How to Predict Disruptions in the Inbound Supply Chain in a Volatile Environment

Andreas Malmstedt,Jenny Backstrand

SPS 2022(2022)

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摘要
The most common solutions to protect the supply chains for disruptions are increasing inventory, adding capacity, and using multiple suppliers. While these approaches in general prove to solve the disruption problem, they come with a negative effect on cost per product and cost of capital. In a highly volatile demand environment with fast pace changing technology, increasing inventory can constitute a big risk for obsolesce, hence additional measures are needed to create a competitive business advantage with such a supply chain. Furthermore, when competing about the same sources, as in the case of semiconductors, Operations Executives need to be able to respond fast when supply issues occur, in order to minimize the potential impact from a disruption. The ability to react and response to a disruption is enhanced with Supply chain risk tools utilizing the most recent technologies, such as Control Tower solutions enabling End-to End monitoring and transparency. However, even with the help of such technology, the decision maker will still be reactive and can merely respond to occurrences. To reach the next level of responsiveness, additional layer of intelligence is needed in the supply chain solution. From the available literature about Supply Chain Resilience, and similar advanced supply chain solutions, we can conclude that the main focus of research has so far been on the demand side, i.e., how to enhance forecast management. There are thus few practical and academic contributions on how to manage the supply side or more precise on how to manage the Inbound Supply Chain in a volatile business environment. The purpose of this paper is to investigate what factors that are crucial to regard when creating a proactive and responsive Inbound Supply Chain.
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关键词
Inbound Supply Chains,Responsiveness,AI,Machine learning,Algorithms
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