Why do university enrolment figures differ between IPEDS and other reports?

Because administrative units define them independently. Baylor University had eight units tracking enrolment and research metrics with no shared definitions, which is what the Department of Education flagged. Forty-two metrics were agreed across all eight and the finding was resolved.

What does manual federal reporting cost a university?

$2.8M a year in staff time at Baylor, with three months of annual reconciliation. Automating IPEDS and NSF reporting from a certified metrics layer took that to $320K and two days.

How long does it take to agree metric definitions across departments?

Eight weeks for 42 metrics across eight units here. The agreement is the hard part and it holds because the units built it together. Implementation and pipeline automation took the remaining twelve weeks.

Baylor University · Higher Education · Houston, TX · 20 weeks

University-wide data governance program established

A private research university faced inconsistent enrollment and research data across eight departments, which risked federal compliance. We implemented a data governance framework that aligned metrics university-wide and automated reporting processes, cutting $2.8 million in annual labor costs.

Challenge

The university’s eight administrative units tracked enrollment and research metrics independently, without shared definitions or oversight. This caused major discrepancies that forced three months of manual data reconciliation every year for federal IPEDS and NSF reports. The process cost $2.8 million in staff time. The Department of Education warned the provost about inconsistent reporting, highlighting the urgent need to fix data governance.

Approach

We gathered representatives from all eight administrative units to define 42 key metrics on enrollment, research, and financial aid. Then, we created a verified metrics layer in the university’s data warehouse and automated IPEDS and NSF reporting processes.

Outcome

By week 8, we finalized and agreed on all 42 metric definitions. By week 20, we automated the IPEDS and NSF reporting pipelines. This cut annual federal reporting labor from $2.8 million to $320,000. The Department of Education’s warning was addressed, and the university passed the next compliance review without issues.

How our definitions changed over four years, and how we rolled up our sleeves to fix the chaos

For four years, each admin unit was winging it, tracking enrollment, research, and financial aid however they saw fit. That created a total data mess. It worked for them individually, but when we tried to pull reports, nothing matched up. So, we jumped in and put together a governance program with clear, standard definitions. The kicker? All eight units actually bought into it.

How We Simplified Data Submission for IPEDS and NSF

Here’s the deal: we built a reliable, certified metrics layer to handle all the federal reporting for IPEDS and NSF. No more wrestling with spreadsheets. Our pipelines pulled data straight from that layer and spit out files ready to submit. What used to take three months of back-and-forth? We slashed it to two days. Frankly, it changed everything.

How We Plugged Compliance Holes for the Department of Education

The Department of Education noticed the university’s enrollment numbers didn’t match up between IPEDS and the Common Data Set. So, we jumped in and created a certified metrics layer to align the data definitions from both sources. That fixed the inconsistencies right away. Then, when they did a compliance review, everything checked out and the issue was officially resolved.

Results

$2.8M Annual reporting labor automated
42 Metrics certified across 8 units
3 months to 2 days Federal reporting cycle
0 Compliance findings in review

The Department of Education flagged us, and we used to spend three months every year doing manual reconciliation. Thinklytics helped us fix the metric conflicts and automated the reports. Now, our compliance review is simple, and what took three months before only takes two days.
Provost, Private Research University

In the client's terms

The question

Which number is right, and who gets to decide?

The situation

Eight administrative units tracked enrolment and research metrics independently with no shared definitions. Reconciling them for IPEDS and NSF took three months of manual work a year at $2.8M in staff time, and the Department of Education had written to the provost about inconsistent reporting.

What we found

The reconciliation was an annual re-enactment of an argument nobody had ever settled. Eight units were each right by their own definition, and the federal submission was the only place the disagreement became visible.

What it produced

All 42 definitions were agreed by week 8 and the reporting pipelines were automated by week 20. Federal reporting labour fell from $2.8M a year to $320K and the cycle from three months to two days. The Department of Education warning was resolved and the next compliance review returned no findings.

The roadmap

Representatives from all eight units worked through 42 metrics covering enrolment, research and financial aid until each had one definition. A certified metrics layer went into the existing warehouse, and IPEDS and NSF reporting were automated against it rather than assembled from it.

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