ABC Analysis – The Ultimate Guide to Inventory Classification

Whether you’re managing a heaving warehouse or a humble shop stockroom, inventory classification is a valuable tool that can take your inventory management to the next level. At its heart, grouping inventory or stock is a powerful way to determine the value of stored items to your business, improving transparency, speeding up storage tasks and enabling informed decision making.

Sadly, inventory classification methods are also littered with abstruse acronyms, which can lead managers to avoid them like the plague. ABC, VED, HML or SOS – what do they mean and what are they all for? Most are extraordinarily easy to explain, with an equally apparent application. In this ultimate guide, we’ll be tackling eight of the most popular categorisation techniques – please check in soon to discover seven more methods!


ABC – Always Better Control



ABC inventory analysis, or Always Better Control, is designed to help prioritise your inventory. The technique is based on the Pareto principle (a.k.a. the 80/20 rule), which suggests that roughly 80% of the results come from 20% of the inputs. In the case of inventory, it’s assumed that approximately 80% of your revenue, unit costs or any value metric of your choosing comes from approximately 20% of your inventory.

The fundamental aim of ABC is to divide your inventory into three groups: A, B and C. Each group represents a different value to your business, with fewer products in A providing the most value and more products in C providing the least. What does ‘value’ mean exactly? In short, almost whatever you want, depending on the types of decisions you’re hoping to inform.

If you’re looking to reduce costs, group A will contain your most costly inventory. If you’re looking to boost profits, group A will contain your most profitable inventory. In other words, group A will contain the items for which careful management will deliver the greatest results.



To perform ABC analysis on your inventory, you’ll need the following starting data:


  1. The total number of each item that passes through your inventory each year, otherwise known as demand or annual usage.
  2. A value metric you’re hoping to improve for each inventory item, which could be purchasing costs, holding costs, revenue, profit or something else. Don’t be afraid to use averages if perfect accuracy is impossible.


Once you’ve found the right data, ABC analysis is achieved in seven basic steps:

Note: we’ve chosen unit purchasing costs for our value metric.


Step 1.

Draw up a table that lists each item alongside its annual demand and unit cost.

Step 2.

Multiply the annual demand and unit cost for each item. In this case, the result is effectively a rough estimate of your total annual variable costs for the inventory item - the number of units you'll use x the cost.

Step 3.

Sum the costs to see your total annual inventory cost.

Step 4.

Now divide the item's annual cost by the total annual cost to find the percentage of total costs each item accounts for.

Step 5.

Reorder your table in descending order of the percentage attained in the last step.

Step 6.

Create a new column and sum the percentages to the left, giving you the cumulative percentage.

Step 7.

Try to find breakpoints in the percentage costs of your inventory, splitting items into three or four groups. Use the cumulative column as a guide: Group A usually comprises 70-80% of costs (or whatever metric your using); Group B, 10-20%; Group C, 5-10%.


In this example, Group A: 71.92% of costs and 20% of items; Group B: 16.89% of costs and 30% of items; Group C: 11.19% of costs and 50% of items.


The last step tends to be the stumbling block. Before getting frustrated, there are two things you should know about ABC analysis that are often overlooked: firstly, it’s by no means an objective analytical approach, relying as much on intuition as on data; secondly, it doesn’t work for everyone.

Group A usually comprises 70-80% of costs (or whatever metric your using); Group B, 10-20%; Group C, 5-10%. However, these are guidelines! You might find that your inventory splits better into four or even five groups, or that Group A accounts for only 50% of your costs. That’s okay.

Remember, the point of ABC analysis is to find meaningful variances in the activity of different inventory items. That’s differences in your inventory, which won’t be quite the same as anyone else’s.

You may even find that your inventory is quite balanced. In that case, ABC analysis probably won’t be all that useful. The general assumption of ABC analysis is that a few items make up most of the cost, revenue, profit or other value metric. Or, if you’re a visual thinker, that the plot of your value metric vs. percentage of items looks something like this:

A graphical representation of an ABC analysis curve

It’s a reasonable assumption, where you have flagship products or cost variability, but it’s not set in stone for every business. For example, If your costs are spread evenly over your inventory, with a number of very similar items, you’re unlikely to find useful breakpoints using ABC analysis. If so, perhaps it’s time to look at some of our other inventory classification guides!



When it works, ABC analysis does exactly what it says on the tin: it helps you keep Always Better Control with the minimum possible resources. The trick is to manage items in Group A with more energy, while attempting to automate or reduce work on items in Group C.

For example, you will want to keep a close eye when ordering Group A items, undertaking the task manually. Group C items, on the other hand, can be managed automatically by your Inventory management software. By watching Group A closely, you’ll avoid the mistakes that’ll hurt your business the most, or cut costs more effectively on products that hold the lion’s share of your inventory value.

ABC analysis can also help you manage a stockroom better. To save time, high volume items in Group C should be placed near the entrance, speeding up trips from the sales floor, while low volume, high value items in Group A should be secured safely away to reduce costly theft.

One of the most popular uses for ABC analysis is to develop efficient cycle counting schedules. In this case, your most valuable items in Group A will be counted more frequently to limit the impact of inventory variance on your most critical materials. Group C can be counted relatively infrequently, cutting labour costs and boosting productivity.

As you can see, ABC analysis is a useful tool to bring to a variety of tasks. It can even shed light on other areas of your business: spend vs. % of customers, page views vs. % of web pages, etc. Ask yourself this question: is it possible that some of your inventory is more important than the rest? If the answer is yes, ABC analysis will help streamline a whole host of inventory activities.


How can we improve this guide? If you spot any errors or anything we’ve missed, please let us know in the comments section or on Twitter @ActionStorage.

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4 comments on “ABC Analysis – The Ultimate Guide to Inventory Classification

  1. Thank you michael, you explained very well about inventory classification.

    • 16-Mar-2017

      Michael said:

      Glad you found it helpful! Do you use any classification techniques yourself?

  2. 28-Apr-2017

    Amit said:

    The explanation was really helpful. Thank you.

  3. Thank you for explaining it so nice and easy. It’s really helpful for the inventory managers like us.

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