Downloadable
In supply chain management, understanding the variability of demand for items is crucial for making informed and efficient decisions. This is where XYZ classification becomes relevant.
In supply chain management, understanding the variability of demand for items is crucial for making informed and efficient decisions. This is where XYZ classification becomes relevant.
In this article, we will examine how you can use XYZ classification to improve the efficiency of your supply chain. Additionally, we will provide you with our Excel template (which you can download here) specifically designed to facilitate the implementation of this type of segmentation and indicate the appropriate strategies for each category.
XYZ classification is a classification technique that focuses on the variability of product demand and allows us to identify items with stable, moderately variable, and unpredictable behaviors.
Understanding XYZ segmentation in depth will allow us to apply appropriate strategies for each category, thus optimizing our company's operations, improving its efficiency, and effectively responding to the challenges posed by demand variability for each type of product.
To remind you, if we have n data points, the mean, standard deviation, and coefficient of variation are calculated as follows:
When performing XYZ classification, we will encounter three different categories: Category X, Category Y, and Category Z. Below, we indicate how to use the data to categorize each item and what each categorization implies:
The level of temporal aggregation we choose when calculating our XYZ classification is very important. For example, if we select an annual level, it is more likely that many references will fall into Category X. However, if we compute our data daily, its CV will increase, and the number of items classified in Category X will be lower.
As a general rule, the higher the level of temporal aggregation, the lower the variability, which implies a lower CV and more references in Class X. Therefore, when selecting the level of temporal aggregation, we must consider the planning horizon we manage, as well as choose a grouping that allows us to discern products from our portfolio. In our template, we propose a monthly level, as it is the most common in companies' planning horizons, since we will use this classification for inventory management and production and distribution policies.
Once we have completed the XYZ segmentation and know which items belong to each category, the next step is to establish a different strategy for each:
Category X:
Category Y:
Category Z:
In summary, for items categorized as Class X, precise planning and production efficiency should be prioritized. For items categorized as Class Y, flexible planning and agile supply chain management strategies should be applied. Finally, for items categorized as Class Z, extremely flexible planning and appropriate risk and contingency management are required.
One issue with segmenting our portfolio using only XYZ classification is that the variability in product sales can be caused by various factors such as seasonality, trends, cycles, and randomness. Let’s look at a couple of examples to understand this better.
Suppose we have a customer who buys a product with a monthly demand of 100 units, while we cannot fulfill an order of fewer than 300 units. As a result, if we look at our sales history, it will appear as follows.
If we analyze this reference, its CV is 1.41, which would fall into category Y, while for us it is very predictable, so we would prefer it to be in category X.
Consider another example, a flower shop with sales peaks on All Saints' Day in November and May. If we look at its history, we might say it is quite predictable.
However, applying XYZ gives us a CV of 0.97, which would classify it as Y.
In SCP, to address this issue, we perform a curve decomposition before applying the XYZ calculation, separating our historical data into trend and cycle components, seasonality, and randomness, and apply this test to these data components. Thus, for these two examples, we would obtain a classification of X for this reference. This changes the focus from variability to predictability, so X represents the most predictable references, and Z represents those with the most difficulty in forecasting, requiring precise measures.
In the Data Source tab, upload the sales data. Enter the product code and description if you are more familiar with your product names. Compute this data monthly for the last 13 months; if you do not have data for the last month, replace it with the forecast for that month.
In the XYZ Summary tab, you can filter and sort references by category, and you will be able to see the specific CV for each reference and the total sales.
In the XYZ Chart tab, you can adjust your XYZ parameters (though we recommend 0.5, 1.5, ∞) and view graphically the distribution of your business, the percentage relative to the total, and the number of references belonging to each category at a glance.
With our template, you can effectively implement XYZ Segmentation in your supply chain. You will gain the following benefits:
Remember that XYZ segmentation provides a solid foundation for understanding and managing variable demand in your supply chain. By applying the appropriate strategies to each category, you can optimize your operations, improve efficiency, and effectively respond to the challenges associated with demand variability for each type of product.
At Imperia, we are experts in optimizing your supply chain with our Supply Chain Planning software, making your company more efficient and sustainable. Don’t wait any longer and request a free demo with our experts!
In supply chain management, identifying key elements that require special attention can make the difference between success and failure.