BuySmarter

Lori Ruderman ,
Lori Ruderman

BuySmarter PMO

Kenneth Thomson
Kenneth Thomson

HHS, Office of the Assistant Secretary of Administration

Published: 29.11.2018.

Volume 1, Issue 1 (2018)

Abstract

Session Description: BUYSMARTER is a transformative, data-driven initiative leveraging the collective purchasing power ($24B/year) of the U.S. Department of Health and Human Services (HHS) to secure lower prices, achieve operational efficiencies, and generate cost savings on goods and services.

 
BUYSMARTER ‘s proof of concept used Artificial Intelligence (A.I.) technology to analyze departmental requirements based on current HHS-wide spend data. This helps identify opportunities to consolidate contract vehicles across agencies within HHS to leverage overlapping requirements at a significant cost savings for the federal government.
 
BUYSMARTER is positive initiative that is driving cultural change in support of HHS Reimagine. It is intended to focus on utilization of new and emerging technologies, like artificial intelligence and robotics, to analyze spend across HHS to make better informed decisions about price conscious purchasing in order to achieve:
•    Collaborative, collective, and coordinated forecasting across HHS that leverages buying power to generate savings through bulk purchasing and effective spend tracking
•    Organizational alignment that eliminates waste and risk through improved transparency and accountability
•    An acquisition organizational structure that is cohesive across HHS and operates in an efficient and effective

Citation

Copyright

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 

Article metrics

Google scholar: See link

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Most read articles