A Data-Driven Educational Journey for Supply Chain Network Analytics

This article presents a data-driven educational approach for supply chain network analytics, focusing on imparting students with a deep understanding of the subject and equipping them with the skills needed for applying data analytics in supply chain management. The framework includes defining learning objectives, designing a teaching plan, selecting effective delivery methods, and allocating necessary resources. Findings demonstrate a systematic teaching approach through real-world classroom experiences and student feedback. It highlights the effectiveness of the teaching methods and tools in preparing students for careers in supply chain management and data analytics. The article offers a blueprint for instructors to create engaging and effective educational programs by incorporating real-world data and industry guest speakers and fostering student engagement. Acknowledging context-specific findings, the study recognizes variations in effectiveness across institutions, student demographics, and cultural contexts. To assess the long-term impact, further research with diverse student cohorts and global perspectives is needed. Practical implications focus on preparing students for supply chain network analytics challenges by integrating data-driven techniques, practical application, collaboration, and industry relevance. The study provides educators a blueprint to prepare students for data-driven supply chain management careers, contributing to supply chain education’s evolution.