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  1. Yesterday
  2. Ramdas has provided the best answer to this question. Well done. Answer from Sachin is also a must read.
  3. Q 686. What is Reverse Logistics? How can Lean Six Sigma help an organization achieve improved customer satisfaction by applying it in reverse logistics? Provide examples to support your answer. Note for website visitors - This platform hosts two weekly questions, one on Tuesday and the other on Friday. All previous questions can be found here: https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/. To participate in the current question, please visit the forum homepage at https://www.benchmarksixsigma.com/forum/. The question will be open until Tuesday or Friday at 5 PM Indian Standard Time, depending on the launch day. Responses will not be visible until they are reviewed, and only non-plagiarised answers with less than 5-10% plagiarism will be approved. If you are unsure about plagiarism, please check your answer using a plagiarism checker tool such as https://smallseotools.com/plagiarism-checker/ before submitting. All correct answers shall be published, and the top-rated answer will be displayed first. The author will receive an honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term. Some people seem to be using AI platforms to find forum answers. This is a risky approach as AI responses are error prone as our questions are application-oriented (they are never straightforward). Have a look at this funny example - https://www.benchmarksixsigma.com/forum/topic/39458-using-ai-to-respond-to-forum-questions/ We also use an AI content detector at https://crossplag.com/ai-content-detector/. Only answers with less than 15-20% AI-generated content will be approved.
  4. Last week
  5. Leavy Jennings chart are a very good way of visually representing QC data providing indication of the performance of an assay. This graphic tool is used in monitoring controls and ensuring that they within desired limits. The L-J Chart allow us to plot the data and records of periodic measurement of quality control samples and then it analyze whether data points are within acceptable range. Chart also highlights outliers with mean and standard deviation between 1 to 3 within (+-3SD) so it will have 1. Time value on X Axis 2. Measured value from quality control samples on Y Axis 3. Horizontal line indicating the mean ( Average) 4. Standard Deviation line indicating acceptability of range. Leavy Jennings charts are simpler to detect trend, shifts or outliers but can only work for individual test performance and can not be account for interaction between different test and process. IMR chart are more powerful when it used for general purpose to understand complexity where individual measurement and their range is critical for overall process control. Unlike L-J chart IMR chart can not be tailor made for Laboratory experiments. It is also required statical knowledge and training to understand and interpret moving range and control limits. L- J Charts are used in healthcare industry or laboratory experiment to ensure that test methods are accurate and stable , Where as IMR Chart are used for Industrial or manufacturing set up. For Diabetes testing L-J Chart can be helpful to monitor blood glucose testing. for that we can 1. Established Control limits i.e. Mean glucose concentration of the QC sample = 100 mg/dL and standard deviation ( SD) is 5mg/dL. 2. We can set up L-J Chart with Time on X Axis and Y Axis as glucose concentration levels and mean value line 100mg/DL and SD lines between 1 to 3 SD. Suppose we take 10 days data and glucose concentration level values are 98, 101, 100, 99, 95, 97, 103,102, 104, 96 mg/ dL. Most of the value are within +- 2 SD that mean testing process is in control. Benefits of using L-J Chart Early detection of issue will help correction which is vital for effective management of diabetes.
