2026-Lean Six Sigma -Practical Approach-A Complete Guide

1. Introduction Lean Six Sigma Black Belt: Hello friends. Welcome to the Lean Six Sigma training program. Let me give you a glimpse about what are you going to expect in this training program. This is going to be divided into four important parts. The first part will tell you why should one be interested in taking up Six Sigma as a journey towards continuous improvement? We will also be covering up the concepts of D Mac as a project management methodology. And what are the different phases in DMAIC? Define, measure, analyze, improve, and control. What are the tools that are required at each of these stages? And some common mistakes which we should be aware of when we're doing this program. I mean to say that when we are picking up a project for Lean Six Sigma, what type of data do we look for? What type of analysis should we be doing? All those things will be covered as part of this program. The general awareness program will make your capable of identifying, should you be diving deep in taking up the Green Belts and Black Belt program. This dot of your interests. If you are a person who loves to make decisions based on data, then this is definitely the program that you should look forward to. I am dental sound and I am a master black belt from Indian Statistical Institute. I have done my black belt from American Society of quality. I'm also a PMP certified from Project Management Institute. I come with more than 21 years of experience and I want to share this experience with you. I want to make this learning journey of learning journey and action-based learning journey. Where at the end of every video, I might give you some small tasks too. When it comes to problem parts like the mathematical problem solving parts during the Lean Six Sigma, I will be giving you plenty of examples which we will be doing it together. And there'll be plenty of examples which you will be asked to do and refer it during the discussion feeds. I hope you enjoyed this journey of learning, Lean Six Sigma with me. Thank you and get started. 2. Concept of Lean Six Sigma: Pase overview, foundation and principle of six Sigma and lien. In this course, we will be introducing you to the foundation and principle of six Sigma and lien along with the values these quality and productivity improvement methodologies bring to the organization. We also cover the key lean tools commonly used in Six Sigma projects and explain what is N, what is six Sigma, and what is the integrated or a unified approach called a Lean Six Sigma. So what exactly is six Sigma? It all begin with an important metric defects per million opportunity, DPMO. DPMO is a scientific measure used to calculate the number of potential mistakes or defects in the delivery of products and services. This DPMO metric sits within the broader organizational system where six Sigma operates. The core competence of this system is the improvement methodology. Which is known as the DMAC cycle, which stands for define, measure, analyze, improve, and control. So together, the metric and the DMAC process forms the foundation of Six Sigma projects. This enables the organization to systematically improve the business process of all time. Why do we need six Sigma? There are several compelling reasons to adopt. The PruATrack record of Six Sigma, which was popularized by Motorola and General Electrics in 1980s and 1990s. Moreover, the COR techniques have been used to nearly a century and have been adopted by leading organization across the industry. The powerful tool kit, Six Sigma offers a structured methodology and a robot set of tools. It identifies and eliminates defects, reducing variation, and improving quality. Though it was born in manufacturing, the Six Sigma has been successfully applied in a wide range of industry, including financial services, government, non profit organizations, healthcare, logistics, and many more. Currently, BPOs use Six Sigma from the last three decades. The key benefits of Six Sigma is that all organizations, whether they are for profit or non profit, everybody faces the challenge of controlling operating cost. While ensuring sustainable revenue growth, Six Sigma addresses these challenges very well. So what are the ways in which Six Sigma helps you manage this cost reduction? Six Sigma has a proven method called cost of poor quality, famously known as COPQ which is used. Six SIGMA emphasizes on the voice of customer VOC, to understand the customer satisfaction level. We are aiming to reduce variation, eliminate inefficiency, and improve the process reliability. Six Sigma helps in profitability and long term value. By improving quality and efficiency, Six Sigma contributes to increased net profits to the organization and improve the value system in the organization. It builds a culture of continuous improvement. So when we focus on continuous improvement, Six Sigma ensures that the organization remains customer focused while enhancing internal capabilities, process controls and process performances. 3. Foundation of Lean Six Sigma: Purse overview. Foundation and principle of six Sigma and lien. In this course, we will be introducing you to the foundation and principle of Six Sigma and LIN along with the values these quality and productivity improvement methodologies bring to the organization. We also cover the key lean tools commonly used in Six Sigma projects and explain what is N, what is six Sigma, and what is the integrated or a unified approach called Lean Six Sigma. So what exactly is six Sigma? It all begin with an important metric defects per million opportunity, DPMO. DPMO is a scientific measure used to calculate the number of potential mistakes or defects in the delivery of products and services. This DPMO metric sits within the broader organizational system where six Sigma operates. The core competence of this system is the improvement methodology. Which is known as the DMAC cycle, which stands for define, measure, analyze, improve, and control. So together, the metric and the DMAC process forms the foundation of Six Sigma projects. This enables the organization to systematically improve the business process of all time. Why do we need six Sigma? There are several compelling reasons to adopt. The fluid track record of Six Sigma, which was popularized by Motorola and General Electrics in 1980s and 1990s. Moreover, the code techniques have been used to nearly a century and have been adopted by leading organization across the industry. The powerful tool kit, Six Sigma offers a structured methodology and a robot set of tools. It identifies and eliminates defects, reducing variation, and improving quality. Though it was born in manufacturing, the six Sigma has been successfully applied in a wide range of industry, including financial services, government, non profit organizations, healthcare, logistics, and many more. Currently, BPOs use Six Sigma from the last three decades. The key benefits of Six Sigma is that all organizations, whether they are for profit or non profit, everybody faces the challenge of controlling operating cost. While ensuring sustainable revenue growth, Six Sigma addresses these challenges very well. So what are the ways in which Six Sigma helps you manage this cost production? Six Sigma has a proven method called cost of poor quality, famously known as COPQ which is used. Six Sigma emphasizes on the voice of customer BOC, to understand the customer satisfaction level. We are aiming to reduce variation, eliminate inefficiency, and improve the process reliability. Six Sigma helps in profitability and long term value. By improving quality and efficiency, Six Sigma contributes to increased net profits to the organization and improve the value system in the organization. It builds a culture of continuous improvement. So when we focus on continuous improvement, Six Sigma ensures that the organization remains customer focused while enhancing internal capabilities. Process controls and process performances. You need to understand that DPMO and process performance are very important when it comes to Six Sigma projects. The concepts like DPMO is the fundamental basis for six Sigma. Once you can measure and capture the data, you can then check the chart performances, compare the actual results to a defined goal or mean. Evaluate deviation from statistical tools. By applying standard deviation, we access how process performs relative to its specification limit. Anything outside the upper and the lower specification limit is considered as out of spec and meets and it fails to meet the customer expectation. A performance chart typically includes a mean, which is the goal line, a range measured as standard deviation or Sigma levels. While many organizations set the tolerance of limit as plus or minus three Sigma, Sig Sigma aims for plus or minus six Sigma, resulting in only 3.4 defects per million opportunities. This means there is a dramatic improvement in the process quality. If our process is operating at six Sigma quality level, we are setting a much higher standard for quality. And operating performance at this level is 99.997% defect free. Meaning there may be only three defects per million opportunities. Why am I not saying 3.4? Some of you might wonder because the textbook definition says 3.4 defects per million opportunity. Understand, can you have a 0.4 defect? No. So we are expecting the defects to be around three for 1 million opportunities. What's the difference between an operation where deliverables are expected to fall within three Sigma versus the operation that works at six Sigma. Do all the operations have to work at that level? The answer is no. The main difference which can surprise you when you look at the numbers is that if an operation limits the defects at 3.4 million per million opportunities, so if the operation limits the defects just 3.4 per million opportunities, the improvements are dramatic. At three Sigma, it could mean losing 20,000 emails on the mailbox per hour. But if the same department is operating at six Sigma, it can be only seven pieces of mail getting lost over a year. Now consider now consider 5,000 incorrect surgeries per week versus just two surgeries with six Sigma. Our electricity outage and many more. Understand a process which involves humans should be operating at six Sigma or beyond six Sigma. For other departments, you can work with two Sigma and three Sigma as well. Six Sigma as a methodology believes that, yes everybody should work at Six Sigma. Think about landing airplanes. Thankfully, airlines today mostly operates at six Sigma level of quantity. Why that plane crash are rare? It is because it is not operating at three Sigma. 4. Lets have some Breakfast: Let me start with the story of the big first time. Even before we get into the concepts of Lean Six Sigma, it's important for us to understand why is Six Sigma projects solving methodology when you are experiencing radiation? Even if before I explain you the concepts of statistics and all, let's listen to the store. I love making breakfast for my family. And you're, as you can see on the image here, I love decorating the bread slices when I made the big fuss for my family. There are six members in my family. And I went to the beaker next door and brought backups of bread. When I brought two packets of bread and I paid him a 100 Indian rupees. I was very happy because when I came home, I found that they were eating slices of bread. Each member of my family got three slices of bread and I could make yummy delicious breakfast for them. This big quest, we all enjoyed. And my daughter said, Mom, I want you to meet the same breakfast again tomorrow. I was very happy. I went to the same beaker again, brought the same two packets of bread, paid him 100 rupees for the bread that I picked up. This time, I received only 15 slices of bread. And it was wondering, there are six people in my home, is the one who leads to compromise. There was a variation. I went back to the baker and said, Listen man, I paid you a 100 of these, picked up two packets of bread and I got 18 slice of bread yesterday. I was able to give six people into three slices of bread, Eating slices of bread. And based on that, today, again, I picked up packets of bread. But today three slices where less. And hence, I did not have my breakfast because I had to give it to my family. So the five people in my family were 33 slices of bread and I was without breakfast. The beaker said, No, ma'am. I need eight gauges of bread yesterday. And on an average, I back 400 grams of bread in every packet. Yesterday, I back 20 packets. And you have picked up two buckets yesterday and two packets to the early morning. It comes from the same place. So how come? He was talking about the average, telling that on an average 400 grams who have bread was present in each bucket. But when he was packing the bread, some packets had for 50 grams of bread and some packets have 350 grams of blood to my desk where the first day I receive the good ones, and hence I received extra slices of bread. But on the next day, I received one packet of 350 grams, and then all 380 grams. On an average, I have received 400 grams of bread. But as a customer, I experienced the mediation. Are your customers experience radiation than six Sigma is a journey towards solving these type of problems, reducing the variation that your customer is expecting. So we're going to learn many tools and techniques of identifying the variations and eliminating them, or at least reducing them as much as possible. So stay connected and continue in the next video. 