With all the information or at least most of the information available on the Web on why and how to apply Six Sigma, this article may dampen your enthusiasm a bit when it comes to application of Six Sigma. My approach to life always has been â€“ If you want to tell someone why or how not to do something, tell them why or how not to do that thing. In this article, I am going to bust certain myths on Six Sigma that a lot of people; neutral outsiders and avid proponents, have forwarded about this discipline.

Six Sigma means perfection
Okay. This is the first myth that actually propels a lot of business owners to embrace Six Sigma as an approach. They feel that Six Sigma will make them perfect. Not really! Six Sigma only makes a company perfect in meeting customer expectations. The problem is customer expectations can vary over a period of time. In such a scenario, the operating model of the company should be flexible to capture the change.

Six Sigma means eliminating variation
Oh no â€“ Not again. Dr William Edwards Deming once said, â€śA process that doesnâ€™t have variation is not a process.â€ť Using Six Sigma as an approach you can only reduce variation and not eliminate it. The key to reducing variation is reducing it to an extent where the process remains in statistical control at all times. When a process is in statistical control, it produces predictable output. When statistical control comes with reduced variability, the goal of Six Sigma approach is as close to being met.

Six Sigma approaches deal primarily with normally distributed data
The saying is, â€śIf you wish to go from Place A to Place B, you can go by five different routes. Why are you so obstinate of choosing Route A always then?â€ť A lot of people have a serious inclination, some kind of an affinity in choosing to work with normally distributed data. Nothing wrong with that because it is just so easy to deal with such data! That said praying and sometimes forcing your data to look normal when it is not is asking a horse to run hundred miles without a guide! For the records --- There are forty different data distributions. Your process data could fall in any of these distributions and not necessarily normal. Did someone shout Weibull?

Six Sigma, is all about DMAIC
I tell you if grapevine is to be believed, DMAIC popularly known as Define Measure Analyse Improve and Control should be awarded the Cure-It-All award. DMAIC has been a pet approach for a lot of practitioners when they wish to improve the performance of processes. But just to say that DMAIC is the only centrifugal point of Six Sigma is telling something that is a bit far-fetched from the truth. For the records, you can use DMAIC only to improve existing processes. Where you donâ€™t have a process or where you wish to re-design a process or re-engineer a process, you should be in a position to use DFSS or Design for Six Sigma.

Six Sigma is a collection of tools that does Magic
Oh yes, this one has to be spoken about in detail. Any practitioner believes that Six Sigma approach just needs to be started and the rest will follow its course. Six Sigma tools are aplenty and you should just use the tools and the results will be delivered. The key here is to know that application of tools just does 20% of the work. The tools would throw numbers at you. If you are not able to make sense out of the numbers and use them for your business results, chances of you getting lost in the maze is high. You are talking of a high probability for sure. And we also have the unsaid power of Brainstorming, a tool that is not dipped into the statistical scheme of things anywhere?

Six Sigma, is all about measuring the data
True Six Sigma places a lot of emphasis on measuring data and the right kind of data, but the importance of other phases like Define, Analyse, Improve, Control shouldnâ€™t be lost out on practitioners. For example, the Define Phase of a Six Sigma project is one that assumes utmost importance in the scheme of things. If you do not define a problem well, the chances of you going astray in days to come are relatively high. By giving you an insight into these myths, the message I wish to convey is â€“ Six Sigma is not an approach which you would have thought of giving into the considerations discussed in this article. Agreed it is a statistical approach and agreed it talks a lot about measuring data and validating data but plenty needs to be done on ground to improve a process.

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