  6. A Levey-Jennings Chart, or LJ chart for short, is like a quality control cop for lab tests. Imagine you run the same test repeatedly on a known sample, kind of like a practice run. The LJ chart tracks these practice runs over time, plotting the results on a graph. Here's the cool part: it also calculates statistically based limits (think upper and lower boundaries) for what's considered "normal" variation. Now, compared to a regular ol' Individual-Moving Range (IMR) chart, the LJ chart has some key advantages: Big picture view: LJ charts focus on averages, giving you a broader perspective on how the test is performing overall. IMR charts tend to be more nitty-gritty, looking at individual data points and their variation. Catches trends: LJ charts are better at spotting subtle trends in the data, like a test slowly drifting out of whack. IMR charts might miss these gradual changes. However, LJ charts aren't perfect. Here's where they might fall short: Needs historical data: To set those control limits, you need a decent amount of past data on the test performance. IMR charts can be used with less historical data. Assumes normality: LJ charts work best when the data follows a normal distribution (think bell-shaped curve). IMR charts can be less sensitive to data that's a bit wonky. So, where do LJ charts shine? They're superstars in: Labs: Monitoring the accuracy and precision of medical tests, ensuring patients get reliable results. Manufacturing: Keeping an eye on production processes, catching any quality issues early on. Research: Tracking the consistency of experiments and measurements. Overall, LJ charts are a powerful tool for keeping an eye on the quality of your processes, especially when you have a good understanding of your historical data. They might not be the answer for every situation, but they're a great option for catching potential problems before they snowball.
  7. Q 685. What is a Levey-Jennings Chart? Highlight advantages and disadvantages of LJ chart over a regular IMR Chart. Provide some use cases where LJ charts are used. Note for website visitors - This platform hosts two weekly questions, one on Tuesday and the other on Friday. All previous questions can be found here: https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/. To participate in the current question, please visit the forum homepage at https://www.benchmarksixsigma.com/forum/. The question will be open until Tuesday or Friday at 5 PM Indian Standard Time, depending on the launch day. Responses will not be visible until they are reviewed, and only non-plagiarised answers with less than 5-10% plagiarism will be approved. If you are unsure about plagiarism, please check your answer using a plagiarism checker tool such as https://smallseotools.com/plagiarism-checker/ before submitting. All correct answers shall be published, and the top-rated answer will be displayed first. The author will receive an honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term. Some people seem to be using AI platforms to find forum answers. This is a risky approach as AI responses are error prone as our questions are application-oriented (they are never straightforward). Have a look at this funny example - https://www.benchmarksixsigma.com/forum/topic/39458-using-ai-to-respond-to-forum-questions/ We also use an AI content detector at https://crossplag.com/ai-content-detector/. Only answers with less than 15-20% AI-generated content will be approved.
  8. Ramdas has provided the best answer to the question. He has explained the concept with a very good example. Well done!
  9. Supriya Rao Dasari

    Apr - Jun 2024

    This album contains Benchmark Six Sigma Training photographs from April to June 2024.
  10. Payback period highlights in years, the time taken for the investment to payback itself, ie to breakeven. Beyond Payback period, businesses can start accruing profits, and it is important to know how soon this time can start. As the name indicates, Payback period = Initial Investment/ Annual Cash flow. As a means of comparison, higher the payback period, less lucrative the investment. The biggest advantage of this metric is the ease of its calculation, and hence it comes in very handy to compare various options, in our case, project selection. On the other hand, the biggest disadvantage of this method is that it ignores time value of money. Simply put 100 units of currency are worth more today than in future. This can be easily accounted in NPV thereby making it a better metric to use.
