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Rupinder N

Excellence Ambassador
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Rupinder N last won the day on August 18 2017

Rupinder N had the most liked content!

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About Rupinder N

  • Rank
    Advanced Member

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  • Name
    Rupinder Narang
  • Company
  • Designation
    Principal Consultant

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  1. Rupinder N

    Force-Field Analysis

    It is great to see that all responses provided relevant examples. The best answer is that of Vastupal Vashisth as he has included additional explanation and goes beyond just mentioning the driving and restraining forces.
  2. Rupinder N


    The best answer is that of M Kumari Lalita. She has chosen a very simple example and stuck to true meaning of the acronym SCAMPER. The answer includes very simple examples that are interesting and everyone can relate to.
  3. Rupinder N

    Hiring a Lean Six Sigma Black Belt Professional

    It is interesting to see that the Excellence Ambassadors have quickly delved into the crux of this question – what are the competencies that we need this person to excel at in order to be successful in this role, if not just a certificate. It is interesting to see how all participants – for and against – cited these competencies in their own way. Some points brought out, in addition, are – does one need to do DMAIC/DMADV projects to become good at these competencies, how is practical knowledge different than theoretical (what competencies do you get to hone). I would add that the success or the lack of it will also depend upon how resourceful this person is, are they willing to learn as they go along, are they someone who builds on and learns from every project, do they read and research extensively or not. FOR – Krishnamurthy Rao mentions some of the competencies that become more developed if one has completed DMAIC and DMADV projects. This includes not only successful projects, but also learning from the projects that were not successful, which is a great point to make. AGAINST – Togy brings out some interesting points about what is really needed in a BB role rather than just focusing on project completion.
  4. Rupinder N

    Zero Defect - Debate

    FOR – A lot of answers indicate that we need to know “what is the definition of defect”, which is a key to this question’s answer. There are some answers which also quote some example e.g. Karthik Mudliar has mentioned an example of a USB slot, Vastupal mentioned that an ATM machine will not accept a card inserted the wrong way, likewise a sim can be inserted only in a certain way etc. Some other examples could be data services automatically being severed after reaching a certain limit (if the customer does not want to be charged for exceeding the limit), a work flow not allowing a request to be sent for further approvals without department head approvals, and many more. The best response in the “FOR” category is that of Vastupal, as he has brought out the definition aspect and also shared a few examples (though in two different responses), which only makes his passion for his point stand out. AGAINST - Some of the answers also provide examples how companies or processes supposed to operate at high level of performance also have failures. Reminder – the question did not ask if it is possible for every process to be zero defect. The best response in the “AGAINST” category is that of Venugopal. He has asked some very pertinent questions. The debate has also brought out some finer nuances such as the cost for going after zero defect could be high, but can that possibly be offset by the reduced rework and COPQ. Well done, Excellence Ambassadors!
  5. Rupinder N

    CV, Coefficient of variation

    Coefficient of variance can be used to compare the spread of two different populations, with values varying over different ranges. Being a unitless value it finds application in several areas as highlighted in several answers. The biggest drawback is that it cannot be used when the mean of a sample is zero. The three best answers are for Kavitha, Rajesh and Mohan. The chosen best answer is Kavitha's which outlines several examples in addition to the pros and cons.
  6. Rupinder N

    Specification Limits

    The twist to this question definitely made it very interesting. It was great going through all the responses and a lot of creativity shows through in the answers. The best answers are those of Anirudh Kund, Rajesh Chakrabarty, Venugopal R and Mohan PB. It was rather tough to choose the best answer to this question as everyone has brought out one or the other unique way to act in this situation. The best answer amongst these 4 is that of Anirudh as it mentions many of the pertinent questions that can be asked in such a situation. The rest of the answers are worth giving a thorough read, too.
  7. Rupinder N


    ARMI provides information on the roles of the key stakeholders and how they may evolve during the course of a project. Whereas, RACI provides role assignment at the level of each task, hence, providing more information and clarity to execute a job well. The three best answers are that of Sumanta Das, Sandhya Kamath and R Rajesh. Sumanta's answer is the chosen best answer because of the sheer detail and how it has been broken out into palatable pieces.
  8. Rupinder N

    Rolled Throughput Yield

    RTY is the percent good in a process with sub-steps. Hence, when RTY is 100%, it is an indication of "effectiveness" and not "efficiency". This effectively means that even though a process may attain higher values of RTY, it may not necessarily be efficient. Keeping the differentiation between effectiveness and efficiency in mind, the three best answers are those of Mohan PB, Venugopal R and Ronaaq. Mohan's answer is the chosen best answer owing to the apt and crisp verbiage, and the multiple examples provided.
  9. Rupinder N

    Type I Error, Type II Error

    This was a tricky question and the answer is that exact reversal of the same statement is not possible. Hence, one situation's null hypothesis, in the same form, cannot be alternate hypothesis in another situation. Keeping this in consideration, Ronaaq's answer has been chosen as the best answer - owing to the fact that this is the only answer that says so. Close second is Venugopal's answer in which he has indicated so with the help of an example. A big applause to everyone who attempted this question as it undoubtedly was a tough one.
  10. Rupinder N

    Process Maturity

    This is a question that fetched us a lot of similar answers, especially about the definitions of maturity levels. The similarity in answers made it specifically difficult to choose the three best ones. Raghavendra Rao answered all parts of the question asked and also articulated the answer in his own words, though it could have been structured better to further improve the quality of the response. Venugopal R has mentioned how assessing process maturity and not rolling back is the way to go. Not verbose at all, very well structured. Rajesh Chakrabarty has clearly outlined how a process evolves and matures and also shared a tabular summary of maturity levels. This is the chosen best answer to the process maturity question.
  11. Rupinder N

