Many companies across the world have introduced Six Sigma mechanism in their organizations to achieve desired results, namely to measure the quality of the product that rolls out from their facilities and always striving to achieve near perfection results. Six Sigma according to many industrialists is a data driven approach and methodologies to keep the defect rate to minimal point. Six Sigma methodologies are not propitiatory to one industrial sector or only multinational firms. This methodologies can be incorporated even in in smaller establishments.
The requirement of today's market is speed, service, quality. In this process huge chunks of data-sets is getting accumulated. The problem here is that the top tier management has the additional challenge, they not only have to define the data-set but also get to the grassroots of the issue. With changes in market trends and requirements, a new approach towards resolving these problems gave emergence to Six Sigma 2.0. You might be wondering how this new mechanism is different with that of the old. Well, the answer is very simple, the new Six Sigma 2.0 inherits same rigorous process from its predecessors, the only difference is that they are far more superior and offers both speed and support which is the demand of today's market.
So what people can watch-out for in the new Six Sigma 2.0 version is listed below.This new mechanism has the same instincts as the previous variant, and also offers speed and support which reduces the burden of hard-working humans. It is particularly suitable for those who are involved in data-intensive processes of Lean Six Sigma projects.
If we look at this new software variant, it is not dependent on hypotheses, which means that it paves a way to monitor and analyze any or entire data from across the entire enterprise and supply chain perspective. And one more thing that we can notice that it is not necessary that the data has to be clean to generate an actionable information. This new breed is base on two concepts namely “non-statistical algorithms,” that does not require any sample or algorithms for validating hypotheses. On the contrast it makes use of large chunks of data and outputs the results from the data alone. Which means that this new mechanism takes the entire available data into account. The second concept is “machine-learning,” that uses algorithms to assess and make predictions about data.
Working with insufficient information or data can be taunting task for the management to identify the problem. And one more backlog of insufficient data is that it takes lot of time to get to core of the problem. This is where this new Six Sigma 2.0 tool comes into picture. This breed is embedded with new techniques does not depend on statistically relevant populations, instead it takes the hold of situation with the available data and identifies what is effecting the processes and provides a solution.
If the above paragraph sounds like a rocket science to you then the gist is that, this new breed identifies “fault regions” that are the root causes of faults. The fault regions provides a set of business rules that offers an economical fix to the issue.
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