This principle is said to apply to various business phenomena, such as 80% of sales being generated by 20% of all customers, or 80% of product defects being caused by 20% of all causes.<\/p>\n\n\n\n
Pareto analysis uses this concept to narrow down the most important issues and causes to address, helping prioritize problem-solving efforts.<\/p>\n\n\n\n
3 Key Benefits of Pareto Analysis<\/h2>\n\n\n\n
By leveraging Pareto analysis, you can take an effective approach to a wide variety of business challenges.<\/strong><\/span> This analytical method visualizes the structure of problems and supports data-driven decision-making. The greatest benefit of performing Pareto analysis is that it becomes clear which issues among many should be addressed first.<\/strong><\/span><\/p>\n\n\n\n For example, when customer complaints span a wide range of topics, responding to all complaints equally is inefficient. By using Pareto analysis to categorize complaint content and charting it by frequency of occurrence, you can identify the small number of complaint causes that account for 80% of the total. In this way, by grasping the overall picture of a problem and identifying the elements with the greatest impact, it is possible to formulate an effective action plan.<\/strong><\/span><\/p>\n\n\n\n A company’s management resources \u2014 people, goods, money, and time \u2014 are finite. Therefore, it is not realistic to tackle every issue with full force. Pareto analysis provides guidance for concentrating those limited resources in the most effective areas.<\/strong><\/span> This prevents resources from being scattered across all fronts with half-hearted results, enabling the execution of cost-effective measures.<\/p>\n\n\n\n Pareto analysis is also effective as a tool for comparing and measuring the effects before (Before) and after (After) implementing improvement measures.<\/strong><\/span><\/p>\n\n\n\n Create a Pareto chart before implementing measures to identify current issues, then create another Pareto chart with the same data after taking action. The Pareto chart used in Pareto analysis can be easily created by anyone using Excel, which is used in everyday business operations, without any specialized analysis software. First, clarify the purpose of the analysis and collect relevant data<\/strong><\/span>. For example, if the goal is to “identify causes of complaints,” tally the types of complaints and their frequency of occurrence.<\/p>\n\n\n\n Once the data is gathered, enter the items and values (frequencies) into an Excel sheet, and organize the data by sorting the values in descending order (largest to smallest).<\/p>\n\n\n\n This sorting step is an important preparatory stage for correctly creating a Pareto chart.<\/p>\n\n\n\n At this point, grouping low-priority items such as “other” or minority opinions into one category can make the chart easier to read.<\/p>\n\n\n\n After sorting the data in descending order, calculate the “percentage” and “cumulative percentage” for each item.<\/strong><\/span><\/p>\n\n\n\n The percentage shows how much each individual item’s value accounts for the total, calculated as “each item’s frequency \u00f7 total frequency.”<\/p>\n\n\n\n The cumulative percentage is calculated by adding up the percentages from the top down; for the second item, it is “1st item’s percentage + 2nd item’s percentage.” Once the calculations are complete, it is time to create the chart. First, on the Excel sheet, select the data range you want to chart (item names, frequencies, and cumulative percentages). This will automatically create a combination chart with a bar graph showing the frequency of each item and a line graph showing the cumulative percentage.<\/p>\n\n\n\n At this stage the chart has not yet taken the shape of a Pareto chart, but the basic foundation of the graph is complete.<\/p>\n\n\n\n To format the combination chart into a Pareto chart, set up the secondary axis. Right-click on the line graph (cumulative percentage) in the chart and select “Format Data Series.” In the settings panel that appears, check “Secondary Axis” under “Series Options” in “Plot Series On.”<\/strong><\/span> This completes the unique Pareto chart format, where the left primary axis represents frequency and the right secondary axis represents cumulative percentage.<\/p>\n\n\n\n Finally, format the chart so that it is easy for anyone to understand at a glance.<\/p>\n\n\n\n First, change the chart title to something that clearly conveys the content, such as “Complaint Cause Analysis.” As an example, adding labels to the vertical and horizontal axes (such as “Number of Cases” and “Cause Items”) as needed will make it even clearer. Adjust the position of the legend, change the colors of the chart, and make other design adjustments as needed to complete a Pareto chart that effectively communicates your analysis results.