Cause-and-Effect Diagram

The Cause-and-Effect diagram provides an efficient summary of factors that impact a process, and hence can be used as a map to guide the overall quality improvement efforts. Therefore, it is one of the important tools for the Define phase of Six Sigma quality control efforts. The diagram is also sometimes referred to as a "fishbone chart," because of its appearance, or an Ishikawa chart. The latter name refers to the work of Professor Kaoru Ishikawa of Tokyo University who developed this diagram to depict variables which are present in a process. The general idea of the chart is rather straightforward. Suppose you want to turn on a reading light in your house one evening, and it won't light up. Now consider the various variables or characteristics that make up the process (cause the light to come on), and which should be considered in order to fix this quality problem:

The cause-and-effect diagram shown above (adapted from Rath & Strong's Six Sigma pocket guide, 2000) spells out the various potential causes of the problem encountered. Usually, the chart is constructed by identifying (1) the major categories of causes that affect the process (in this example Power, Bulb, Plug/Cord and Lamp), and (2) the individual factors or causes that can be classified into these major categories (e.g., Power outage, No house current, etc.). You could now use this map as a guide to troubleshooting the problem you encountered turning on your reading light. You can also further "augment" this chart (using the Custom drawing and other tools of STATISTICA graphics) by adding various sub-sub causes, causes that you ruled out, solutions you have tried, etc.

The cause-and-effect diagram plays a central role in Six Sigma quality programs. During the first stage of the Define-Measure-Analyze-Improve-Control (DMAIC) cycle, this diagram can be of great utility in order to identify the areas, departments, processes, and stakeholders that should be involved in the effort. See Harry and Schroeder (2000), Pyzdek (2001), or Rath and Strong (2000) for additional details; see also the Six Sigma topic.

For details, see also Cause-and-Effect Diagrams in the Introductory Overview of Process Analysis.