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When talking about reorder quantity calculations, there are a lot of various mathematical models to choose from. For example, you can easily find plenty of various equations on the web.

At first glance, all of these models may seem logical, but which one is the best choice? Of course, the business specifics of a company should be evaluated here, as well as many other factors. But in this article, we will try to provide you with some essential guidelines that can help make a choice.

Let’s assume that our task here is to find the best reorder quantity calculation model in terms of inventory efficiency. This means that we need to find a model that allows us to minimize the current inventory we have and lower our operational costs, while still providing a high amount of product availability for our clients.

Let’s start from dividing these models into two general groups that we will call:

• Reorder point models

• Reorder schedule models.

### Reorder point models

You can recognize **Reorder point models** from the set of parameters used in the formula. Such parameters as next order date, or reorder period are missing, and the order quantity is calculated without care about when this item should be reordered again. Usually, order quantity in these equations corresponds to minimal costs (for example, the Economical order quantity model) or biggest profit value (for example, the Newsboy problem equation). Also, some of these models evaluate various levels of discounts that are available when purchasing some larger quantities, while on the same hand, evaluating costs and risks. Probably the simplest example of a reorder point model is ordering according to a minimal order quantity set by the vendor. After we receive the ordered goods, we need to track their inventory level in order to find out just the right moment to reorder. It means waiting until the inventory level reaches the Reorder point and then order a new batch. The reorder point is usually calculated as the quantity in-stock when the present inventory is only enough for Lead Time, plus some safety stock.

Picture 1 shows the inventory dynamics of 1 SKU that is managed with a reorder point model.

Everything looks very logical so far. **So where is the problem?**

In fact there are a few major problems that do not allow reorder point models to be as efficient as we would like them to be in real life.

### First major problem with Reorder point models

In almost every reorder point model we need to forecast future demand as a parameter, which is critical in determining how long we will stock a specific amount of SKU and therefore, how large our holding costs will be. The longer the period is for which we order an item, the greater risk is that demand will fluctuate against our favour. That is one of the exact reasons for overstock. So someone that uses reorder point models must be very careful, and always evaluate additional risks, especially when ordering for long periods of time.

Picture 2 demand fluctuates against our favour

Second major problem with Reorder point models

When the order quantity of an item is calculated without considering its next reorder date, we assume that this item can be reordered individually as soon as the inventory reaches the reorder point. But in real life, we usually deal with cases when the items should be reordered in some groups in order to minimize the logistic costs. For example, a whole assortment that is supplied from one vendor or one warehouse should be reordered with the same order and shipped with one shipment in order to save on freight charges. Another example can be production when some group of items should be produced in one batch in order to squeeze more efficiency from the production line. In these cases, our desire would be that the inventory of the majority of items in this group approach their Reorder point at nearly the same time. In other cases, there are only 2 options:

#### The First option

is to skip the reorder point of the very first items and wait for more items to reach their reorder point and only then reorder. That decision leads to running out of stock and even worse – to running out of the best-selling items.

Picture 3 shows the negative effect when orders are synchronized, but stock outages appear.

The Second option

is to reorder as soon as first item reaches its reorder point. In this case, we will find our inventory far away from its desired efficiency, because of unnecessary inventory added to the existing stock besides its efficient quantities.

Picture 4 shows the negative effect when orders are synchronized, but overstocking occurs.

Reorder schedule models

Reorder schedule models work better in cases when items should be ordered in groups. The main difference from reorder point models is that here, that essential parameter is the next order date or reorder frequency. How to choose the optimal replenishment frequency was described in one of our previous articles. According to the reorder schedule of a whole group, individual optimal inventory levels are calculated for every single item. The so-called inventory buffer corresponds to the demand expected until the next replenishment, plus some safety stock. It doesn’t matter what the inventory level of an item is, the order quantity is always calculated to fill the optimal inventory buffer 100%. If the reorder period is set approximately right, at every reorder moment, the approximately desired size of the total order will be calculated, only the distribution of quantities among the items can be different. This approach is widely used for inventory optimization in modern logistics, as it allows efficiently setting and managing extremely minimized inventory levels.

Picture 5 shows how the orders are synchronized, while the reorder quantity of each item is more flexible, allowing the total amount of each order to be closer to optimal.

Combining Reorder schedule with Reorder point

It would be nice if Reorder schedule ideas could be used 100%. Unfortunately, minimal order quantities and packaging restrictions persist in real life. Also, very high demand fluctuations can force us to increase the replenishment frequency in order to react faster to unexpected sales and have higher availability, while on the other hand, the throughput of logistic chains (ex warehouse) can be limited, thus creating a bottleneck. The good news here is that in a SOFT4Inventory, the Reorder schedule model is extended with Reorder point features, allowing you to minimize inventory while optimizing load on the logistic chain, minimizing logistic costs and dealing with such restrictions as packaging levels and moq. This topic can probably be for our next article, or you can contact us to get more information about SOFT4 capabilities.

*SOFT4, as a provider of software solution for efficient inventory management, is constantly releasing blog articles about how to meet and cope with the trends, tendencies, and challenges, and give suggestions as to how to react to the changing environment in order to stay competitive.*

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