Procurement Glossary
Min-Max Control: Definition, Methods, and Application in Inventory Management
November 19, 2025
Min-max control is a proven method for automated inventory control that ensures continuous material availability by defining minimum and maximum stock levels. This scheduling method minimizes both shortages and excess stock, thereby optimizing capital commitment. Find out below how min-max control works, which methods are used, and how you can successfully implement it in your company.
Key Facts
- Automatic order triggering when stock falls below minimum levels
- Replenishment always takes place up to the defined maximum stock level.
- Particularly suitable for items with regular, predictable consumption
- Reduces manual scheduling efforts by up to 70%
- Optimizes capital commitment through demand-driven inventory levels
Contents
Definition: Min-Max Control – Fundamentals and Purpose
Min-max control is a fundamental scheduling strategy based on setting lower and upper limits for inventory levels.
Basic principle and mode of operation
With min-max control, two critical stock levels are defined for each item: the minimum stock level as the trigger point for reorders and the maximum stock level as the target level for replenishment. As soon as the available stock falls below the minimum level, an order is automatically triggered to bring the stock level back up to the maximum.
Min-Max control vs. reorder point method
In contrast to the reorder point method, min-max control does not calculate optimal order quantities. Instead, the difference between the current stock level and the maximum value is always ordered. This greatly simplifies material planning, but can lead to suboptimal batch sizes.
The importance of min-max control in Procurement
For purchasing organizations, min-max control offers an efficient solution for automating recurring procurement processes. It enables a continuous supply of materials while reducing administrative effort and supports the strategic focus on value-adding activities.
Methods and procedures for min-max control
The successful implementation of min-max control requires a systematic approach to parameter determination and continuous monitoring of the control logic.
Determination of minimum stocks
The minimum stock consists of the safety stock and consumption during the replenishment period. For precise calculation, historical consumption data is analyzed and fluctuations in demand and delivery times are taken into account. Regular adjustments based on current market developments ensure that the parameters remain up to date.
Determination of maximum stocks
The upper limit is based on storage capacities, capital commitment targets, and the desired inventory range. Best-before dates, obsolescence risks, and seasonal fluctuations must be taken into account. The parameterization focuses on achieving the optimal balance between availability and cost efficiency.
Monitoring and adaptation
Continuous inventory management monitors the effectiveness of the min-max parameters through regular evaluations of service level, turnover rate, and capital commitment. Deviations are identified promptly and corrected by adjusting parameters.
Tacto Intelligence
Combines deep procurement knowledge with the most powerful AI agents for strong Procurement.
Key figures for controlling
The performance measurement of min-max control is based on specific key figures that evaluate both supply security and cost efficiency.
Service level and availability indicators
The delivery service level measures the proportion of demand requirements fulfilled without delay and represents the key performance indicator. In addition, the stockout rate documents the frequency of shortages, while the average shortage duration quantifies the impact on downstream processes. These key figures enable a precise assessment of supply quality.
Inventory efficiency and capital commitment
Inventory turnover shows how efficiently inventory is being used and is calculated by dividing average inventory by consumption. The capital tie-up rate illustrates the financial impact of holding inventory, while the obsolescence rate quantifies the risk of obsolete inventory.
Disposition quality and process efficiency
The hit rate of automatic order suggestions evaluates the quality of the parameter settings. In addition, key figures such as the number of manual interventions and the processing time per disposition measure the efficiency of the automated process and identify potential for optimization.
Risks, dependencies and countermeasures
The use of min-max control involves specific risks that can be minimized and controlled by taking appropriate measures.
Parameter risks and mismanagement
Inappropriate min-max parameters lead to systematic errors in inventory control. Minimum stock levels that are too low cause stockouts and production interruptions, while excessive maximum values result in unnecessary capital commitment. Regular parameter reviews and data-based adjustments based on inventory analyses counteract these risks.
Fluctuations in demand and market volatility
Unforeseen peaks or slumps in demand can quickly render static min-max parameters obsolete. Seasonal fluctuations, market trends, or external shocks require flexible adjustment mechanisms. Integrating consumption forecasts and scenario analyses increases the robustness of the system.
Supplier dependencies and supply risks
Min-max control requires reliable suppliers with stable delivery times. Delivery failures or extended procurement times can lead to critical bottlenecks. Diversified supplier portfolios and alternative procurement sources significantly reduce these dependencies.
.avif)
Practical example
An automotive supplier implements min-max control for 2,500 C-items in electronics manufacturing. For standard resistors, a minimum stock level of 1,000 units (corresponding to 14 days' consumption plus safety stock) and a maximum stock level of 5,000 units are specified. If the minimum stock level is not reached, the ERP system automatically triggers an order for 4,000 units. This system reduces the company's manual planning efforts by 65% and achieves a service level of 98.5% while reducing capital commitment by 15%.
- Automated monitoring of all 2,500 items by the ERP system
- Weekly parameter review based on consumption analyses
- Integration with supplier portals for accelerated order processing
Current developments and effects
Min-max control is undergoing continuous development as a result of technological innovations and changing market requirements, opening up new opportunities for more precise and efficient inventory control.
AI-supported parameter optimization
Artificial intelligence is revolutionizing traditional min-max control with self-learning algorithms that dynamically adjust parameters to changing market conditions. Machine learning models analyze complex consumption patterns and external influencing factors to generate more accurate forecasts. This development leads to a significant reduction in shortages while optimizing capital commitment.
Integration into digital supply chain ecosystems
Modern ERP systems seamlessly integrate min-max control into comprehensive supply chain solutions. Real-time data analysis enables immediate response to inventory changes and fluctuations in demand. Networking with supplier systems creates transparent, automated procurement processes.
Sustainability and circular economy
Environmental awareness is increasingly shaping the design of min-max parameters. Companies are increasingly taking sustainability criteria into account when optimizing inventory and integrating aspects of the circular economy into their planning strategies. This leads to a more holistic view of inventory costs, taking ecological factors into account.
Conclusion
Min-max control is a proven and efficient method of automated inventory control that is particularly suitable for items with regular consumption. By clearly defining minimum and maximum stock levels, it enables a continuous supply of materials while reducing administrative effort. Success depends largely on the precise determination of parameters and regular adjustment to changing market conditions. Modern AI-supported approaches open up new possibilities for even more precise and efficient inventory control.
FAQ
What is the difference between min-max control and order point control?
With min-max control, stock is always replenished to the maximum level, regardless of the optimal order quantity. The order point method, on the other hand, calculates economical batch sizes and orders them when the order point is reached. Min-max control is easier to use, but can lead to suboptimal order quantities.
For which items is min-max control particularly suitable?
Min-max control is ideal for items with regular, predictable consumption and low value (C items). Standard parts, consumables, and auxiliary materials with stable delivery times are particularly suitable. For high-value A items or items with highly fluctuating demand, other scheduling methods are often more economical.
How are the min-max parameters optimally determined?
The parameters are determined based on historical consumption data, delivery times, and desired service levels. The minimum stock comprises the safety stock plus consumption during the replenishment period. The maximum stock takes into account storage capacities, capital commitment targets, and shelf life restrictions. Regular adjustments based on current data are essential.
What are the advantages of automating min-max control?
Automated min-max control significantly reduces manual planning efforts and minimizes human error. It ensures continuous material availability, optimizes inventory levels, and allows buyers to focus on strategic tasks. In addition, it improves response times to inventory changes and increases process standardization.
.png)
.png)
.png)