5. What do Customer Experience: Let us understand, what do we experience as a customer? I told you the story of my big plus time. The baker very clearly said that on each bucket the, of the bread, it was very clearly written 400 grams. The beaker also confirm that yesterday he made eight gauges of bread and packed it into 20 different packets. Confirming that on an average 400 grams of bread was packed. On an average. What really happened? But yes, On an average he was back 400 grams. But some packets of bread had for 20 grams of bread, which was actually a good for customer like me, where I was able to sell my family, but it is a loss to the business. On the second day when I receive 350 grams of bread, I was definitely dissatisfied. Customer always experiences of radiation, the customer never experiences to average. The journey of Lean Six Sigma focuses on identifying the variation in the process and reducing them. Identify waste in the process and eliminating them. Let's understand the story further when we go in the Lean concepts. Thank you. 6. Belts and roles: The Six Sigma organization and the hierarchy and the rules. Within a Six Sigma, there are organizational hierarchy and different rules exist within this hierarchy. Each one of these rules carry a unique responsibility in the deployment of six Sigma. The organizational hierarchy begins at the top level of the organization within the executive teams and the champions. These are individuals who can provide the vision for the organization. Next, we have Master Black Bells. They work alongside with the champions to help select the project. Master Black Belts also mentor Black bells who are actively involved in leading Six Sigma projects. Further down the hierarchy, we have green belts. At this level, process improvements are occurring within the Green Belts job function or the department in which the Green Belt is working. Finally, at the bottom of the hierarchy, we have yellow belts. These are individuals who can participate in the team activities and have a general understanding of six sigma. Within the hierarchy of master black belts, black belts, and green belts are the professional designation. The executive leadership and the champions are made up of chief executive officer, the CEO, and other top executives of the organization. So now let's explore each of these roles, starting with executive leadership and champions. Executive leadership is responsible for a vision and the implementation of Six Sigma. As a Six Sigma projects are implemented, the role of the executive leadership is to ensure that these projects help the organization achieve the long term strategic vision. Champions are essentially the power brokers. These are individuals who help secure any necessary resources and often secure the improvement projects. They often sponsor the improvement projects. Champions act like a bridge between executive leadership and the Master Black Belt to ensure that each project aligns with the organizational goal. Therefore, champions have to fully understand the corporate culture and should have a basic understanding of sig sigma. The executive leadership and the champions have a general understanding of what is six Sigma and what is their role in linking six Sigma efforts to the long term vision and the organizational goals. The Master Black Belts are the consultants to the team members. They work on conducting or they work as a bridge between the champion and the Black Belts to ensure that the appropriate projects are being selected. In addition, Master Black Belts are generally responsible for training and mentoring Black Belts. So it is important that we have a full and thorough understanding of Six Sigma. In comparison to the Master Black Belt, a Black Belt are the people who lead the project. They are also the project managers leading Six Sigma projects. They are typically team leaders and for any Six Sigma initiatives. In addition, their role is mentoring green belts. Within Six Sigma hierarchy, there are several levels that are providing mentorship. The Master Black Belt mentors the Black Belt. The Black Belt mentors the green belt. Therefore, the Black Belt plays an important role in disseminating Six Sigma knowledge throughout the organization. The entire organization has an opportunity to learn from the black belt. The bottom level of the hierarchy as comprised of green bells and yellow bells. These are the operating team leaders, and they typically work on the projects that can give direct results. These are the people whose job is to work in that department, take out some time and do improvements and continuous improvement in their processes. In addition, they use process improvement tools within the context of their project. Finally, yellow bells have a basic six Sigma training and are actively involved in the projects alongside of green bells and black bells. Thank you. I'll see you in the next lesson. 7. Role of Lean Guide: The role of a lean guide as organizations mature in their lean journey, the need evolves for just running projects to building a culture of continuous improvement. And this role can easily be managed by a person called Lean Guide. The lean guide is the one whose role goes beyond applying just tools. The lean guide becomes a coach, a mentor, and a culture carrier. Someone who empowers the team nurtures problem solving and aligns improvement with strategic goals. We will break down exactly what a lean guide does and how it differs from a lean practitioner or a project lead. Think about someone in your workplace who doesn't just solve problems but helps others get better at solving them. Would you call them as Lean guide? 8. Difference between Lean Guide and Practioner: Duties and responsibilities of a lean guide. Their job is conducting training sessions. Lean guides are responsible for organizing and leading training sessions to educate teams on lean methodologies and principles. They're also responsible for coaching team. Understand? Coaching means going with them, sitting with them, and helping them implement the lean practices effectively to enhance productivity and efficiency. They oversee the lien projects. Lien guides oversee these projects, ensuring that all the processes are aligned with the lien principles and objectives. They identify areas of improvement. They assist team in identifying areas of improvement by streamlining the process and increasing the efficiency. The key traits of an effective lien guide is they have strong leadership skills, effective communication, and deep understanding of the lien principle. What's the role of a lean practitioner? We might get confused that my friend is a lean practitioner. How are they different? Driving continuous improvement within the organization is led by Lean practitioner. They focus on eliminating Tim woods, reducing inefficiencies, and streamlining workflows, data driven decision making, analyzing performance metrics like cycle time, error rate, and customer satisfaction score. They use root cause analysis, FIs pareto analysis to identify problem before they escalate. Practitioners facilitate in lean training and cultural development. They do not drive it on their own. So let's do a quick comparison of rules of the lean guide versus a lean practitioner. Scope of work and influence. The role of a lean guide is broad, because they are mentoring across multiple projects and fostering the overall team development. They are strategic, focusing on organization wide lean culture and continuous improvement. Whereas the lean practitioner, they are concentrating on implementing specific task of improvement, focusing on improvements within their own teams. Their solutions are tactical, focused on processes, tasks and workflows. So remember, a lean practitioner is focused on execution at the team level, whereas a lean guide is involved in driving strategic and embedding lean into the culture. Handling resistance within the team. Let's understand this scenario. During a process improvement initiative, some team members are resistant to change being introduced. The project lead steps in, facilitates a root cause analysis session, and helps the team co create a new workflow to reduce resistance. Does this behavior reflect hands on problem solving like a line practitioner or a strategic facilitation and mentoring across multiple teams? The project lead steps into facilitating root cause analysis and help co create a new workflow to reduce the resistance. Yes, it's the role of a lean practitioner because he's helping and problem solving. Scaling improvements across departments. A pilot project to reduce customer onboarding time is successful. The project LD is now working with leadership to roll out this solution across sales, operation and finance. This is aligning with the business strategic and coaching session. The question is, is this focus on cross functional alignment and strategic typical of a lien practitioner or a lien guide? So as I explained to you, it belongs to the lien guide. 9. Teams in Lean Six Sigma Implementation: This lesson, we will understand about teams in an i Sigma. Teams are an integral part of LIN Six Sigma implementation. Typically, a lean Si Sigma activities are carried out collaboratively, making them team a critical factor in the success of any initiative. When forming teams, it is common to build cross functional groups. These teams bring together members from different parts of the organization, enabling diverse perspectives and a better alignment with the overall business rules. Additionally, involving teams from various functions helps empower them to actively contribute to process improvement efforts. Types of Six Sigma projects. There are four key types of Six Sigma projects. Define, measure, analyze, improve, and control. This is called as a DMAC cycle. The second one is designed for six Sigma, DFSS. Plan Do Check at PDCA. That's the third type. Lean Kison or Kison list is the fourth methodology. 