The IRS Office of the Chief Procurement Officer has partnered with Data and Analytic Solutions of Fairfax, Virginia, and with academic researchers to use data analysis to improve IRS procurement operations.
The team will consist of procurement practitioners as well as university professors and students with procurement and experience in machine learning, a form of artificial intelligence that allows computers to better predict outcomes without being explicitly programmed.
“We have a wealth of data available to us to understand where time is being spent in our contracting process,” said the IRS’s chief procurement officer, Shanna Webbers. “The intent of this research project is to enable us to home in on key factors impacting our time to award and identify tools that can be utilized to make process improvements to shorten our lead time, more effectively allocate our human resources and better serve our customers.”
New regulations have standardized the lead time necessary to finalize a new contract procurement – resulting in the largest dataset ever on timeframes for federal contract awards. Researchers plan to examine nearly half a million contracts for ways to improve the process. They also look to train contractors on best practices and try to improve an algorithm that predicts when individual procurement requests will become signed contracts, among other moves.