Housing Office Assistant @ Georgia Tech

Overview

I transformed a standard administrative role into a data-driven operations study, using SQL analysis to identify bottlenecks in maintenance ticket lifecycles and improving student service response times by 15%.

Since my freshman year, I have worked with the Housing Office to manage the logistical needs of on-campus residents. While the role began with standard administrative duties, I identified an opportunity to apply my Systems Engineering coursework to a real-world problem: the inconsistency of maintenance request fulfillment. My goal was to move our team from a reactive posture (putting out fires) to a proactive one (optimizing workflows), using the maintenance log data we generated every day to uncover root causes of delay.

Learning and Growth

This role was my first practical experience in Process Improvement and Queueing Analysis. The core problem was that while we had plenty of data on maintenance issues (200+ active tickets), it was unstructured and underutilized. I took the initiative to export this data and query it using SQL, performing a cohort analysis to track the "lifespan" of different ticket types (e.g., plumbing vs. HVAC).

This taught me that data analysis is useless without Operational Context. My SQL queries showed where delays were happening, but I had to collaborate with the maintenance staff and area managers to understand why. I discovered that specific "hand-off" points between departments were the primary bottlenecks. I presented these findings to leadership, recommending adjustments to our Service Level Agreements (SLAs). This collaborative approach led to a 15% reduction in average response time, directly improving the quality of life for residents.

Takeaway

I learned that you don't need a formal "Analyst" title to drive operational efficiency and that opportunities for optimization exist in every organization if you look closely enough at the data. It bridged the gap between the theoretical queueing models I study in class and the messy reality of logistics. I gained confidence in my ability to spot inefficiencies, quantify them with code, and communicate solutions to non-technical staff to get results.