Procurement Glossary
Optimal order quantity: definition, calculation and strategic importance in Procurement
November 19, 2025
The optimum order quantity is a central concept in procurement logistics that determines the most cost-efficient quantity for an individual order. It optimally balances order costs and storage costs and minimizes the overall costs of warehousing. Find out below how the optimum order quantity is calculated, which methods are used and what strategic advantages it offers in modern Procurement .
Key Facts
- Minimizes the sum of ordering and storage costs through mathematical optimization
- Based on the classic EOQ formula (Economic Order Quantity) by Ford Harris
- Takes into account annual requirements, order costs per transaction and inventory cost rate
- Reduces capital commitment and optimizes stock turnover while ensuring security of supply
- Automatically calculated and continuously adjusted by modern ERP systems
Contents
Definition: Optimal order quantity
The optimum order quantity is the quantity of an item that minimizes the total costs of ordering and storage costs for an order.
Basic components of order quantity optimization
The calculation of the optimum order quantity is based on three main cost factors:
- Ordering costs: Fixed costs per order process (personnel, administration, transportation)
- Storage costs: Variable storage costs (interest, rent, insurance, shrinkage)
- Annual requirement: Forecasted consumption quantity of the item per year
EOQ formula vs. extended models
While the classic EOQ formula assumes constant parameters, modern approaches take quantity discounts, fluctuating demand and delivery times into account. The order point method supplements the optimum order quantity with the time aspect of order triggering.
Importance of the optimum order quantity in Procurement
In strategic order management, the optimal order quantity enables data-based decision-making. It supports purchasers in reducing stock levels without jeopardizing security of supply and helps to optimize working capital efficiency.
Methods and procedures
The optimum order quantity is determined using various mathematical and analytical methods, which are adapted depending on the company context.
Classic EOQ calculation
The Economic Order Quantity is calculated using the formula EOQ = √(2 × annual requirement × order costs / inventory cost rate). This method is suitable for items with constant demand and stable cost structures.
- Determination of the annual order costs per item
- Calculation of the inventory cost rate (typically 15-25% of the value of the goods)
- Application of the EOQ formula with current parameters
ABC analysis and segmentation
The combination with the ABC analysis enables differentiated order quantity optimization. A-items receive a precise EOQ calculation, while C-items are processed using simplified procedures. Master data management provides the necessary article classifications.
Dynamic adjustment procedures
Modern ERP systems use machine learning to continuously optimize order quantities. These processes take into account seasonal fluctuations, trend developments and supplier performance. Integration into e-procurement systems enables automated order triggering when the optimum order point is reached.
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Important KPIs for optimal order quantities
The success of order quantity optimization is measured using specific key figures that evaluate both the efficiency and effectiveness of procurement.
Inventory turnover rate and capital commitment
Inventory turnover measures how often the average stock level is turned over per year. An optimized order quantity should lead to higher stock turnover while maintaining security of supply.
- Stock turnover rate = annual consumption / average stock level
- Capital commitment rate = capital tied up / total sales
- Average storage period in days
Order frequency and process costs
The number of order processes per year and the associated process costs show the efficiency of order quantity optimization. An order quantity that is too low leads to frequent, costly orders.
Service level and degree of availability
The availability level measures how often an item is available when needed. Optimal order quantities must not jeopardize the security of supply. The incoming goods inspection documents the actual delivery quantities and qualities, which are included in the KPI calculation.
Risks, dependencies and countermeasures
The use of optimal order quantities entails various risks that can be minimized by taking appropriate measures.
Forecast inaccuracies and fluctuations in demand
Incorrect demand forecasts lead to suboptimal order quantities and can cause stock shortages or overstocks. Seasonal fluctuations and unforeseen market changes exacerbate this problem.
- Implementation of rolling forecasts with regular updates
- Use of safety stocks to cushion forecast uncertainties
- Establishment of flexible framework orders with suppliers
Cost parameter changes
Fluctuating order costs, inventory costs or interest rates can affect the validity of calculated optimal order quantities. Particularly volatile markets require frequent recalculations of the EOQ parameters.
Supplier dependencies and supply risks
Focusing on cost-optimized order quantities can lead to supply risks being neglected. Single-source strategies increase this danger. Countermeasures include diversifying the supplier base and integrating risk costs into the order quantity calculation. The dual control principle for critical ordering decisions also increases security of supply.
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Practical example
A mechanical engineering company optimizes the order quantity for standard screws with an annual requirement of 50,000 pieces. The ordering costs amount to 80 euros per transaction, the inventory cost rate is 20% of the value of goods of 0.50 euros per screw. The EOQ calculation results in √(2 × 50,000 × 80 / (0.50 × 0.20)) = 8,944 pieces. By switching from monthly orders (4,167 units) to the optimum order quantity, the company reduces its total annual costs by 15% and improves planning reliability at the same time.
- Reduction in order frequency from 12 to 5.6 orders per year
- Reduction in total costs from 1,200 to 1,020 euros per year
- Improvement in stock turnover rate by 8%
Current developments and effects
Digitalization and the use of artificial intelligence are revolutionizing the calculation and application of optimal order quantities in modern procurement.
AI-supported demand forecast
Artificial intelligence significantly improves the accuracy of demand forecasts. Machine learning algorithms analyze historical consumption data, external factors and market trends to determine more precise annual requirements. This leads to more stable optimal order quantities and reduces the risk of over- or understocking.
Real-time optimization through IoT
Internet-of-Things sensors enable continuous monitoring of stock levels and consumption rates. This real-time data flows into the order quantity calculation and enables dynamic adjustments. Integration with spend analysis tools creates additional transparency regarding cost trends.
Sustainability aspects in order quantity optimization
Environmental factors are becoming increasingly important in order quantity planning. CO2 costs for transport and storage are increasingly being integrated into optimization models. Companies are developing "green" EOQ models that take ecological effects into account alongside traditional cost factors and support sustainable procurement strategies.
Conclusion
The optimal order quantity is a proven tool for cost optimization in procurement that is continuously being developed using modern technologies and AI-supported processes. It enables a data-based balance between ordering and storage costs and helps to improve working capital efficiency. Companies that systematically apply and regularly adjust optimal order quantities achieve demonstrable cost savings and improve their competitiveness. Integration into modern ERP and e-procurement systems makes order quantity optimization a strategic success factor in digital Procurement.
FAQ
What is the optimum order quantity and how is it calculated?
The optimum order quantity is the quantity that minimizes the sum of order and storage costs. It is calculated using the EOQ formula: √(2 × annual requirement × ordering costs / inventory cost rate). This mathematical optimization optimally balances the opposing cost types and reduces the total cost of procurement.
What factors influence the optimum order quantity?
Three main factors determine the optimum order quantity: the forecast annual requirement, the fixed order costs per transaction and the inventory cost rate. In addition, quantity discounts, minimum order quantities, storage capacities and shelf life restrictions can influence the practical implementation and make adjustments to the theoretically optimal quantity necessary.
How often should the optimum order quantity be checked?
The review should be carried out at least quarterly, or monthly in the case of volatile markets or critical items. Automated ERP systems can make continuous adjustments. Significant changes in demand forecasts, cost structures or supplier conditions require an immediate recalculation of the optimum order quantity.
What are the advantages of using optimal order quantities?
Optimal order quantities reduce the overall costs of procurement, improve liquidity by tying up less capital and increase planning reliability. They support data-based decision-making in Procurement and create transparency regarding actual procurement costs. They also enable a better negotiating position with suppliers thanks to predictable order volumes.
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