Data By Design: Building a Successful Court Data Program

February 04, 2026 by Ellen Reed

In 2020, courts digitized rapidly in response to the pandemic. Integrated court technology created an influx of electronically recorded data, enabling court leaders to gain greater visibility into day-to-day operations without increasing staff’s data entry responsibilities.

Over time, we have seen a shift in which data is no longer viewed as an operational compliance burden; instead, it is valued as a core asset to validate decision-making, strengthen efficiency, and justify investment allocation.

However, court data is more than just static information. Data includes reports, metrics, statistics, and key performance indicators (KPIs). A data program allows you to specifically design data collection and presentation to validate or disprove assumptions and definitively show whether a process or change is working as desired. Data helps prove operational success while surfacing bottlenecks that may be hidden in day-to-day routines.

While data in a modern court is increasingly digital, the data itself remains highly complex. It can be siloed and inaccurately entered in the case management system (CMS). For data to be most useful, it must be thoughtfully designed and programmatically supported.

As a practitioner of working with data in the justice system, I’ve had hands-on experience building data programs focused on leveraging courtroom technology within county and statewide agencies and courts. The evidence-based insights and what I’ve learned along the way in creating these programs data is what I’ll share today.

Beginner-Friendly Steps for Starting a Court Data Program

Many courts make traction on their journey to a successful data program by following a prescribed pattern.

Step 1: Clean up your court data. In any given court, it’s common for cases to have invalid business processes, or for thousands of open cases to actually be closed. This throws off the initial measurement of performance metrics, such as time to disposition or age of active pending cases. Cleaning up this data, though manual and unpleasant, is critical to accurately reflect the court’s work and ensure continuous, accurate data flow. This lays the foundation for trusted data. Until staff and stakeholders trust the data, it will be used minimally or not at all.

Step 2: Start with a small and discrete set of data. Collecting data with a specific purpose helps users understand not only how the data will be used but also how it should be input. Both the National Open Data Standards and the CourTools framework, through the National Center for State Courts, equip courts with a starting point for identifying data elements and producing performance measures from their CMS.

Step 3: Measure your baseline. This allows court leaders to understand the present state and what to expect if processes remain unchanged. When processes are changed, the baseline measurement is important because it serves as a comparative point for assessing the impact of change. For example, adding staff during peak e-file submission windows or allowing an AI agent to accept or reject certain pleading types can help decrease your e-filing processing time. This KPI then helps prove the return on investment of the implemented change. While they may not be completely satisfactory in the early stages of your data program, your KPIs enable a story of success and larger-scale data collection efforts in the future.

Step 4: Democratize your court data. The goal for many courts is to empower all justice stakeholders — analysts, administrators, clerks, and policymakers — to make the best possible decisions about resource allocation, procedural workflows, and policy. Investing in data accessibility enables those on the ground, with the most context on operational challenges, to make data-driven decisions. Courts can instantly measure the effects of experiments, celebrate successes, and show the value of investing in clean data.

Key Features of a Sophisticated Court Data Program

Whether you partner with a vendor on an analytics platform or develop your own, here are a few key features that agencies across the country are incorporating into their data program to make it more actionable.

Self-service access. Tangible, up-to-date metrics enable frontline users to make evidence-based decisions in daily operations.
Proactive alerts. An essential feature of any data program, proactive alerts allow staff to troubleshoot or investigate potential issues before they become problematic. For example, if cases are aging past a certain threshold or there’s a large volume of new filings in a certain category, these are early indicators of challenges ahead that could create a domino effect on staffing or workloads.
Flexible analysis. From bar charts and overtime charts to slicing data by time of day or geospatial analysis, having flexibility in how data is presented helps staff spot trends and answer key questions.

Collin County, Texas, has been innovating in this area to analyze their jury operations. Their Jury Analytics dashboard will help them understand their juror utilization, yield, and failure-to-appear rate, zip codes most summoned, the number of jurors disqualified and why, the most popular payment type chosen by jurors, and more. Together, these KPIs paint a clear picture of how people move through the jury process, enabling the court to gain new efficiencies and cost savings.

Built-in sharing. Tools for easy collaboration, such as sharing and exporting mechanisms, enable staff to have more focused discussions on issues revealed by the data because stakeholders are looking at the same information.
Instant drill-down. Being able to see exactly what the chart represents, down to the case number or status event level, allows staff to check and validate data more effectively. This also opens the door for questioning and understanding the root cause of the original concern so that appropriate action can be taken.

Court Data: The Fuel to Scalable Artificial Intelligence

Artificial intelligence (AI) is grounded in the data it has access to. AI thrives on data to learn patterns and reproduce prescribed outcomes. Simply put, data fuels AI. But the data must be clean and accurate for court AI and automation programs to be most successful. Otherwise, courts risk the integrity of the results.

Once your court is confident in its data, AI and automation can help break through inefficiencies — from inconsistent e-filing processes to cumbersome document review and processing. These are real-world court problems that AI can solve.

For many courts, success comes from both data diligence and practical, scalable AI programs.

Designing the Future with Data

My vision for courts and justice agencies is they feel empowered to transform data into action — to create meaning from noise. Understandably, data can be difficult to decipher, but a robust judicial analytics solution can help separate and quantify data in a way that is actionable and clear. That clarity is what builds confidence in improving due process and outcomes in the justice system.

For more insights on court data analytics, watch my recent webinar sponsored by the National Association of Court Management.

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