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Vivek Madan

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Everything posted by Vivek Madan

  1. Half knowledge is really dangerous . This Question is a great example of people who don't understand Six sigma as a methodology and try to hold on to a single assumption to prove a point. Let me ask a few Questions to clarify my point. Do we face business problems in corporate environment ? Are some of these problems recurring ? Do we need to understand the customer and business viewpoint (VOC/ VOB) to solve/ frame these problems? Is there a need to form project teams and review forums to ensure real issues get leadership attention & support ? Should we focus on data to make inferences on some hypothesis/assumptions ? Is there a need to establish root causes and then solve for them ? Do we need to design solutions to mitigate causes/ risks ? Is it worth the time to sustain proven solutions ? If answer to one or more of the above questions is "Yes" then a structured method which caters to all the above is Six sigma. I agree that it is more than just the above e.g. a metric , a management system and a philosophy but at the core, six sigma is a problem solving methodology which uses voice of customer, data and a structured approach(including change management) to provide sustainable solutions. Moreover, six sigma has evolved over time and complements the latest technological developments like Robotics process automation, Predictive analytics, Blockchain , Internet of things (IOT) and Artificial intelligence keeping it relevant and effective. Infact as the world turns more digital every day, the abundance of data will further strengthen the need for six sigma. I must also mention that there is tendency to malign proven methodologies in the market space to sell new names or to get attention .There are also senior leaders who look for new flavours and get attracted to new names but these are generally “fads” or “old wine in new bottle” that does not meet their expectations and newer names are added to the list. Finally, as a business leader, I love people who bring structure to solving problems and provide sustainable results like six sigma professionals. Three cheers to all of you!!!
  2. First up, let me thank VK for putting up such an interesting & thought provoking Question. I must say that the variation was very high and E was the rightly chosen most number of times (also with other options as well) Arunesh continues to amaze me with his narration and rightly pointed out that Zero defect is a philosophy and way of life. R Rajesh went on to explain all the options and stuck his neck out to include the best and the worst as well. I also liked Karthik's explanation giving the advantages and disadvantages of Zero defect adding another dimension to the definition. So overall a lot of good answers and R Rajesh get my vote due to his choice & effort in providing his answer. Congratulations & all the best team !
  3. It was nice to see that most people understood the importance of rational subgroups and are actively using it in their projects. R Rajesh gave a very good example to identify the right subgroup but the best answer goes to Venugopal for providing detailed definition and scenarios thus winning my vote !
  4. Most people got this right. In summary stability is seen over a period of time and capability is calculated at a point in time. In our quest to create the excellence glossary, I am biased towards someone who gives a concise and well written answer covering all aspects. In this case, I will choose Arunesh's answer as the best highlighting key points & important definitions
  5. Thanks to all participants for making this a rich discussion. Almost all of you spelled out the correct definition of Continuous and Attribute data and provided good examples. Also some of you pinpointed the area of confusion when the metric is a mix of continuous and discrete data e.g. percentages , practical usage of data, large amounts of discrete data being used as continuous , measurement gauge used etc.Kavitha Sundar provided a comprehensive explanation to data types with examples and inference. Congratulations Kavitha and thanks everyone for the your inputs.

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