Statistical capability analysis involves superimposing the quantitative requirements of a customer onto the probabilistic outcomes of a business process. The net result is an estimate of the probability that those specific customer requirements can be met or exceeded. Armed with such information, business leaders can structure their respective processes to reduce costs, while more precisely targeting customer requirements. This article provides a case study in the use of statistical capability analysis to predict a service business' capability on performance metrics. The analysis begins by evaluating the prerequisites of statistical capability: statistical control, sufficient statistical power, and the elimination of alternative competing hypotheses. Although the use of statistical capability analysis is well known in manufacturing contexts, this article contends that the analysis is broadly applicable to most business processes, assuming the foundational assumptions of this analysis are known and the methodological requirements are met.
|School:||California State University, Long Beach|
|School Location:||United States -- California|
|Source:||MAI 50/05M, Masters Abstracts International|
|Subjects:||Statistics, Operations research|
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