The conversation about education and workforce data moves fast: new reports, new discussions, new debates. But the issues that determine whether data actually improves people’s lives don’t change nearly as often as the headlines suggest. Back to Basics is DQC’s ongoing series on the fundamentals: the data policies, practices, and principles that have always mattered—and still do. Each post steps back from the moment to explain what’s really at stake—and why getting it right is worth the sustained effort. This post is the second installment of Back to Basics; read the other posts in this series here.
Statewide longitudinal data systems (SLDSs) don’t always make headlines, but they should. In fact, SLDS data dominates the news cycle, in ways big and small, even if people don’t always realize it. Conversations about the new Workforce Pell program, AI disruption in the workplace (and uncertainty around workforce pathways as a result of that disruption), credentials of value, career and technical education, dual enrollment strategies, and high school redesign are all grounded in data and people’s ability to access it for decisionmaking. And perhaps more importantly, these issues matter to families, students, educators, institutions of higher education, researchers, state legislators, governors, and federal policymakers.
Each one of the issues I’ve listed requires data collection and analysis in K–12, postsecondary, or workforce… or across all three. SLDSs are integral because, at their best, they are the connective tissue of state education and workforce systems. That continuity matters because students don’t experience their lives in silos, and data systems shouldn’t either.
When states and the federal government invest in strong SLDSs, they aren’t just building infrastructure—they’re building insight. Insight into whether students are on track to pursue their next steps. Insight into which pathways lead to real opportunity. Insight into where systems are serving students well and where they are not.
Within the last 20 years, state leaders (supported by federal policy and funding, philanthropy, and advocacy partners) have built robust SLDSs designed (ideally) to answer whatever “today’s” burning questions are. These systems should be nimble as those questions evolve and change over time and sometimes suddenly (e.g., COVID-19). At a minimum, these systems include individual-level data that is securely linked over time and across systems and sectors.
But this wasn’t always the case! While states have always collected data from districts, prior to around 2005 (when the Data Quality Campaign launched and federal funding began to flow), data was collected in the aggregate from districts and used almost exclusively for federal compliance reporting. Back then, districts made the rules. Graduation rates illustrate this perfectly. Prior to the 2008 requirement to report a cohort graduation rate (a longitudinal statistic!), a state would collect rates from districts; many of whom simply divided the number of graduates by the number of students who started as seniors in a given school. Yet, those numbers don’t hold if students transfer to a different school or drop out earlier than the twelfth grade. The 98 percent graduation rates districts were reporting often didn’t pass the laugh test. States have come a long way since then.
Now, a new report from the Lumina Foundation shows that a majority of parents want their kids in some type of postsecondary education or training after high school. And only an SLDS can provide the kind of information parents and students need to understand the value of any of the paths available to them.
The value of an SLDS isn’t just in bringing data together. It’s in how people then use that data responsibly, transparently, and in ways that actually improve decisions for students. That means:
- Ensuring data is accessible to the people who need it most;
- Protecting privacy while enabling meaningful use; and
- Focusing on questions that matter to students, families, and communities.
In a moment where AI and advanced analytics are rapidly expanding what analysis is possible, the foundation that analysis is built upon matters more than ever. High-quality, connected, and trustworthy data systems are what make innovation useful—not just impressive.
The question isn’t whether states have data. It’s whether they’re using it to create better outcomes. That’s the promise of an SLDS, and it’s one worth delivering on.
