Why ABC-analysis is inadequate for your supply chain

When asked to analyze demand, most probably turn to what is known as the ABC-analysis. ABC-analysis typically groups items in classes referred to as A, B, and C based upon their demand value over a certain period. But from a supply chain perspective, this can be considered inadequate. An A-item, sometimes even called a “runner”, can very well be in the top class due to a single or only a few large orders with fluctuating quantities. At the same time, a C-item, or “stranger” could be in the tail while still being required highly frequently and regularly, in small and stable quantities. Important demand characteristics such as variability and frequency are not considered in an ABC-analysis, although they are probably more important to look at than volume. And the aspect of urgency, i.e., how quickly an item is required, is hardly considered at all despite its relevance for decisions regarding the company’s supply chain. This post explores the four aspects that should be covered by customer demand analysis: volume, variability, frequency, and urgency.

Shortcomings of ABC-analysis

The ABC-analysis has its origins in Pareto’s Law or the Pareto Principle, popularly known as the 80-20 rule. But instead of using a dichotomy, the ABC-analysis categorizes items into three classes, named A-, B-, and C-items. The analysis comes down to sorting all items by a criterion and using limit values on the cumulative value to group items into the three classes. These value typically are 80, 15 and 5%, or 70, 20, and 10%.

Now, the first issue with the ABC-analysis is that the criterion often proposed is the inventory value. This is due to its first published application in the field of materials management in the early ’50s, by H.F. Dickie. When you want to run an ABC-analysis to better understand the demand for items in your product portfolio, use demand as the criterion, not inventory. This seems evident, but still…

Related to using demand as a criterion is that you should carefully define demand, particularly as you use a certain period based upon which you do the analysis. For me, demand means required by the customer. However, I often witness that customer demand analysis in companies is done based upon production, invoices, or shipments. Just saying…

And now that we are on the topic of demand, do give it a good thought whether you will be using quantity (sometimes called the P-Q analysis in that case) or value. And if you choose value (particularly if you must due to a mix of units of measure for your products, e.g., pieces, liters, tons, square meters, and so on), think about whether you will be using sales, gross margin, or cost-of-goods-sold (COGS), the latter having my preference.

RRS: Runners, Repeaters, Strangers

The next issue with ABC-analysis that I already mentioned in the introduction, is that it does not consider the frequency of demand. In Lean circles, therefore, the RRS-analysis is sometimes proposed. The RRS-analysis focuses on the interval with which items are required. Items are “labeled” as being required daily, weekly, bi-weekly, monthly, quarterly, yearly, and so on. The most frequently required items are then called “runners”, next on are the “repeaters”, and finally the “strangers” (sometimes also called “rogues”).

A problem that I have seen with the labels of the RRS-analysis, is that they are being used for the ABC-classes from the ABC-analysis… Now, although there might be some correlation between value and frequency, it is not necessarily the case, and you should, therefore, be careful to liken the ABC-analysis with the RRS-analysis.

Doing a proper RRS analysis, based upon the required numbers, and using absolute categories for the demand intervals would already be a big step forward. Demand intervals have always helped me in better understanding what would be required to overcome the difference between the actual interval and the pattern that would result from the application of heijunka. Or to put it differently, the difference between the actual demand interval, and takt time. But I just wonder how many even perform a proper customer demand analysis using a technique like RRS in the first place…

By the way, I also distinguish between the interval or frequency of demand (which is an average over a certain period), and the item’s demand regularity (which can be seen as the stability of its demand interval). When demand is concentrated in a certain period, and not spread out in more or less isochronal intervals, this, of course, can still create certain challenges in your production system and supply chain…

Adding variability to the mix: XYZ-analysis

To add one more abbreviation to the forest of abbreviations in customer demand analysis, let’s introduce the XYZ-analysis. One of the mentioned shortcomings of the ABC-analysis is that it does not consider variability of demand. The RRS-analysis also does not take this into account, despite variability being relevant to deciding upon the way your production system and supply chain is going to satisfy demand.

The XYZ-analysis, therefore, is an additional technique that quantifies the degree of variability of the demand for an item, using the coefficient of variation, or the relative standard deviation, of the demand pattern. A word of caution here: I have seen the XYZ-analysis being presented to classify items based upon the frequency of demand. You now know that’s wrong.

The RRS- and XYZ-analysis together are powerful approaches to analyze your customer demand. You do have to take care though whether you do the analysis based upon order lines or dates. This seems like a small remark, but I can tell you from experience that seeing demand as an attribute of the order line, gives a different result than seeing the demand as an attribute of the date.

And what about urgency?

And urgency? Have you come across a customer demand analysis that considers urgency, that is to say, the time allowed by your customer to supply the required goods? This aspect is also relevant in deciding how you will be serving your customers. Just remember Shingo’s P-D ratio and the related order penetration or customer order decoupling point.

Comparable to volume, variability, and frequency, urgency also deserves to be studied as an integral part of customer demand analysis. And the demand for items should be categorized according to certain lead time categories.

Proper customer demand analysis

When asked to analyze customer demand, most people turn to the traditional and relatively straightforward ABC-analysis. I hope this post has shown you that this suffers some serious shortcomings if you want to base your supply chain decisions upon only the aspect of volume. To complement the ABC-analysis, this article proposes to also analyze the demand characteristics of frequency, regularity, variability, and urgency.

In my work, I typically do so, as it provides an extraordinarily rich and detailed, quantitative view of the current state. Such a quantitative analysis enhances the more qualitative techniques such as the value stream analysis (VSA) or material and information flow analysis (MIFA) typically being done before commencing initiatives to rethink the way we run our supply chains.

If you are interested to learn more about this topic, I recommend having a look at our rich online course on customer demand analysis (see the video introduction below), and our Excel-based applications that allow you to profile your demand like described, in an instant! You can download free trial versions of our customer demand analysis applications from our shop. You can also watch a demonstration of these applications, and more, in the special playlist on this topic on THE JIT COMPANY’s YouTube channel.