Yearly Incident Procurement Classification Report
Description
As part of planning for the upcoming fire season, all previous year incident-related procurements are categorized manually. This is a time-consuming process and humans may not be able to identify more nuanced, purchasing patterns.
Detailed example
The outputs are classification numbers representing common purchase categories identified by procurement staff.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
b) Pilot – The use case has been deployed in a limited test or pilot capacity.
Expected benefit
The goal is to identify patterns and cost savings opportunities for purchases in the upcoming fire season, which in turn could lead to quicker resource allocation to incident locations.
Controls / human review
ATO: No; PIA: Not published
Data needed
Training data inputs were item descriptions (i.e. protective work gloves) of purchases from 2023. Validation data was human-labeled item categories from the same year.