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SPC as a tool for creating a successful business measurement framework

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  • S. Y. Coleman
  • G. Arunakumar
  • F. Foldvary
  • R. Feltham

Abstract

Many companies are trying to get to the bottom of what their main objectives are and what their business should be doing. The new Six Sigma approach concentrates on clarifying business strategy and making sure that everything relates to company objectives. It is vital to clarify each part of the business in such a way that everyone can understand the causes of variation that can lead to improvements in processes and performance. This paper describes a situation where the full implementation of SPC methodology has made possible a visual and widely appreciated summary of the performance of one important aspect of the business. The major part of the work was identifying the core objectives and deciding how to encapsulate each of them in one or more suitable measurements. The next step was to review the practicalities of obtaining the measurements and their reliability and representativeness. Finally, the measurements were presented in chart form and the more traditional steps of SPC analysis were commenced. Data from fast changing business environments are prone to many different problems, such as the short previous span of typical data, strange distributions and other uncertainties. Issues surrounding these and the eventual extraction of a meaningful set of information will be discussed in the paper. The measurement framework has proved very useful and, from an initial circulation of a handful of people, it now forms an important part of an information process that provides responsible managers with valuable control information. The measurement framework is kept fresh and vital by constant review and modifications. Improved electronic data collection and dissemination of the report has proved very important.

Suggested Citation

  • S. Y. Coleman & G. Arunakumar & F. Foldvary & R. Feltham, 2001. "SPC as a tool for creating a successful business measurement framework," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(3-4), pages 325-334.
  • Handle: RePEc:taf:japsta:v:28:y:2001:i:3-4:p:325-334
    DOI: 10.1080/02664760120034063
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