As the labor market works to crawl back from this year’s sharp downturn, getting the U.S. workforce prepared for and placed in secure, lasting jobs will be a complex process — one that requires close coordination among educators, employers, and workforce development.

One key to success when so much is at stake: equipping stakeholders and decision-makers with the most complete, updated information available. And one emerging tool that helps harness the power of data and makes sharing safer and easier is the data trust.

Making decisions without data is like trying to complete a puzzle without all the pieces. Every stakeholder across the education-to-employment landscape has valuable information that could improve workforce outcomes — but this information is typically siloed in separate data sets, making it difficult to share equally or easily among everyone involved.

“Historically, we’ve had a difficult time figuring out how to connect these data sets in a way that complies with all the necessary laws, but more importantly, in a way that honors the sacred trust that each of those institutions has with the people that they serve,” said Matt Gee, CEO and co-founder of BrightHive, a data collaborative company.

Learning providers know who enrolled in and who completed a program, but likely have little information about what graduates did next. Employers know who they hired and how long they stayed at the organization, but may not share those outcomes with the programs that trained their workers. Local agencies may have access to regional labor market information, but few opportunities to connect the dots between labor supply and demand.

And individuals forging their way from education to employment have incomplete information on which training programs to choose, or which career paths to pursue — forcing them to fly blind into the most important decisions of their lives.

“What that ends up creating for the talent marketplace is a complete lack of information about whether there are meaningful returns to different kinds of credentials from different kinds of providers,” Gee explained.

Many barriers stand in the way of creating a connected data system — barriers that are legal, technological, emotional, and more. Combined, they make progress very difficult.

Data trusts work by combining mission, legal agreements, and technology to enable purpose-driven data sharing. Data trusts are now being deployed by a handful of regional and state systems, allowing them to harness the power of their data to make more informed investments and better serve citizens.

For example, Colorado is working with BrightHive on a data trust to create better resources for individuals navigating education and employment. Colorado state agencies responsible for higher education, workforce development, K-12 education, and labor and employment, plus higher education providers, have come together to share their collective data to create a platform that allows individuals to track their goals and accomplishments and learn about relevant education and career opportunities.

Data trust applications aren’t limited to public organizations; private organizations also are leveraging data trusts to intentionally, securely, and transparently reap the benefits of shared data sets. Goodwill Industries International is working with BrightHive and Google Inc. on the Data Impact Collaborative, a program that aims to measure and improve the impact of programs delivered through community Goodwill organizations.

Creating the data infrastructure to enable sharing is complex, and admittedly unsexy, work that is foundational to a better functioning education and workforce system. Data trusts present one approach, and more investment is needed to broaden options for data sharing and build organizational and public trust in data-sharing approaches that advance social good efforts. In a world where we all learn and earn throughout our lives, sharing data widely — and safely— to improve education and work benefits everyone.

Strada Education Network is an investor in BrightHive.