The Importance of ABC Analysis in Inventory Management
- ABC inventory analysis
- The three classifications used in ABC analysis
- The 80/20 rule of ABC analysis
- The applications and advantages of ABC analysis
- Disadvantages of ABC analysis
- Considering demand in ABC analysis
- Automating ABC analysis
ABC inventory analysis
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, whilst C items are the least valuable. The objective of ABC inventory analysis is to help 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.
The three classifications used in ABC analysis
In a warehouse different stocked items (or SKU’s) 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.
- A classification items are very important and sometimes business critical. These typically have a high value or are sold in large volumes.
- B classification items are important, but less important than ‘A’ items and more important than ‘C’ items. These are typically mid-range in inventory value and demand.
- C classification items are marginally important. Typically, they have a low inventory value.
The 80/20 rule of ABC analysis
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%.
The applications and advantages of ABC analysis
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. Read about how to calculate ABC analysis here.
Focus on your category A items. This could include 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 prioritise 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.
Disadvantages of ABC analysis
Whilst ABC analysis is a relatively easy way to prioritise 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 categorising your most important inventory.
With only three categories, ABC analysis lacks granularity. With 100’s, sometimes 1000’s of items in one segment, it’s a big generalisation 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 visa 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 categorisation 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.
Considering demand in ABC analysis
Taking ABC analysis to the next level, it’s possible to cross-analyse the annual consumption value of your items with their demand variability. This allows you to classify products based on their value and their forecastability e.g how likely demand will vary from the forecast.
For example, some products will have a regular demand, whilst 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. Read more about ABC XYZ analysis here.
Automating ABC analysis
There is a way to overcome the shortfalls above and use ABC analysis effectively. The answer lies in utilising software to analyse and categorise your inventory. Whilst 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 optimisation tool.
ERP apps, such as EazyStock, will take ABC analysis to the next level, carrying out multi-dimensional item categorisation that considers a range of variables including:
Demand volume – number of units sold
Sales frequency – what % of historical periods have a sale
No of picks – number of times picked over the year
Value of annual usage – sales volume x unit cost
The result is a far more advanced 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 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. For more information on how EazyStock can deliver advanced ABC analysis functionality download our whitepaper.
With the analysis and hard work done for you, you’re then able to manage by exception, focusing on the categories or even SKUs that EazyStock suggests need your attention.
Post first published 10 July 2015, updated June 2019.