How one state makes education-to-employment data more accessible
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Nora Morris has spent her career using data to help people better understand complex systems. Today, she leads the longitudinal education-to-employment data system for the state of Minnesota, which tracks students from pre-kindergarten through employment to help gauge the effectiveness of education and training programs and target improvements that can help aspiring students.
But Morris’ career began in another complex data system: health care. In Morris’ earliest days as a data scientist (“before we even knew there was such a term,” she says), medical organizations were just beginning to promote national standards of care, and her job was to share with doctors how they compared to their peers.
Those interactions with physicians taught her critical lessons about how individuals engage with data. Some were politely interested but didn’t act on the information. Others reacted angrily and accused Morris of trying to tell them how to practice medicine.
But some physicians — the ones who were curious about how data could help them improve their approach and wanted to measure progress — validated Morris’ belief that data can help solve problems and shape the future.
“My whole career has been built around how we get people from fear and status quo and into embracing data,” said Morris, director of Minnesota’s State Longitudinal Education Data System, or SLEDS. “How do you take data and information and actually work with real life human beings to get them to use it when they're making decisions?”
The work Minnesota does through SLEDS was highlighted recently through the release of the 2025 State Opportunity Index, which centers on five research-backed keys to improving employment outcomes for learners and employers alike: Clear Outcomes, Quality Coaching, Affordability, Work-Based Learning, and Employer Alignment. Home to one of the nation’s leading education-to-employment data systems, Minnesota was featured for its work in Clear Outcomes.
“I’m a numbers person, but I have come to realize most people are not ... So how do we take those numbers and make them into something that people can absorb and understand intuitively?”
— Nora Morris, director of Minnesota's State Longitudinal Education Data System
At an October convening in Washington, D.C., where more than 300 education and industry leaders from 36 U.S. states learned from one another about how states are connecting education after high school with economic opportunity, Morris shared some lessons she has learned about making data more useful and approachable for policymakers and Minnesotans:
- Publicly accessible dashboards need to be available to anyone at any time and on any type of digital device.
Morris tries to keep the end user in mind when developing the interactive tools her agency creates with the data — and sometimes that means thinking about college-aged Minnesotans who awake at 2 a.m. wondering about their future and scrolling through their phones. “They can pull up our dashboards, and they can look at the results for what happens if you make different choices around different majors or different institutions,” Morris said. “It has to be available to them at all times.”
- In order to be effective, the data need to be presented in a visually appealing way that is simple to process and absorb.
As a data scientist, Morris relies on the expertise of others, such as neuroscientists and data visualization experts, to ensure the state tools are user-friendly. More than elite datasets that require specialized knowledge to interpret, the state’s dashboards are designed to be used by those who need them most. “I’m a numbers person, but I have come to realize most people are not,” Morris said. “So how do we take those numbers and make them into something that people can absorb and understand intuitively?”
- Because humans process data through stories, they need to be able to envision reality through the data.
Individuals “need to be able to see their own story in our data” in order to interpret what the data are saying, Morris said. Through Minnesota’s dashboards, individuals can analyze outcomes by high school, higher education institutions, race, ethnicity, gender, disability status — the sorts of demographic details that help them make sense of what the data reveal. “When they can see their own story, they can start to trust the data,” Morris said. “And only after they trust the data will they start to incorporate that into their decision-making.”
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