10. Stages of Team development: The types of team in Six Sigma projects. The four most common types of teams in a Six Sigma projects are process improvement teams. These teams focuses on enhancing specific business processes. Their goal is to deliver immediate results often by implementing solutions that are simple and quick to execute. This approach helps ensure that the implementation is fast and tangible outcomes are ensured. The second one is the quality team. The role or the aim of the quality team is to improve internal efficiencies that affect the final output, an area closely tied to customers expectation. Their work typically involves either improving a specific process or developing a quality plan for a department or the entire organization. Ad hoc teams. These teams create a complete project with a well defined specific requirements. These teams are goal oriented and have a narrow focus and usually exist for a limited time. They are often a cross functional team. They're interdepartmental or tailored to address a particular stakeholders need. Ad hoc teams are very useful when you want to kill a project or kill a problem using a project methodology, get the team together and solve it. Self managed or agile teams. These teams are responsible for managing their own work and leading their own improvements. They are required a high level of collaboration and functions with minimal directions from the management the self directed team, the team leader in such an environment, is also acting like a facilitator, a guy, rather than just being a supervisor. What do we understand from this? Regardless of the team time, the effective teamwork is essential for the success of Lean Six Sigma projects. By leveraging the strength of each team structure, organizations can drive meaningful improvements and sustainable change. What are the stages for team development? Teams go through various stages of development, primarily because project dynamics tend to evolve over time. These changes occur not only due to the natural progression of the project, but also as the team members become more familiar and more mature with each other. This allows them to collaborate more effectively towards a shared goal. Additionally, the nature of the project itself may shift, influencing how the team functions and adopts. One of the most critical factor for ensuring a strong team performance is effective leadership. Strong leadership contributes significantly to the team's ability to evolve, align, and improve over time. When managing team dynamics, two key responsibilities fall to the manager. Managing people, managing the overall team and the team's performance to navigate these responsibilities successfully, it's helpful to understand the stages of team development. This typically includes forming, storming, norming and performing. And adjourning. Recognization is the next stage that has been recently added to this. In the first stage that is forming stage, this is the initial stage where the team is put together. At this point, the team leader provides clear direction, delegates a role and responsibility. The focus is on setting expectations and helping team members understand the project goals. During this stage, team members begin exploring the nature of work and learning about each other's strengths. Since this is a functional phase, it is essential for the team leaders to clearly define objectives, timelines and communication protocols. Team development in Six Sigma projects continue. Let's continue with that. During the storming stage, team members may begin to test the boundaries and assert their opinions. At the same time, they are learning how to communicate effectively with one another. In Six Sigma logics, team often consist of individuals from diverse professional and cultural background. As a result, communication style can vary significantly, which may lead to misunderstandings or conflict. The norming stage begins once the team members have gain a better understanding of the project and the objective of the project. They have learned to communicate more clearly and respectfully. This is when the relationship begins to solidify and the team starts to collaborate more effectively on the shared task. The team members begin to appreciate each other's working style and now reach a consensus on how to approach their progress and do the process improvement. At this stage, it's essential for the team leaders to encourage active participation and foster a collaborative environment. Promoting team engagement helps ensure everyone is aligned and moving towards a common goal. Once the team has established strong working relationship and clear communication, they enter a performing stage. This is the most productive phase of the team development. The team functions cohesively, communicates seamlessly, and is highly focused on achieving project goals. In the performing stage, the team leader adopts more for a supervisory role, stepping back to allow the team to operate with greater autonomy and confidence in their process improvement efforts. The next phase is adjoining, which marks the conclusion of the project. At this point, the team is dissolved because the project goals have been met. However, this stage can bring about two different reactions. Some team members may feel reluctant to let go of the project, while others may lose interest because all the tasks are completed. It is important to ensure that all the remaining activities like the project closure, documenting the lessons learned and wrap up any loose ends that needs to be addressed. The final stage of team development is recognizon. Once the team has successfully completed a project, it's important to acknowledge and celebrate their contribution. During this stage, the team leader provides feedback and recognize individuals and collective achievements. Effective recognizon reinforce positive behavior, boost morale, and highlights what is valued within the organization. When celebrating team's success, ensure that recognizon reflects both the outcome achieved and the values upheld during the project. By understanding and managing these stages of team formation that is forming, storming, norming, performing, adjourning and recognizon, team leaders can guide their teams through the natural progression of development, ultimately, maximizing their performance and project success. 11. What is Lean: Let us understand what is laid in the lean journey. In the journey of Lean Six Sigma, what do we mean by lean? Lean is a methodology about problem-solving. And in Lean, we focus on eliminating waste. You would have heard this a lot. Lean manufacturing, Toyota lean production system. And whenever we think about the, we're thinking about creating value for the customer. So the first step towards understanding Lean is identifying the value. You identify this value from the customer's point of view. The second step is to map the value stream. When you are doing Lean, it's technically a process where we try to map the process tree, the value string. The third one is about creating a flow. In traditional service or production environment. Usually we used to do batch processing. Lean very clearly believes that we should have a one-piece flow in an organization. Establishing a put. Lean does not believe in pushing the product and services which are manufactured to the customer. In fact, the customer demand should pull the goods or services. Moving towards perfection. That is about Lean. Lean is about creating perfection in your journey towards excellence. Thank you. 12. What is Six Sigma: What is Six Sigma? Let's try to understand what is Six Sigma in the concept of Lean Six Sigma. Six Sigma is a target. It's a number. Statistician's have defined that if a process has less than 3.4 defects per million opportunities, then the process is said to be performing at Six Sigma journey. You cannot achieve that number overnight. It's a journey where we are changing the culture of the company. It definitely means that when we are talking about changing the culture of the company, it must involve everyone in the company. An organization is supposed to be on the journey of Lean Six Sigma where everybody is in board getting trade on the concepts of Lean Six Sigma is involved in the process of process excellent. Taking the product and services that they offer towards near perfect. It transforms the way the company does business. It's going to be successful for itself because it's going to make profits. It's going to be beneficial to the customer because it's going to give them affordable goods and services. So in the journey of Lean Six Sigma, six Sigma is not about the standard deviation that we have learned, but it's about a calculation which we will be covering in the coming videos. If you have any queries, please write down in the discussion section. I will be happy to answer them. 13. Defects Per Million Opportunities Dpmo: You need to understand that DPMO and process performance are very important when it comes to Six Sigma projects. The concepts like DPMO is the fundamental basis for six Sigma. Once you can measure and capture the data, you can then check the chart performances, compare the actual results to a defined goal or mean. Evaluate deviation from statistical tools. By applying standard deviation, we access how process performs relative to its specification limit. Anything outside the upper and the lower specification limit is considered as out of spec, and it fails to meet the customer expectation. A performance chart typically includes a mean, which is the goal line, a range measured as standard deviation or Sigma levels. While many organizations set the tolerance of limit as plus or minus three Sigma, Sig Sigma aims for plus or minus six Sigma, resulting in only 3.4 defects per million opportunities. This means there is a dramatic improvement in the process quality. If our process is operating at six Sigma quality level, we are setting a much higher standard for quality. And operating performance at this level is 99.997% defect free. Meaning there may be only three defects per million opportunities. Why am I not saying 3.4? Some of you might wonder because the textbook definition says 3.4 defects per million opportunity. Understand, can you have a 0.4 defect? No. So we are expecting the defects to be around three for 1 million opportunities. What's the difference between an operation where deliverables are expected to fall within three Sigma versus the operation that works at six Sigma? Do all the operations have to work at that level? The answer is no. The main difference which can surprise you when you look at the numbers. So if the operation limits the defects just 3.4 per million opportunities, the improvements are dramatic. At three Sigma, it could mean losing 20,000 emails on the mailbox per hour. But if the same department is operating at six Sigma, it can be only seven pieces of mail getting lost. Now consider 5,000 incorrect surgeries per week versus just two surgeries with six Sigma. Our electricity outage and many more. Understand a process which involves humans should be operating at Six Sigma or beyond six Sigma. For other departments, you can work with two Sigma and three Sigma as well. Six Sigma as a methodology believes that, yes, everybody should work at Six Sigma. Think about landing airplanes. Thankfully, airlines today mostly operates at six Sigma level of quantity. Why that plane crash are rare? It is because it is not operating at three Sigma. Crash far more common if it is operating at three Sigma or anything less than six Sigma. Six Sigma is highly adaptable and is commitment. Any organization, regardless of the size and the industry, work towards the level of performance. From manufacturing to consulting, from profit to nonprofit, government agency and private sector. Everyone can apply Six Sigma. The great example of Six Sigma application is customer facing organizations such as call centers. We also call them as contact centers. But there is no restriction. An organization can adopt and benefit from Six Sigma. 