    Continuous data

    This question again challenged us to think beyond what we always stress upon - collecting continuous data wherever possible.Kudos to everyone who made an attempt. Great examples provided by Venugopal, Mohan PB, Kavitha and R Rajesh. The chosen best answer is that of Kavitha's as she provides a direct comparison of examples where we have continuous data but still choose to collect discrete data.
  12. Rupinder N

    Statistical Significance

    It is heartening to see that the complexity of the topic did not deter so many of us from taking a stab at the answer. That shows the true spirit of excellence! There were two parts to this question, and that was the tricky part. Not all attempts answered both parts - the meaning of statistically significant and practical application. Needless to say, articulation in your own words is a key, too. The answer which was complete in all respects was by Mohan PB. Rajesh Gadgil and Venugopal R made a very good attempt too. Cheers to everyone who contributed.
  13. Rupinder N

    VOC, Voice of customer

    We have the winning answer for this question. Thank you all for taking out the time to contribute to the World's Biggest Dictionary, during the festive season. The best answer is given by Venugopal R of Club 46. This answer clearly explains, with the help of examples, where over emphasis on VOC could cause more harm to the business than benefits. There were other answers that were close, but examples and articulation in your own words is always going to get some brownie points. Cheers to excellence!
  14. Rupinder N

    Hypothesis Testing

    Hypothesis Testing is among the most powerful tools used in Business Excellence. It takes away the decisions based on gut feeling or experience or common sense e.g. Site A has better performance than Site B, we should hire more experienced employees as their accuracy is higher, it takes lesser time if we use System A vs System B, older customers are less likely to use self-help as compared to other age groups, are we meeting the cut-off defective %age or not, based on the proportion defectives we see. Hypothesis testing allows to collect valid sample sizes and make decisions for population - it keeps the gut feeling and statements such as "in our experience" out of the picture. You have statistical proof of whatever you "feel" or "think" is right. What must be kept in mind is that it is an OFAT testing technique - only one factor under consideration can be varied while all other Xs must be maintained constant. Hypothesis Testing can be used in any and every phase of the DMAIC cycle. Define - Usually all "1" tests or tests where we compare a population to an external standard are used in this phase e.g. 1 proportion test (if I have x out of y defects, am I meeting the client quality target of 95%?), 1 Sample Z, 1 Sample T, 1 Sample Sign etc. (Has the cost of living gone up as compared to the mean or median cost 10 years ago?). It helps us decide "do we even have a problem". Measure - One can look at data and the eye can catch a "trend". But can we really say that the performance has dipped, is the difference in performance statistically significant. Hypothesis testing can give you the answer. Analyze - this hardly needs any explanation as everyone has using hypothesis testing extensively in this phase to compare two populations or multiple populations e.g. do the five swimming schools create the same proportion of champions out of all enrolled in them, is the lead time for a process on machine A better than machine B, does Raw Material X give better quality than Raw Material Y, does Training Methodology 1 give better results as compared to Methodology 2, 3 and 4, does Vendor A have fewer billing discrepancies than Vendor B etc. Improve - tests involving two populations are generally used. E.g. comparing Y pre and post solution implementation (we implemented a solution to improve the yield of a machine). Is the post-solution yield higher than pre-solution yield, is the TAT post solution better than the TAT before implementing the solution, are more customers buying our product than before etc. Control - We get different CTQ numbers every month post we made an initial improvement. Can we really say that we have improved as compared to before? For 5 months after improve, if we saw a lower number for the metric, was that really different than other months. Can we say that we are consistent? We can use Hypothesis testing again. Business Excellence is nothing but an iterative process to drive excellence throughout the business. As Hypothesis Testing helps us validate or invalidate what we suspect every step of the way in the DMAIC cycle, it is a "must use" tool for the armor.
  15. Rupinder N

    Root Cause Analysis

    Necessary - X is a must for Y to occur. Y cannot occur unless X is present. Sufficient - X is enough to cause Y. However, Z may also cause Y. Scenario 1 - Cause is necessary but not sufficient. X occured at some time for Y to have occured but alongside other factors. In this case, other causes that could have caused Y when combined X have to be found. E.g. there was a case of cars catching fire if hit from behind when the right indicator was on. Having the right indicator on was necessary but not sufficient for a car to catch fire. It had to be combined with the other factor of being hit from behind in order for it to catch fire. Hence, we are looking for critical combinations of other causes with this X. 2. Cause is sufficient but not necessary - means that X on it's own can cause Y. But this is not the only cause leading to Y. It is required in this case to make sure that other causes are also found out, else the problem may remain unresolved even when X is fixed. E.g. not having enough water in a day can cause headaches. But so can not eating on time. Even if you keep having water, but not having food could.still trigger the headaches. 3. Neither sufficient nor necessary - Even if X happens, Y will not occur. In this case this cannot.be deemed as a root cause. Solving for this X will be futile. Other causes ought to be explored in order for the problem to be solved. E.g. an executive assistant not having an app for calling a cab for her boss is neither a reason sufficient to not get a cab, nor is it necessary. A cab can still be called via a phone call, by asking someone else to order, or booked through a website, by hailing from the street. 4. Both sufficient and necessary - must be solved for as whenever X occurs Y will occur. If this is not solved, you have not resolved the problem