SlottingAnalysen

SlottingAnalysen are a set of methods used in warehousing and retail logistics to determine the optimal placement of products within storage locations. They combine historical movement and demand data with product attributes and storage constraints to produce a slotting plan that assigns SKUs to specific locations, with the aim of minimizing travel time and maximizing space utilization.

Typical inputs include annual demand, unit size and weight, case pack, handling requirements, temperature or hazard characteristics, product life cycle, and aisle or rack constraints. The output is a slotting map and a prioritized list of items for repositioning. Approaches range from velocity-based slotting, which places fast-moving items in more accessible locations, to ABC analysis and clustering, as well as optimization and simulation models. Deterministic optimization can minimize travel distance or picking time under space and service constraints, while heuristics offer practical solutions when data or computing power is limited.

The workflow generally covers data collection and cleaning, product profiling and categorization, space modeling, scenario generation (for example dedicated versus mixed storage or pick-face versus bulk), solving with an optimization or heuristic method, and pilot testing before broader rollout. Ongoing monitoring uses key performance indicators such as pick rate, travel time, order accuracy, and stock turns to assess effectiveness and guide adjustments.

Applications are common in distribution centers, e-commerce fulfillment facilities, grocery and retail stores, and pharmaceutical warehouses. Benefits typically include reduced picking time and labor costs, higher storage density, improved stock availability, and more consistent fulfillment performance. Challenges include data quality, dynamic demand and seasonality, product proliferation, and the costs associated with re-slotting and reorganization.