14. Cost saving and reducing defects: Course overview, foundation and principle of six Sigma and lien. In this course, we will be introducing you to the foundation and principle of six Sigma and LIN along with the values these quality and productivity improvement methodologies bring to the organization. We also cover the key lean tools commonly used in Six Sigma projects and explain what is N, what is Six Sigma, and what is the integrated or a unified approach called lean Six Sigma. So what exactly is six sigma? It all begin with an important metric defects per million opportunity. DPMO. DPMO is a scientific measure used to calculate the number of potential mistakes or defects in the delivery of products and services. This DPMO metric sits within the broader organizational system where Six Sigma operates. The core competence of this system is the improvement methodology, which is known as the DMAC cycle, which stands for define, measure, analyze, improve, and control. So together, the metric and the DMAC process forms the foundation of Six Sigma projects. This enables the organization to systematically improve the business process of all time. Why do we need six Sigma? There are several compelling reasons to adopt. The Proud track record of Six Sigma, which was popularized by Motorola and General Electrics in 1980s and 1990s. Moreover, the code techniques have been used to nearly a century and have been adopted by leading organization across the industry. The powerful tool kit, Six Sigma offers a structured methodology and a robot set of tools. It identifies and eliminates defects, reducing variation, and improving quality. Though it was born in manufacturing, the six Sigma has been successfully applied in a wide range of industry, including financial services, government, non profit organizations, healthcare, logistics, and many more. Currently, even BPOs use Six Sigma from the last three decades. The key benefits of Six Sigma is that all organizations, whether they are for profit or non profit, everybody faces the challenge of controlling operating cost. While ensuring sustainable revenue growth, Six Sigma addresses these challenges very well. So what are the ways in which Six Sigma helps you manage this cost reduction? Six Sigma has a proven method called cost of poor quality, famously known as COPQ which is used. Six Sigma emphasizes on the voice of customer BOC, to understand the customer satisfaction level. We are aiming to reduce variation, eliminate inefficiency, and improve the process reliability. Six Sigma helps in profitability and long term value. By improving quality and efficiency, Six Sigma contributes to increased net profits to the organization and improve the value system in the organization. It builds a culture of continuous improvement. So when we focus on continuous improvement, Six Sigma ensures that the organization remains customer focused while enhancing internal capabilities. Process controls and process performances. You need to understand that DPMO and process performance are very important when it comes to Six Sigma projects. The concepts like DPMO is the fundamental basis for six Sigma. Once you can measure and capture the data, you can then check the chart performances, compare the actual results to a defined goal or mean. Evaluate deviation from statistical tools. By applying standard deviation, we access how process performs relative to its specification limit. Anything outside the upper and the lower specification limit is considered as out of spec and meets and it fails to meet the customer expectation. A performance chart typically includes a mean, which is the goal line, a range measured as standard deviation or Sigma levels. While many organizations set the tolerance of limit as plus or minus three Sigma, Sig Sigma aims for plus or minus six Sigma, resulting in only 3.4 defects per million opportunities. This means there is a dramatic improvement in the process quality. If our process is operating at six Sigma quality level, we are setting a much higher standard for quality. And operating performance at this level is 99.997% defect free. Meaning there may be only three defects per million opportunities. Why am I not saying 3.4? Some of you might wonder because the textbook definition says 3.4 defects per million opportunity. Understand, can you have a 0.4 defect? No. So we are expecting the defects to be around three for 1 million opportunities. What's the difference between an operation where deliverables are expected to fall within three Sigma versus the operation that works at six Sigma? Do all the operations have to work at that level? The answer is no. The main difference which can surprise you when you look at the numbers. So if the operation limits the defects just 3.4 per million opportunities, the improvements are dramatic. At three Sigma, it could mean losing 20,000 emails on the mailbox per hour. But if the same department is operating at six Sigma, it can be only seven pieces of mail getting lost. Now consider 5,000 incorrect surgeries per week versus just two surgeries with six Sigma. Our electricity outage and many more. Understand a process which involves humans should be operating at Six Sigma or beyond six Sigma. For other departments, you can work with two Sigma and three Sigma as well. Six Sigma as a methodology believes that, yes, everybody should work at Six Sigma. Think about landing airplanes. Thankfully, airlines today mostly operates at six Sigma level of quantity. Why that plane crash are rare? It is because it is not operating at three Sigma, if it is operating at three Sigma or anything less than six Sigma. Six Sigma is highly adaptable and is commitment. Any organization, regardless of the size and the industry, work towards the level of performance. From manufacturing to consulting, from profit to nonprofit, government agency and private sector. Everyone can apply Six Sigma. The great example of Six Sigma application is customer facing organizations such as call centers. We also call them as contact centers. But there is no restriction. Any organization can adopt and benefit from six Sigma. And we will explore the timelines of Six Sigma and understand the evolution over time. The importance of Six Sigma concept is the standard deviation. This was defined in 19th century. Going back to the late 1800s, we find that Frederick Taylor, the rise of Taylorism. His economic theory and divisions of labor laid the groundwork for many principles we associate with six Sigma. In 19 twentyes, pionists like Henry Ford, Walter Shuhart, George Box contributed to what would be evolving into today's modern six Sigma practices. In 1940s, the US government began publishing quality control in the military manufacturing. This led to the rise of statistical process control, SPC, as we call it. Thanks to this part of early teaching by the statistician Walter Stuhart. After the World War two, figures like doctor Edward Deming, doctor Joseph Juran worked extensively in Japan. Their contribution helped transform quality into a competitive advantage for Japanese industry. It was during this time that the Japanese Union scientists and engineers, JUSE Jews was established. Laying the foundation of many practices will later adopt a six Sigma. 15. Evolution of LSS: We will explore the timelines of Six Sigma and understand the evolution over time. The importance of Six Sigma concept is the standard deviation. This was defined in 19th century. Going back to the late 1800s, we find that Frederick Taylor, the rise of Taylorism. His economic theory and divisions of labor laid the groundwork for many principles we associate with Six Sigma. In 19 twentyes, pionists like Henry Ford, Walter Shuart, George Box contributed to what would be evolving into today's modern Six Sigma practices. In 1940s, the US government began publishing quality control in the military manufacturing. This led to the rise of statistical process control, SPC, as we call it, to this part of early teaching by the statistician Walter Stuhart. After the World War two, doctor Edward Deming, doctor Joseph Juran, worked extensively in Japan. Their contribution helped transform quality into a competitive advantage for Japanese industry. It was during this time that the Japanese Union scientists and engineers, JUSE Jews was established. Laying the foundation of many practices will later adopt a six Sigma. 16. Understanding the DMAIC Roadmap: The MC approach at the d.school Mac roadmap, whenever you are picking up a Six Sigma project, we usually follow the DMAIC approach that is called as a team Mac roadmap. Why is each of these teach important? Let us try to understand that. In the define phase, we define the problem and the optic disc that we want to achieve by doing this project. During the measure phase, we tried to establish, can we measure the problem? Suppose if we are doing a project on reducing the turnaround time for a process or reducing the number of defects from a particular machinery. Whatever is my metric, can I measure it? And what level am I today? I tried to understand my current process capability. Once I understand where do I stand in terms of my current process capability? We then move into the analyze phase, which is the third phase of the project, where the maximum effort takes place. During the analyze phase, we tried to analyze the process. We take updated or approach. We take up the process to report and we try to define what are the factors which are influencing my problem. You remember, I covered what is y is equal to a function of x. You project metric is getting impacted by a lot of inputs. We try to understand which of those inputs which are actually creating are influencing my output. Concepts like root cause analysis. We do test of hypothesis. We do Gemba walk, we draw the process maps, we do swim lane diagrams and many more things. With that, we then understand how to pick 20 x's are 15 X's that you have for your process. What are those whiter five or seven x which are actually implementing are causing the problem. Sometimes that could only be a two or three axis. Once I have established what is causing this problem, then we go into the improved phase. In prophase is the fourth stage of a project. Some of the organizations also call it as an engineer fees. Suppose if you are doing a service related process, are you are trying to fix a process which is from a service industry or which belongs to the support services. We usually call it as an improved because we're trying to improve from wherever we there. We call it as an engineer. If you are in a manufacturing setup because you need to engineer the solutions. So as you understood, during this phase, we try to identify what could we the solutions and order the multiple solutions that we have. Bit solution will actually helped me in going towards the outcome that I won't post, which we go into the control phase after we have successfully done the pilot. And we see that the pilot phase is giving me the results that I want. We want to then go for a full-scale implementation. During the control phase, we have seen the sample results during the pilot phase. Now how can I do a full-fledged are a complete roll-out across all the processes which are in scope. Number two, how do we ensure that the results which I receive now will continue to remain and I sustain the increments. As you would have heard, many people say that I did the project during the project fees. There was a lot of benefit. But once the be moved out of the project, the benefits stopped coming and the process slowly moved back their own way. There are many tools and techniques like responsibility, assignment, matrix, control, plan, project closure document, which are very important, which we will be covering during the control phase of the project. With that, let's move to the next slide. This slide talks about what exactly happens during each of the phases. So during the define phase, I reviewed a charter, I validate the problem statement. I validate the voice of customer. I validate what could be the approximate dollar seats, validate high level VSM. We do need to do this. This is also called as a SIPOC. We establish a communication plan. We establish, select the team, and we develop a project plan or shade you, and ensure that we go through the defined tollgate review. Technically, you should be able to complete this phase of your project in max of one week to ten days. Because you should not do our analysis because the project charter is a live document. I go and measure the data. During the measure phase, I can go back and update my project charter with the correct numbers in the problem statement. And I can revisit my goal statement if required. So hence, it's important for you to establish what is the project you're going to work on. What is the voice of the customer? Does a customer wants you to work on this project? Do you have proper communication plan? Do you have the proper team who will work with them? And can I complete this project in a span of three to five months? Six Sigma project, which is going beyond five months. Out of my practical experience, never gets done because it would then become like a regular business operations. And it would be like, okay, this project is going on right in-between. We would come do some artsy, but there is no practical change on the process. We understand that it is the concept of continuous improvement. But you also need to understand that continuous improvement in terms of continuously doing the project. We then move into the measure phase. During the measure phase, some of the activities that you do are you understand the as-is process map, our SIPOC, you develop the data collection plan. You validate the measurement system that the data that I'm collecting. Is it correct? We will be seeing all these things in detail during the future program. We established the current baseline, we determine the current