Using Pareto & Paynter Charts in a Quality Improvement Program

Pareto charts and Pareto-derived Paynter charts are important statistical tools in quality improvement programs. Six Sigma and other methodologies rely upon Pareto analysis to define and focus continuous improvement efforts.

Although the term Pareto principle (or Pareto effect) has become a standard term in business and quality improvement jargon, it is often not clear when to use Pareto charts, or how to use them effectively. At Statit, Inc., Pareto and Paynter charting capabilities are built into our Statit e-QC product. Combined with the ability to "drill down" dynamically through layers of data, Statit e-QC enables you to bring these powerful tools to your Continuous Quality Improvement (CQI) program. In this article we define the Pareto principle, the Pareto chart and Paynter charts. Further, we illustrate when to use these tools and how to maximize their use. References for further study are provided.

The Pareto Effect

The term Pareto Effect, or the Pareto Principle, is based upon the research of Italian economist Vilfredo Pareto, whose 19th century study established that 80% of the land in Italy was owned by 20% of the population. The findings of Pareto's research are observable in many phenomena and the principle has become generalized into the 80/20 Rule. It turns out the 80/20 rule can be observed and measured in many disciplines and fields of study, and often characterizes variations in processes and products for which cause can be assigned. The term Pareto effect is widely used in analyzing many business processes. To illustrate how commonly used this principle has become, one often hears observations such as 20% of our products account for 80% of our sales, or 80% of our customers only utilize 20% of the features in our product. Although the term Pareto principle has become widely used, it is not always clear how to specifically use Pareto analysis techniques in a CQI program.

When to Use a Pareto Chart

The Pareto chart is a specific tool of statistical analysis used to find one or more areas in which to focus process improvement efforts. It is important to note that you do not need to discover 80% of your variances can be assigned to 20% of your causes. Your results may reveal that indeed, one defect, which is only 20% of total defects, results in 80% of product rejects. Use Pareto analysis when you want to determine the "vital few" causes that are responsible for the majority of defects in a product. Pareto analysis can also be "weighted" so that you can determine which defects result in the most costs, or which defects result in the most customer complaints. The Pareto chart allows you to focus your efforts to achieve the greatest improvements by identifying the largest issues facing the process, and helps you in determining priorities in maximizing return of investment of time and expense.

Your criteria or weighting of factors may vary (such as "cost to fix", critical defect, customer impact, etc.), but the goal and results of Pareto analysis remain the same: to provide focal points for process improvement.

When to Use a Paynter Chart

The Paynter chart is an extension of a Pareto chart that provides further definition to a Pareto chart. The Paynter chart is used to indicate what items make up the count for each Pareto reporting period or count. By drilling down through Pareto and Paynter results, Statit e-QC allows you to see different views and slices of your data that gives a more complete picture of your process variations.

How to Use Pareto Charts

The first step in a Pareto analysis is to define groups (categories, bins) for the defects you wish to track. Whether you are sampling process measures in a continuous flow, count data, or taking measurements of discrete components, you decide on the categories for grouping defects, and then collect sufficient data to create a sample for analysis.

The next step is to determine counts or frequency of each occurrence. In the example above of the physical characteristics, you have several categories and the total number of defects for each category summing to 100% of the rejected parts. Statit e-QC will automatically create the Pareto chart based on your data. In the Pareto chart, the left vertical axis is labeled with frequency (the count), the right vertical axis is the cumulative percentage. The horizontal axis of the Pareto chart is labeled with the group names. The Pareto chart is a histogram or bar chart ordered in descending frequency magnitude, with a graph line representing the cumulative percentage total of each bar adding up to 100% as it approaches the upper right of the chart. The results clearly display categories having the highest frequencies on the left side of the chart.

An Example Pareto Analysis

A part you are manufacturing may be sampled for physical characteristics and measures. You measure length, width, thickness, density, and other physical specifications. For the sake of illustrating this example, the Pareto chart shows that "length" is the most frequent reason for part rejection. Again, you don't need to have 80% for the Pareto analysis technique to be effective. Possibly, you have 10 different categories or bins for rejects, and length rejects account for 50% total of all rejects. Although not quite the 80/20 rule, most quality experts would agree that further investigation into the "length" defect is suggested by these results, certainly if you are trying to reduce the total number of defects.

An Example Paynter Analysis

The Paynter chart is used to further analyze the results of a Pareto chart. Continuing with this example, let's agree that rejects due to "length" are either grouped as "very shorts", "shorts" or "longs". The Paynter chart will show these sub-groups as separate bars within the "length" bar of the Pareto histogram. In this example, length rejects are shown as: "very shorts" = 5%, "shorts" = 15%, and "longs" = 80%.

At first glance, it appears that you would want to focus on fixing the "longs" problem because they cause 80% of rejects due to length. But, in order to determine where to focus your process improvement efforts, you decide to factor in, or weight, these results by the costs associated with each type of "length" defect. It turns out that "longs" are easily fixed at a cost of 0.5 units of labor and materials. "Shorts" and "very shorts" must be scrapped at an estimated loss of 10.0 units of labor and materials. "Very shorts" have the additional liability that should one of these parts make it to final assembly, it could cause failure of the entire engine, resulting in production stoppage and loss of customer goodwill that cannot be determined through cost accounting techniques. Thus a weighted Pareto and Paynter analysis of this manufactured part reveals that, for the "length" defect, 20% of the defects, result in over 70% of the costs associated with that defect. It would appear that by eliminating the class of "short" defects, substantial cost savings and improved customer satisfaction would result. Eliminating the "long" defect, although it would reduce the total number of defects, would not achieve as great a cost savings or customer benefits as eliminating the "short" defect.

Statit e-QC Gives you the Tools for Pareto and Paynter Charting

As you collect data and process results in Statit e-QC, you can use drill-down techniques in the software to analyze differences due to shifts, days-of-week, production lines and many other production factors. Often, the clues needed to solve manufacturing variances are hidden in the details. The tools that Statit e-QC provides enable you to unlock those mysteries and solve real problems.

You can view a live demo example of Pareto and Paynter charts at The chart below is an example of a Pareto chart from the demo example.

The live demo allows you to click through several scenarios and example with actual manufacturing sample data.

Listen to our Pareto/Paynter Charting Webinar

For more information about Pareto charts, Paynter charts, drill-down techniques and weighting factors, watch and listen to the webinar presented by Guy March, VP of Professional Services, Statit.

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