Supply Chain Analytics

当今的供应链管理在很大程度上依赖于数据分析和实时决策来应对快速变化的环境和日益增长的客户期望。加拿大供应链分析研究主席旨在通过利用运筹学(OR)和机器学习(ML)技术的预测和决策分析来改变计划和执行过程，并弥合该领域学者和实践者之间的差距。其主要目标是实现计划和实时执行的无缝集成，提供供应链弹性，并创造能够学习和适应动态环境的供应链智能。

Supply chain management nowadays relies heavily on data analysis and real-time decision making to deal with rapidly changing environments and ever-increasing customer expectations. The Canada Research Chair in Supply Chain Analytics aims to transform the planning and execution processes through predictive and decision analytics that make use of operations research (OR) and machine learning (ML) techniques, and to bridge the gap between academics and practitioners in the field. The main objectives are to enable seamless integration of planning and real-time execution, to provide supply chain resilience, and to create supply chain intelligence which learns and adapts to the dynamic environments.