CONSIDERING DATA QUALITY FOR DATA SCIENCE, PREDICTIVE ANALYTICS, AND BIG DATA APPLICATIONS IN SUPPLY CHAIN MANAGEMENT

摘要

Today's supply chain professionals are inundated with data, motivating new ways of thinking about how data are produced, organized, and analyzed. This has provided an impetus for organizations to adopt and perfect data science, predictive analytics, and big data (DPB) functions in order to enhance supply chain processes and, ultimately, performance. However, the decisions made as a result of DPB are only as good as the data on which they are based. In this presentation, we introduce the data quality problem in the context of DPB for supply chain management (SCM) and highlight interdisciplinary research topics based on complementary theory.