Safety Stock Level Optimization uses AI to compute the optimal safety stock quantity per material and location that minimises holding cost while meeting a defined service level target, enabling systematic reduction of excess buffer stock without increasing stockout risk, by solving a stochastic inventory optimisation across demand and lead-time uncertainty distributions, across materials planning and inventory management workflows.
Materials planners set safety stock levels using fixed-days-of-supply rules that do not adapt to changes in demand variability or supplier lead-time uncertainty. High-variability materials are under-buffered (causing stockouts) while low-variability items are over-buffered (tying up working capital unnecessarily).
The AI estimates demand variability and supplier lead-time uncertainty per material and location, and solves for the safety stock quantity that achieves the target service level at minimum holding cost. Outputs are updated periodically as variability patterns change and fed directly into the planning system.
Inventory holding cost decreases; service level on safety-stocked materials improves.
No intrinsic risk triggered.
No controls triggered.
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