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Optimizing Supply Chain Resilience through Predictive Analytics: A Case Study Approach

Vishwakarama B

Abstract


In an era of increasing global uncertainty, supply chain resilience has become a crucial aspect of strategic management. This paper investigates the application of predictive analytics to enhance supply chain resilience, focusing on a case study of a multinational manufacturing firm. By integrating predictive models with real-time data, the study demonstrates how companies can proactively identify and mitigate potential disruptions. The findings reveal significant improvements in the firm's ability to anticipate supply chain risks, optimize inventory levels, and maintain continuous operations. The research highlights the critical role of advanced analytics in transforming traditional supply chain management practices, offering actionable insights for practitioners and scholars alike.


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References


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