
Optimization of MIN-MAX parameters vs. supply chain costs
6 November 2024
Challenges in implementing indicator analysis in the area of stock management
17 January 2025

Optimization of MIN-MAX parameters vs. supply chain costs
6 November 2024
Challenges in implementing indicator analysis in the area of stock management
17 January 2025Management of MIN-MAX parameters during and after the holiday peak period

The holiday season is a time of increased demand for products, which poses a major challenge to inventory management. However, it is worth remembering that after the holidays the situation changes dramatically – demand drops sharply, leading to the risk of excess inventory. Effective management of MIN-MAX parameters under these exceptional conditions allows companies not only to meet high holiday demands, but also to adjust inventory accordingly after the season. So how do you manage these parameters before, during and after the holiday season?
MIN-MAX policy based on quantity e.g. MIN=100 units MAX=200 units.
1. Preparing for the Christmas peak: increasing MIN and MAX values
Before the holiday season, it is worthwhile to analyze sales data from previous years to better understand the level of demand for specific products. On this basis, you can temporarily increase the values of the MIN and MAX parameters , if you use a method based on quantities rather than days of coverage. A corresponding increase in the MIN volume reduces the risk of running out of stock at a time of increased demand, while an increase in the MAX value allows you to meet anticipated larger orders without having to place numerous, expensive orders on an ongoing basis.
Examples of activities:
- Forecasting demand based on historical data, market trends and analysis of consumer behavior, e.g. under the influence of promotions
- Set higher MIN-MAX volume thresholds for key seasonal products, taking into account their popularity and the nature of the holiday season.
2. Stock monitoring during the holiday season
During the season, it is a good idea to regularly monitor inventories, as actual demand may differ from forecasts. In a situation where demand turns out to be higher than predicted, a quick adjustment of the MIN-MAX quantity parameters can prevent a shortage of goods availability. However, if forecasts turn out to be too optimistic, it is better to immediately reduce the level of these parameters to reduce the risk of overstocking, which can generate unnecessary costs after the holiday season.
Examples of activities:
- Daily analysis of actual sales in seasonal product categories.
- Adjust replenishment volume according to demand forecasts.
3. Optimization of MIN-MAX parameters after the holiday period
Once the holiday period is over, the MIN-MAX parameters should be adjusted immediately to avoid costs associated with excess inventory. In practice, this means reducing MIN values to standard levels, or even lowering them temporarily below the norm, in order to use up accumulated inventory without the need for immediate replenishment. It’s also worthwhile to conduct a thorough inventory analysis, identifying products that may require more intensive promotion or price reductions to avoid overstocking and related costs.
Examples of activities:
- Reduce MIN levels to standard values or lower to sell off accumulated stocks.
- Conduct promotions or product sales to minimize excess inventory.
4. Benefits of dynamic MIN-MAX optimization during the holiday season
Effective management of MIN-MAX parameters during and immediately after the holiday peak brings numerous benefits:
- Minimize storage costs and post-season losses.
- Increased sales due to better product availability during peak demand periods.
- Reduction of inventory shortages during critical periods, resulting in higher customer satisfaction.
- Increased operational flexibility – dynamic parameter management allows faster response to unpredictable changes in demand.
MIN-MAX policy based on days of coverage, e.g. MIN=10 days MAX =20 days
When using MIN and MAX parameters based on days of sales coverage, we do not need to make MIN-MAX quantity adjustments, as increasing demand will automatically translate into higher quantities. For example, MIN=10 days of sales coverage could mean 50 units before the season. (because that was the demand for 10 days), while during the season it could be 200 items (demand during the season was 4x higher)
Summary
The holiday season is a challenging time for any supply chain management department, but proper optimization of MIN-MAX parameters before, during and after the season helps maintain inventory control and minimize costs. By dynamically adjusting inventory levels, companies can not only meet increased customer demand, but also effectively manage inventory when demand returns to normal.
The use of MIN-MAX based on days of coverage is a more flexible approach because it allows for self-adjusting quantities that build safety stock and subsequent orders. Of course, determining the right MIN-MAX parameters alone is a challenge, as we wrote about in a previous episode of our series.
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.
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