Warehouse Slotting Optimization uses AI to compute the optimal storage location assignment for each SKU in the warehouse, minimising picking travel time and congestion, by solving a slot assignment problem that weighs velocity, weight, and pick frequency against location constraints, across warehouse operations and inventory management workflows.
Warehouse managers assign product storage locations based on receipt sequence and available space, not on picking efficiency. Fast-moving SKUs stored in remote locations and slow-moving SKUs blocking prime forward-pick zones create excessive picker travel time and congestion in the pick face, reducing throughput per shift.
The AI analyses SKU velocity, pick frequency, weight, and dimensional data alongside warehouse zone topology to compute an optimised slot assignment. The output is a recommended slot reassignment plan staged by zone, designed to minimise picking travel time while respecting product handling and safety constraints.
Average picks per hour increases; picker travel distance per order decreases.
No intrinsic risk triggered.
No controls triggered.
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