EDP Meets the Challenge with Cost of Quality


Pinter, Louise Fuller   (1988, ASQC)   American Family Life Assurance Company, Columbus, GA

Annual Quality Congress, Dallas TX    Vol. 42    No. 0
QICID: 3511    May 1988    pp. 743-748
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Article Abstract

Electronic data processing was born in the 1950's. Emphasis during the next decade was on acceptance. This was accomplished by displacing costs in areas such as payroll and accounting. During the 1970's, the computer came of age. It penetrated all areas of the organization, and computer systems were developed to cover all aspects of the business. In the rush to install systems, however, corners were cut and attention was focused on getting the job done -- some way, any way -- not on doing it right.

The time has now come for data processing to respond to the challenge. The main thrust must be on quality -- on systems that deliver the right function, at the right time, every time. The aim can no longer be for systems that provide accurate results most of the time. Today the focus must be on systems that always produce correct results. Quality within the data processing environment must be a primary concern today because the alternative is far too costly. While many organizations are paying a stiff price for poor quality data process products and procedures, few have any idea what that cost is. A reasonable estimate based on studies contained in QUALITY DATA PROCESSING: The Profit Potential for 80's by Claude W. Burrill and Leon W. Ellsworth indicates that the costs associated with poor data-processing quality in a typical organization are about equal to its entire data processing budget. Cost-of-quality measurement combining prevention, appraisal, and failure costs within data processing is the first step in achieving data processing quality. This paper will present a set of working definitions along with methods and procedures tailored to fit the data processing environment which can be used to initiate a cost-of-quality measurement program. The results of these measurements can be used for identifying improvement projects that offer the highest potential paybacks and for evaluating the successes of quality improvement efforts. Thus, establishment of cost of quality can act as a driving force for the implementation of an ongoing quality improvement program within data processing.


Software quality,Cost of quality (COQ)

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