Min/Max is one of the earliest automated replenishment methods that is now used across almost every piece of inventory software on the market. Its roots can originally be traced back to around the 19th century; it was developed as a visual method where you could physically see the amount of stock in a carefully sized bin.
The core idea was that once stock reached a certain point, this would trigger a replenishment, which would return the bin back to its maximum levels, without the need to ever count the exact amount of stock that it contained. Since then, this fairly ancient method of automating variants has grown in popularity and is now used in various guises by almost every modern day company.
The approach is built on two conditions: initially we start by tracking the current stock level - which is typically the sum of the stock-on-hand, plus the stock-on-order for every single SKU. Then, when the total stock reaches a Minimum value, the system automatically alerts the user, and a subsequent reorder is placed targeting a specific Maximum total stock level.
Therefore, we can say that the main benefit of a Min/Max approach is its simplicity. However, don’t let this fool you: choosing the levels for a Min/Max approach is anything but… And this is where dragons can lie! If lead times were immediate, then in reality most businesses would reduce their minimums to just one unit, in order to save storage costs. However, in reality, the longer the lead time becomes, the higher the Min has to be, in order to account for delivery delay.
It is worth bearing in mind that one of the core assumptions of a Min/Max concept is that the environment is static, with constant demand and lead times. Of course we know that this is far from reality, as lead times may be extended, or demand may be bigger or smaller than first predicted. All of these factors can potentially result in a stockout.
Naturally, business leaders are aware of this and adapt their minimums according to the uncertainty that they have in their business and the relative importance of the product. Typically, an ABC Analysis approach similar to the one we discussed in a previous episode can be applied, with A-products having higher Mins and a greater safety margin. So whilst appealing with simplicity, the challenge of the Min/Max world is that the underlying assumptions of a static constant world can give a false sense of security.
To conclude, as each individual SKU has its own economic characteristics such as MOQs, lot sizes and carrying costs - as well as non-price sensitive factors such as expiration dates and seasonality -, there are an awful lot of factors which need to be combined to get any sort of rational Min/Max levels. All of this can only be properly accounted for through a dynamic approach, which is constantly refined based on the latest information.
Find out more about the Min/Max Inventory Method.