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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 by Nicole Sackedis
Master of Accountancy Program
University of South Florida, Fall 2000

Control/Controllership Main Page | SPC Main Page

Problems related to the Traditional Approach to Cost Control

1. Traditional engineering cost control techniques fail to provide timely information. The ability of operating managers to control processes is limited severely by reporting frequency. Losses are a signal for corrective action. However, losses occur before correction is implemented. This is an example of retrospective management.

2. The traditional cost control approach also fails to promote improvement. Traditional control techniques influence the organization toward a lesser objective, i.e., just meeting standards. It is harmful if waste is built into the standard. Engineering departments don’t have a system designed to update standards on a frequent basis. This results in accounting systems lagging engineering reality.

3. Traditional end measurements do not point to corrective action. The information that comes from the standard cost system only serves as a control function, not a corrective tool.

4. The traditional approach is production oriented only. Assumptions made using engineered costs cause some problems.

5. The performance of the system is multidimensional. Achieving the most for the least, can lead to dangerous conflicts on dimensions of quality, deliverability and service. The assumption that summed sub-factor efficiencies will lead to global efficiency is questionable.

6. In addition, data aggregation is a serious shortcoming since aggregation of time order data is accumulated into variances of performance overtime. Data behavior overtime is needed to provide important evidence about causes of process behavior.

7. The traditional top down control approach worked well in repetitive and process focused manufacturing. However, work is now being organized in cross-functional teams, resulting in the definition of responsibility centers expanding. A top down approach does not provide for employee improvement. The consequences of the top down approach include:

Fear and improper tracing of responsibility.

Performance Levels are measured against standard levels ignoring issues of variation.

Statistical Process Control

The original use of SPC was to improve the output of manufacturing systems. SPC control charts preserve the time order of data and provide the audit trail for improvements. This is important to accountants for two reasons:

1. Processes that are not in control are not predictable, and

2. The performance appraisal system should be able to recognize the distinction between processes that are in control and those that are out of control.

There are two types of variation - process variation and product variation.

Summary

The table below summarizes the differences between traditional engineering control and statistical process control.

Traditional Engineering Control versus to Statistical Process Control
Traditional Engineering Control Statistical Process Control
Not timely Real time data
Fails to promote process improvement Promotes continuous process improvements
Focuses on ends measures of performance Focuses on causal factors of performance
Myopic - production oriented only Multi-factor oriented, productivity, quality, time
High level of data aggregation Time order of data preserved
Top-down narrow control Horizontal and process control
Performance levels, ignores issues of variation Performance bands and variation highlighted

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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. 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. https://maaw.info/Chapter3PartII.htm

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

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

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

Reeve, J. M., and J. W. Philpot. 1988. Applications of statistical process control for financial management. Journal of Cost Management (Fall): 33-40. (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).

Roth, H. P. and T. L. Albright. 1994. What are the costs of variability? Management Accounting (June): 51- 55. (Summary).

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