An ABC analysis is a method that helps you to prioritise. It arranges a set of predefined objects into three classes with different meanings:
A, B and C.
Everything that falls into the A class is of great importance. B-objects are less important, and C-objects are negligible (at first). ABC analysis is always used when data needs to be classified and prioritised to identify the most important objects.
In business administration, ABC analysis is used in a wide variety of cases. A typical example would be the following question: Which products or customers contribute the most to total turnover - and which the least?
The inventor of ABC analysis is H. Ford Dickie, who was a manager at General Electric at the time. He first described the method in 1951 in his article "ABC Inventory Analysis Shoots for Dollars, not Pennies.
In doing so, he transferred the findings of the Pareto principle (also known as the "80/20 rule") and the Lorenz curve for the first time into the practical context of corporate management.
The Pareto principle states that 80% of results are achieved with 20% of the effort. For the remaining
20 % is therefore 80 % of the effort required.
The Pareto principle, discovered as early as 1906 by the Italian Vilfredo Pareto, is still used today in the context of project and time management to achieve fast results with relatively high quality (80%).
The Lorenz curve graphically visualizes an uneven distribution. It illustrates the extent of the inequality and shows the relative concentration within the distribution.
The Lorenz curve got its name from its inventor Max Otto Lorenz. The American statistician and economist developed the Lorenz curve in 1905 as part of an essay on income distribution.
The logic behind this visualization is still used in practice today, for example in ABC analysis.
You know what it's like: In most companies and departments there is simply far too much to do. However, due to the high level of complexity, you often don't know what exactly you should prioritize.
The ABC analysis helps you to focus on the essentials. It provides you with a validated basis for deciding where to set your priorities (A area) and what is not important at first (C area). By identifying those areas that contribute less to your overall success, the ABC analysis can also help you to reduce unnecessary effort.
Originally, the ABC method was developed for materials management, but quickly found its way into many other areas of business management.
An ABC customer analysis looks at the customers of a company in relation to another parameter. In most cases this is turnover or the contribution margin. A-customers are then those who generate the most turnover, for example. C-customers are logically those who contribute the least to total turnover.
An ABC product analysis serves to identify the strongest products in terms of another parameter. This often involves looking at turnover, contribution margin, rotation speed or sales figures.
If you know your A-products, you know where further investments will probably pay off most.
In the area of procurement, an ABC analysis can help identify cost reduction potential for procured materials.
The basis for this is often the annual requirement value (number of units x average purchase price) for individual materials.
In its historically first application, the ABC analysis classifies parts or entire assemblies according to their value. Here, too, one is generally quite free in the choice of criteria that determine this value.
For example, manufacturing costs can be included just like the annual purchasing volume.
In time and project management the ABC analysis helps you to classify projects and tasks according to their priority.
In the context of project management, the ABC analysis is often based on soft factors, as estimated values are used as a basis. On the one hand this concerns the predicted time required for certain tasks, but on the other hand also the importance for the company's success that is attributed to individual tasks.
In terms of agile project management or hybrid project management, both the forecast values and the resulting decisions must then be adjusted in the course of the project.
In the context of time management, AI-based project management software can not only make it easier to prioritize tasks, but also help you to manage continuous change more easily.
There are not only software solutions for time management, but also sophisticated solutions for effective portfolio and demand management, or budget-management.
