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IRS announces procurement research partnership to improve contracting processes

Monday, November 23, 2020


WASHINGTON — The Internal Revenue Service’s Office of the Chief Procurement Officer today announced a research partnership with Data and Analytic Solutions, a small business located in Fairfax, Virginia. The partnership also includes a group of academic researchers with a goal to use data science to improve IRS procurement operations.

The effort will bring together a multi-disciplinary team comprised of procurement practitioners as well as university professors and students with procurement and machine learning experience. Machine learning is a form of artificial intelligence that allows computers to become more accurate at predicting outcomes without being explicitly programmed.

“As with many agencies, we have a wealth of data available to us to understand where time is being spent in our contracting process,” said Shanna Webbers, IRS Chief Procurement Officer. “The intent of this research project is to enable us to hone-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.”

One topic that researchers will examine is the length of time it takes to award a government contract. New regulations have standardized the lead time necessary to finalize a new contract procurement. That has resulted in the largest ever dataset on timeframes for federal contract awards. Using this information, researchers plan to examine nearly half a million contracts looking for ways to improve the process.

Overall, the goal is to enable federal agencies to buy mission-critical services at a speed similar to the private sector’s contracting process. The IRS research partnership is intended to better understand the key factors impacting the time it takes to award contracts and how to execute contracts more efficiently.

The team will also try to improve the accuracy of an algorithm that predicts when individual procurement requests will become signed contracts. The partnership also plans to train contracting officials on best practices and grow a talent pipeline of acquisition professionals with data expertise.


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