Why Standardized Data Definitions Are Critical for Local Accountability

In our work to clarify equity patterns in Milwaukee’s dual-enrollment programs, one of the most challenging barriers we confronted was inconsistent terminology and calculation methods across schools. Without a shared definition of what counts as a dual-enrollment participant, schools reported participation based on varied criteria—some including students who merely enrolled in a course, others counting only those who completed it with a passing grade. These inconsistencies made it nearly impossible to compare outcomes across schools or to identify systemic disparities in access for historically underserved groups.

Establishing standardized definitions not only improved comparability but also enabled more focused policy conversations. For instance, once we aligned our metrics with the Wisconsin Department of Public Instruction’s public data portal, we could clearly see which schools had disproportionately low participation rates among Black and Latinx students, despite having similar enrollment sizes and course offerings. This level of transparency allowed school leaders and community advocates to ask more pointed questions about resource allocation, counselor support, and student outreach efforts. Research from the Data Quality Campaign supports this approach, emphasizing that consistent, high-quality data is essential for local leaders to make informed decisions that truly benefit students across all demographics¹.

Designing Dashboards That Support Equitable Decision-Making

The development of our “dual enrollment report cards” was not just an exercise in data cleaning—it was a strategic move to make equity actionable. Each report card displays participation rates disaggregated by race, economic status, and English language proficiency. We included simple visual cues, like color-coded indicators and trend arrows, to help school staff and families quickly identify gaps and progress. This design choice was guided by the principle that transparency should not require a background in data analytics to be useful. According to the Government Finance Officers Association, public dashboards must prioritize usability and contextual clarity to drive public trust and engagement².

Other cities looking to replicate this work should focus on creating dashboards that move beyond compliance reporting and toward continuous improvement. That means integrating feedback loops, where school staff can annotate data with local context, and ensuring that the dashboard is updated regularly using verified public data sources. In Milwaukee, we relied heavily on DPI’s WISEdash portal, which provides publicly accessible data on student outcomes, course offerings, and enrollment trends. By anchoring our dashboard in this trusted data source, we reduced confusion and eliminated competing narratives about what the numbers actually mean³.

Applying These Lessons to Workforce and Postsecondary Readiness

The same principles we applied to dual enrollment data can be extended to workforce development and postsecondary readiness dashboards. For example, cities often track high school graduates’ employment or college enrollment rates, but inconsistent definitions—such as whether “employment” includes part-time, seasonal, or military enlistment—can cloud the picture. Municipal leaders must work with school districts, workforce boards, and state agencies to adopt shared performance indicators. This alignment not only improves data quality but also supports cross-sector collaboration, which is essential for addressing systemic barriers to opportunity.

One practical step cities can take is to convene an interagency data governance group. This group should include representatives from local school districts, community colleges, workforce development agencies, and municipal departments. Their role is to agree on common terminology, data-sharing protocols, and reporting timelines. In Colorado, for instance, the TalentFOUND network has implemented a statewide data framework that connects education and workforce outcomes using standardized metrics, helping local governments make smarter investments in career pathways⁴. Such models demonstrate how cities can extend the transparency we achieved in dual enrollment to broader indicators of student success and economic mobility.

Building Internal Capacity to Sustain Data Transparency

For any city or school district, maintaining consistent and transparent dashboards requires more than good intentions—it requires staff training, technical infrastructure, and a culture of continuous improvement. In Milwaukee, we invested in professional development for our data analysts and school-based staff to ensure they understood the logic behind the metrics we were using. We also created internal documentation that outlines how each figure is calculated and what the limitations are, so that misinterpretation is less likely. This internal clarity has been just as important as the public-facing transparency we aimed to achieve.

Other municipalities should consider assessing their current data infrastructure and investing strategically in tools that support version control, data validation, and user access management. Open-source platforms like Metabase or Tableau Public can be leveraged to build low-cost dashboards, but the effectiveness of these tools ultimately depends on how well the data is prepared and maintained. According to the National League of Cities, cities that invest in data capacity see stronger cross-department collaboration and more targeted interventions in both education and workforce programs⁵.

Embedding Transparency into Policy and Budget Conversations

Finally, transparency must be integrated into the decision-making processes that shape education and workforce policy. In our case, presenting standardized dual enrollment data during school board budget hearings helped align resource allocation with equity goals. When decision-makers can see, in plain terms, which schools are serving low-income students well and which are falling short, budget discussions become more grounded in evidence rather than anecdote or politics. This approach aligns with recommendations from the Urban Institute, which advocates for data-informed budgeting as a way to reduce disparities and improve outcomes in local government programs⁶.

To embed transparency in this way, cities should establish formal expectations for public reporting on key metrics at regular intervals—such as quarterly board meetings or annual budget reviews. Additionally, inviting community stakeholders to interpret and respond to the data can increase accountability and foster trust. In Milwaukee, we distributed our report cards to parent advisory councils and youth-serving nonprofits, encouraging them to use the data in their advocacy and programming. This practice helped shift the role of data from a compliance tool to a community resource, deepening local engagement with our education system.

Bibliography

1. Data Quality Campaign. “Why Education Data Matters for Equity.” 2022. https://dataqualitycampaign.org/resource/why-education-data-matters-for-equity/

2. Government Finance Officers Association. “Designing Effective Public Dashboards.” 2021. https://www.gfoa.org/materials/designing-effective-public-dashboards

3. Wisconsin Department of Public Instruction. “WISEdash Public Portal.” Accessed June 2024. https://wisedash.dpi.wi.gov

4. Colorado Workforce Development Council. “TalentFOUND Data Framework.” 2023. https://cwdc.colorado.gov/talentfound-dashboard

5. National League of Cities. “Data Practices for Local Government: A Guide for City Leaders.” 2021. https://www.nlc.org/resource/data-practices-for-local-government/

6. Urban Institute. “Using Data to Advance Racial Equity in Budgeting.” 2021. https://www.urban.org/research/publication/using-data-advance-racial-equity-budgeting