What should we reorder and when?
Use expected demand, lead time and uncertainty to decide reorder timing and quantity.
Inventory Optimization · Forecast to Action
A demand forecast is not an inventory decision.
Use forecast distributions, lead times, service targets and operating constraints to decide what to reorder, allocate or hold, including where inventory should sit across warehouses and stores.
Questions this decision model answers
Start with the commercial or operational choice.
Where should scarce stock go?
Prioritise locations, channels or customers when available inventory cannot satisfy every forecast.
How much safety stock is justified?
Balance service targets against inventory cost and the cost of stockouts.
Where should inventory sit across the network?
Decide how much stock belongs centrally, regionally or at store level when service, lead times, transport frequency and working capital pull in different directions.
Which stock should move between locations?
Recommend transfers between warehouses, stores or channels when the expected stockout, markdown or service benefit justifies transport and handling cost.
Which SKUs need attention now?
Rank inventory exceptions by expected business consequence rather than presenting another long alert list.
From data to decision
Connect demand uncertainty to an executable stock action.
The decision layer uses the forecast as an input, then adds economics, service targets and constraints.
Estimate demand and uncertainty
Forecast demand at the product and location level needed for the stock decision.
Add cost and service objectives
Include margin, carrying cost, stockout cost, service targets and lead times where available.
Model operating limits
Respect inventory capacity, minimum order quantities, supply limits and allocation rules.
Recommend reorder or allocation
Return the reorder, allocation or transfer action, expected impact and the assumptions that drove it.
Decision boundary
The same forecast can support several different inventory decisions.
A forecast says what demand is likely to be. The inventory decision depends on service level, cost, lead time, stock position and supply constraints. That is why forecast accuracy alone does not determine the best reorder or allocation.
What demand is likely?
Estimate future demand and uncertainty.
What is feasible?
Apply stock, supply, lead-time and order constraints.
What should move?
Choose reorder, allocation, transfer or safety-stock actions against the business objective.
Related decision problems
Follow the decision chain.
Direct answers
Questions buyers ask about this decision.
Is inventory optimization the same as demand forecasting?
No. Forecasting estimates future demand. Inventory optimization decides what stock action to take given demand, uncertainty, service goals, costs and constraints.
Can it work at SKU-store level?
Yes, when the underlying demand and operational data are reliable enough at that level.
Can it include service-level targets and lead times?
Yes. These are central inputs when the goal is to balance stock availability against working capital and stockout risk.
What is multi-echelon inventory optimization (MEIO)?
MEIO treats inventory across warehouses, regional nodes and stores as one network decision rather than optimising each location independently. The goal is to place safety stock where it protects service most efficiently while accounting for lead times, replenishment frequency, minimum order quantities, transport or expediting cost and working capital.
Can inventory optimization recommend transfers between warehouses or stores?
Yes. When location-level inventory, demand, transfer lead times and costs are available, the decision can compare doing nothing with moving stock between nodes. The objective can include stockout risk, markdown exposure, service level, capacity, transport cost and handling constraints.
What does the model return?
Typical outputs include reorder quantities, allocation priorities, stock-transfer recommendations, safety-stock and network-placement recommendations, exception rankings and expected service or economic impact.
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Bring the decision, constraints and data you already have.
We will structure the model around the action your team needs to take and the evidence required to support it.