Data Science, Predictive Analytics, and Big Data in Supply Chain Management: Current State and Future Potential
基于对供应链管理专业人士的大规模调查和一所研究型大学预测分析硕士项目的经验，评估了预测分析在供应链中的使用现状、动机、收益和障碍，并指出了数据科学家所需技能及课程设计方向。
While data science, predictive analytics, and big data have been frequently used buzzwords, rigorous academic investigations into these areas are just emerging. In this forward thinking article, we discuss the results of a recent large‐scale survey on these topics among supply chain management ( SCM ) professionals, complemented with our experiences in developing, implementing, and administering one of the first master's degree programs in predictive analytics. As such, we effectively provide an assessment of the current state of the field via a large‐scale survey, and offer insight into its future potential via the discussion of how a research university is training next‐generation data scientists. Specifically, we report on the current use of predictive analytics in SCM and the underlying motivations, as well as perceived benefits and barriers. In addition, we highlight skills desired for successful data scientists, and provide illustrations of how predictive analytics can be implemented in the curriculum. Relying on one of the largest data sets of predictive analytics users in SCM collected to date and our experiences with one of the first master's degree programs in predictive analytics, it is our intent to provide a timely assessment of the field, illustrate its future potential, and motivate additional research and pedagogical advancements in this domain.