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  • June 11, 2008
  • By Marcia Gulesian
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Appendix 4: Time Related Data

Although the normal distribution is best known, time related data frequently takes the form of a Weibull distribution.



Click here for a larger image.

Figure 10: A Weibull distribution with parameters suitable for describing time-related data

Here's an example of a process where the data is time related: In a given organization, the IT department and the rest of the business might agree to set the times to fix laptops in their service level agreement (SLA). The IT department will want to measure whether the target times are met, to report to the business about its performance.

  • Process definition: Under the SLA, customers will be helped in less than one hour with all laptop problems they experience.
  • Measurements: 30 laptop problems will be independently timed from the moment a customer reports the problem to the moment a customer agrees on the fixing of that problem.
  • Upper specification limit (USL): 60 minutes
  • Lower specification limit (LSL): 0 minutes (a boundary)

Does the process have to be Six Sigma? The answer is usually no, it does not. It depends entirely on the service level agreement.

References

  • Hambleton, L. Treasure Chest of Six Sigma Growth Methods, Prentice Hall (2007)
  • Brussee, W. Statistics for Six Sigma Made Easy, McGraw-Hill (2004)
  • Creveling, C. M. et al Design for Six Sigma, Prentice Hall (2002)
  • Harmon, P. Business Process Change, Morgan Kaufman (2007)
  • Kumar, D. Six Sigma Best Practices, J. Ross (2006)
  • Boer, S. et al Six Sigma for IT Management, ITSMF-NL (2006)
  • Summers, D. Six Sigma: Basic Tools and Techniques, Prentice Hall (2006)
  • Pyzdek, T. The Six Sigma Handbook, McGraw Hill (2003)
  • Breyfogle, F. Implementing Six Sigma, Second Edition, Wiley (2003)
  • Jelen, B. Special Edition Using Microsoft Office Excel, Que (2006)
  • Gulesian, M. Service Level Agreements

About the Author

Marcia Gulesian is an IT strategist, hands-on practitioner, and advocate for business-driven architectures. She has served as software developer, project manager, CTO, and CIO. Marcia is author of well more than 100 feature articles on IT, its economics, and its management.





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