ABC analysis is a method of analysis that divides the subject up into three categories: A, B and C.
Category A represents the most valuable products or customers that you have. These are the products that contribute heavily to your overall profit without eating up too much of your resources. This category will be the smallest category reserved exclusively for your biggest money makers.
For example, a software company might engineer different pieces of software, but one is a niche software that can be sold at a significantly higher price than the others. That’s why it accounts for about 60% of the overall revenue, although the company sells far less of these products compared to other software categories. Hence, this specific software is a category A product.
Category B represents your middle of the road customers or products. Many wrongly approach this group as those who contribute to the bottom line but aren’t significant enough to receive a lot of attention.
Yet, category B is all about potential. The members of this category can, with some encouragement, be developed into category A items.
Category C is all about the hundreds of tiny transactions that are essential for profit but don’t individually contribute much value to the company. This is the category where most of your products or customers will live. It is also the category where you must try to automate sales as much as possible to drive down overhead costs.
THE PARETO PRINCIPLE
ABC analysis is based on what is called the Pareto Principle, an economic principle created by the economist Vilfredo Pareto. Pareto gained notoriety for saying that most economic productivity comes from only a small part of the economy. Essentially, it shows that there is an unequal relationship between your input and your output.
For example, a business might get 80% of its results from only 20% of its staff. This demonstrates that 20% of the staff are more productive than the other 80% of the team.
Another common example of the Pareto Principle suggests that you get 80% of your sales from only 20% of your customers. In this case, these 20% would be your category A customers, hence, those who make the biggest contribution to your revenue. Basically, only 20% of your customers are valuable enough that losing one would significantly hurt the business.
You can bring the Pareto Principle even further into ABC analysis when you consider lifetime value. The relationship between your input and output plays a major contribution in a customers’ lifetime value. It also forms the foundation of ABC analysis by providing guidelines for breaking down customers into different groups (A, B and C).
WHY USE ABC ANALYSIS?
The main use of ABC analysis is to improve your ability to deal with large and complex data sets by breaking them down into three segments. These segments define the priority of the data within whatever area you are using them in.
Once the data is broken down into segments, it is easier to focus on the data and use it in a meaningful way. Breaking down the data into these segments makes specific issues in the data more obvious. It also helps in prioritizing the different segments.
For example, ABC analysis can be used to segment your customers and break down customer-specific data.
First, you would divide the customers into each of the three categories based on the sales volume the customer provides. Then, you would consider how that volume relates to your margin contribution.
If you segment the customers successfully, the customers with the most value will go into the high priority category A, while less important customers would be placed in the bottom category C. Customers that are somewhere in between will stay in category B.
The segmentation allows you to pinpoint your most valuable customers. It then allows you to examine them separately so that you can form a plan of action. When you can look at things in three different categories, it is easier to allocate your resources in a more strategic way than it is if you’re flitting back and forth between charts or just trying to make sense of heaps of raw data. The benefit of taking this extra step is that it makes it easier to analyze the data strategically which in turn makes it easier to maximize your profits.