  11. Earlier
  12. Payback period is one of the simplest method to measure project profitability and risk. Payback period simple meaning is time taken to recoup the initial investment. It is useful when company has limited resources and need to know how quickly they will recover their investment. Calculation of payback period = Initial investment / Annual cash flow. Since payback period is very simple compare to other investment investment or project appraisal techniques. a. for example IRR ( Internal rate of returns) help to analyze and compare the incremental profit in terms of rate of returns Vs. Risk to be taken for example. if we invest same amount of money in to Financial market ( Equity/ Debt) we may get average 10% IRR Vs. Project should reflect 5-7% incremental returns for efforts, time and risk taken on the project to justify the project selection. b, Net Present Value indicates difference between present value of cash inflow and cash outflow. Here NPV of any project negative then you should not accept the project is thumb rule. While projection selection all three method or financial metrics can be use but payback period suits to organization with limited resources and high intensity cashflow/ liquidity requirement. Lets understand advantages and disadvantages of using Payback period while project selection. Ram wanted to open Small Cafe. He needs 1000000 ( 10 Lakhs) as initial investment. He tells his friends and relatives invest in this business as it will give him 100000 ( 1 Lakhs) profit every month. Payback period = 10 Lakhs/ 1 Lakhs = 10 Months. Now the funny part 1st Month Ram Open Cafe earns 1 Lakhs 2nd Month there was big event like fun fair, exhibition happened near to his cafe. Profit for this month increase to 2 Lakhs. 3rd Month there was coronavirus 2nd Wave hit and all shops, cafe were closed for month. So No Profit. 4th Month, 5th and 6th month his profit was again 1 Lakh per month. 7th and 8th Month there was 3rd Wave of COVID 19 so no profit 9th and 10th Month there was bulk order from big corporate event leading to profit of 3 Lakhs . So Profit so far is 9 Lakhs and still need 1 more lakh profit for Break even. Considering up and down his relative were very happy and start taking more bets on his idea and encouraging him to expand his cafe chain by opening 1 more outlet, delaying the payback further. So learning here payback period is simple and help assess risk of investment but it ignore 1. Time value of money 2. Cash flow after payback 3. Doesnt measure profitability. So Payback period is useful when liquidity is highest priority .
  13. The winning answer has been provided by Jayanth. Well done! P.S. Nowadays most statistical packages have the ability to deal with botched runs (in case one occurs in your DOE). So we might not be required to redo the whole experiment.
  14. Q 684. What is Payback Period and how does it help in project selection? What are its advantages and disadvantages? Note for website visitors - This platform hosts two weekly questions, one on Tuesday and the other on Friday. All previous questions can be found here: https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/. To participate in the current question, please visit the forum homepage at https://www.benchmarksixsigma.com/forum/. The question will be open until Tuesday or Friday at 5 PM Indian Standard Time, depending on the launch day. Responses will not be visible until they are reviewed, and only non-plagiarised answers with less than 5-10% plagiarism will be approved. If you are unsure about plagiarism, please check your answer using a plagiarism checker tool such as https://smallseotools.com/plagiarism-checker/ before submitting. All correct answers shall be published, and the top-rated answer will be displayed first. The author will receive an honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term. Some people seem to be using AI platforms to find forum answers. This is a risky approach as AI responses are error prone as our questions are application-oriented (they are never straightforward). Have a look at this funny example - https://www.benchmarksixsigma.com/forum/topic/39458-using-ai-to-respond-to-forum-questions/ We also use an AI content detector at https://crossplag.com/ai-content-detector/. Only answers with less than 15-20% AI-generated content will be approved.
  15. Botched Run in designed of experiment refers to kid of mistakes which change original recipe and may affect the test results. for example we testing effect of 7 Different spices on taste of a Briyani Rice. Lets say in one of our test we accidently add too much chilies, more than the recipe called for. This mistake changes original recipe and may affect the test results. However as long as the changes are not too extreme, we can still analyze and learn from experiment. This kid of mistakes called as " Botched Run" . In DOE, Deviation from planned settings can impact the study's output in serval ways. 1. It may altered results by reflecting true effect of the factor being studied. 2. precision of the experiment's result might be reduced. 3. Overall validity and reliability of experiment can be questioned. To prevent these errors in Design of Experiment ( DOE) you need to take following preventive measures. 1. SOP for experimental procedure. 2. Training and detailed planning on the SOP and execution of SOP. 3. Pilot run if possible 4. Regular monitoring of experiment in progress to catch deviations early and correct them. 5. System to report, highlight errors as soon as they occur. Above steps can help to maintain reliability of experimental results.
  16. Hello Jayanth You may refer to the below links to get an understanding on the 2 concepts https://www.benchmarksixsigma.com/forum/topic/35351-central-limit-theorem/ https://www.benchmarksixsigma.com/forum/topic/34877-central-limit-theorem-law-of-large-numbers/ Regards Mayank Gupta
  17. Hi Sahil, You have a valid point, and we are considering a method to incorporate such needs. Thanks for sharing your perspective.
