A study of the costs of quality in a renewable resource environment



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Texas Tech University


This study provides an in depth literature review of the cost of quality (COQ) research, a COQ compendium, a comparison between the COQ for a manufacturing meta-analysis and 3 water utilities and a sensitivity analysis of the water utilities. These water utilities are El Paso, Lubbock, and San Antonio.

The Manufacturing Meta-Analysis consisted of 38 useable studies which included a variety of industries and manufacturing processes. These were used to develop the comparison populations for the prevention, appraisal, failure, and total COQ variables against the water utilities. The water utilities were chosen because they represent three different populations, three difference water source combinations and three different county water usages. The three utilities together also represent 10% of the large water systems and approximately 11% of the population in Texas.

Monthly financial data was collected from each water utility. Lubbock provided 33 observations, El Paso 45, and San Antonio 12 after the removal of outliers. This data was then categorized into the Prevention, Appraisal, and Failure (PAF) costs based on annual reports, budgets, utility input and the PAF Cost Compendium.

The primary hypotheses of this research were to compare the COQ PAF and Total COQ ratios of the manufacturing meta-analysis with the water utilities to identify, determine the Juran Point for the water utilities and show that it is representative of a mature market, test the materiality of the Opportunity Costs, and determine the significance of the Environmental Opportunity Costs.

The results of these hypotheses show that Prevention, Failure, and Total COQ are not the same for water utilities versus manufacturing companies. The Total COQ % for the water utilities was twice as large as the manufacturing companies. Interestingly, Appraisal costs were statistically the same between the water utilities and manufacturing utilities. Also, opportunity costs may or may not be material depending on the utility, but they were about $1M and $1-$2M for El Paso and San Antonio respectively. Hypotheses 2 and 4 were not able to be calculated from the information made available during the study.

The sensitivity analysis also showed differences between the utilities. Population may have an impact on the % of Prevention costs. Appraisal costs were still equal across the water utilities. It also showed that wages were the single largest costs factor and that rainfall amounts have no effect on the costs of quality.

The conclusions of this research are that differences do exist between water utility and manufacturing company COQ. Further research is needed to completely understand the causes of the differences. What is the reason that even with higher a high % prevention the water utilities have two times the % Total COQ? Are those differences due to risk aversion, public health, regulatory reasons, etc.? More research needs to be conducted to identify the Juran Point and Environmental Costs. The applications for this research is vast and includes over 3900 water utilities serving populations > 10,000, waste water utilities, energy utilities, and storm water utilities to name a few. This research is another tool that utilities could use to better allocate monetary resources to solve gaps in their funding.