Eli Lilly and Company Uses Integer Programming to Form Volunteer Teams in Impoverished Countries

Stephen Mahar (), Wayne Winston () and P. Daniel Wright ()
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Stephen Mahar: Department of Management and Operations, Villanova School of Business, Villanova University, Villanova, Pennsylvania 19085
Wayne Winston: Department of Operations and Decision Technologies, Kelley School of Business, Indiana University, Bloomington, Indiana 47405
P. Daniel Wright: Department of Management and Operations, Villanova School of Business, Villanova University, Villanova, Pennsylvania 19085

Interfaces, 2013, vol. 43, issue 3, 268-284

Abstract: Each year, Eli Lilly and Company (Lilly) offers its worldwide employees the opportunity to participate in paid volunteer teams serving communities in impoverished countries. The company’s Connecting Hearts Abroad service program gives employees a unique opportunity to take part in service trips aimed at improving global health. Lilly annually offers about 23 trips, enabling employees to serve some of the world’s most resource-constrained regions where people lack basic resources or access to healthcare. A selection committee at Lilly manually forms volunteer teams from a large pool of applicants. Unfortunately, the manual selection process is time consuming and often fails to meet employee preference or adequately represent some applicant groups. This paper describes how we developed a mathematical programming model to improve Lilly’s process of volunteer selection. We incorporated the model into a decision support tool that assigns applicants to volunteer assignments and maximizes the chosen volunteers’ preferences under constraints that help ensure fair team compositions. Running the model against the prior year’s applicant data pool took less than two minutes to configure teams such that all volunteers received their first-choice assignment. The automated decision support system also provides a more consistent method of configuring teams that appears fair to the applicants.

Keywords: integer programming; decision analysis; preference application; healthcare (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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