The Internal Revenue Service is pairing up with a Virginia research firm in an effort to improve the agency’s procurement operations.

Data and Analytic Solutions of Fairfax, Va., will team up with the IRS and a group of academic researchers with a shared goal of using data science to better understand and streamline the procurement process—the process the government uses to purchase goods and services from outside vendors.

Time for a team approach?

The effort will bring together a multi-disciplinary team made up of procurement practitioners, university professors and students with procurement and machine learning experience. Machine learning is a form of artificial intelligence that makes computers more accurate at predicting outcomes without being specifically 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."

Time is money!

One topic on the top of the researchers’ list is the length of time it takes to award a government contract.

New regulations have standardized the lead time needed to finalize a new contract procurement, resulting in the largest-ever set of data on timeframes for federal contract awards. Researchers plan to use this information to examine nearly a half-million contracts as they look for ways to improve the overall process.

The overall goal is to find the right process so that federal agencies can buy the mission-critical goods and services it needs at roughly the same speed as private industry.

The main intent of the research is to better understand key factors that impact the time it takes to award contracts and how to execute contracts more efficiently.

In addition, 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 the officials tasked with processing and executing contracts on the best practices of the process. Also in the works: a talent-hiring “pipeline” that can provide a steady stream of contact and resume information on acquisition professionals with data expertise.

Source: IR-2020-261