Six Sigma Statistics

Six Sigma statistics is a compilation of the time-tested management strategies, which has always proved to be beneficial for the overall improvements of the companies. There are certain tools which are widely used to reduce the number of defects from a system.

Six Sigma is a data-driven methodical approach applied to the running processes in a company for improvement in the performance and the overall quality of services and goods. It is a tactic adopted towards perfection, or almost perfection that helps in the company’s competence in the market. Many companies like Motorola, Allied Signal, Xerox, and General Electric have used it and have experienced drastic improvements in the level of customer satisfaction and market value of the shares. This is obviously a good thing since it places the company in a good position to avail of further opportunities. No doubt, Six Sigma statistics is the best set of management tools that is available in the market at the moment.

  • Definition of Six Sigma Statistics: The statistical approach of Six Sigma can be defined as a quality objective that is to be achieved by successfully implementing a Six Sigma project. It judges in a quantitative manner, if the products manufactured by a company are meeting the customer’s demands or not. The model that is followed universally in the Six Sigma statistics is the DMAIC model. It stands for Define, Measure, Analyze, Improve and Control. In short, define the problem, measure the scopes and probable effects of the project, analyze various aspects of the problem, improve the system in a systematic manner and control the standard of the process. This is how the Six Sigma works. But for the model to work properly, a number of statistical tools and methodologies are used. These include all the tactics that are generally used in other quality management projects. But they are incorporated in the DMAIC model which accounts for its effectiveness.
  • Significance of the Statistical Methods: The statistical methods used in the Six Sigma process are not like the tailor-made stilted programs of any statistical training institute. They are specific to a company and its problems. The Six Sigma statistics help maintaining the goals and objectives of the company. Some manufacturing organizations may include lean thinking to the program while this is not normal in regular training institutes. Six sSigma statistics basically reinforce the use of observational and experimental attitude in the problem situations. Two levels of factorial experimentation are followed along with extensive use of graphical methods and technologies keeping an eye on the experiments done. They check the scopes of an experiment done, facilitating the understanding of the statisticians.
  • Benefits of the Six Sigma Statistics: Not going to the mathematical details of it, to precisely put it across, Six Sigma statistics mean Six standard deviations from the arithmetic mean, taking a lower specification limit and an upper specification limit. Standard deviation is the quantification of the variation existing from the mean, depending on the placing of the data points. If it takes up a lot of space, then variation is large, if it takes up little space, then the variation is negligible. Now, if a large portion of the variation extends out of the specification limit, then it makes a low Sigma score. But when it extends a little from the mean and doesn’t extend much out of the specification limit, it makes a high Sigma score. When we are talking of Six Sigma statistics, we are actually talking of this score. The standard variation is around 3.4 defects per million opportunities.  It statistically ensures that out of 100, 99.997 products would meet the target quality.

Hence, Six Sigma statistics is by far the most effective management strategy that evolved from the time tested rules and techniques.

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