# What Is a Pareto Chart? (With Components, Uses and Steps)

By Indeed Editorial Team

Published 9 November 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Businesses often encounter challenges to attain their objectives and utilise their resources well. To help companies with these situations, they can use a Pareto chart to analyse their products' performance and optimise their production lines. Learning more about Pareto diagrams can help you use this tool to address various scenarios that a company handles during production. In this article, we define what a Pareto chart is, outline its components, explain when to use one and provide steps for creating this chart and answers to FAQs.

## What is a Pareto chart?

A Pareto chart, also known as a Pareto diagram or a Pareto analysis, is a cause analysis technique that combines a line graph and a bar graph. It represents a product's defects or causes of complaints regarding an item. Pareto diagrams can also measure other factors, such as time or cost. Each bar can show a type of problem or defect. A bar's height indicates an important unit of measure. For example, it can show the frequency of a problem's occurrence or its cost. Its bars are in descending order, which quickly indicates the more frequent defects.

The chart's line represents the cumulative percentage of problems. A cumulative percentage is a running sum of a data set's percentage values, ending at 100%. The cumulative percentage of problems shows the proportion of issues the company can resolve by addressing each defect type. The organisation can have more frequent defects and considerable losses when the line is steeper and bars reach higher points. Companies use the Pareto principle, also known as the 80/20 rule, to find and address the 20% of defect types causing 80% of the defects. Reducing defects can help the organisation improve its product or operation.

Related: 10 Most Essential Data Analysis Skills

## Components of a Pareto diagram

Understanding a Pareto diagram's components can help you construct or interpret one. A Pareto chart is a bar graph with two important variables forming the y-axis and x-axis. The x-axis plots the different data categories. The y-axis shows the number of occurrences in each category.

You order the bars from the highest to lowest frequencies, placing them from left to right. Use a line graph to show the cumulative percentage of the sum of occurrences. You can use the line graph to identify whether the data set follows the Pareto principle.

## When to utilise a Pareto diagram

The following are some situations in which a Pareto diagram can help you:

• Evaluating a product: An organisation's employees can capture information from customer reviews or survey customer returns on a Pareto diagram. They can interpret the chart to determine a product's flaws and if they can correct or reduce them.

• Comparing problems: Pareto diagrams allow individuals to compare various product issues and prioritise fixing the important ones. They can address the largest bar's problem first before fixing challenges that occur less frequently.

• Analysing problems: Dividing issues into components using a Pareto diagram can help you find possible causes. The division can highlight the common challenges, allowing the organisation to address them and satisfy interested parties.

• Presenting data: A Pareto diagram can help individuals present data sets. They're captivating, allowing the presenter to inform interested parties about important challenges and different ways to address them.

Related: Reverse Logistics: Definition, Components and Benefits

## How to create a Pareto diagram

The following steps can help you develop and use this type of chart:

### 1. Determine the information to discover

When receiving many complaints about an item, you can use a Pareto diagram to discover why the complaints occur. Identify the product to investigate and review its causes for complaints. You can start to classify the complaints for the chart and understand the frequency of certain categories.

Example: Rexic Textiles is a clothing store. Many customers have been returning the shirts they buy. So, the company can use a Pareto diagram to begin understanding why clients return the shirts. They can discover how many customers return them due to various issues, such as the design, size or delivery.

Related: What Is Lead Time and Why Is It Important? (With an Example)

### 2. Choose problem categories

Pick the types or categories of defects to measure. You can classify the various issues into these groups. Ensure you obtain the data for each defect category through reliable data collection methods, such as customer surveys.

Example: When customers return the shirts to Rexic Textiles, they can complete a short survey about their reasons for returning the item. Then, the company's staff can classify these reasons, such as if the delivered shirt was too small or the wrong item.

Related: What Is Good Customer Service? Definition and Guideline

### 3. Collect the data

Select a data collection technique, such as customer surveys and questionnaires, and collect the data in a simplified manner to help customers input the relevant information quickly. You can choose the duration for the data collection stage, such as a typical production cycle, week, month or year. Find the total occurrence frequency for each category within a specific period. You may also measure other factors, such as time or cost.

Example: Data from customer surveys show that 15 customers returned the shirts because they were too big and five were too small. In their shipment package, three customers received shirts with damage and two received a shirt they didn't order.

Related: What Is Research Methodology and Why Is It Important?

### 4. Prepare the data

You can use tables to organise the data. Put the data points for the frequencies of each defect category in descending order. Add these frequencies together to obtain the sum of defects. Preparing this data can show the chart's range.

Example: The frequencies for each defect category for the shirts, in descending order, are the following:

Defect category frequency: 15, 5, 3, 2

To obtain the sum of defects for the period, use the following equation:

Sum of defects = 15 + 5 + 3 + 2
= 25

### 5. Calculate the cumulative percentages

To prepare the cumulative percentage data, divide the most common defect's first data point by the sum of defects. Multiply the outcome by 100 to get the first percentage. Add the next data point to the preceding data point before dividing the result by the sum of defects and multiplying it by 100. The following percentage is the sum of the first and second percentages. Repeat this process with the other data points. The last cumulative percentage is 100%.

Example: You can get the first cumulative percentage by dividing the most common defect by the sum of defects and multiplying this result by 100. The following shows this equation using the data from Rexic Textiles:

First cumulative percentage = (15 / 25) × 100
= 60%

To calculate the next cumulative percentage, add the subsequent defect to the first data point before dividing by the sum of defects and multiplying it by 100, as shown in the following equation:

Second cumulative percentage = [(15 + 5) / 25] × 100
= (20 / 25) × 100
= 80%

The following are the remaining cumulative percentage calculations:

Third cumulative percentage = [(15 + 5 + 3) / 25] × 100
= (23 / 25) × 100
= 92%

Fourth cumulative percentage = [(15 + 5 + 3 + 2) / 25] × 100
= (25 / 25) × 100
= 100%

### 6. Draw the bar graph

On the horizontal x-axis, write the labels for each defect category from left to right in descending order. Number the vertical y-axis on the left side from zero to a number slightly higher than the data's highest frequency value. Use intervals of regular and round numbers. You can plot the bar graph with bars corresponding with the frequency total for each defect type.

Example: The Rexic Textile's example has the highest data point at 15. The company's employees can number the y-axis from one to 16 with intervals of one.

Related: Key Differences Between a Bar Chart vs. Histogram

### 7. Draw the line graph of cumulative percentages

Label the graph's right vertical axis using percentages. You can match 100% with the highest frequency point. Draw dots for the calculated cumulative percentages from step five in ascending order and reaching 100%. Connect the dots to get a line graph.

Example: The Pareto diagram shows that most clients are returning the Rexic Textile's shirts because they're too big or too small. This means that fixing the size problem can solve 80% of the company's challenges. The company can consult its design department to address this challenge and eliminate or reduce returns.