Oakland University
Main Location: Auburn Hills and Rochester Hills, Michigan
Type: Public, Doctoral Research University
Campuses: 3
Students: ~15,768
Faculty/Staff: ~2,000
Undergraduate Programs: 132+
Graduate Programs: 138+
Founded: 1957
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Reaching Stop-Out Students at Scale with Argos

Reduced query times from 20+ minutes to under 30 seconds, saving over 40 minutes every cycle
Freed staff from manual, IT-dependent processes, enabling focus on strategic student success initiatives
Delivered faster, more reliable data to support retention and graduation planning across multiple departments

The Challenge

At Oakland University, the process of identifying and analyzing “Stop Out” students (those who had enrolled in the past but not graduated or re-enrolled) was anything but efficient. Using a legacy system, the university’s data analysis team relied on outdated queries that took over 20 minutes to run, followed by an equally long review process. In total, each Stop Out processing cycle consumed more than 40 minutes, stalling downstream departments like Student Financial Services and Transfer Services, which depended on this data to support retention strategies and graduation planning.

The legacy system came with additional pain points: slow performance, lack of scalability, and a growing risk of obsolescence. It couldn’t handle increasing demands for data-driven strategy, and operational bottlenecks were hindering broader institutional goals.

“The old process just wasn’t working for us. Waiting 40-plus minutes every cycle meant we were always behind, and it affected everyone from our team to the departments relying on this data.”
Bob Griffith

Sr. Data Analyst, Oakland University

The Solution

Oakland University turned to Argos to overhaul its Stop Out reporting process. Implementation began by recreating the core query functionality in Argos, carefully rebuilding what previously lived in the legacy system into optimized Argos reports. Within weeks, the team achieved a dramatic breakthrough as query runtime dropped from over 20 minutes to under 30 seconds, resulting in a 97% improvement.

Rather than relying on IT or external consultants, the implementation was led internally, with collaboration between Data Analyst and Registrar, and eventual support from University Technology Services to manage file uploads for the National Student Clearinghouse review.

The entire transition took about six months.

“Argos empowered us to take full control of the process. We didn’t have to wait on IT or outside help, and the results came faster than anyone expected.”
Bob Griffith

Sr. Data Analyst, Oakland University

The Results

The impact of Argos has been both immediate and significant:

  • 97% reduction in query time (from over 20 minutes to under 30 seconds)
  • Over 40 minutes saved per processing cycle
  • Ability to reallocate time from data prep to strategic analysis
  • Elimination of maintenance headaches and performance issues tied to the legacy system
  • New capacity to respond to ad hoc data requests from multiple departments

With multiple Stop Out cycles occurring throughout the year, the cumulative time savings are substantial, freeing up resources and enabling faster data delivery to teams responsible for retention and graduation pathway planning.

Even before the full rollout was complete, the move to Argos transformed a time-draining task into a streamlined, scalable process, positioning the university for deeper data engagement.

“The time savings alone have been a game changer, but the real win is how we’re able to shift our focus toward supporting students better with faster, more reliable data.”
Bob Griffith

Sr. Data Analyst, Oakland University

The Future

As Oakland University finalizes the remaining components of the Stop Out solution, the benefits of Argos continue to grow. Once the review process is complete, additional performance gains are expected, along with a smoother experience for all downstream users. More importantly, this transformation has laid the foundation for a broader cultural shift, from reactive reporting to proactive decision-making.