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Evaluating Facility Management and Operational Efficiency

Christiana Lee

27 Feb 2026

Challenge

Vendors supporting facility operations (e.g., janitorial, HVAC, fire, and life safety) must abide by standard operating procedures. Auditors perform and report on hundreds of inspections. Procurement Managers face major challenges in reviewing these reports, especially when it comes to aggregating the sentiments in the various textual responses entered by Auditors. Having to read all the textual responses is time-consuming. Procurement Managers need a data-informed approach to make smarter decisions about vendors.


AI-Enabled Solution



Our solution enables Procurement Managers to evaluate the sentiment of every textual inspection finding and utilize aggregated scores to compare vendor performance objectively.


  • Guidance is provided to the LLM performing sentiment analysis:

    • Which findings are actionable

    • How to evaluate “positive” and “negative” sentiment

    • Directives on what to include and exclude from the output

  • AI sentiment is generated by feeding the Large Language Model (LLM) with three inputs:

    • Inspection form question

    • Textual response (entered by Auditor)

    • Question Instructions (help for that specific question) 



Example: Chemical Safety using AI-Enabled Solution

The Fortune 500 company using the solution has vendors working across numerous sites (work areas). For this example, we focus on chemical safety, which ensures vendors have proper procedures for limiting hazardous exposure and handling waste.


Auditor

An auditor is on site to complete inspection forms for each relevant vendor (e.g., janitorial, HVAC, fire, and life safety).

Procurement

Manager

A Procurement Manager analyzes completed inspection forms for recurring issues in documentation, training, and implementation. Negatively flagged keywords signal potential risks and are reviewed to assess whether corrective action is needed.


Below is a sample Manager dashboard comparing 3 vendors.



Below is the granular-level sentiment analysis performed once Auditors have completed the assessment.



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