process capability. With that, we go to the measure phase tollgate review. Six Sigma very clearly believes that at the end of each phase, I need to go back to my stakeholders and tell them that how am I progressing? With that? We go to the analyze phase and that key activities during the analyze phase is to determine the critical inputs. Identify the root causes. Narrow down the root causes, determine the impact of root causes on my project, right? Prioritize the root causes to be worked. Analyze the as is process map in terms of value-added and non-value-added activity. These are some of the Lean concepts which we implement during this phase. Nowadays, we call it as a Lean Six Sigma because we want to get the best of both worlds. Both switch, we go for our analysts tollgate review. During the improve phase. As I have already established, what are the root causes, I will go ahead and develop the potential solutions. I evaluate and select optimized solutions are the best options. I have tools like solutions, selection metrics for the path matrix, and many more. I then do a small pilot with limited resources and see if I'm getting the results for which I have set up. I can form by doing a test of hypothesis that actually the results are in favor of the objective with which we started the project. If it works out well, then we go for an implementation plan and we come to the end of the improve phase. We then go to the control phase where we try to establish that, okay, these are the solutions. How can I make this solutions? Mistake proof. I applied the concept of Poka Yoke. I developed a training plan, implement the solutions. I ensured what are the lessons that were learned during this journey? Those are all documented before I complete my project. Right. Then I do the animal control phase review and then I transition this causes to the operations team. B will understand more in details in the next chapter. 17. Understand the Deliverables for each of the DMAIC project phases: Based on understanding what are the key activities we do during each phase of the project life cycle? Let us understand what are the key deliverables. For each phase. There could be multiple deliverables, but at least we should ensure that what I have mentioned on the screen, those 15 deliverables are there in your project. And you ensure that you work towards getting this deliverables. During the define phase, at least we need the project charter, the CTQ tree, and the SIPOC. Please do not compromise on any of the tool because all of these tools are equally important. The project charter is also a change. Management to CTQ validates the voice of customer. And SIPOC sets the boundary of your project. For the measure phase, the three important deliverables or your measurement system analysis. You collect the data and you establish your baseline or the current process capability. During the third phase, that is, the analysts fees identify the sources of variation I found on the causes, and I validate the root cause. Tools and techniques can be different. You can take a process door approach, you can take a data-driven approach. You will be doing hypothesis testing and so on. But we ensure that we have enough deliverables under each of this bucket. During the ego fees. The three important deliverables are, I generate a lot of solutions. I select the best-fit solution, and I pilot the solutions and confirm that the results, what I want. If that does not work, you actually go back to your solution dashboard and identify the next solution which actually can work. If all the solutions which we generated, none of them are working successfully during the pilot, it means that you have not analyzed your project or the cause of your deviation Very well. Then you need to go back to the analyze phase where you would be investigating the root causes one more time. Usually this doesn't happen. But in case that happens, you should be flexible enough in doing this. During the control phase, the three important deliverables are you implement the full-scale solutions. You monitor the process and monitor the results. You're not only going to monitor the output, you're also going to want it to the input because y is a function of x, then you ensure that you have a project plus process project closure document and you share the best practices with the others that what have you learned in the last three to five months. With that, we will be moving into the defined phase of the project life cycle. And we will try to understand what are the different types of tools that we use during the define phase. 18. Y is a function of x(s) y=f(x): I keep repeating the statement multiple times during the entire training, as well as if I'm entering any of your projects. Why is the function of x where y is the customer CTQ, or the thing that we need to improve with Lean Six Sigma x, or the internal processes that directly affects the customer seek to you. So your output is a symptom which is affected by your inputs, which is can positively or negatively affect your output. So how do I define what is the customer's? Ctq stands for? Critical to quality. Ctq for a process or product or a service characteristic should be measurable. You would hear me specifying, stressing on the word measurable, measurable, measurable. Six Sigma strongly believes what can be measured, can be improved. What cannot be measured, cannot be improved. So it's important for you to have this metric measure. Let's take some examples. It could be characteristics like speed, accuracy, timelines and cost. In the leading lending environment, the time to receive the final decision whether the loan is approved or not, is a critical metric. And it could be your CTQ. Number of documents required to make the final decision can also be a CTQ. For opening a new account. The waiting time to receive a debit card can be a metric which you want to improve. Example in India earlier to get a debit card to only had to wait two weeks. Today, you walk into a bank, you open an account, you do the verification, and they give you a welcome kit. The debit card is in your hand. They have literally did a beautiful process improvement where the turnaround time has been reduced from 15 days to 0 minutes. And this card is safe and secure because we are talking about a banking as a process. I didn't hospital. It may be a patient waiting time already. We know that the patient is not really well. If he has to go to the hospital and wait endlessly for two hours, three hours for 15 minutes. It is a very uncomfortable moment that could become acidic. Because the patient will say, I do want to go to a particular hospital or a particular cleaning because I have to read in spite of booking an appointment, the number of incorrect bills issued. We see that the doctors are excellent in a particular hospital. They do amazing surgeries. They ensure that the patient is recovering very fast. When it comes to the billing department, there are a lot of arrows and then they spend two to three hours fixing it and the patient is waiting for to go back home. These are some examples of CTQs that can be. 19. How do I find an opportunity for improvement: One of the important questions which is commonly asked by my participant during my training workshop is how do I identify an opportunity for improvement? I don't have a project in hand. I don't know how to identify a project. I'm going to tell you some simple tips which can help you identify an opportunity for improvement. When you are identifying and opportunities tried to see in both the worlds, one internal, the other is external. Let's first understand how do I identify internal improvement opportunities? You can brainstorm with cross-functional team who can tell you what are the problems that we face when we are handing off the process from one department to another. Sometimes you can identify an opportunity for improvement by analyzing the core business processes, either by mapping them or by examining their historical performances. Are the performance going towards the negative side? If everything is in control, those things can be identified. You can sometimes even look at the financial analysis of the business unit. Ease my department making the profit that is required is my particular product making the profit that is required. How is it when compared to industry best standards? Is the profit less than what the industry people are making? Then also it's an opportunity for improvement. I can measure it against my past that I was making. X percentage of profit. It has my profit reduced. As my cost increases. I can identify opportunities for improvement in this field so that you can review some of the repeated processes, products and service issues and challenges that you receive. So if you are repeatedly receiving a challenge or issue relating to your product process or service, you can identify that as a project and take it further. You can identify the business goal and metrics that have been missed or you add poorly executing. Look at your SLA documents for the service sector, or look at the customer contract where we have paid penalties to the customer for not meeting the metrics that we had agreed during the contract street. These could be some of the improvement opportunities which can be picked up as a project. If I go to the external opportunities, technically, the external opportunities are driven by our customers. It could be auditor's. Does customers of the final product or service. The project idea from the external source can be identified by conducting surveys, analysis of the existing customer feedback, direct dialogue with the customer. If a new discovery fees for an improvement opportunities, you may actually identify several opportunities. Now, because you have identified multiple opportunities, you might have a question, how can I prioritize them all eliminates some of them. Asking the following questions should help you in reading of this process. How can, what can I do to improve the situation? How important is this issue to your customer? East opportunity or, and, or the error in need of improvement, measurable. Other data available are easily generated. Can the benefits be quantified? Is the process table or against controllable? Is the scope of your problem narrow enough to finish the improvement in four to six months. Is there a sponsor or champion who's willing to provide you the help that requires you for this project in terms of resources and the support. By getting answers to these questions, you will be able to identify which are the projects which you need to keep and which are not an important projects are important opportunities. Answering these questions will help you help the team with products and action very easily. For example, if the data is not available or easily generated, validating the problem, baseline the current state, and ultimately proving that the improvement has taken place becomes impossible. What can be measured, can be improved. In data. We trust. We do not trust in any gut feeling. The other way of saying is In God We Trust. And indeed I dressed. However, when that project should not be selected immediately, the data collection plan can be implemented in order to meet the opportunity possible in the future. As you can see, these are some important questions which needs to be addressed. The other issue you can face is the project's scope is too large that the opportunity requests substantial amount of resources in terms of human capital as well as investment in daughters. Or if they take longer than six months to complete, then perhaps you need to raise, cope your project. As I told you earlier. Out of my practical experience, I have seen, if the project does not get completed in four to six months, the project lead technically gets tired and never completes the project. Hence, you can define to reduce the scope of your project to ensure that you achieve the success. Because when the scope is within what is possible, the team requirement, the dollar requirement, will also be substantially appropriated. But most importantly, what you choose as a project idea, it must be driven by the customer. This can be your internal customer or this can be your external customer. You cannot have a project idea because you feel that you need to do on a project. Or your boss is telling do here, but not the customer feels. So. Hence, it