Business problem
German and European planning teams need transparent reorder rules that balance service level, supplier lead time, demand variation, and inventory cost.
Germany & Europe Inventory Case Study
Inventory Optimization Project
A working replenishment model for German distribution and industrial spare-parts scenarios. It connects demand variability, supplier lead time, service level, stock cover, safety stock, reorder point, EOQ, and inventory cost.
Portfolio model using transparent formulas and illustrative sample data. It is not connected to a live company ERP system.
Current planning output
Inventory position stable
Reorder point
1.157 units
Safety stock
149 units
Recommended order
735 units
Stock cover
15.0 days
Optimization brief
Inventory position stable
Maintain the current replenishment rule and review demand variability weekly before the next supplier order.
Safety stock
149
units
Reorder point
1.157
units
EOQ
735
units/order
Orders/year
28.6
estimated
Inventory position
Current stock1.260 units
Reorder point1.157 units
Recommended order quantity735 units
Stock cover
15.0
days
Average inventory
517
units
Annual cost view
Holding cost7.231 €
Ordering cost5.143 €
Relevant inventory cost12.374 €
Costs are illustrative and exclude purchase price, transport, taxes, and shortage penalties.
Planner interpretation
Safety stock responds to demand variability, lead time, and the selected service target.
The reorder point combines expected lead-time demand with the calculated safety buffer.
EOQ balances annual ordering and holding cost to create a transparent order-size baseline.
Analytics solution
An interactive model calculates safety stock, reorder point, EOQ, stock cover, order frequency, and annual relevant inventory cost.
Business value
Supports replenishment discussions, stockout prevention, excess-stock review, and clear communication between planning, purchasing, and operations.