Optimale Bestellmenge

What is the optimal order quantity?

The optimal order quantity refers to the order size at which the total costs of two opposing cost components – ordering costs and inventory holding costs – reach their minimum. The larger an order, the less frequently orders need to be placed and the lower the fixed ordering costs per unit. At the same time, however, the average inventory level rises, increasing capital tied up in stock, storage space requirements, and inventory risk. The optimal order quantity is calculated at exactly the point where both effects balance each other out.

The EOQ model as a calculation basis

The most widely used method is the classic EOQ model (Economic Order Quantity). It assumes a constant, uniform demand and requires three input variables: periodic demand, fixed costs per order, and the inventory holding cost rate per unit per time period. The latter typically includes capital carrying costs, storage space costs, insurance, and shrinkage and spoilage. The model provides a simple formula that can be calculated quickly and is built into many ERP and planning systems.

It is important to understand that the EOQ model is a simplified calculation model. It assumes, among other things, that demand and lead times are stable, that no price breaks apply, and that no minimum order quantities (MOQ) are imposed by the supplier. In practice, these assumptions regularly deviate from reality, which is why the result should always be treated as a starting point rather than a fixed requirement.

Practical application and influencing factors

When applying the model in practice, you should consider the following aspects:

• Price breaks: Supplier discounts for larger quantities may make it worthwhile to order beyond the calculated optimal quantity. A comprehensive cost analysis is required here that evaluates purchase price, holding costs, and ordering costs together.
• Minimum order quantities and packaging units: Many suppliers specify MOQs or fixed pack sizes that override the model's result and force an adjustment.
• Demand fluctuations: When demand is volatile or follows seasonal patterns, the basic model loses its predictive value. Supplementary safety stocks and dynamic replenishment methods are then more appropriate.
• Actual holding costs: Often only direct costs are included. Capital carrying costs and opportunity costs tend to be underestimated in practice, leading to systematically inflated order quantities.

Modern planning systems calculate the optimal order quantity automatically, but allow correction factors for MOQs, delivery cycles, and tiered pricing. The quality of the result depends directly on the currency of master data – outdated cost rates or incorrect demand forecasts will significantly distort the outcome.