An ABC inventory classification system, also known as the Pareto Analysis, primary and secondary factor analysis, ABC analysis, ABC management method, and the 80-20 rule, is a technique used to categorize inventory into three categories based on their value.
They feature a small proportion in quantity and a large proportion in value.
They are important less important than "A" items and more important than "C" items.
They feature a large proportion in quantity and a small proportion in value.
The essence of this classification method is that a few items contribute most of the value. Take style and sales volume as an example: Products in Style A account for 10% of the total sales volume, but account for 80% of the sales revenue.
By classifying objects according to their main technical or economic characteristics, you can distinguish between prior and general objects and thus apply different management methods. ABC analysis divides the analyzed objects into three categories: A, B, and C, and there are no fixed thresholds for each class.
For details on the dashboard, see Pareto Analysis of Merchandise Sales.
In the component “Pareto Analysis of Commodity Brand Sales” of “Pareto Analysis of Merchandise Sales”, you can view the sales amount of each brand's products and the corresponding cumulative sales proportion. According to the ABC analysis method, you can sort products of different brands in descending order by cumulative sales volume and divide them into three brands A, B, and C according to the cumulative sales volume percentage of 80%, 10%, and 10%, respectively. And you can display them in different colors of bar charts as shown below:
By processing existing data when creating analysis subjects or adding calculation indicators using formulas when making components, you can calculate the cumulative proportion indicator. Based on that you can divide objects into A, B, and C when making components (divide objects into 80%-class and 20%-class for 80-20 analysis), and present the analysis results through different colors of bars. The data processing idea is shown in the following figure:
The key to implementing the ABC proportion division is to calculate the cumulative proportion, and then divide objects according to the indicator. This article introduces two methods for calculating cumulative proportions.
Example 1: Create the cumulative proportion by adding calculation indicators in the dashboard and processing data using formulas.
Example 2: Calculate the cumulative proportion with data in the subject. The indicator can be used in multiple components.
(1) To create an ABC analysis subject, choose My Analysis > New Subject, select Store sales statistics from the built-in public data, and click OK to add data, as shown in the following figures.
(2) Click Field Settings, deselect Store name and Area, and click Save And Update, as shown in the following figure.
Click Component in the bottom left corner, as shown in the figure below:
Click to add a calculation indicator, name it Cumulative Proportion, enter the formula ACC_SUM(SUM_AGG(Sales Volume)/TOTAL(SUM_AGG(Sales Volume),0,'sum')), click OK, as shown in the figure below:
The formula is explained in the following table:
Procedure
Formula
Explanation
Calculate the total sales of each brand
SUM_AGG(Sales Volume)
SUM_AGG: Return the sum value of the indicator fields in the current analysis dimension.
Calculate the total sales of all brand products
TOTAL(SUM_AGG(Sales Vlolume),0,"sum")
TOTAL(): Calculate the aggregation of sum values of the indicator fields in the current dimension.
Calculate each brand's sales
SUM_AGG(Sales Volume)/TOTAL(SUM_AGG(Sales Volume),0,"sum")
/ represents division and can be used to calculate percentages.
Calculate cumulative percentage
ACC_SUM(SUM_AGG(Sales Volume)/TOTAL(SUM_AGG(Sales Volume),0,"sum"))
ACC_SUM(): Calculates an accumulating sum for the fields in the current dimension.
In addition, calculating the cumulative sales first and then calculating the proportion is accepted, too. The formula is as follows: ACC_SUM(SUM_AGG(Sales Volume),0)/TOTAL(SUM_AGG(Sales Volume),0,"sum")
Drag the field to be analyzed into the corresponding horizontal and vertical axes, select Custom Chart, and set Sales Volume as a bar chart and Cumulative Proportion as a line chart, as shown in the following figure:
Set the value axis for Cumulative Proportion as shown in the following figure:
Select Right-value Axis as Shared Axis, check Display Range > Custom, and set Maximum and Minimum as shown in the figure below:
For detailed settings, see Setting Category Axis on Charts.
Sort Brand Description in descending order based on Sales Volume, as shown in the following figure:
1) Add a calculation indicator named ABC Classification with the formula IF(Cumulative Proportion<0.8,1,IF(Cumulative Proportion>0.9,3,2)), where 1 represents Class A products, 2 represents Class B products, and 3 represents Class C products,
Note:
The steps are roughly the same for 80-20 analysis, but you need to modify the formula to classify analysis results in different colors. The formula should be modified to IF(Cumulative Proportion<0.8,1,2), which analyzes the few brands that account for 80% of the sales volume and classifies them as Type A with a return value of 1, while the rest represent Type B with a value of 2.
2) Divide different classes of brands by color. Drag ABC Classification into Color under Graphic Properties>Sales Volume(Sum), and select Continuous Gradient for Gradient Type. According to the divided categories, select the number of colors. Since there are three categories, set it to 3 and set the corresponding colors as shown in the following figure:
Set the cordon for the Pareto chart as shown in the following figure:
At the same time, you can make the Pareto charts dynamic by adding filtering components and other required component types.
See section Expected Effect.
Taking Store sales statistics in the built-in public data as an example, perform a Pareto analysis on the sales volume of each brand and determine the most important brand for the company.
1) Add the table Store sales statistics in the analysis subject, click Field Settings, and deselect Store name and Area, as shown in the following figure.
Click Group Summary, drag Brand Description into Group, and drag Sales Volume into Total, as shown in the figure below:
Click Sort, click Add Sorting Indicator, select Sales Volume, and select Descending, as shown in the following figure:
1) Click Summary Column.
2) Name the new column Total Sales, set Summary Field as Sales Volume, and Summary Method as Sum, and then click OK as shown in the following figure:
1) Click Summary Column, name the new column Cumulative Total, set Summary Field as Sales Volume, Summary Method as Accumulation, Sort Field as Sales Volume and sort in descending order, and then click OK, as shown in the following figure:
2) Get the cumulative total as shown in the following figure:
1) Click Formula Column, name the new column Cumulative Proportion, enter the formula Cumulative Total/Total Sales and click OK, as shown in the following figure:
2) Get the cumulative proportion as shown in the following figure:
Click Save And Update, enter the subject interface, and you can preview the data, as shown in the figure below:
Refer to Preparing Components of this article for the calculation method of the chart components.
See Expected Effect.
You can draw a conclusion from creating this dashboard that 40% of the brands in this category account for 80% of the sales.
Brand Name
Proportion of Brand Number
Proportion of Brand Sales
Class A brand
ZIPPO, PAW IN PAW, NEW BALANCE, HANG TEN
40%
80%
Class B brand
SINOMAX, O.C.T.MAMI
20%
10%
Class C brand
WHO.A.U, RACB JJQN, LESPORTSAC, X.ZHINING
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