ABC inventory analysis is a method used to classify a business’s stock items into three categories – A, B and C, based on their value to the business. A items are the most important in terms of the value they bring a company, while C items are the least valuable. ABC inventory analysis is important as it helps managers focus their time on their most valuable/important products and adapt their inventory control policies accordingly.
In this blog post we’ll delve deeper into the intricacies of ABC analysis and how it can help businesses improve their inventory management practices. For further details on applying ABC analysis to your own inventory operations, look at our blog on calculating ABC analysis.
In a warehouse different stocked items (or SKUs) will all have different values in terms of how much money they make the business. One way to differentiate products based on their value is to segment them into categories (A, B, and C).
As there are many ways to define ‘value’, this classification can be based on many criteria, including annual sales revenue, average profit margin, annual sales volume or annual consumption value.
You’re no doubt familiar with the ’80/20 rule’ (also known as the Pareto Principle). This rule of thumb can also be applied to inventory consumption, where 80% of a business’s annual sales value comes from 20% of its items e.g. category A items. Categories B and C then make up the remaining 20%.
How the 20% is split between category B and C items will vary, based on a business’s product portfolio.
The graph below shows how ABC analysis conforms with the Pareto Principle. You can see that 20% of the annual sales volume comes from a small number of A category items, while a large number of B, C and D items make up the remaining 20%.
ABC analysis is a simple framework to work out which items in your warehouse are the most important, and should therefore consume most of your time in terms of stock control and management.
Focus on your category A items. This includes reviewing and updating their demand forecast more frequently to guarantee stock availability or interacting more regularly with suppliers to improve lead times.
ABC analysis can also help you work out appropriate inventory rules for each category. It makes sense to set different service levels, safety stock levels and re-ordering parameters for each category. You can then prioritize the management of the policies based on their category classification.
For example, you may want to focus on improving the service levels of your A class products, over your Bs and Cs by increasing your safety stock levels. Avoiding stockouts on A items should be a priority.
While ABC analysis is a relatively easy way to prioritize the management of your inventory, it also has a number of limitations:
ABC analysis arguably over-simplifies the classification of goods. Especially if the classification is done based on ‘gut feel’ and not hard data. The ABC classes are also very one-dimensional, as they only take into account one variable – such as sales value. Factors such as demand variability or the effect of risk-of-runout are arguably equally as important to consider when categorizing your most important inventory.
With only three categories, ABC inventory analysis lacks granularity. With 100’s, sometimes 1000’s of items in one segment, it’s a big generalization to suggest that all SKUs have the same characteristics and should be treated equally.
ABC analysis lacks dynamism. In a marketplace where trends come and go and product sales can be erratic, items can move from category C to A very quickly. Without constant analysis and reclassification, your ABC classification groups can quickly become out of date. Treating A products as C products and vice versa can be very harmful to a business, leading to out-of-date inventory policies and consequently stockouts or excess inventory.
With the risk of your ABC categorization getting out-of-date quickly, it can be time-consuming to constantly re-evaluate your As, Bs and Cs and look for signs of movement between the groups. Inventory management teams could face spending more time on classifying their goods than acting on the implications of the results.
To take ABC analysis to the next level, cross-analyze the annual consumption value of your items with their demand variability. This allows you to classify products based on their value and their forecastability (that is, how likely demand will vary from the forecast).
For example, some products will have a regular demand, while others will have intermittent demand. Having this level of insight helps you to make informed decisions about which products to stock and what safety stock levels to set.
In its simplest form this is known as XYZ analysis. You can learn about the added value of XYZ analysis here.
There is a way to overcome the shortfalls above and use ABC analysis effectively. The answer lies in using software to analyze and categorize your inventory. While some ERP systems will have basic ABC (and XYZ) analysis functionality to do this, for more advanced capabilities you should look to invest in an inventory optimization tool.
ERP apps, such as EazyStock, will take ABC analysis to the next level, carrying out multi-dimensional item categorization that considers a range of variables including:
The result is a far more advanced ABC inventory classification matrix with 81 categories (instead of the usual three) which EazyStock then uses to recommend your inventory policies, providing service level targets and safety stock levels for each product category – and down to SKU level.
Because the classifications are automatically re-calculated and updated on a daily basis, EazyStock can provide alerts when products move from one category to another so the segmentation is always in line with market dynamics.
With the ABC analysis and hard work done for you, you can simply manage by exception, focusing on the categories or even SKUs that EazyStock suggests need your attention.
Contact us today for a demo or to discuss your inventory challenges call: (844) 416-5000.
Post first published July 2015, updated May 2021.