Better Data Practices, Better Insights: How Two Districts Transformed Their Analytics 

Your district is sitting on a goldmine of data. But for most administrators, getting meaningful insights from that data feels impossible when dealing with inconsistent entries and information scattered across different platforms.   

We recently polled nearly 100 district administrators about their data practices related to College and Career Readiness. After sharing all the indicators that frameworks like Redefining Ready use—grades, ACT and SAT benchmarks, enrollment in Algebra II, AP coursework, attendance, activity involvement, and community service to name a few—we asked, “How many places would you need to go to find all of this data?” Most respondents—52%–indicated they would need to check 3-5 different places. Another 34% reported needing to look in 1-2 locations, while 3% required 6 or more sources. See the results below. 

If this sounds familiar, you’re not alone. 

The Real Cost of Poor Data Practices 

As a K-12 administrator, you’ve likely experienced the frustration of trying to analyze student data only to find: 

• Three different ways to label the same behavioral incident 
• Missing attendance records 
• Course codes that don’t match across systems 
• Student activity data living in a spreadsheet you don’t have access to 

These aren’t just annoying inconsistencies—they’re roadblocks preventing you from using analytics to make informed decisions about your students’ futures. 

Success Story #1: How Troy Community Consolidated School District 30c Standardized Their Discipline Data 

When Troy Community Consolidated School District 30c in Illinois looked at their discipline data, they saw chaos. Their student information system had become a jumble of similar-but-different behavior labels: “failure to comply”, “failure to comply with directions”, “failure too comply”—you get the picture.  

Their solution? They brought together a Discipline and Behavior Committee of administrators and staff who: 

1. Consolidated duplicate discipline types 
2. Aligned everything with their student handbook 
3. Created a single, clear system for reporting 

The result? For the first time, they could actually analyze behavior patterns across their buildings and target their PBIS and MTSS interventions where they were needed most. 

Success Story #2: Altoona’s Analytics Journey 

Altoona School District in Wisconsin faced a different challenge. They wanted to analyze college and career readiness indicators, but their data practices made it impossible: outdated course codes, gaps in student records, and critical information spread across multiple systems. 

They spent a year implementing better practices: 

• Standardizing course codes across all systems 
• Validating historical records 
• Creating clear data entry protocols 
• Bringing athletics and activities data into their main system 

Now, instead of hunting through spreadsheets, they can analyze student readiness through a single dashboard. 

The Impact of Better Data Practices 

The benefits of clean, consistent data extend far beyond improved reporting. Take teacher retention—according to a recent 2024 RAND survey, student behavior management is the #1 cause of teacher stress. Districts with standardized discipline data can spot patterns early, identify where additional support is needed, and help reduce teacher burnout through targeted interventions. 

Clean data also strengthens dropout prevention efforts. Research consistently shows that the ABCs—attendance, behavior, and course performance—are the strongest predictors of student success. When this data is properly maintained and integrated, districts can identify at-risk students early and provide support before they fall through the cracks. 

Your Action Plan: Where to Start 

Ready to improve your district’s data practices? Here’s your roadmap: 

1. Audit Your Current Practices: Look for duplicate entries, inconsistent labels, and data living outside your main systems. 
2. Control Access: Limit who can modify critical data fields. More access points = more inconsistency. 
3. Create Clear Protocols: Document exactly how data should be entered and who’s responsible for what. 
4. Consolidate Your Sources: The fewer places data lives, the easier it is to analyze. 
5. Put Your Clean Data to Work: Once your data is reliable, you can analyze it to show progress, identify needs, and make the case for resources. 

Remember, this isn’t about perfect data—it’s about having information you can trust to drive decisions that affect real students and teachers in your buildings. 

Discover the Power of Student Analytics Lab – Data-Driven Insights for Smarter K-12 Decision-Making 

Uncover trends, identify risks, and drive student success with Student Analytics Lab—the advanced analytics solution built for K-12 administrators. With research-backed models and real-time data, you can confidently make informed decisions to support students, optimize resources, and improve outcomes across your district. 

From dropout prevention to college and career readiness—see the impact of data-driven leadership in action.