Procurement Glossary
Lot size according to Andler: Calculating optimal order quantities in Procurement
November 19, 2025
Andler's lot size is a mathematical formula for determining the cost-optimal order quantity in procurement. This method minimizes the total costs of ordering and storage costs and forms the basis for efficient inventory planning. Find out below how the Andler formula works, which methods are used and which current developments influence lot size optimization.
Key Facts
- Mathematical formula for calculating the optimum order quantity based on annual requirements, order costs and storage costs
- Minimizes the sum of fixed ordering costs and variable storage costs by determining the cost optimum
- Basis for modern scheduling systems and inventory optimization in procurement
- Takes into account constant demand and constant delivery times as basic assumptions
- Will be further developed through digital tools and AI-supported forecasts
Contents
Definition: Lot size according to Andler
Andler's lot size describes a mathematical method for determining the cost-optimal order quantity. The model was developed by German business economist Kurt Andler and is based on minimizing the total costs of procurement and warehousing.
Basic components of the Andler formula
The calculation is based on three main cost factors:
- Annual requirement of material or products
- Fixed order costs per order
- Storage costs per unit and period
Andler formula vs. other disposition methods
In contrast to min-max control or consumption-based scheduling, the Andler formula focuses exclusively on cost optimization. While other methods take service levels or delivery time fluctuations into account, the mathematical minimization of total costs is the main focus here.
Importance of lot size according to Andler in Procurement
The method forms the foundation of modern materials planning and supports purchasing departments in strategic inventory planning. It enables data-based decision-making and reduces both capital commitment and procurement costs.
Methods and procedures
The practical application of the Andler formula requires systematic data collection and regular adjustment of the parameters. Modern ERP systems automate these calculations and integrate them into ongoing scheduling.
Calculation of the optimum order quantity
The classic formula is: Optimal order quantity = root of (2 × annual requirement × order costs / storage costs). This calculation assumes constant parameters and provides the theoretically most cost-effective lot quantity. In practice, additional factors such as minimum order quantities or discount scales are taken into account.
Data acquisition and parameter maintenance
Successful application requires precise cost data and regular updating. Scheduling parameter maintenance includes the recording of ordering costs, inventory costs and consumption data. Modern systems use historical data and forecasting algorithms for more accurate forecasts.
Integration into scheduling systems
The Andler formula is integrated into automated order proposals and combined with other replenishment methods. Automatic replenishment uses the calculated lot sizes as the basis for order recommendations, taking into account current stock situations and delivery times.
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Key figures for controlling
Measuring the success of the Andler formula requires specific metrics that evaluate both cost efficiency and operational performance. These metrics support the continuous optimization of the ordering strategy.
Cost-based performance measurement
The total cost trend from ordering and storage costs is the key performance indicator. In addition, capital commitment costs and obsolescence risks are measured. The average stock level shows the efficiency of lot size optimization and its impact on liquidity.
Service level and availability
The delivery service level measures the impact of optimized order quantities on customer satisfaction. Stockout rates and deliverability show whether the calculated lot sizes ensure sufficient availability. These metrics balance cost optimization with operational excellence.
Disposition quality and forecast accuracy
The deviation between planned and actual consumption assesses the quality of the underlying forecasts. Forecast errors and planning accuracy reveal optimization potential. Regular key figure analyses promote the continuous improvement of the ordering strategy.
Risk factors and controls for lot size according to Andler
The application of the Andler formula harbors specific risks that can arise due to unsuitable parameters or changing market conditions. Systematic controls and adjustments minimize this risk.
Limitations due to assumptions
The classic formula assumes constant demand and stable cost structures. In volatile markets, these assumptions lead to suboptimal order quantities. Fluctuating raw material prices, seasonal demand or unforeseen market changes can render the calculated lot sizes obsolete and lead to over- or understocking.
Data quality and parameter accuracy
Inaccurate or outdated cost data significantly distort the calculation results. Incorrect ordering costs, incomplete inventory costs or incorrect consumption forecasts lead to economically disadvantageous decisions. Regular inventory analyses and cost controls are therefore essential.
Liquidity and capital risks
Large lot sizes tie up considerable capital and put a strain on liquidity. In the event of product changes or a drop in demand, obsolete stocks arise with corresponding depreciation risks. A good balance between cost optimization and flexibility is crucial for sustainable corporate success.
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Practical example
A mechanical engineering company optimizes the procurement of standard screws using the Andler formula. With an annual requirement of 50,000 pieces, ordering costs of 80 euros per order and storage costs of 2 euros per piece, the optimum order quantity is 2,000 pieces. This calculation reduces the total annual costs by 15 percent compared to the previous ordering practice.
- Data collection: recording historical consumption data and cost structures
- Calculation: Application of the Andler formula with current parameters
- Implementation: Integration of the optimal lot size into the ERP system
- Monitoring: Regular checking and adjustment of parameters
Current developments and effects
The digital transformation is fundamentally changing the application of the Andler formula. AI-supported systems extend the classic model with dynamic parameters and real-time adjustments.
AI integration and machine learning
Modern scheduling systems use artificial intelligence to improve the Andler formula. Machine learning algorithms analyze consumption patterns, seasonality and external influencing factors. These technologies automatically adjust order quantities to changing market conditions and continuously optimize the cost structure.
Dynamic lot sizing
Static calculations are giving way to flexible, data-driven approaches. Systems take into account fluctuating demand, variable delivery times and changing cost structures. The consumption forecast is enhanced by external data sources such as market trends or weather information.
Sustainability and circular economy
Environmental aspects are increasingly being taken into account when calculating batch sizes. Companies are taking CO2 emissions, transport routes and packaging optimization into account when determining optimal order quantities. This development expands the classic cost model to include ecological factors and promotes sustainable procurement strategies.
Conclusion
The Andler lot size remains a fundamental tool of modern procurement, which is continuously evolving through digital technologies. Its mathematical precision provides a solid basis for cost-optimized ordering decisions, while AI integration and dynamic adjustments overcome the classic limitations. However, successful application requires precise data quality and regular parameter adjustment. The strategic importance of the Andler formula lies in its ability to combine cost efficiency with operational excellence and promote sustainable corporate success.
FAQ
What is the lot size according to Andler?
Andler's lot size is a mathematical formula for calculating the cost-optimal order quantity. It minimizes the total costs from ordering costs and storage costs by determining the most economically advantageous order quantity based on annual requirements and cost structures.
How is the optimum order quantity calculated?
The calculation is made using the formula: Optimal order quantity = root of (2 × annual requirement × order costs / inventory costs per unit). This formula assumes constant parameters and provides the theoretically most cost-effective lot quantity for the respective material category.
What advantages does the Andler formula offer in Procurement?
The method reduces overall costs by optimizing order quantities, minimizing capital commitment and procurement costs. It provides an objective, mathematical basis for ordering decisions and supports strategic inventory planning through data-based optimization of planning parameters.
What are the limits of the classic Andler formula?
The formula assumes constant demand and stable cost structures, which is problematic in volatile markets. External factors such as discount scales, minimum order quantities or delivery time fluctuations are not taken into account. Modern systems therefore extend the classic model to include dynamic parameters and real-time adjustments.
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