Using Pareto Charts for Lean Six Sigma Metrics

Prioritizing efforts and identifying defects are critical concepts in implementing a lean Six Sigma conversion. As a result, a system of metrics is needed to compare multiple issues simultaneously. The Pareto Chart can prove to be a particularly useful tool when it comes to prioritization issues.

History of Pareto Charts

This metric was named in honor of economist Vilfredo Pareto who created a formula to represent uneven distribution of wealth. This formula came to be known as the 80-20 rule, which asserts that a small number of factors have widespread effects. Dr. J.M. Juran later applied this concept to defect analysis to show that typically a small number of issues within a production environment lead to a majority of unit defects.

Purpose of the Pareto Chart

The Pareto Chart graphically displays the relationship between data categories. Applied to a lean manufacturing Six Sigma environment, it depicts the comparative frequency of production defects. The manner in which the information is presented simplifies the process of determining which issues and processes are most significant. This information ensures that process change efforts are directed effectively.

Not only can this tool greatly simplify prioritizing work, it also increases the chances of a successful lean Six Sigma program. By enabling an organization to identify and focus upon the most significant issues first, solutions developed as part of the transformation are more likely to have a profound impact upon performance.

Constructing a Pareto Chart

Virtually any spreadsheet software may be used to construct a Pareto chart. The first step is to divide the data into categories. A study of product returns, for example could include these categories:

  • Incorrect item shipped
  • Defective item shipped
  • Shipment arrived late
  • Item did not perform as expected.

The data is then plotted on the chart. The left vertical axis defines the frequency, or number of times a particular issues occurs. The right vertical axis notes the cumulative percentage. The data categories or variables are listed along the horizontal axis.