Stop material shortages from becoming your #1 downtime driver.
Optimize replenishment and routes using deviations from historical behavior—then adapt plans when constraints change.
Why this matters
Typical pains
A clear view of what breaks in the real world—so the model is built for what actually happens.
Material shortages are a top driver of lost output.
Static schedules break under volatility and shortages.
Paths and buffers are optimized locally, not end-to-end.
Outcomes
What improves
A measurable way to evaluate scenario variants and the decisions you will make.
Stops due to material
down
Transport distance
optimized by scenario
WIP & buffers
rebalanced based on reality
Deliverables
What you get
A decision-ready package: model, scenarios, and an actionable rollout path.
Deliverables
- Optimized replenishment plan aligned to the production plan
- Route optimization based on actual layout constraints
- Deviation-aware simulation (scrap, delays, variability)
Recommended capabilities
Start with the minimum set needed for the outcome, then scale to historical and live data as the use-case matures.