  18. My question is about past participants who would like to go through this program again because of AI tools which have been added now.
  19. To inquire use the following link https://tinyurl.com/BenchmarkSixSigmaInquiry
  20. DOE helps us to identify the relationship between cause and effect. It provides an understanding of interactions between causative factors and helps us to determine the levels at which the controllable factors need to be set to optimize reliability. It is mostly used by the engineers in the manufacturing industry to maximize yield and decrease variability. Botched Run is when the experiment is not conducted properly. This results in datasets which are inconclusive and not possible to analyze. Effects on the output of Botched run: · Inaccurate data · Unexplained variability · The output of the overall experiment may not be accurate Steps to prevent Botched run: · The experiment needs to be planned thoroughly, considering all possible variables · SOP’s should be created for all experiment procedures · All the people involved in the experiment should be well trained · Monitor the experiments continuously and document any variations
  21. What is Law of large numbers and Central Limit theorem. how are they useful to statisticians. give examples for each of them.
  22. Botched Runs: Throwing a Wrench in DOE Results: While Design of Experiments (DOE) is a powerful statistical technique used to understand the cause-and-effect relationships between different factors and how they impact a process or system, there are Achilles’ Heel to DOE project successes as well like Botched Runs, unforeseen phenomena, limited resource etc. Let’s deep dive on Botched Run: Botched run refers to an experimental trial where something goes wrong, causing the data collected to be invalid or unreliable for analysis. A Botched run occurs when an experiment with in a DOE project deviates from the planned conditions. This can happen due to various reasons impacting the overall results of your DOE study. Reasons for Botched Runs: Below are some of the reasons for Botched Runs Equipment malfunction: A faulty sensor, incorrect calibration, or unexpected equipment failure can lead to inaccurate measurements or incomplete data collection. Human error: Misreading instructions, setting incorrect parameter values, or mishandling materials can all contribute to botched runs. External factors: Changes in ambient temperature, unexpected power fluctuations, or even contamination of materials can introduce unwanted variables into the experiment. Impact of Botched Runs: Inaccurate/unreliable outcome: Since the data from a botched run isn't representative of the actual effect of the factors being studied, it can skew the overall results. This can lead to misleading conclusions and hinder the ability to identify the optimal settings for your process. Reduced Statistical Power: DOE studies rely on a statistically significant number of valid data points for robust analysis. Botched runs effectively reduce the usable data, potentially weakening the statistical power of the study and making it difficult to draw definitive conclusions. Wasted time and resources: Botched Runs leads to "Muda of rework", this will lead to waste of time and resources as the outcome is not reliable and the whole experiment has to be repeated. Loss of Momentum and Morale: The frustration caused due to Botched run may demoralize the research team. This can lead to a decrease in their motivation and potentially hinder their efficiency in moving forward with the project. Below are some precautions to be taken to minimize the occurrence of botched runs in DOE: Thorough Planning: Clearly define the experiment's objective, factors, and their levels. Plan the number of runs considering potential for errors or unexpected events. Meticulous Setup: Ensure equipment is properly calibrated and functioning correctly. Double-check the settings for each run to avoid errors. Data Recording and Monitoring: Record all observations and measurements meticulously. Regularly monitor the experiment to identify any deviations or unexpected behavior. Standardized Procedures: Develop clear and detailed protocols for conducting the experiment. Train personnel involved to ensure consistent execution. Pilot Run: Consider performing a pilot run with a limited number of trials to identify and rectify any potential issues before the main experiment. Contingency Plans: Have a plan for handling minor equipment malfunctions or unexpected situations. This might involve having spare parts or rerunning specific data points if possible. By implementing preventive measures and having a plan for handling Botched Runs, companies can ensure the integrity of their DOE studies and make informed decisions that optimize their processes and avoid costly mistakes.