is important that everything that we do in Lean Six Sigma project is always customer-focused. In the event that you approached by a business leader with a project idea or a business issue that needs to be addressed. It is critical to note that no project ideas should be accepted as factual or a 100% accurate. What makes this phase challenging? Ease the burden of validating the opportunity. And the problem falls on the shoulder of the project leader. Validating this opportunity or a problem. It is the responsibility of the project leader. This validation and tails both defining the problem and establishing its magnitude and the frequency of its occurrence. A well-defined problem statement helps provide a better answer to who care situation. I don't care about this process. The customer keeps complaining. These are not some good things to listen to. Hence, it is important that we address this by identifying the correct opportunity and fixing it. 20. Project Charter How to Guide: The most important tool in your define phase. In fact, I should say, the most important tool in your Six Sigma project is your project charter. It. I also call it as the lighthouse because just like the way the lighthouse guide the ship towards the shore, project charter will guide all the team members towards the goal that the project has been initiated. When you are building a project charter. The purpose with which you build the project charter is that you want to clarify what is expected from the team. It keeps the team focused. It keeps the team aligned with the organizational priorities and transfer the project from the champion to the process improvement team. As you can see, it's very critical for us to build a project charter very carefully. The different elements of the project charter or the problem and the goal statement. It describes the problem and opportunities and objectives in a clear and concise manner. Your process will be ensuring that it's a measurable process because Six Sigma very clearly believes what cannot be measured, cannot be improved. We then try to understand, please the business case into the project charter. Business case explains why to do this project in the first place. It will help you to convince your stakeholders that why is this project important? Project scope, what is in scope, and what is out of scope. This is a very critical space. Your project charter. If you do not fill this up correctly, you might end up having a scope creep in your project. And your project will be endlessly increasing. And your stakeholders will be unhappy during that you're not achieving the results because the scope is going on in milestones. They are the key steps and the dates by which you want to achieve. As you know, Six Sigma is a structured approach if you ensure that all the elements are there in place in each of the tools, the success to your project is sure. My student, knowing when I will complete my define, measure, analyze, improve, and control is very important. If there is a delay, you can put in the remarks, it gets the team back on goal. We also define the roles and responsibilities of the people in the team in the project charter to ensure that everybody is clearly a sample project charter looks something like this. It has a business case. It has the problem statement. Do not get fixed on the structure. Every company follows a different way. I have tried to give you a very simple for blocker, which will make it easy for you to build your project charter. You name of the project is on the top. You first start with the business case below it, you have the problem that the company is facing. Below that, you have the goal statement which clearly defines what is the goal you are set out to achieve. You are clearly defining your in-scope and out of scope of the project. You are identifying your team members. Potential financial benefits is what you're right during the project charter fees are, I should say, during the define phase in the project charter to what are the milestones and shadows. You are going to clearly mentioned each phase of your project. What are the planned date? What is your actual date? If there is a delay, you will ensure the remarks I mentioned. If it's on time, you can just see everything is in order. This looks as a very simple tool, but this is the lighthouse of your entire journey of your project. Hence, do not underestimate this shadow. Now, I will help you in understanding how we build a business case. The business case is, please, in your project charter, which clearly defines why is this project what doing? What is the process that we are trying to improve? Why is it important for me to do it? Now? What are the consequences of not doing this project? How does this fit within the business or the process but priorities we have it today. Can you see if you're able to answer these few questions correctly, you will automatically develop a good business case. The next element is the problem statement in your project charter. You want to ensure that you describe what is wrong with your process. When and where did the problem occurred? You are trying to measure and tell what is the size and impact of the problem. Now some of you might have a question telling that, how can I measure the size and impact? I do not have so much data now. So do I need to collect the data before I start with the project charter? Know there will be a hint. It is said that when you are identifying the opportunity, you will have received a hint either from the survey or from some other dashboards that this is the problem. You take that number and fitted over here when you go through the measure phase and you find that the numbers are different, you can always come back to your project charter and update those numbers. Customer, be happy if they know that I'm working on this project. Can you see how beautiful is this question? Because practically you are able to tell that, why is this project important? What is the pain that we are facing and when the customer be happy by address this pin. Yes. So then we go to the next element. That is my smart goal. So what happens in the smart goal? The goal is supposed to be smart. We all are aware of this smart as an acronym. Specific, measurable, attainable, realistic, and time-bound example, reduced the transformer rejection from 5.25% to 2% by September 2022. I'm very specific that I'm looking at reduction in the transformer rejection and no other rejections in my organization. I'm currently at 5.25 and my target is to reach 2%. By when do I reach by September? I'm specific. Is the metric measure of it? Yes. Is 2% achievable? Yes. If I would have said 0%, then it would have not been attainable. Realistic to reduce from 5% to 2% by September? Yes, because I have started this project before five months or I'm starting this project in FAB and a dagger to complete it by September. Let's take one more example. Improve the productivity of the contact center team from 85% to 95% by September 2022. I have kept in mind that we have initiated this project somewhere in March or April of 2022. Right? I'm specific that I'm looking at the productivity as a metric. Within which department? The contact center D. Is it measurable? Yes. Triviality. If a person is ninety-five percent attainable, yes. Is the target realistic? Yes. Because if I would have said include the productivity of contact center 200 person, it would have not been a realistic target. Are you getting my point? If you have any questions, do not forget to ask. In the discussion section below, I'll be happy to address those wires. Input the revenue through sales of washing machine by 20 per cent. Currently we are too close in INR, right? So when you are defining your goal, your goal statement should be a one liner because that is what will help you achieve it. Here is the sample guide of the project charter. I have put up the business case. This is for a manufacturing setup. The service incident rate of ABC washing machine model indicates the machine time of failure and subsequent replacement rate is higher during 2020 fiscal year. This contributes to 40% of the overall service incidence rate. And most of the complaints are from the eastern and southern region of the country. Where did I see the problem? How big is the problem? Which department is facing this problem? I have mentioned all of it and the business case, you can definitely improve it further. But this is just a sample. In the problem statement. If said that 40% of the overall service incidents are from the timer failure for a semi automatic washing machine. I will company serves multiple products, but we are receiving service incidents from this particular model. The goal is to reduce the timer field failure of EBC washing machine model by 80% by 20th March 2021. What is in scope, semi-automatic washing machine. Out of scope. All the other washing machine and then any other electronic product produced by ABC limited. I clearly define the names of the team members, ms. Eggs, Mr. a, Mr. B, Mississippi, and so on. Financial benefit, the incoming ABC timer inventory reduction by 25 per cent leads to an x dollar saved in the overall inventory cost. The field work and part replacement reduction by 30 per cent leads to an approximately of so many dollars. You are giving an approximate financial benefit numbers in the project charter stage. Clearly defined my define, measure, analyze, improve, and control timelines. What was the plan did? And I will keep updating the actual dates as and when I progress to tollgate reviews. I hope you got an idea of what to do in the project charter. 21. Understand with more examples Lean six Sigma: Understanding the transfer function in six sigma. Let's now explore the function and its relevance in six sigma. This begins by understanding the mathematical relationship. Y is a function of X. In this equation, Y represents the output and the results or the outcome we want to improve. X represents the input variable or the pattern. F represents the function or the transformation that can be applied on those inputs. In essence, fix Sigma is about identifying and optimizing the X factor, the inputs that drive the output. By improving the Xs, we must improve the Y or we focus on improving the Y. The transfer function example in Dmth. Let's consider an example, calling a technical support to resolve a computer ratio. In the defined phase, we define a problem, how long it takes for a customer to receive a resolution. Y, which is equal to the time to resolution, O is the total time it takes to resolve the customer's issue. In the measure phase, we identify and measure the various factors involved in the call. Like the time in the queue, the time with support, the time spent transferring the calls between agents, the resolution time. Analyze phase, we determine which Xs are critical and what are the typical variations across the factors. During the improve phase, we implement changes to reduce the time spent in each step. Perhaps automating certain responses or optimizing routine logic is what is covered there. During the control phase, we monitor the system to ensure that the Y that is a time to resolution has indeed improved and stayed in cop over time. This process can be repeated continuously to drive further improvements. When followed rigorously, DMAC is a powerful repeatable methodology for achieving measurable return. Additional improvement, methodologies in six Sigma that we have pen. Sixema nan by other proven tools and techniques and practices which includes statistical process control. It utilizes Controls chart to monitor the variation over time. It uses the upper and lower control limit to identify when the process is statistically out of control. SPC tools can trigger the DMX cycle when variation and defect exceed the acceptable threshold. Variation and defect reduction tools include commonly in total quality management. They help identify the root cause, opportunities for optimization. These tools play a key role during the analyse and the improve phase of DMC. Teamwork and quality circles. Originated in Teta emphasis were based on team based approach to the process improvement. Employees at all levels collaborate regularly to solve a problem using the tools and methodologies provided in six Sigma. The quality circles often integrate statistical tools, DMAT, and DPAtRduction techniques. Next, Six