Discusses the composition of three states’ workforce data systems and the states’ processes for making data available to outside stakeholders while also ensuring the confidentiality of individuals in the data systems.

“A variety of stakeholders recognize the need for state agencies to collaborate with each other and with external entities in order to collect longitudinal data and conduct research. Such analysis can contribute to effective policymaking and improve programs. State agency employees and national non-profit representatives have discussed this need at a number of national meetings, workshops, and webinars. The U.S. Departments of Education (ED) and Labor (DOL) have also promoted the benefits of longitudinal data analysis by providing states with millions of dollars through the Statewide Longitudinal Data System (SLDS) and Workforce Data Quality Initiative (WDQI) grants to build, expand, and utilize longitudinal data systems.

Many state agencies have used this federal funding to develop longitudinal data systems that enable valuable cross-agency data sharing and analysis. While building a strong data infrastructure is a crucial step, making use of the data is just as important. However, many states lack the requisite funding and staff to do so. Accordingly, some states have collaborated with subject matter experts and data scientists from outside the state government to analyze data and determine how to improve programs and promote effective policies. This external collaboration may allow states to increase their capacity for analysis at a minimal cost.

Kentucky, Minnesota, and New York all have unique processes to utilize data contained in their data systems. They have strategically collaborated with external organizations to enhance their capacity for research, data analysis and interpretation, and unbiased assessment of outcomes. Thus, these states are able to use their data not only to meet federal reporting requirements, but also to conduct actionable research that can help prioritize effective programs. In addition, these states have enacted significant privacy protections to ensure that confidential information remains private and secure as it is collected and used for research” (p.1).

(Abstractor: Author)

Full publication title: Making the Most of Workforce Data: State Collaboration with External Entities for Actionable Research

Major Findings & Recommendations

The authors find that “Kentucky, Minnesota, and New York have demonstrated various approaches to increasing analytical capacity and producing actionable research by collaborating with external entities. [They offer] some recommendations for other states exploring ways to share data that enables more rigorous research that can improve policy and practice. 1. Identify key leaders who will champion the use of data to improve policy and programs. 2. Demonstrate the value of the data early during the process of establishing a data system, so that stakeholders support and promote the system from inception. 3. Secure a legislative mandate, which can help to jumpstart data sharing (both between state agencies and with external collaborators) and clarify the value of data sharing to stakeholders. 4. Encourage data requesters or collaborative research organizations to centralize requests instead of making multiple small requests, as this will reduce the time agencies spend on filling the requests. 5. Consider establishing and governing the data system in a centralized location outside of the participating agencies. 6. Grant different levels of access to different users to help secure data and maintain privacy. 7. Consider charging a reasonable fee to cover the costs of providing data. 8. Establish, within state agencies, networks and rules for sharing data to better utilize the data collected in the state systems. 9. Use best-practice methods of ensuring data quality, which will ultimately help analysts to assess programs and policies more accurately. 10. Prioritize using data to inform program and policy decisions, instead of prioritizing collecting it. 11. Establish strong cross-agency communication to ensure that data is shared, used effectively, and kept private and secure” (p.7). (Abstractor: Author)