Supply Chain Analytics

如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，以应对快速变化的环境和不断增长的客户期望。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 * 分析来改变规划和执行过程，并弥合该领域学者和从业者之间的差距。* 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，并创建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.