Sigma projects and the Yellow Belt road. In the next section, we will discuss the Six Sigma projects and highlight what a yellow belt needs to know, including the project roles, responsibilities, and the value the Yellow Belt brings to the improvement team. Typically, the duration of a six Sigma project can vary significantly. A short term project may last just a few hours or day, especially when it is driven by small quality team aiming for incremental icuments. A long term project can span over a year, particularly when the scope is complex and cross functional. This is where the black belt comes into play. However, the most typical Six Sigma projects, which are a green belt run about four to eight weeks, allowing enough time to gather the data, move through all the phases of the DMC cycle. Teen roles in six Sigma projects. Each team member plays a distinct and critical role. Let's understand them. A master black belt and a Blag. These people are leading and managing projects. They ensure alignment with strategy and mentor the team members. Green belts. They handled a detail analytics, data gathering, and help implement process improvement. Yellow belts are the people who provide key inputs, assist with data collection, and support the implementation activity. Though not as project leaders, yellow Bells have a very essential team member role which are driving the day to day execution of the Six Sigma project. What are the common goals Six Sigma projects have? Project varies in scope and often focus on reducing variation in customer experience. In today's world, experience matters a lot. Accelerating time to market, eliminating errors and defects, lowering operational costs, some critical consideration for implementing Six Sigma and executive sponsorship and management bid. Project without strong leadership support and funding and visibility are very unlike ecofaxe. Appropriateness of the methodology. Pi Sigma is so powerful, but it is not right for every problem. Avoid a one size fits all methodology or a mentality. Start small and then scale. Build confidence and skills that are smaller manageable projects before taking up a broader transformation effort. Do you know when to use other approaches? In some cases, alternative methodologies can be more appropriate. Lean initiative, Business process reengineering, we call it as BPR, Business Process Management or BPM. Or the other methodology which can be used. Scope control is very important. If the project scope is too broad and it lacks a clear outcome, it becomes unmanageable. Cost versus benefit. Consider the ROI before investing time and resources. Example, spending 100 hours to save only 10 hours annually is not an effective trade off. Conducting a readiness assessment before taking up a project is very important. This helps your organization's preparedness before we dive into picking up a project. Define the desired outcome. What are we trying to achieve and why? Establish a success criteria. What does success look like for both the organization and the individuals involved? Evaluate the data availability. Do we have reliable, relevant and timely data to support analysis? Assemble the right team. Do we have people with the skills, influence, and commitment to make the product successful? Build a business case. What is the value of improvement? Who tends to benefit and who might resist? What's the expected ROI? Assisting the organizational readiness is very important when you plan for a six Sigma project. Are these key questions because they are very important. Is, how does the future state look like compared to current situation? Are we solving a real life problem in our business? Is now the right time to implement Six Sigma? Carefully assessment ensures that the six Sigma project is not only relevant, but it's also achievable and impactful for our organization. Are we evaluating the performance? Do we have a strong rationale about applying six sigma in our business case? And finally, is there something else going on in your project that needs your attention? In Six Sigma, is there actually right approach? These questions can be certain that our organization is ready for six SEMA for a given problem. There are three key steps to assess the organizational readiness. Step one, assess the outlook and the future path. Ask the question, I chain critical? Business need it right now. Evaluate the current performance. Ask the question. Is there a strong strategic rationale for applying six Sigma into our business? Review the systems and the capacity for change. Ask the question, can the existing improvement deliver the level of change needed to keep us successful, competitive without using six Sigma? To get started, consider the importance of customer experience, customer satisfaction. We're focusing on voice of customer to drive change. Improvements are essential and customer needs them. This is where six Sigma data analysis tools come handy. It helps us in understanding how the customer truly cares about. Six Sigma provides powerful tool, future strategic planning by improving marketing effectiveness, getting things right the first time and identifying what really matters to the customer regarding our projects and services. One such valuable tool in six Sigma Toolkit is the CO model, which helps us understand and prioritize customer needs more effectively. The CO model is a method for gathering data from customers and understanding what truly matters to them. What differentiates our offerings from the rest? It helps us in identifying important things like what are the features that can increase customer satisfaction when delivered well attributed to the customer. What are the potential dissatisfactor that could harm the customer experience if not address? By analysing these feedbacks, we can prioritize improvements that can create greater value for our customer. Now, let's consider strategic planning. Six Sigma analytics can play a critical role by identifying key factors driving customers. Customer satisfaction, integrating them into strategic planning. Performance improvements are most needed. I an organizational culture part of a standard approach of TIC Sigma through effective project chartering, metric development, control systems, and quality circle teams can significantly enhance performance alignment across the organization. Profitability remains a top priority. Six Sigma is specifically effective in reducing cost of quality. Many organizations spend 20 to 75% of cost simply ensures quality in products and services. By lowering these costs, we stay closely aligned with customers expectation and consistently deliver better and faster than our competitors. Okay. Concept of len. Lean manufacturing, particularly in a service sector environment means recognizing continuous improvement initiative. At its core, N focuses on streamlining and enhancing processes to create more value with your resources. TahiOo often regarded as father of modern lien thinking, emphasized that the essence of lien lies with one simple principle, calculated time from receiving customer order to receiving the payment for fulfilling it, and then work continuously to make that time as short as possible. Len is fundamentally about eliminating waste across the entire value sting, reducing unnecessary time, effort, and resources. The result is to maximize value, improve efficiency, better quality, and higher customer satisfaction. In a manufacturing setup, an success stories are many. Currently, we have a lot, even in the service sector. 22. How to find a Project Defining the Opportunity for Improvement: One of the major problem which the Six Sigma professional are many students who come to me for training have experienced this. How do we identify a project? I cannot find a project in my workplace in my company. Six Sigma is not very strong around the first person from my company who's going through the Six Sigma training. And I don't know how to identify the project. This video or this session of the course is focused about how do you define an opportunity for improvement and what could be the steps that we can take for doing this. The improvement opportunity that is identified will ultimately define your project. What is broken in your process, how often it breaks, and the impact on the customer and the form. As a project owner, you will need to ensure that the opportunities has the characteristics required for a great project. What defines a great project? The opportunity has a clear boundaries and measurable goals. The opportunity that you have identified is aligned with the business critical issues or initiatives with the businesses driving. Suppose, if the business is thinking about robotics, process automation by 2020, then your process of identifying an opportunity could be any process where it's highly manual so that you can pick that up and go ahead. If your project, if your business initiative is about ensuring that everything is on one platform, you can find something where you have processes which are on different platforms. So depending upon the business critical issues or the initiatives with the businesses driving, you can identify the project. What the customer will feel about the improvement is an important question which you need to answer. That will the customer feel happy that, Oh wow, you're working on this project. Or he feels that why do you I don't even care if you do a process improvement over here. If the answer is the second one, then you should not be working on this project. Now the most commonly asked question is, how do I find an opportunity for improvement? 23. Voice of Customer Practical approach: The first important to, during the define phase is the voice of the customer. What does the customer need? Sometimes the customer explicitly mentioned what he needs, and sometimes it is implied and we need to understand what exactly he needs from our product or service and how well the process meets those needs from the point of view of the customer and not from our point of view or the process point of view or the business point of view. To understand this, we can use some of the tools and techniques which can help us get what is the point of view the customer has and what are his needs. We may get involved in direct discussions are in W with the customer to understand what. We might sometimes roll out a survey after we send the product or service to understand what he or she needs, we should regularly check the complaint box to understand. Are there any concerns because of one bad customer expedience will ensure that our 100 of your good customers you're going to lose. So regularly checking your complaint box is also very important. If suppose you do a direct discussion and there are no complaints. Testimony is very happy. You rule out a survey. You get very good survey results. You go to the complaint box and there are no complaints. It does not mean that you should sit back and relax. You should keep looking at the benchmark, what the market is doing within my industry and other industries, which can create a thread. Is the customer moving away from me toward somebody else? That could be analyzed through the bench marking exercise. Hence, it is important for us to do this VOC exercise very diligently. Now, most of us also have a problem that how do I define an opportunity? I will identify a project. I'll be continuing with that topic in the next chapter. 