Management And Accounting Web

Nolan, T. W. and L.P. Provost. 1990. Understanding Variation. Quality Progress (May): 70-78.

Summary by Jennifer Ryan
Master of Accountancy Program
University of South Florida, Fall 2000

Deming Main Page | SPC Main Page

The Basics of Variation

There is variation in all aspects of our lives.

Typical losses resulting from misinterpretation of variation include:

Blaming people for problems beyond their control.

Spending money for new equipment that is unneeded.

Wasting time looking for explanations of a perceived trend when nothing has changed.

Taking other actions when it would have been better to do nothing.

Definitions

Process – set of causes and conditions that repeatedly come together to transform inputs into outcomes.

System – an interdependent group of items, people, or processes with a common purpose.

Note: As used below, the term "process" is taken to mean "process and/or system".

Indicators of performance, or quality characteristics, of any process can be identified and measured. Some examples are number of accidents, number of billing errors, and time of delivery. All vary over time. Often variances are used for action on the process, which is sometimes not appropriate.

Classifying Variation

The traditional view of variation is that it is either good or bad. This method is used for inspection of products and services and for grading in schools. One shortfall of classifying variation as good or bad is that there is no information on the causes of the variation.

Walter Shewhart developed the concept of variation based on the idea that a quality characteristic has two types of causes:

Common causes – causes that are always part of the process and affect everyone working in the process.

Special causes – causes that are not part of the process normally, or do not affect everyone, but are attributable to specific circumstances.

To determine whether the cause of variation is common, Shewhart created the control chart, which consists of three lines and points plotted on a graph. The points reflect measurements of a quality characteristic at regular intervals. Two of the lines represent the upper and lower control limits, which are above and below, respectively, the center line or average.

Concepts were developed for manufacturing, but can be used for processes of management, administration, and service.

Stable Processes

A process with only common causes affecting the outcome is stable, or in a state of statistical control. Stable means only that the variation is predictable within statistically established limits, not that there is no variation.

An unstable process is one where the variations can be attributed to both common and special causes.

W. Edwards Deming describes the benefits of a stable process as:

A process has an identity and its performance is predictable; therefore there is a rational basis for planning.

Costs and quality are predictable.

Productivity is at a maximum and costs are at a minimum for the process.

The effect of changes in the process can be measured faster and more reliably.

If a stable process is adjusted, perhaps due to misunderstanding of the variances, variation will increase rather than decrease. (See the funnel experiment in Deming's Chapter 9 for more on the effects of tampering).

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Related summaries:

Albright, T. L. and H. Roth. 1993. Controlling quality on a multidimensional level. Journal of Cost Management (Spring): 29-37. (Summary).

Deming, W. E. 1993. The New Economics For Industry, Government & Education. Cambridge: Massachusetts Institute of Technology Center for Advanced Engineering Study. (Summary).

Francis, A. E. and J. M. Gerwels. 1989. Building a better budget. Quality Progress (October): 70-75. (Summary).

Holmes, D. S. and R. E. Hurley. 2003. How SPC enhances budgeting and standard costing - Another look. Management Accounting Quarterly (Fall): 57-62. (Summary).

Martin, J. R. Not dated. Chapter 3: Cost Behavior Analysis & Statistical Process Control - Part II. Management Accounting: Concepts, Techniques & Controversial Issues. Management And Accounting Web. http://maaw.info/Chapter3PartII.htm

Martin, J. R. Not dated. Deming's Theory of Profound Knowledge. Management And Accounting Web. http://maaw.info/DemingExhibit.htm

Martin, J. R. Not dated. Illustration of common cause vs. special cause variation. Management And Accounting Web. http://maaw.info/DogInYard.htm

Martin, J. R. Not dated. What is Six Sigma? Management And Accounting Web. http://maaw.info/SixSigmaSummary.htm

Martin, J. R. Not dated. What is the red bead experiment? Management And Accounting Web. http://maaw.info/DemingsRedbeads.htm

Reeve, J. M. 1989. The impact of variation on operating system performance. Proceedings of the Third Annual Management Accounting Symposium. Sarasota: American Accounting Association: 75-89. (Summary).

Roehm, H. A., L. Weinstein, and J. F. Castellano. 2000. Management control systems: How SPC enhances budgeting and standard costing. Management Accounting Quarterly (Fall): 34-40. (Summary).

Taguchi, G. and D. Clausing. 1990. Robust quality. Harvard Business Review (January-February): 67-75. (Summary).

Walter, R., M. Higgins and H. Roth. 1990. Applications of control charts. The CPA Journal (April): 90-93, 95. (Summary).