Why Supply Chain is the Best Domain for Data Scientists in 2026 (And How to Learn It)

Supply chain provides an excellent domain for data scientists due to its rich problems and potential for tangible impact. Descriptive analytics can be used to bring visibility to operations, such as using warehouse heatmaps to identify congestion and improve capacity. Diagnostic analytics, employing methodologies like Lean Six Sigma and statistical tests, helps find the root causes of problems like transportation delays without relying solely on assumptions. Finally, prescriptive analytics uses optimization techniques like linear programming to solve complex problems such as supply chain network design and resource allocation to support decision-making.