This episode of Techsplainers explores supply chain analytics and how organizations use data to make smarter, faster decisions across increasingly complex global operations. The episode explains how analytics brings together information from ERP systems, warehouses, transportation networks, suppliers, IoT devices and market signals to create a clearer picture of supply chain performance.

In logical flow, the discussion breaks down how supply chain analytics helps teams understand what is happening, why it is happening and what might happen next. It covers the four major types of analytics—descriptive, diagnostic, predictive and prescriptive—and shows how each supports better planning, risk management and operational efficiency. The episode also looks at how AI is expanding analytics capabilities through demand sensing, digital twins, natural language interfaces and automated decision-making.

Real-world applications include demand forecasting, supplier risk monitoring, transportation optimization, warehouse efficiency, sustainability tracking and end-to-end visibility. Along the way, the episode highlights both the benefits of better forecasting and resilience and the challenge of maintaining strong data quality across fragmented systems.

Find more information at https://www.ibm.com/think/topics/supply-chain-analytics-use-cases

Find more episodes https://www.ibm.biz/techsplainers-podcast

Narrated by Mimi Sun Longo