<ul data-eligibleForWebStory="true"><li>This paper introduces a new method for identifying the root causes of delivery risks in supply chains by combining causal discovery with reinforcement learning.</li><li>Traditional approaches to root cause analysis struggle to handle the complexity of supply chains, often resulting in misleading correlations and suboptimal decisions.</li><li>The proposed approach utilizes causal discovery to reveal true causal relationships among operational variables and reinforcement learning to refine the causal graph.</li><li>This method accurately identifies key factors contributing to late deliveries, including shipping methods and delivery statuses, offering insights to enhance supply chain performance.</li><li>The technique is tested on a real-world supply chain dataset, showcasing its effectiveness in pinpointing reasons for delivery delays and suggesting ways to mitigate risks.</li><li>The study's outcomes carry substantial implications for enhancing operational efficiency, customer satisfaction, and financial gains in supply chain operations.</li></ul>

Root Cause Attribution of Delivery Risks via Causal Discovery with Reinforcement Learning

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