The Problem

University Residence Life operations involve a continuous flow of routine queries — duty scheduling questions, policy lookups, workflow confirmations — that land on staff at unpredictable times, including nights and weekends when the standard support structure isn't available. The cost of these interruptions compounds: staff time, delayed responses, and operational inconsistency.

At the same time, planning and scheduling data lived in formats that made weekly and monthly strategy meetings more reactive than proactive. Reports were manually assembled, and the time spent preparing them reduced the time available for the decisions they were supposed to support.

The Solution

In my role as AI & Business Intelligence Analyst at OU Residence Life, I built two interconnected systems to address these problems:

AI Chatbot for Duty-Staff Queries

A custom chatbot using the OpenAI GPT API, trained on Residence Life documentation — policy documents, duty protocols, scheduling guides, and procedural references. The chatbot provides 24/7 access to accurate, document-grounded answers for duty-staff questions without requiring human intervention for routine queries.

Training the NLP model on Residence Life–specific documentation was essential: general-purpose AI responses aren't reliable enough for operational queries where getting a procedure wrong has real consequences. Anchoring the model to actual documentation kept responses accurate and auditable.

Tableau and Excel Dashboards

I designed a suite of Tableau and Excel dashboards that surfaced key operational data — staffing patterns, scheduling metrics, duty coverage analysis — in a format accessible for weekly planning cycles. The dashboards replaced manual report assembly with automated data pipelines feeding directly into the visualization layer.

Roompact Workflow Automation

I also configured automated workflows within Roompact, OU's residence management platform, to reduce manual steps in routine administrative processes.

Outcomes

From my role at OU Residence Life:

  • Strategy planning time reduced by 15% through more efficient dashboard-driven preparation
  • Scheduling efficiency boosted by 30% through better data visibility and automation
  • 24/7 duty-staff query resolution without manual escalation for routine questions
This project does not have a public GitHub repository. The work involves internal university systems and documentation that are not publicly shareable.

Tools

  • OpenAI API — GPT-based chatbot engine
  • Python — backend integration and data processing
  • Tableau — operational dashboards and planning visualizations
  • Excel — supplementary reporting and scheduling data
  • Roompact — workflow automation for residence management processes