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# Pareto Chart

Pareto Chart is named after Vilfredo Pareto, who formulated the Pareto Principle.

Pareto Principle:

Pareto Principle is the 80-20 rule. It basically states that, 80% of the results come from 20% of the causes.

Ex: 80% of Sales happening because of 20% of Products.

Use of Pareto Chart:

Pareto Chart is a great way to visualize the 80-20 rule. It is used to highlight the factors that cause the biggest impact among a typically large set of factors.

For example, in quality control, it can be used to represent the most common sources of defects, the highest occurring type of defect or the most common reasons for customer complaints etc.

So, it is mainly used for Quality control and identify biggest opportunities for improvements.

What is Pareto Chart?

Pareto Chart is basically a dual-axis combination chart in Tableau with Bars and a Line graph, where individual values are represented in descending order by bars and a cumulative total (in Running Percentage of Total format) is represented by the line graph in ascending order.

Now get into creating a Pareto Chart:

For this, I am using data from Sample Superstore data set. Since this is a mock up data, it might not follow the 80-20 rule but helps in understanding the Pareto Chart.

Go to Tableau, connect to the Data source which is excel file in our case:

The excel sheet has 3 sheets in it: Orders, People, Returns

In this Pareto Chart we are trying to analyze what Product Sub-categories are Returned most compared to others.

So, we need Orders and Returns sheets.

We do a Left Join on these 2 sheets based on ‘OrderID’ which is common for both the sheets.

Now the data is ready to be analyzed.

Create a Calculated Field ‘Returns’ to get the Total number of Orders Returned:

Now start creating the Pareto Chart.

First, create a Bar Chart, by bringing ‘Returns’ to Rows and ‘Sub-Category’ to Columns and sort in descending order:

Now, create a Dual Axis chart, by bringing ‘Returns’ to the Rows again. Keep the Primary axis Mark type as Bar, and change the secondary axis mark type as line and change it to a different color. Then merge these 2 graphs.

Now, add a ‘table calculation’ and a ‘secondary table calculation’ for the second ‘Returns’ pill to display the Cumulative Percentage Total of Returns across the Product Sub-Categories.

Select ‘Running Total’:

Add Secondary Calculation, Percentage of Total:

The graph will look like this:

Now add label to the Line graph with Running Percentage Total of Returns:

To check the 80-20 rule, add constant line to show 80% mark:

From the above chart, we can say that, 80% of the Returns are coming from Sub-Categories – Binder, Paper, Phones, Furnishings, Accessories, Chairs, Storage and Art.

This is a basic Pareto chart.

We can modify this chart, to get, what percentage of Sub-Categories amount to 80% of Returns.

i.e., on X-axis instead of Sub-category names we can show percentage of Sub-Categories.

Let’s get into that:

Now repeat all the steps that you did above to get the line graph with cumulative percentage of total and add ‘Sub-Category’ to the ‘Details’ in Marks.

Now instead of showing the Sub-Categories in the X-axis, we create a calculation that rather shows the percentage of the Sub-Categories.

In order to do that we need to do the below steps:

1.     To create a calculation on dimension, first change it to Measure with ‘Count (Distinct)’.

2.     Now do a ‘quick table calculation’ of ‘Running Total’ and secondary calculation of ‘Percentage of Total’ on Sub-Category

After this step, chart looks like this:

At this step, the chart is sorted based on Sub-Categories instead of the Returns. Now change the sort to as per Returns.

Now add the constant lines to show the 80-20 rule:

Now add the Bar chart as well and make it Dual Axis. After which the Chart should look like this.

Now, we have dots instead of line for Cumulative Percent of Total for Returns, so add the Sub-Category to ‘Path’ in Marks.

Now the final Visualization should look like this:

Now you have the 80-20 Pareto of Sub-Category vs Returns showing the percentages.

The final Chart looks like this:

From this chart we can say that, “50% of the Sub-Categories amount to 80% of the Returns”. Since this is a mock up data, it does not follow 80-20 rule but it is a great way to understand the biggest impacting factors.

Conclusion:

Pareto charts are powerful tools for solving business problems because every process produces defects, mistakes and errors and hence the need of qualitative analysis. A Pareto chart analyses the frequency of the problems or causes of problems in a process and this technique works wonders to find out the reasons for the problems.