Pareto Chart

What is Pareto Chart?

A Pareto chart, also known as a Pareto diagram, is a specific type of chart used to analyze and display data in order to identify the most significant factors or categories that contribute to a particular outcome or problem. It is named after Vilfredo Pareto, an Italian economist who observed that a large portion of wealth in society is concentrated in a small percentage of the population.

A Pareto chart consists of both bar and line graphs. The vertical axis represents the frequency or count of occurrences of a specific category or factor, while the horizontal axis represents the categories or factors themselves, listed in descending order. The bars are arranged in decreasing order from left to right, with the tallest bar indicating the most significant category.

When to use Pareto Chart?

The Pareto chart is particularly useful in the following situations:

  • Problem-solving: When you want to identify the most critical problems or issues that are affecting a process, product, or service, a Pareto chart can help you prioritize and focus your efforts on the vital few factors that contribute to the majority of the problems.
  • Root cause analysis: When investigating the root causes of a problem or failure, a Pareto chart can help you identify the main factors or causes that are responsible for the majority of the issues. This allows you to address the primary causes and achieve more effective solutions.
  • Quality improvement: When working on process improvement or quality control initiatives, a Pareto chart can help you determine which factors or defects are most prevalent and have the greatest impact on quality. This information can guide your improvement efforts towards the areas that will yield the most significant results.
  • Decision-making: When faced with multiple options or alternatives, a Pareto chart can provide insights into the factors that have the most influence or contribute the most to the desired outcome. This helps in making informed decisions and allocating resources effectively.
  • Performance evaluation: When assessing performance metrics or analyzing data sets, a Pareto chart can highlight the most critical areas or variables that are driving the desired outcome or have the biggest impact on performance. This enables you to focus on the key areas that require attention or improvement.

In summary, a Pareto chart is a valuable tool for prioritization, problem-solving, root cause analysis, quality improvement, decision-making, and performance evaluation. It is most effective when dealing with complex data sets and when you want to identify and concentrate on the factors that have the most significant impact.

Guidelines for correct usage of Pareto Chart

  • Collect summary data or raw data.
  • Summarized data represents categories and can be in the form of counts or calculated values like means.
  • Raw data represents individual occurrences or defects, with each observation in a separate row.
  • Create a chart using either summarized data or raw data.
  • Ensure the validity of your results by following the mentioned guidelines.

Alternatives: When not to use Pareto Chart

  • Histogram: A histogram is a bar chart that represents the distribution of continuous data. It can be useful when you want to understand the frequency distribution of a variable or identify patterns in data. Histograms are especially helpful when dealing with large datasets and continuous variables, whereas Pareto charts are more suitable for discrete variables.
  • Bar Chart: A bar chart is a simple and straightforward way to compare different categories or groups. It can be used to display categorical data, such as sales by product category or the performance of different teams. Bar charts are effective when you want to show a clear comparison between different groups, whereas Pareto charts prioritize items based on cumulative frequencies or impact.
  • Scatter Plot: A scatter plot is used to display the relationship between two continuous variables. It can be helpful in identifying correlations or trends between variables. Scatter plots are commonly used in statistical analysis and research to examine the strength and direction of relationships, whereas Pareto charts focus on the frequency or impact of individual items.
  • Box Plot: A box plot, also known as a box-and-whisker plot, provides a summary of the distribution of a dataset. It shows the median, quartiles, and any outliers present in the data. Box plots are useful when you want to compare distributions or identify the spread and skewness of data. They are particularly valuable when dealing with large datasets and multiple variables, while Pareto charts are more suitable for prioritization purposes.

Example of Pareto Chart?

To prioritize improvement projects, an inspector from a clothing manufacturer examines various sources of clothing defects. The inspector carefully monitors and records the quantity and nature of these defects throughout the manufacturing process.

Subsequently, an engineer utilizes the data collected by the inspector to develop a Pareto chart. This chart helps to prioritize the defects identified by the inspector, highlighting the most significant or frequently occurring issues that require immediate attention. She has performed this in following steps:

  1. She worked all day and gathered the necessary data.
  2. Now, she analyzes the data with the help of
  3. Inside the tool, she feeds the data along with other inputs as follows:
  4. After using the above mentioned tool, she fetches the output as follows:

How to do Pareto Chart

The guide is as follows:

  1. Login in to QTools account with the help of
  2. On the home page, you can see Pareto Chart under Graphical analysis.
  3. Click on Pareto Chart and reach the dashboard.
  4. Next, update the data manually or can completely copy (Ctrl+C) the data from excel sheet and paste (Ctrl+V) it here.
  5. Next, you need to map the data with relevant parameters
  6. Finally, click on calculate at the bottom of the page and you will get desired results.

On the dashboard of Pareto Chart, the window is separated into two parts.

On the left part, Data Pane is present. In the Data Pane, each row makes one subgroup. Data can be fed manually or the one can completely copy (Ctrl+C) the data from excel sheet and paste (Ctrl+V) it here.

On the right part, there are many options present as follows:

  • Defects or attribute data: In a Pareto chart, attribute data refers to qualitative or categorical data that describes the characteristics or attributes of a particular item or category. Attribute data is non-numeric and typically represented by labels, categories, or discrete values.
  • Frequencies: In a Pareto chart, frequencies represent the number of occurrences or observations of a specific category or event.
  • Pareto threshold percent: In a Pareto chart, the Pareto threshold percent refers to the percentage value that is used to determine the cutoff point for identifying significant contributors. The Pareto threshold percent is the point on the chart where the cumulative percentage of the factors reaches or exceeds the specified threshold. It helps determine which factors contribute significantly to the overall effect.
  • Combining remaining attributes after threshold: In a Pareto chart, combining remaining attributes after a certain threshold means grouping together all the attributes or categories that fall below a specified threshold and treating them as a single category or group. This is done to simplify the chart and focus on the most significant contributors.
  • Chart cumulative percent: In a Pareto chart, the cumulative percent refers to the cumulative percentage of the total value or frequency represented by each category or group in the chart. It helps in analyzing the contribution of each category to the overall total.