Governance, State Advocacy

Prioritizing Data Governance Enables State Leaders to Set Bigger Goals

Prioritizing Data Governance Enables State Leaders to Set Bigger Goals

A state’s education goals should be a rallying point for education leaders across sectors, encouraging them to work together, share best practices, and continually improve outcomes—all in service of student success. But too often, state leaders limit their goals to what can be measured or create goals without the data necessary to actually assess them. Data governance, in which agencies from early education to workforce development formally share data and meet regularly to discuss data-related issues, has the ability to equip state leaders with the cross-sector data they need to confidently set big goals and accurately measure their progress.

According to the most recent data from the National Center for Education Statistics, states appropriated over $400 billion to K–12 and higher education. To ensure that these investments support state goals and encourage quality teaching and learning, state legislators and education leaders have developed a variety of accountability systems, from state assessments and teacher evaluations in K–12 to accreditation standards in higher education. For these systems to truly capture the experience of students, they require high-quality data that accurately measures the effectiveness of institutions, educators, programs, and more.

Ideally, state leaders would determine a set of state goals, develop a course of action, and then measure progress toward those goals through accountability systems. But often, state leaders do not have access to the necessary data, and must choose state goals that can be measured within the current system or use incomplete or inaccurate measures—degrading trust in the entire accountability system.

Some of the most data-heavy accountability systems are funding formulas. For example, Tennessee has an outcomes-based funding formula that distributes funding to institutions based on improvement on key measures of student success (e.g., number of students earning credentials). Meaning, when institutions improve their students’ outcomes at a higher rate than other institutions, they receive an increased share of the funding. With over a billion dollars at stake, institutions and state leaders are invested in using quality data, leading one state leader to say, “If we don’t have the data, we will not integrate it into the formula.”

Currently, Tennessee state leaders are reviewing the formula, as they do regularly, to incorporate new state goals. The Governor’s office is interested in providing incentives for universities to help students earn credentials that meet workforce needs. But during this process, many questions ensued, including:

  • Do leaders have detailed information on workforce needs?
  • What if the workforce needs vary across the state? If so, could leaders determine the local workforce needs for the counties surrounding an institution?
  • Can leaders match credentials earned to the jobs students pursue afterward?

The answer was: maybe, eventually.

What if the answer was a resounding “yes”? What if data leaders from workforce development, higher education, and K–12 were already meeting regularly and were preparing for the upcoming data needs?

What if their data systems were already linked and ready to use? What if stakeholders already trusted the accuracy of the data?

While Tennessee has made strides in connecting data across the early childhood, K–12, higher education, and workforce sectors, it does not yet have the cross-agency governance necessary to confidently build accountability systems that measure outcomes throughout a student’s life stages. This outcome is the data governance dream each state should be working toward—with a structure that holds state agencies accountable for collecting and reporting quality data, requires leaders from various sectors to convene together regularly, is responsive to the data needs in the state, and ensures the security and accuracy of the data.

With effective cross-agency data governance, it is possible to set more expansive goals, knowing progress towards those goals can be accurately measured.