Pricing Analytics for Rotable Spare Parts

Forthcoming, INFORMS Journal on Applied Analytics

Columbia Business School Research Paper Forthcoming

29 Pages Posted: 6 Nov 2019 Last revised: 14 Apr 2020

See all articles by Omar Besbes

Omar Besbes

Columbia University - Columbia Business School, Decision Risk and Operations

Adam N. Elmachtoub

Department of Industrial Engineering and Operations Research & Data Science Institute, Columbia University

Yunjie Sun

affiliation not provided to SSRN

Date Written: October 28, 2019

Abstract

In this paper, we describe a comprehensive approach to pricing analytics for reusable resources in the context of rotable spare parts, which are parts that can be repeatedly repaired and resold. Working in collaboration with a major aircraft manufacturer, we aim to instill a new pricing culture and develop a scalable new pricing methodology. Pricing rotable spare parts presents unique challenges ranging from complex inventory dynamics and minimal demand information to limited data availability. We develop a novel pricing analytics approach that tackles all of these challenges and that can be applied across all rotable spare parts. We then describe a large-scale implementation of our approach with our industrial partner, which led to an improvement in profits of over 3.9% over a 10-month period.

Keywords: price optimization, reusable resources, rotable spare parts, large-scale implementation, analytics

Suggested Citation

Besbes, Omar and Elmachtoub, Adam and Sun, Yunjie, Pricing Analytics for Rotable Spare Parts (October 28, 2019). Forthcoming, INFORMS Journal on Applied Analytics , Columbia Business School Research Paper Forthcoming, Available at SSRN: https://ssrn.com/abstract=3476437 or http://dx.doi.org/10.2139/ssrn.3476437

Omar Besbes

Columbia University - Columbia Business School, Decision Risk and Operations ( email )

New York, NY
United States

Adam Elmachtoub (Contact Author)

Department of Industrial Engineering and Operations Research & Data Science Institute, Columbia University ( email )

535G S.W. Mudd Building
500 West 120th Street
New York, NY 10027
United States

HOME PAGE: http://www.columbia.edu/~ae2516/

Yunjie Sun

affiliation not provided to SSRN

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