Glossar

Predictive analytics refers to the analysis of historical and current data to predict future developments, events, or behaviors. Using statistical methods and artificial intelligence, forecasts are generated that enable informed decisions and forward-looking planning.

In logistics, predictive analytics is used to identify demand, delivery times, maintenance intervals, and capacity utilization at an early stage. Analyzing large volumes of data from sensors, ERP, WMS, and TMS systems helps prevent bottlenecks, optimize resource allocation, and continuously improve processes. This enables companies to increase their efficiency and respond more quickly to changes.

Practical example:
A logistics service provider analyzes shipping data from previous years to predict seasonal order peaks and plan staffing and vehicle capacity in a timely manner.

See also: Big Data, Industry 4.0, Artificial Intelligence (AI), Machine Learning, Predictive Maintenance, Supply Chain Management, Warehouse Management System (WMS)