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Overstock, under-stock, and out-of-stock! Does your organization struggle with any of these issues?

 

While running a commerce business, most managers perfectly know that the troubles of inventory management lie in the following areas: 1. overstocks, 2. under-stocks, and 3. out-of-stocks. Companies should never understock or run out-of-stocks to avoid losing sales and ultimately profitability, but extra stocks, above normal demand, and safety stocks drain the cash flow. Hence, it is important to maintain a balanced and agile stock situation to ensure business profitability and sustainability.

 

In general, overstocking happens when a business orders more inventory needed. This dangerous situation has one apparent pitfall for a business: storage volumes. Not only will overstock increase warehouse costs, but also these extra purchases will drain a company’s cash flow due to a slow rotation of their inventory. In parallel, understocking and out-of-stock take place when a business orders insufficient stock. Understocking negatively influences sales and profitability, and tarnishes the brand’s image, reversing years of hard work and pushing customers to look for alternatives.

There are many strategies to avoid inventory mismanagement. Here is a simple three-fold guideline to follow:

  1. Select key items:Determine which items to sell/order and the require quantities for each. To do this, evaluate your historical trends or base your assessment on management forecast.
  2. Define your reordering point and max point:There is a minimal quantity amount that a business needs on-hand before reordering merchandise to prevent an understock situation. There is also a maximal amount needed, known as the max-point, or the point after which a business should stop ordering a given stock to avoid any overstock.
  3. Determine your consumer demand:To determine consumer demands, businesses should focus on product categories depending on consumers’ desires, the novelty in existing categories, and the customers’ preferences regarding the products. If a business decides to buy a new item it is better to check if there is an economic market for it before purchasing it.

 

From a data analytics standpoint, many businesses use the “Pareto Analysis” to determine an items’ classification, while several others have taken this method to the next level by combining it with the XYZ demand distribution.

 

In its most original form, the “Pareto Analysis” ranks item assortments based on revenue share. According to Pareto’s Law (known also by the 80/20-rule), about 80% of total revenue is earned by only 20% of the items. Since these items are the larger contributors to revenue, they are therefore considered to be important and labeled as “A-items”. Pareto’s Law further predicts that the next 15% of revenue is earned by the next 30% of the assortment. These items are labeled B-items. Finally, the last 5% of total revenue is earned by the remaining 50% of the assortment. These C-items are to be discarded from every supply chain manager list as they have low revenue contribution. Simultaneously, A and B items deserve more attention when forecasting demand, as they should be purchased more frequently.

 

Yet, the “Pareto Analysis” is not always a straightforward process. For example, a fast-moving product can easily be a C-item, if its price is relatively low. While the customer expects and demands a high service level for this type of item. Reversely, a slow-moving item can still be an A-item if it is expensive. And a similar item is also relatively expensive to keep in stock. To circumvent these issues, a two-sided ABC-analysis, known as the ABC/XYZ-analysis, should be applied. In this analysis, not only is revenue considered, but simultaneously a second criterion, demand type (X being uniform demand, Y being seasonal demand, and Z being irregular demand), is applied. This results in a 3×3-matrix. For every square of the matrix, a different target can be set. Let’s consider an example of an ABC/XYZ analysis. The AX-items, the items with the highest revenue and most constant demand are given the highest service level target. The CZ-items, the items with the lowest revenue and least constant demand, should be liquidated. By applying the right criteria in this analysis, high savings can be obtained.

 

Inventory management includes thousands of different ways for item optimization. 70% of data collected by businesses remains un-analyzed and un-tapered. The Ranalytics team developed a customized dashboard that assists businesses in analyzing their inventory situation based on an ABC/XYZ analysis. Through a simple visual process, the platform analyses the items in stocks to assess what needs to be kept, maintained, or liquidated. It also helps businesses identify the reordering point of each item and its inventory coverage.

 

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