Supply chain analytics helps to make data-driven decisions, based on patterns and insights from the massive amounts of data from applications tied to the supply chain, such as procurement, inventory, order, warehouse, and transportation management.
Types of supply chain analytics including descriptive analytics, which provides visibility and a single source of truth across the supply chain; predictive analytics, which helps an organization understand the most likely outcome or future scenario and its business implications; prescriptive analytics, which helps organizations solve problems and collaborate for maximum business value; and cognitive analytics, which helps an organization answer complex questions in natural language.
Supply chain analytics enables to reduce costs and improve margins, better understand risks, increase accuracy in planning. It can also help companies identify where they’re vulnerable and how to avoid preventable problems, find ways to solve problems when they do occur, and uncover opportunities to streamline the supply chain to improve it even further.