<\/p>\n\n\n\n A Pareto chart is not complete once it is created \u2014 what matters is what you draw from it. By correctly analyzing the completed chart, the true nature of the issues to be addressed becomes clear.<\/strong><\/span> Here, we explain two important points for effectively reading issues from a Pareto chart.<\/p>\n\n\n\n The most fundamental point when reading a Pareto chart is to focus on the group of items included before the cumulative percentage line graph reaches the 80% mark.<\/strong><\/span><\/p>\n\n\n\n These items, lined up from the left side of the chart, correspond to the “vital 20% that produces 80% of results.” In other words, concentrating improvement measures on these few items is the most efficient shortcut to improving the whole.<\/strong><\/span> The first step in analysis is to accurately identify which items are included up to this 80% line.<\/p>\n\n\n\n Another point of focus is the change in the slope of the line graph showing the cumulative percentage.<\/strong><\/span> On the left side of the chart, the slope is steep, indicating that each individual item has a large degree of influence on the whole.<\/p>\n\n\n\n On the other hand, as you move to the right, the slope gradually becomes more gradual, indicating that the influence of individual items is decreasing. Rather than addressing every item, this serves as an objective indicator for narrowing down to the items with the greatest impact.<\/p>\n\n\n\n Due to its simplicity and versatility, Pareto analysis is used as a tool for problem discovery and decision-making in a wide variety of business scenarios. It can be applied in any situation where you want to prioritize based on data, regardless of industry or job type. In the fields of marketing and sales, Pareto analysis is frequently used to analyze sales data.<\/p>\n\n\n\n For example, by analyzing the sales figures of all products and creating a Pareto chart, the so-called “best-selling products” that generate the majority of overall sales become clear. Similarly, by analyzing purchase amounts by customer, you can identify the “high-value customer segment” that deserves priority follow-up.<\/strong><\/span><\/p>\n\n\n\n Based on these analysis results, it becomes possible to formulate more effective sales strategies, such as expanding inventory of best-selling products or implementing special campaigns targeting high-value customers.<\/p>\n\n\n\n In quality control (QC) activities in the manufacturing industry, Pareto analysis has long been used as one of the “7 QC Tools.”<\/p>\n\n\n\n Defective products occurring in a factory are classified by cause (e.g., “scratched parts,” “uneven coating,” “dimensional errors”), and a Pareto chart is created based on the number of occurrences.<\/strong><\/span><\/p>\n\n\n\n This allows you to see at a glance which of the many defect causes occurs most frequently.<\/p>\n\n\n\n By intensively addressing the identified primary causes, you can expect to efficiently improve overall product quality and significantly reduce the defect rate.<\/strong><\/span><\/p>\n\n\n\n There are many opportunities to apply Pareto analysis in daily operations, such as mistakes in clerical work or complaints received by call centers.<\/p>\n\n\n\n By compiling data on the content of mistakes or types of complaints and applying Pareto analysis, it may become clear that many of the problems are concentrated in specific business processes or a subset of products and services. A method often discussed in relation to Pareto analysis is “ABC analysis.”<\/p>\n\n\n\n The two share the common foundation of the Pareto Principle, but there are clear differences in their purposes and outputs.<\/strong><\/span><\/p>\n\n\n\n Pareto analysis is an analytical method aimed at identifying the primary factors causing a problem and “prioritizing” countermeasures.<\/strong><\/span><\/p>\n\n\n\n ABC analysis, on the other hand, applies the concept of Pareto analysis to “rank” targets (products, customers, etc.) into three groups \u2014 A, B, and C \u2014 based on their importance, as a management method for differentiating how they are handled.<\/strong><\/span> Pareto analysis is a powerful framework based on the “80\/20 Rule” for identifying the most impactful and important elements from among many options.<\/p>\n\n\n\n No specialized tools are required \u2014 anyone can easily create a Pareto chart using Excel and visually grasp challenges. By building on the insights gained through analysis to formulate concrete action plans for improvement and putting them into action, you can achieve greater operational efficiency and improved results across the entire organization.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n