  23. We have taken the MBB program to the next level by adding cutting-edge AI modules that perfectly complement various competencies. This means you can generate ideas like never before and learn to execute them precisely using the latest and greatest AI tools. To begin with, we will all get a trial version of multiple AI platforms to experiment and learn. Let me provide you with some application concepts from Master Black Belt competencies. Creativity and Innovation Practitioner - We have created some advanced scripts that will provide you with unique solution ideas for specific contradictions in Creativity and Innovation competency. Business Modelling Expert (Simulations for Rapid Improvements) - With our AI-powered approach, you will learn how to quickly structure your simulation model for Excel. Without AI, people struggle to set up the logic and fields in Excel. AHP Practitioner (Advanced Decision Making)- Some participants face challenges in creating a decision-making hierarchy. Our AI guidance will enable you to consider alternative hierarchies and their comparison. Lean Practitioner and Lean Guide - The AI tool guidance helps in several ways when applying advanced Lean. From selecting tools to planning powerful communication and suggesting automation methods, you can accomplish a lot once you are geared up. By incorporating these AI modules, our AI-enabled MBB program exceeds usual MBB expectations, preparing you for future-ready competence. Remember, a lot is happening in AI; we all need the latest insights to be at the forefront. Respond to this message by logging into the forum if you have any questions.
  24. Q 683. What is a Botched Run in Design of Experiments (DOE)? How does it affect the output of the study? What steps will you take to prevent them during DOE? Note for website visitors - This platform hosts two weekly questions, one on Tuesday and the other on Friday. All previous questions can be found here: https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/. To participate in the current question, please visit the forum homepage at https://www.benchmarksixsigma.com/forum/. The question will be open until Tuesday or Friday at 5 PM Indian Standard Time, depending on the launch day. Responses will not be visible until they are reviewed, and only non-plagiarised answers with less than 5-10% plagiarism will be approved. If you are unsure about plagiarism, please check your answer using a plagiarism checker tool such as https://smallseotools.com/plagiarism-checker/ before submitting. All correct answers shall be published, and the top-rated answer will be displayed first. The author will receive an honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term. Some people seem to be using AI platforms to find forum answers. This is a risky approach as AI responses are error prone as our questions are application-oriented (they are never straightforward). Have a look at this funny example - https://www.benchmarksixsigma.com/forum/topic/39458-using-ai-to-respond-to-forum-questions/ We also use an AI content detector at https://crossplag.com/ai-content-detector/. Only answers with less than 15-20% AI-generated content will be approved.
  25. Jayanth has provided the best answer to this question. Answer from Sachin is also a must read.
  26. Authority bias:- Authority bias is a tendency to give more weight to information or decisions provided by people whom we perceive as authorities. We often trust their judgment simply because of their position or credentials, without critically evaluating the content itself. This bias can significantly influence decision-making within organizations. The authority bias will indeed effect the organizational decision making and below are some of those impacts: Unquestioning Acceptance: Employees might accept a manager's directive without considering alternative approaches, even if a better solution exists. This stifles innovation and critical thinking. Information Distortion: Authority figures might sugarcoat bad news or downplay risks to maintain a positive image. This can lead to poor decision making based on incomplete information. Groupthink: When a leader strongly advocates for a particular course of action, others may hesitate to disagree, fearing repercussions or social pressure. This creates an environment of "groupthink" where dissenting voices are stifled. Example: The Consultant's Recommendation: Imagine a company facing declining sales. They hire a consultant with high price tag who is known for turning around struggling businesses. After a brief analysis, the consultant recommends a drastic restructuring plan with significant layoffs. Despite internal concerns from experienced employees who have intimate knowledge of the customer base and operations, the leadership team is heavily swayed by the consultant's reputation and hefty price tag. They approve the plan without much debate. This scenario showcases authority bias in few ways: Price as Expertise: The high cost of the consultant creates an assumption of superior knowledge, despite the limited time spent understanding the company's specific situation. External Validation: The consultant acts as an