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Strategic Supply Chain Planning and Risk Management: Experiment of a Decision Support System Gathering Business Departments Around a Common Vision

Abstract : Strategic supply chain planning and supply chain risk management are two fields of supply chain management that are inseparable nowadays. The ability to consider risks is essential to maintain business performance. In addition, integrating the different business departments’ visions in a common business vision is necessary to properly plan the future of a company. However, it is still a challenge for companies to design and maintain a decision-making process supporting strategic supply chain decisions that integrates risk management and unify business vision across departments. This paper relates an industrial experiment as an attempt to meet this challenge. This experiment was asked by a pharmaceutical company with the aim of supporting strategic decisions regarding its network of suppliers. It led to a decision-making process including the use of a computerized information system composed of a software for computations and a business intelligence software to easily make decisions. This process was put in practice on a pilot use case with two years old data. It resulted in the identification of several decisions that could have been made if the process was in operation two years ago, which is considered as a first validation of the approach. Finally, limitations have been identified regarding the data collection, opening avenues for future research on an innovative approach combining supply chain hyperconnectivity and event-driven principles.
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Contributor : Raphaël Oger <>
Submitted on : Friday, December 20, 2019 - 4:18:19 PM
Last modification on : Wednesday, June 24, 2020 - 4:18:43 PM
Long-term archiving on: : Saturday, March 21, 2020 - 6:25:01 PM

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Raphaël Oger, Matthieu Lauras, Frederick Benaben, Benoit Montreuil. Strategic Supply Chain Planning and Risk Management: Experiment of a Decision Support System Gathering Business Departments Around a Common Vision. 8th International Conference on Industrial Engineering and Systems Management (IESM 2019), Sep 2019, Shanghai, China. p. 306-311, ⟨10.1109/IESM45758.2019.8948116⟩. ⟨hal-02384806⟩

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