Multi-echelon optimization that retunes itself as demand and lead times drift - cash comes off the shelf, service stays up, and every buffer can explain what it is for.
Buffers re-solved across the whole network as demand and lead-time variability move - with the cash released and the service held shown side by side.
Safety stock solved across the whole network every week, not set once by ABC class and quietly forgotten.
See what each service point costs before you commit to it, by segment, by customer, and by node.
Where to hold generic stock and where to commit to finished goods, with the working capital difference attached.
Actual supplier and lane variability measured continuously, then fed straight back into the buffer that depends on it.
Slow-moving and expiring stock surfaced early, with the recovery play ranked while it is still worth more than the markdown.
Daily push, pull, and lateral transfer recommendations - each one carrying its freight cost and its service gain.
Network, lead times, service targets, and on-hand positions pulled from your ERP and WMS, with variability measured from history.
Buffers solved and backtested against 24 months of actuals - the cash and service trade-off quantified before go-live.
Recommended buffers flow back to your ERP under planner review. Value assessment lands with your CFO in week ten.
Inventory is not one number to cut. It is a thousand small bets, and most of them are placed at the wrong node.