The inventory management strategy based on the MIN-MAX policy is one of the most popular and daily used methods of maintaining and renewing inventory. This is due, among other things, to its relatively simple design. Is the application of this method so simple and obvious if only in the context of selecting optimal MIN-MAX volumes? Over coffee today, we will lean into the problem of optimizing MIN-MAX parameters in the context of balancing supply chain costs.

First, a brief description of the MIN-MAX method. In general, the MIN-MAX policy is to set lower (MIN) and upper (MAX) stock limits for a given product. Limits can be defined by quantity, e.g. 100 units, or by days of coverage, e.g. 10 days of sales coverage. Thus, it can be seen at a glance that optimization of these parameters can lead, on the one hand, to a significant reduction in costs of, among other things, warehousing and transportation, and on the other hand, to an increase in sales and thus an improvement in the customer service index.

MIN-MAX optimization vs. storage costs

Warehousing costs can be one of the biggest financial burdens in the supply chain. Too much inventory entails the need for warehouse space, the cost of capital tied up in inventory, and the risk of out-of-date or obsolete products. On the other hand, too little inventory increases the risk of unavailability shortages, which can lead to lost sales or costly efforts to quickly procure missing goods.

Procurement and transportation costs vs. MIN-MAX parameters

Each stock renewal order involves costs: administrative, logistical and transportation. When order frequency is high, operating costs increase, and the time spent on delivery affects overall process efficiency. With an optimized MIN-MAX policy, you can better adjust the frequency of orders and their size, which allows you to be closer to the cost optimum from the perspective of balancing transportation costs and inventory holding costs.

Costs of lost sales and contractual penalties

Customer satisfaction is one of the key indicators of supply chain performance. Customers expect product availability, fast order fulfillment and adequate service quality. Exceeding or failing to meet inventory levels can result from a failure to optimally size MIN-MAX parameters and lead to delays or shortages, which negatively affects customer service levels.

Why optimize MIN-MAX parameters?

Optimization of MIN-MAX parameters not only reduces costs, but also helps companies better adapt to dynamic market conditions and maintain the required level of availability (service level). When properly applied, it allows:

1. Reduce storage costs – avoiding excess inventory and reducing the risk of expired products.
2. Manage shipping and ordering costs – by better matching frequency and size of orders.
3. Improve liquidity – by maintaining adequate inventory levels without over-investing capital.
4. Increase customer satisfaction – through better product availability and on-time delivery.

How to conduct MIN-MAX optimization?

Performing effective MIN-MAX optimization requires analysis of several key factors:

• Historical analysis of sales and inventory data – allows assessment of demand variability and order frequency.
• Supply chain constraints – consider the impact of information such as MOQs, bulk orders, available warehouse space, etc.
• Storage costs, transportation costs, lost sales, contractual penalties, etc. – a thorough understanding of what the unit costs are.
• Risk analysis and supplier availability – assess supplier reliability to prevent delays and disruptions in deliveries.

Summary

Optimal MIN-MAX parameters should reflect the trade-off between different types of costs and supply chain constraints. By setting appropriate MIN-MAX thresholds, companies can adjust orders for inventory renewal and maintain safety stock in relation to business objectives, optimizing costs and respecting supply chain constraints.

DATURE ENTERPRISE software uses artificial intelligence and machine learning in the process of demand forecasting and inventory optimization. The Dature system allows the collection of cost information in the supply chain and its application to calculate optimal inventory control parameters using a mathematical objective function with constraints. This makes it possible to ensure the required availability of goods at the lowest possible total supply chain cost.

The system provides methods for forecasting seasonal demand and demand influenced by calendar days. Inventory management methods allow for both pre-season inventory building approaches, dynamic safety stock control and JIT.

TheDATURE application ENTERPRISE can also use expertise in the demand forecasting process. Authorized users can enter expert forecasts and adjust statistical forecasts with them. The process is fully auditable in terms of who changed the forecast when and how. This makes it possible to track the accuracy of both statistical and expert forecasts. As a result, the organization learns how to forecast more accurately and improve process efficiency.