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Reeve, J. M., and J. W. Philpot. 1988. Applications of statistical process control for financial management. Journal of Cost Management (Fall): 33-41.

Summary by Aarti Nirgudkar
Master of Accountancy Program
University of South Florida, Summer 2002

Continuous Improvement Main Page | SPC Main Page

The purpose of this article is to provide a brief overview of the basic concepts of Continuous Process Improvement (CPI) and statistical management. As the emphasis on quality and productivity is increasing in the U.S., financial managers and internal auditors are realizing the effectiveness of CPI, which highlights the cause of the problem for evaluating, controlling, and improving processes.

What is Continuous Process Improvement (CPI)?

CPI allows managers to continuously improve the quality of all kinds of processes (production, administrative, and service) within a firm. Moreover, it is a customer-driven system, in which both internal and external customers of the firm define and demand their requirements that are then implemented into the system. The new required tools for CPI to effectively operate include “statistical analysis, process analysis techniques (such as IBM’s Department Activity Analysis), and group problem-solving techniques (such as cause and effect diagrams, or more recently, Fukuda’s CEDAC approach) (p. 34).” However, one of the most powerful and widely used tools in implementing CPI is statistical process control.

What is Statistical Process Control (SPC)?

The first step in SPC is to define the process from the point of the view of the financial manager. Then, the characteristics of the process are observed and measured over time. The numbers obtained from these observations are used to monitor the process by calculating the average and examining the natural variation around the average (mean) over time. This method of studying the variation from the mean is known as control charting, as it pinpoints if the process has encountered any special variation that needs special attention. Control charts that depict no special problems indicate that the process is in control and predictable. However, if the control charts show unusual variations (by points outside the acceptable range) it may indicate some problem within the process. Usually the problem is caused by a temporary circumstance and thus, can be resolved by a localized solution rather than changing the general policy. (Exhibit 1 on page 10 of the article provides basic definitions for statistical control charts.)

Statistical management concepts are useful to the manger in the following three areas:

1.Improving financial administrative processes;
2. Monitoring critical success factors and cost drivers; and
3. Post-audit evaluations of capital expenditures.

Improving financial administrative processes:

Top management needs to focus on long-term planning (instead of short-term profit maximization), making fundamental improvements to existing systems, and providing “professional, appropriate, accurate, complete, responsive, and accessible” administrative and service functions (p. 35).

Managers should clearly state and communicate job objectives to their employees, should be more accessible to them, and have a more friendly relationship (that of a coach or a problem-solver instead of a supervisor) with them.

Managers, as well as employees at all levels, should be trained in the use of appropriate statistical, problem-solving, and communication tools.

Implement a systematic procedure to identify the root causes of problems and prevent them from occurring again.

Managers should encourage teamwork, reward the team for their accomplishments, and remove any inter-departmental barriers.

Monitoring critical success factors and cost drivers:

Critical success factors like ROI, on-time deliveries, throughput, customer lead-time, and headcount productivity can all be monitored using statistical techniques (i.e. control charts). Thus, the natural variations in the critical success factors become evident. Moreover, control charts create performance “bands,” which represent the natural variation of a process that is under control. Anything outside the band indicates an out-of-control process and may need further investigation if it is not a one time event.

Cost drivers of various processes can also be monitored with control charts. A few examples of factors that affect cost are cycle times, overtime, schedule attainment, machine availability, setup time, etc. All of these factors can be evaluated using SPC techniques. Like in the case of critical success factors, control charts highlight the natural variations and averages of cost drivers. With the use of control charts, firms can reduce variation and the level of cost driver activity. For instance, firms can reduce non-value-added manufacturing lead-time, improve manufacturing quality, and increase equipment availability.

Moreover, “control charts reveal the process mean and variation of costs and can be used to monitor the efforts managers make to address costs (p. 37).” In general, SPC techniques are a useful tool in evaluating the direct impact of management decisions on production processes.

Post-audit evaluations of capital expenditures:

Traditionally, firms conducted audits of capital assets to determine if the intended benefits were materialized. However, under this approach, any capital expenditure was justifiable. With the use of SPC techniques, firms are now capable of demonstrating in concrete terms if the capital expenditure is meeting expectations and if it is being used as planned. The specific variables documented in the control charts depend on the purpose for which the capital asset was acquired. For instance, if a machine was purchased to improve quality, then quality data is collected, charted, and compared to previous data.


The authors provide three examples to illustrate the CPI and SPC concepts. The first example involves a problem with uneven invoice processing in accounts payable. Using SPC the analyst discovered that managers were holding invoices during the month to avoid budget overruns. This behavior caused a very unbalanced work load for AP. Identifying the cause led management to change the company's budget evaluation policy from emphasis on monthly budget variances to evaluations over longer periods. This change helped create a more even work flow for accounts payable.

The second example involved excessive setup times for a process. The SPC analysis revealed a problem when regular machine operators were absent and inexperienced workers were required to perform the setups. The results lead to a program of job-rotation and cross training to systematically improve setup times.

A third example is related to the post audit of an investment and the effectiveness of attempts to improve machine utilization. Plotting the machine utilization data showed that a special marketing effort improved sales and the related machine utilization in the short run, but in the long run had simply shifted sales from the future to the present. No solution to the problem of low utilization was found.


The primary purpose of SPC techniques is to encourage continuous improvement and to simplify the administrative and production processes. Control charts help managers in eliminating waste by allowing them to evaluate the stability of a particular process, determine the mean and the variability within the process, and monitor the effects to improve the process. CPI is widely used in Japan and is considered the key for a company’s long-term survival and success. With the use of CPI, firms are able to significantly improve organizational effectiveness, product quality, and process efficiency. “The competitive playing field of the next decade will shift from east versus west to CPI adopters versus CPI ignorers (p. 39).”


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).

Hammer, M. 1990. Reengineering work: Don't automate, obliterate. Harvard Business Review (July-August): 104-112. (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.

Martin, J. R. Not dated. What is Six Sigma? Management And Accounting Web.

Martin, J. R. Not dated. What is the red bead experiment? Management And Accounting Web.

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

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).

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).