ABC Pareto Analysis Model - Model Scenario

ABC Pareto Analysis

Often companies spend a lot of time managing items/entities that have a low contribution to the profit margin. Every item/entity inside your shop does not have equal value - some of them cost more, some are used more frequently, and some are both. This is where the ABC Pareto analysis steps in, which helps companies to focus on the right items/entities.

ABC analysis is a classification method in which items/entities are divided into three categories, A, B, and C.

• Category A is typically the smallest category and consists of the most important items/entities ('the vital few'),

• while category C is the largest category and consists of least valuable items/entities ('the trivial many').

So far this is the simplest model, i.e only 2 columns are needed in your dataset.

You have to identify

• ID column
• numeric column

An ID column in your dataset is usually Product ID or name, SKU, etc. Based on the selected values, the data will be grouped by that column.

After that, you have to select the numeric column (feature) which represents the value of the ID column (for example, product/customer revenue or the number of sold units,...).

And that's it - in the next post, we are going through the Model Results.