external, supposedly objective voice, giving their recommendation more weight than internal suggestions. Disregarding In-House Expertise: Experienced employees with valuable insights might be hesitant to challenge the consultant's plan, fearing they'll be seen as questioning authority. This example highlights the potential pitfalls of authority bias in business decision making. It's crucial to weigh all perspectives, internal and external, and ensure decisions are based on a comprehensive understanding of the situation, not just the perceived authority of the source. Mitigating Authority Bias: Below are some strategies that can be leveraged to reduce the impact of authority bias in organizations: Encourage Open Communication: Foster a culture where employees feel comfortable questioning decisions and offering alternative solutions, regardless of hierarchy. By encouraging open communication and diverse teams, a wider range of ideas are brought to the table. This allows for a more thorough examination of problems and potential solutions, ultimately leading to better choices. Data-Driven Decisions: Make data and evidence the primary basis for decision making, not just the bosses opinions. When decisions are based on evidence and data, organizations are less likely to fall prey to flawed ideas or biases held by individuals in positions of authority. This leads to more reliable and successful outcomes. Diverse Teams and Perspectives: Assemble teams with varied backgrounds and expertise to encourage critical thinking and challenge assumptions. Blind Reviews: Implement anonymous reviews for proposals, promotions, or product ideas to focus on merit rather than titles or positions. Mitigating authority bias fosters a more collaborative and critical thinking environment. This allows organizations to make well-informed decisions, reduce risks, and ultimately achieve greater success.
  27. Alright, let's unpack this concept of authority bias and how it can trip us up at work. Imagine this: you're in a meeting, brainstorming a new marketing campaign. The CEO throws out an idea, and suddenly, the room seems to nod in agreement. Not because it's the absolute best idea, but because, well, it's the CEO's idea. That's authority bias in action. Here's the deal: authority bias is that tendency to give more weight to ideas simply because they come from someone higher up the food chain, a perceived expert, or someone with a fancy title. We tend to trust their judgment more, even if we have our own thoughts or doubts. This can be a real problem in organizations because it can stifle creativity and lead to subpar decisions. Here's a real-world example: let's say the marketing director, who's been with the company for years and has a proven track record, suggests a social media campaign. But then, the new, fresh-out-of-business-school VP of marketing chimes in with a different, less-tested approach. Because of the VP's title and perceived expertise, the team might be swayed in that direction, even if the director's idea has more merit. So, how do we combat this bias? Here are a few strategies: Focus on the merits, not the messenger: Encourage everyone to evaluate ideas based on their strengths and weaknesses, not who proposed them. Empower diverse voices: Create a safe space for everyone to share their ideas, regardless of their position. Blind evaluation: For certain decisions, consider anonymously presenting options to remove the influence of titles. Seek out dissent: Don't be afraid of healthy debate! Sometimes the best ideas come from challenging the status quo. By being mindful of authority bias and implementing these strategies, we can make sure that the best ideas, not just the ideas from the highest voices, rise to the top. This leads to better decision-making and a more innovative and engaged workplace for everyone.
  28. Authority Bias is when people tend to give too much importance to the opinions and decisions of authority figures, like Managers or experts, often ignoring their own or others' good ideas. Examples : A manager asks to follow a specific script for customer interactions. Even if agents think a different approach would solve problems faster, they might stick to the script because the manager said so. During a high volume of customer complaints, the call center manager decides to extend working hours. Agents might accept this without suggesting other solutions even if they are aware of one. A Team Leader suggests a new method for handling calls. Even if some team members have concerns or better ideas, they might not speak up to avoid conflict, leading the team accept potentially less effective method. Mitigation Plan : Create an environment where everyone feels comfortable sharing their ideas and feedback, regardless of their position. Allow employees to provide feedback without revealing their identity, so they feel safe sharing honest opinions. Build teams with a mix of junior and senior staff, as well as different areas of expertise, to ensure different perspectives. Use clear processes for making decisions that require considering multiple viewpoints and evidence.
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