ABC analysis
ABC analysis
ABC analysis is a controlling used to prepare decisions on business management issues. For this purpose, objects are divided into three categories (A, B, C). The objects are, for example, products, customers or markets.
The objects are described with a relevant parameter (e.g. share of total turnover per year or total costs per year) and sorted in descending order according to this parameter. The sorting produces a list in which the most important object (A) comes first and the least important object (C) last. This form of processing makes it easy to identify objects that are important for the business. For example, key accounts can be identified that are responsible for a large share of the turnover, or expense items that significantly drive the costs of a product.
The list entries are then categorised into A, B and C objects based on their cumulative share of the key figure. The following classification is usually used:
| Share of the object in the parameter | Category |
|---|---|
| The first 80 % | A |
| The next 15 % | B |
| The last 5 5 % | C |
The classification is illustrated by the example of a customer analysis: The company under consideration asks itself which customers are particularly valuable for its turnover and which cause more costs than the turnover justifies.
To answer this question, the individual customers are first sorted in descending order according to their share of the company's total turnover per year. This could look like this, for example:
| Name of the customer | Share of customer in total turnover p. a. |
|---|---|
| Customer 1 | 50% |
| Customer 2 | 25% |
| Customer 3 | 12% |
| Customer 4 | 7% |
| Customer 5 | 4% |
| Customer 6 | 2% |
The turnover shares are then cumulated in another column:
| Name of the customer | Share of customer in total turnover p. a. | Cumulative share of total turnover p. a. |
|---|---|---|
| Customer 1 | 50% | 50% |
| Customer 2 | 25% | 75% |
| Customer 3 | 12% | 87% |
| Customer 4 | 7% | 94% |
| Customer 5 | 4% | 98% |
| Customer 6 | 2% | 100% |
Now the customers can be divided into A, B and C customers according to the given categories. To do this, look at the column with the cumulative share of annual turnover. At each point where a threshold value is exceeded, a new category begins. According to this logic, A customers account for the first 80 % of turnover, B customers for the next 15 % (i.e. cumulative share between 80 % and 95 %) and C customers for the last 5 % (i.e. cumulative share between 95 % and 100 %).
| Name of the customer | Customer's share of total turnover p. a. | Cumulative share of total turnover p. a. | Category |
|---|---|---|---|
| Customer 1 | 50% | 50% | A |
| Customer 2 | 25% | 75% | A |
| Customer 3 | 12% | 87% | B |
| Customer 4 | 7% | 94% | B |
| Customer 5 | 4% | 98% | C |
| Customer 6 | 2% | 100% | C |
It can be seen that customers 1 and 2 are of high importance to the company because together they are responsible for three quarters of the annual turnover. They therefore clearly belong to the company's A-customers. Customers 5 and 6, on the other hand, do not have much influence on the total turnover. With this knowledge, for example, decisions can be made in key account management or measures can be taken to retain customers.
A heuristic related to the ABC analysis is the Pareto principle, also known as the 80/20 rule. The ABC analysis is well suited for graphical processing because it organises complex information and reduces it to the essentials. It can be applied to almost any parameters.
With the ABC analysis in projectfacts you can divide your customers not only according to turnover, but also, for example, according to project times. This way you can see at a glance which customers cause a high project effort and compare this information with the share of turnover. In this way, you keep an eye on key accounts and do not lose sight of your profitability.