Data Transformation and Process Capability (Cp/Cpk)
Effective improvement relies on data that can be interpreted correctly and measures that reflect real risk. Data transformation supports valid interpretation when distributions are skewed or non-linear. Process capability (Cp/Cpk) then quantifies whether a stable process can meet specification limits consistently.
Technique Overview
Data Transformation and Process Capability (Cp/Cpk) Definition
Data transformation involves deliberately changing how data is expressed to support reliable analysis when raw data behaves unpredictably. Because transformation alters how results appear, findings must be explained carefully so they remain meaningful for practical decisions (Fink, 2009). Process capability is used to judge whether a stable process can meet specification limits. Measures such as Cp and Cpk indicate whether performance issues stem from excessive variation, poor centring, or both, helping organisations focus improve.
Data Transformation and Process Capability (Cp/Cpk) Description *
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Business Evidence
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Business Application
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Further Reading
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Data Transformation and Process Capability (Cp/Cpk) references (4 of up to 20) *
- Agarwal, S. (2013) Data mining: Data mining concepts and techniques. In: Proceedings of the International Conference on Machine Intelligence and Research Advancement (ICMIRA). IEEE, pp. 203–207. https://doi.org/10.1109/ICMIRA.2013.45
- Fink, E.L. (2009) ‘The FAQs on data transformation’, Communication Monographs, 76(4), pp. 379–397. https://doi.org/10.1080/03637750903310352
- Gupta, V., Jain, R., Meena, M.L. and Dangayach, G.S. (2018) ‘Six-sigma application in a tyre manufacturing company: a case study’, Journal of Industrial Engineering International, 14, pp. 511–520. https://doi.org/10.1007/s40092-017-0234-6
- Kotz, S. and Johnson, N.L. (2017) Process Capability Indices. Boca Raton: Chapman & Hall/CRC.
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