How to drive holistic end-to-end supply chain risk management

Jian Huang
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Jian Huang: HELLA GmbH & Co. KgaA, Rixbecker Straße 75

Journal of Supply Chain Management, Logistics and Procurement, 2020, vol. 2, issue 4, 294-306

Abstract: The constantly rising supply chain risk probabilities and increasingly negative performance impact on the supply chain force us to rethink and define an effective supply chain risk management approach. When a certain risk occurs, all internal and external stakeholders along the entire supply chain are affected. Therefore, it is essential to drive a holistic end-to-end supply chain risk management by setting up a dedicated supply chain risk management organisation with interfaces to all relevant business functions, by implementing an customised supply chain risk management process and by putting digital information technologies (eg artificial intelligence [AI]) in place in order to enable the process. The organisation builds a solid fundament and acceptance environment of the process implementation, while the process determines the strategic direction and scope of the information technologies selection. Only a clear vision, mission, strategy and roadmap can ensure and keep the enterprise-wide supply chain risk management programme running in the most efficient way. The systematic set-up of risk and business continuity management in the supply chain requires a sophisticatedly designed organisational structure and a comprehensive stakeholder management. An independent supply chain risk management organisation could be a recommended option in order to drive this strategic topic without any target conflicts between different business functions. The coverage and responsibility share between supply chain risk management and enterprise risk management must be aligned in order to use the existing enterprise-wide risk governance framework, methodology of risk quantification and risk management knowledge. A corporate supply chain risk management process defines a standard approach with roles and responsibilities and should cover the entire risk management cycle: identification, analysis and evaluation, treatment, monitoring and review. Both preventive and reactive supply chain risk management approaches should be considered and integrated as a complete concept. With advanced intelligent information technology, for example machine learning or risk management tools, the complete supply chain risk management process can be automated and digitalised. The process can be managed with minimum human effort and maximum benefit for the entire enterprise.

Keywords: supply chain risk management and resilience; supply chain transparency and visibility; business continuity; stakeholder management; enterprise risk management; machine learning; predictive analysis (search for similar items in EconPapers)
JEL-codes: L23 M11 (search for similar items in EconPapers)
Date: 2020
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