How Data-Driven Cultures Are Supporting Federal Innovation
Federal policies are enabling agencies to build data-driven cultures in support of data modernization efforts.
Since the 2018 bill requiring agency data to be accessible, the departments of Health and Human Services and Veterans Affairs and the National Science Foundation are emphasizing how a data-driven workforce is support these efforts.
A lot of these efforts are uniting federal agencies to collaborate on approaches together.
“For a long time, the federal government has been evolving and using data more and more for data-driven decision-making, but we were doing that in isolation. The evidence act brings together all the elements that were working independently and allows us to leverage our combined strengths,” said NSF CIO Dorothy Aronson during a FedInsider virtual event last week. “We are able to grow as a government all at once.”
The other part of the bill requires agencies to plan to develop statistical evidence to support policymaking.
HHS’ Administration for Children and Families recently published its first agency-wide research and evaluation plan, as well as the framework and procedures for data governance, noted Naomi Goldstein, deputy assistant secretary for planning, research, and evaluation in the Office of Planning, Research, and Evaluation (OPRE) at the agency. ACF also conducts assessments of data and evidence capacity and is fostering new inter-agency relationships.
“We worked, for example, to build logic models and better align data with those logic models,” Goldstein said.
Agencies are also implementing new workforce initiatives, like training and educational sessions, to support data management and modernization efforts. NSF is teaching the workforce how to effectively and successfully use data and create analytics.
“It seems like we’re moving now into a world where we’re getting to see a culture of data. People are getting more comfortable with data. We’re learning about new data tools and the power of data informally through our normal conversations,” Aronson said. “We’re getting to leverage each other’s accomplishments and spring off of those to advance our understanding of this new world.”
By collaborating across agencies, Goldstein explained that technology leaders are better able to pinpoint cross-cutting challenges. Equity and diversity are key obstacles as agencies develop new solutions and modernize data collection and analysis.
“One recurrent theme in these discussions is to make sure we’re taking into account perspectives of diverse stakeholders at all stages of the work, from building evidence to learning from it, and applying it to policy and practice,” Goldstein said.
Kshemendra Paul, chief data officer at VA, said the agency is improving the ways it uses data to drive positive change in its veteran programs, like the Electronic Health Record Modernization program and the Million Veteran Program. The program has collected voluntary information from veterans to analyze genetic data and compare it to socioeconomic data to better inform research and innovation.
“It’s a unique data set and a great example of how VA is positioned to lead American health care, lead American wellness,” Paul said.
VA is building a cross-cutting, data-driven environment to support larger modernization efforts, like EHR modernization. The agency is partnering with the Defense Department to boost data interoperability and create a seamless flow of information for individuals transitioning from service member to veteran. As VA works to enable this transition, the agency will focus on mitigating complexities and ensuring data is reliable to support operations.
“A key part of the comprehensive lessons learned process and the work that we’re doing around data management is ensuring that we’re maintaining high semantic interoperability between the two systems, with our partners at DOD, with our partners in the community, to stay on top of the core data management challenge,” Paul said.
Goldstein explained that interoperability is one of the largest challenges facing both government and industry. She is looking to prioritize data sharing to add greater value and understanding to data sets.
“This is one of the major challenges facing the federal government, as well as the state, local and private sector partners, so we have a lot of valuable and useful data, and it could be even more valuable and useful if we had more standardized, streamlined ways of combining data from different sources while still protecting people’s privacy,” Goldstein said.
As federal agencies continue to modernize, Aronson said there must be a “data epiphany” and a continued, active effort to advance the knowledge and functions of data.
ACF is looking to boost understanding of data and its use through leadership buy-in. Senior leaders should support learning, objectivity and transparency and allocate resources to data priorities.
“I would really like to see a culture of data and a culture of evidence across my agency and across the government,” Goldstein said. “It certainly exists to some extent, but I would really like to see use of data and questions about data across the decision-making, policymaking and implementation functions of government. That requires data skills among staff as well as really persistent attention to data by agency leadership.”
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