The Six Sigma method takes its name from a statistical term used to measure variation in a process. In statistics, “sigma” (s) represents the standard deviation of a data set, which is a measure of the dispersion or variability of values from the mean.

Meaning of “Six Sigma”

Six Sigma literally means “six standard deviations.” As part of process quality, this results in performance where 99.99966% of products or services are free of defects. In other words, this corresponds to a maximum of 3.4 faults per million opportunities (DPMO). This very ambitious goal aims to almost entirely reduce errors and variations in industrial and commercial processes.

Origin of the Method

The Six Sigma method was developed by Motorola in the 1980s. It was introduced by engineer Bill Smith in 1986, with the support of then-Motorola CEO Bob Galvin. The aim was to address quality and process variability issues that affected customer satisfaction and production costs.

Motorola found that traditional quality management methods were not sufficient to achieve the desired levels of performance. By combining rigorous statistical techniques with a structured methodological approach, the Motorola team was able to develop an effective strategy to identify, measure, analyze, improve, and control processes. This strategy was called “Six Sigma” in reference to the statistical performance objective it aimed at.

Adoption and Evolution

The success of Six Sigma at Motorola quickly caught the attention of other major companies. General Electric, under the leadership of Jack Welch, was one of the first to adopt and popularize the method in the 1990s. Since then, Six Sigma has been widely adopted in a variety of industries, ranging from manufacturing to healthcare, financial services, and information technology.

Conclusion

The Six Sigma method is so called because of its objective to reduce variations in processes to a very low level, corresponding to six standard deviations from the mean. Developed by Motorola in the 1980s, it revolutionized quality management by introducing a systematic and statistical approach for continuous process improvement.

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