Mayank Gupta

Shashikant's answer has been selected as the best answer for highlighting the responsibilities of employees and what their actions should be during a crisis situation

Hello Varad Could you elaborate more on the following 1. What is the nature of the interactions? 2. How are you calculating the DPMO - is it for each interaction? of for a sample of interactions? You may like to use our DPMO calculator for ease of usage. Link as below https://www.benchmarksixsigma.com/calculators/sigma-level-calculator-discrete-data-defects/

Hello Ransingh Both Type I (alpha) and Type II (Beta) errors may be critical. However, mostly we are interested in knowing whether the process has changed or not. Hence we look at the p-value and then compare it with alpha. Reason is because alpha error is the threshold for deciding whether the sample data is coming from the same population or from a different population. If the p-value (calculated) is more than alpha, we go conservative and conclude that the sample data is coming from the same population, whereas whenever p-value is less than alpha, we conclude that there is reasonable confidence that the sample is from a different population. Type II (Beta) error plays a significant role in deciding the sample size for hypothesis testing. And therefore, we first decide the minimum sample size and then carry out the hypothesis testing. The above is the traditional knowledge, however there are instances where we are interested in process not changing at all. In such cases, the Null and Alternate hypothesis are interchanged (a word of caution - not the usual practice except for in some industries). With the Null and Alternate hypothesis changed, alpha effectively becomes beta error and vice versa. E.g. Checking for bio-equivalence in pharma industry. Refer the below links for more clarity 1. https://www.benchmarksixsigma.com/forum/topic/34918-type-i-error-type-ii-error/ 2. https://www.benchmarksixsigma.com/forum/topic/35850-test-of-equivalence/

Hello Ruchika Please refer the below link to get some insights on how Lean Six Sigma can be applied to a Real Estate Company. This will also help you understand the key metrics for them https://www.benchmarksixsigma.com/forum/topic/546-six-sigma-in-real-estate/

All correct answers have been published. Best answer has been provided by Dr. Shashikant Adlakha for first explaining the concept of OEE, detailing the 6 big losses and finally highlighting the ways to avoid these losses. Please go through the answer by Benchmark Expert- Mr. Venugopal as well.

Hello Palaniappan Measurement system can be classified into the following depending on how the data is being collected 1. Automated system for collecting data 2. Operator using a gauge to collect data (Continuous data) 3. Only Operator collecting data (Discrete data) Hope this helps.

All answers are correct. Mohamed Asif's answer has been selected as the best as he provided inputs on specific tools that are used for Fraud Prevention and Detection

Hello Marcel You may like to go through the below link to get some clarity on Discrete vs Continuous Data https://www.benchmarksixsigma.com/forum/topic/34894-continuous-data-attribute-data/#comment-44200 Hope this helps.

Great answers to highlight the concept of Nash Equilibrium. Best answer was provided by Nilesh Gham for giving varied examples where this concept can be applied. Please have a look at Expert View (Venugopal's response) as well.

Dear Manoj Times of India might have removed the page. You may read more about the incident at the below link https://www.rediff.com/sports/report/f1-red-bull-change-pitstop-procedures-formula-one/20130714.htm

Kudos to all respondents for providing the correct answer. Best answer has been provided by Shashikant Adlakha for explaining the phenomenon and how it can be used for business benefits. Congratulations Shashikant!! Nilesh's answer is also a must read to understand how this phenomenon can be used to artificially inflate the performance numbers. Also review the answer provided by Mr Venugopal R, Benchmark Six Sigma's in-house expert.