Pricing Analytics for Rotable Spare Parts

Omar Besbes (), Adam N. Elmachtoub () and Yunjie Sun ()
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Omar Besbes: Columbia Business School, New York, New York 10027
Adam N. Elmachtoub: Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027; Data Science Institute, Columbia University, New York, New York 10027
Yunjie Sun: Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027

Interfaces, 2020, vol. 50, issue 5, 313-324

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 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orinte:v:50:y:2020:i:5:p:313-324

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