Supply Chain Risk Mitigation: Modeling an Approach for Greater Visibility in Moroccan Automotive Industry

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Abstract

Managing the customer-supplier relationship in procurement has always been characterized by its complexity, especially during crises. Large enterprises manage to mitigate risk thanks to their ability to adopt high-performance tools that ensure real-time visibility across their entire supply chain (SC). In contrast, small and medium-sized firms struggle to adapt. This study examines visibility enhancement strategies in emerging automotive markets taking the Moroccan model as a leading example, revealing that there are effective technological tools that are not accessible or widely adopted by most companies. To fill this gap, this study presents a conceptual architecture of a decision support tool that will assist manufacturers and researchers alike in achieving better visibility of their supply chain and identifying capacity risks based on the trilogy of customer, Tier I, and Tier II suppliers. Findings reveal that managing risk in the supply chain requires a multifaceted approach. Firstly, it identifies crucial measures such as establishing backup suppliers and planning overtime based on stakeholders' responsibilities, which are essential for mitigating risk. Secondly, the study proves that risk localization within the supply chain is feasible, enabling companies to target their risk management efforts more effectively. Finally, it underscores the significance of monitoring supplier performance through a dedicated key risk indicator (KRI) called supplier risk follow-up (SRF-U), ensuring that suppliers meet performance standards. These findings collectively provide a comprehensive strategy for improving supply chain resilience (SCR) and efficiency. This study implements a short-term solution, increases visibility, and responds quickly to complicated crises.

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APA

Lehmam, S., & El Hassani, H. (2024). Supply Chain Risk Mitigation: Modeling an Approach for Greater Visibility in Moroccan Automotive Industry. Journal Europeen Des Systemes Automatises, 57(3), 757–766. https://doi.org/10.18280/jesa.570313

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