obstacles, the usefulness of non-sensitive data is often reduced by issues regarding quality and consistency of the data, as well as the timing and regularity with which it is updated. Our projects and government partners use administrative data to not only evaluate program outcomes, but also to support continuous improvement processes by helping governments and providers understand how they can make real-time program modifications to improve population outcomes. When the release of non-sensitive data lags for a year or more behind its collection (as is the case with many of these datasets), its usefulness to providers and governments is severely diminished. To address this concern, the Federal Data Strategy should consider investing in tools and resources to shorten the time from measurement to useful insights such as application program interfaces (APIs) APIs and machine-readable formats.
Use Case for Federal Data: Learn To Earn
Use Case for Federal Data: Learn To Earn
Third Sector’s ongoing work in Massachusetts as part of our Empowering Families Initiative provides an example of how the above recommendations could amplify the efforts of state and local governments. Learn To Earn is an initiative of the Baker-Polito Administration that seeks to improve coordination across state public assistance programs. One focus of this initiative is creating new data sharing arrangements between state agencies responsible for public assistance programs to help them better understand and support individuals who interact with multiple programs. Currently, these programs are each designed to serve a single need and operate independently from one another, despite often serving the same population. By improving data sharing among these agencies, Learn To Earn will help give each agency a comprehensive view of their participants through the use of aggregate-level data, and will ultimately inform the Commonwealth's resource allocations and policy decisions.
State data is often limited in its scope and quality. Easier access to federal data would greatly enhance the ability of state governments to undertake similar efforts to Learn To Earn. The data reported to the federal government, through both the tax system and detailed reporting requirements for federal grants, covers a broader set of individuals than state data and would permit a more detailed understanding of the full picture of an individual or family's income, educational outcomes, and labor force participation. This data could help states coordinate eligibility requirements across programs to avoid disincentives to work, and better understand the interactions between different sets of benefits programs to ensure individuals and families are receiving the most effective mix of supports to obtain the education and skills they need to succeed in the labor force.
Specifically, Third Sector believes it would be most helpful if states could more easily access federal tax data. This data is more robust and more useful than wage data that is accessible through state unemployment insurance systems. The data is reported more frequently, and includes individuals who are self-employed or operate as independent contractors. Easier access to federal tax data would both accelerate the work already ongoing in Massachusetts and make it easier for other states to replicate this approach to better understanding and ultimately improving their portfolio of public assistance programs.