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Manufacturers in Europe, Japan, and the USA have widely employed the Taguchi methods of robust experimental design in optimizing product designs and manufacturing/assembly processes. However, these methods have made relatively little inroads into the service industries, for rather obscure reasons. Develops a robust experimental design to study the variabilities of a service process, namely, a customer complaint correction process, used by a small export company. The goal of the study is to reduce system response time to failures resulting from human or equipment error, equipment malfunction or damage, or unspecified abnormalities in the hardware or software modules of the system. Successfully identifies factors that affected the system response time in a statistically significant manner and yielded the optimum combination of factor levels that produce best results as measured in terms of system response time. Also demonstrates the usefulness and applicability of Taguchi methods in a service environment ‐ thus chipping away at the myth that Taguchi methods work only in a manufacturing environment.

Despite the clear need to prioritize requirements in software projects, finding a practical method for requirements prioritization has proven difficult. Existing requirements prioritization methods that provide the most consistent results are also the most complex, and therefore the most difficult to implement. More informal methods save time and are easier to apply, but may not be suitable for practical scenarios because they lack the structure and consistency required to properly analyze requirements. This paper proposes a novel and practical approach for prioritizing requirements in software projects. The proposed approach attempts to quantify the quality of requirements to provide a measurement that is representative of all quality criteria identified for a specific software project. The derived quality measurement can be easily computed to serve as the main metric for requirements prioritization.

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