Specifically, it clarifies the priority of issues to address and enables efficient allocation of limited resources.<\/strong><\/span> It also functions as a metric for quantitatively measuring the effectiveness of initiatives after implementation, contributing to continuous improvement activities.<\/p>\n\n\n\nClarifies the Priority of Issues<\/h3>\n\n\n\n
By focusing countermeasures on the causes with the greatest impact, a clear path to efficiently reducing overall complaint numbers becomes visible.<\/p>\n\n\n\nEnables Focused Allocation of Limited Resources<\/h3>\n\n\n\n
By focusing resources on the “vital 20% that influences 80% of the whole” identified through analysis, you can expect maximum results from minimal investment.<\/strong><\/span><\/p>\n\n\n\nAllows Numerical Measurement of Improvement Results<\/h3>\n\n\n\n
By comparing the two charts, you can objectively evaluate in numerical terms how much the proportion of the items you focused on has decreased, and how the cumulative percentage curve has changed.<\/strong><\/span> This allows you to judge whether a measure was effective based on data and gain new insights for the next round of improvement activities.<\/p>\n\n\n\nEasy with Excel! A 5-Step Guide to Creating a Pareto Chart<\/h2>\n\n\n\n
Once your data is ready, following a few steps will complete a chart that visualizes your problem points.<\/p>\n\n\n\n![\"\"](\"https:\/\/mirai-works.co.jp\/consulnext\/wp-content\/uploads\/2025\/10\/framework_pareto1.jpg\")
Here, we will explain the specific steps for creating one, broken down into 5 easy-to-understand steps for beginners, so try it out with your own data.<\/p>\n\n\n\nStep 1: Collect and Organize the Data You Want to Analyze<\/h3>\n\n\n\n
Step 2: Calculate the Percentage and Cumulative Percentage for Each Item<\/h3>\n\n\n\n
Repeating this process through the last item will result in a final cumulative percentage of 100%. These values become the source data for the Pareto chart.<\/p>\n\n\n\nStep 3: Create a Combination Chart (Bar and Line)<\/h3>\n\n\n\n
Next, go to the “Insert” tab in Excel, select “Insert Combo Chart” from the “Charts” group, and choose “Clustered Column \u2013 Line on Secondary Axis.”<\/strong><\/span><\/p>\n\n\n\nStep 4: Set the Secondary Axis to Shape the Pareto Chart<\/h3>\n\n\n\n
A new vertical axis (secondary axis) will be added to the right side of the chart, and the line graph will reference this secondary axis.<\/p>\n\n\n\nStep 5: Adjust the Chart Title and Design<\/h3>\n\n\n\n
Additionally, fixing the maximum value of the secondary axis to “1.0” (100%) often makes the chart easier to read.<\/p>\n\n\n\n2 Key Points for Reading Issues from a Completed Pareto Chart<\/h2>\n\n\n\n
Particularly in sales analysis and quality improvement, which part of the chart you focus on is key to determining the next action.<\/p>\n\n\n\nFocus on Items That Account for 80% of the Cumulative Percentage<\/h3>\n\n\n\n
This way of thinking also forms the basis of ABC analysis, a management method that ranks products by importance and differentiates how they are managed.<\/p>\n\n\n\nLook for Where the Line Graph’s Slope Becomes Gradual<\/h3>\n\n\n\n
By identifying the “inflection point” where the slope transitions from steep to gradual, you can use it as a criterion for deciding which items to manage as priorities and which to treat as “other.”<\/strong><\/span><\/p>\n\n\n\n\u3010Examples\u3011Main Application Scenarios for Pareto Analysis<\/h2>\n\n\n\n
Here, we highlight three representative scenarios \u2014 sales analysis, quality control, and business improvement \u2014 and introduce with concrete examples how Pareto analysis is used and what effects it brings.<\/p>\n\n\n\nSales Analysis: Understanding High-Contributing Customers and Products<\/h3>\n\n\n\n
Quality Control: Identifying the Main Causes of Defective Products<\/h3>\n\n\n\n
Business Improvement: Pinpointing the Causes of Frequent Mistakes and Complaints<\/h3>\n\n\n\n
By identifying these “areas where problems are concentrated” and linking them to specific improvement measures such as revising business manuals or conducting employee training, organizations can achieve improvements in productivity and customer satisfaction across the entire organization.<\/p>\n\n\n\nHow to Distinguish Between Pareto Analysis and ABC Analysis<\/h2>\n\n\n\n
For example, in inventory management, Group A inventory with high sales contribution is managed intensively, while Group C management costs are kept low. The key difference is whether the process ends at analysis or is carried through to a management method.<\/p>\n\n\n\nSummary<\/h2>\n\n\n\n
Its applications are wide-ranging, from identifying key products through sales analysis, to investigating causes of defects in quality management, to reducing mistakes in daily operations.<\/p>\n\n\n\n