24. SIPOC: The third important tool during the define phase of the DMAIC life cycle is SIPOC. Some people also call it as Scopus. It's actually the reverse of SIPOC is COP IS, do you call it as a SIPOC or a coop is the output diagram will be the C. Sipoc is actually an acronym for suppliers input, process, output, and customers. This diagram is a visual tool for documenting the business processes from beginning to end. The SIPOC diagram is also referred as a high-level process map because they do not contain much detail. The reasons I book is created is it will help you set the boundaries for your project. Though it looks as SIPOC or some people call it as Scopus. The first thing which I do out of my practical experience is that I fill up the process steps first, which would be in maximum of five to seven steps. To do this process, what do I need? I fill that in my input. Who is going to provide these inputs? It is my suppliers. From this process. What are the output did I receive? And what, who's going to consume that output is my customer. Now you need to understand those SIPOC looks like a very simple tool. It helps you have measurable metrics because your process can have some KPIs. Your output can have some requirements or specifications given by your customers. Your inputs need to be exactly in the same requirement that the process needs to ensure that this output comes out where you have some measurable metrics. You also get to know who's going to supply and who's going to consume. So when you build your SIPOC and show it to your stakeholder, he can clearly identify our contract is coming to an end with a particular supplier. It will help you address the problem at the very initial stage. If suppose the project scope is too wide, number of customers might be too many or too many outputs are present, then it will be easy for you to visualize who is the scope manageable? Or if you stake holder fields that these are the set of customers who might do not want to focus at this point of time. I think the scope is increasing. We need to divide it into two separate projects. We will be able to do that. Let's take a sample sidebar. This is very easy. I'm going to prepare some pizza favorite, right? So I will go into first fill up the process steps. So at a high level, how do we make a pizza? You prepared a doubt. You add a source at toppings, at cheese bigger than the old one, removed and package it. To do this process, what are the inputs that you need? I need I need sauce, pepperoni, cheese, and Peppers. Who's going to supply me this input is my grocery stores, dairy farm and vegetable farms. From this process, what is the output that I'm going to receive? It's nothing but my whole pizza. And then I'm going to get them into pizza slices. Who's going to consume it? Either the customer may decide to dine in at my hotel. They might be a takeaways and they could be ordering for home delivery. This looks as a very simple process. You can see that I'm not specifying how should be the texture of the dough. Is the person ordering a thin crust pizza or the normal hand toasted pizza? What type of sauces He wants? Easy looking for a pure veggie pizza or a cheese pizza, or a mutton pizza. We are not specifying what type of doping it is. The process is kept at a very high level and simple, right? If it is a three types treaties, visa or a margarita pizza, if you're in India, you have three types of pizza and they might not require any peppers and so on, right? So you are defining your process at a very high level and specifying the inputs and suppliers. You're not going to specify what is a baking oven temperature for how many minutes do I need to bake it and so on. Over here. All those things we're going to do when we do a detailed process map during the next phase of our project, that is a measure phase. This diagram, when I show it to my staple that along with the project charter and the CTQ, the stake holder will be able to see, oh, you're only focusing on the Piazza park, whatever the cupcakes that we are selling. So you can clearly see it is out of scope. So a quick recap. How do I build this SIPOC or coppice? I begin with the process, define the process in general terms at a very high level. I specify the start and end. I list outputs. In this process, I specify our identify the customers, including internal or external customers willing to receive this output. I list down the inputs required for this process. Identify the suppliers who are going to provide these inputs. It is a very simple tool and a very powerful tool. You can clearly identify what is in scope, what is out of scope. Some of you might say that I have already written this during my project charter stage. Do I need to write it again? Yes. You need to write it again because you are reinforcing the fact that what is the scope of your project. So all the three tools we are going to use during the define phase are mandatory. Like the project charter, the CTQ tree, and the sidewalk. You are free to add one more tool which is a RACI matrix, which we will be covering later on. 25. Kano: I just explained you conceptually. How do I identify projects? My internal stakeholder from external stakeholders, what questions I asked and so on. Now, I will show you a tool which will help it and make it easy for you to identify a project. There are multiple tools. You have project selection matrix. You will have the other VOC techniques that I had told you earlier. Sometimes we can also use Kano model, which will help me identify a pain point that the customer is facing. In the model. You can see that I have on the lower left corner, the must-haves in the middle as a green diagonal line, I have one-dimensional desires. And on the left top corner, I have the delighters or unexpected unknown things. You, before I even get into those three, I want you to understand. My x-axis is about how my job is done. The x-axis on the right side Does that the job is done well. And on the left says that the job is not done well. The y-axis is how my customer views. As my customer feels satisfied, it goes up, and as my customer feels satisfied, it goes down. Now let us understand what is a must-have or unexpected quality requirement which your customer might set up. These are those needs which the customer has, which he has not spoken about. These are taken for granted and spoken if not met. The one-dimensional type of metrics are these are the desired quality metrics with the customer has specifically asked, he has spoken to you that I need this. These are something that are measurable and it gives them a range of fulfillment that Yes, Good, I bought this product or services. When you look at a delighters, these are something that are unexpected, unknown features of your product or services. Nobody has spoken about it. Nobody was expecting this to happen and they are unknown to the customer. So what you see is that even if you do your job really well for must-haves, the customer is never going to reach the satisfaction level. Our image just as to satisfy can because that's your job. That was was required. So let me give a simple example. If I'm going by a flight, Do I have to ask specifically that the flight will take off on time? Will they allow me to 15 gauges of baggage? Would they allow me a handbag? No. These are some unspoken needs and they're taken for granted. Yes. If the flight is mentioned could be departing at seven AM and reaching the destination by say ten. It should be around the same time. Because if the flight is delayed, we are going to be unhappy. So the characteristics of a must-have is they are spoken if they are not met. Do you know last time when I went by an XYZ airlines, it just kept me at the airport for three extra hours. All my day was plan, did not go. I missed my customer meeting, etcetera, etcetera. Does the customer asked you that will the flight depart on time? No. These are unspoken requirements. These are taken for granted requirements. If you don't, you have to do these requirements and ensure that all the metrics relating to this are met. When I look at the green line. These are one-dimensional design or activities or desired quality characteristics or CTQs with the customer has. In the flight, I might say that I need a business class ticket. I'm willing to pay for it. I need a sandwich because I have paid for it and I've booked it. I need more space and I'm willing to pay extra $50 for the extra space at the beginning or in the middle and soar. The customer has specifically asked, I need extra speeds. I need a particular food because in India for the domestic flights you have to pay to, you consume the food. For example, I need extra baggages and you are going to charge me, say, 300 Indian rupees for extra KG of packet. So I see I have extra luggage. I want to book 50 cases of extra luggage, right? So these are something that the customer is specifically asking. They are measurable and the customer is also willing to pay for it. Now suppose I have booked my flight ticket, saying that I need some extra space with some extra baggage. I have paid that extra money to the airlines and my night reach the airport. The flight officers and the crew members tell me, I'm sorry. The seed is not available. We will give you a normal seat. I will get unhappy if the job is not done well, there is a drastic reduction in my satisfaction level. If the job is done well, I booked for it and then it was seamless SSO I get into when the job is done, when I get into the satisfaction zone as a customer. So these are one-dimensional arrays. These are at metrics which are desired quality characteristics of the customer has from the product or service. Now let's understand what are delighters? These are some unspoken needs of the customer. So let's assume that I read the book, my flight, I reach the airport, I got into the flight. The lady over there Give me a bouquet of flowers and a small gift. I was not expecting it. Did I ask for it? No. When I received it, do the gift was something that I may or may not use at first, very small, maybe just a $5 or some 500 rupees. I would feel very delighted, you know, last time when I went for the flight. I receive this as a complimentary gift. They buy, just give you something, a pen, or a small toy for your kid who's traveling with you. These are something which you are not expecting. Even if it's something which is very poorly done, the customer feels delighted. Now how do we help me in identifying the project? Let's take an example of the conference room booking. Let's assume that I was not taking this training online, but I had planned for meeting or further training in a conference room in one of the five-star hotel. What are the must-have requirements? The easy in the conference room should be appropriate. They should be comfortable. Ct because of my workshop is going to go on for five days, for eight long hours, every day. These are some expected needs. What if I go to the conference room and I find that those guys have said that for each extra chair, you need to pay some amount. I really beat the satisfied I said when I booked the conference room, I'm expecting you to give seating for my audience. Right? If the EC is not working or if it's too hot or too cold, it's not acceptable and get upset because my customers are my participants of the conference. I'm not comfortable. These are some must-have requirements which needs to be as per the requirements, what the client needs. Even if I'm not going to ask, they should know that it should be. These are some basic things. When somebody's book in the conference room. The desired objectives of my conference could be that I need a strong Wi-Fi connectivity because I'm going to ask participants to download the dataset and I'm going to make them submit their project work, etc. I will say that I need a strong Wi-Fi connectivity. It's because it's not a speech, but it's an educational workshop. I need a strong Wi-Fi connectivity. I need a projector, which is an LED format because even the participants who are on the backside of the conference room should be able to clearly see the presentation that I'm showing. When I do this, leaves the conference room and I find the Wi-Fi is not working. I'll get this satisfied as a customer. If the Wi-Fi is working as expected, I'll say Yes, I'm happy. They have arranged for the LED what I asked for and be happy. But if this is sorry, ma'am, We forgot the LED. I will get the satisfied. I even say very clearly, I had very clearly instructed you that I used to things and I was also willing to pay for it, and so on. Right? What comes out as a delight is that I was not expecting them to give a free valet parking for my participants. So not only did they give free valet parking, which met them, which made them feel Royal. They also give a customized coffee mug which had the imprint of the participants who were coming for this conference. I was also not aware that he's going to give a customized coffee mug. He just asked me, can you give me the names of the participants who are going to attend? How many of them? I said, yeah, this is a list. This other 25 parties tend to overlook come. And then he had ensured that he goes to LinkedIn, finds the picture in, prints it on the coffee mug, and gave those customized coffee mugs to my participants. Now there could be an instance when one, the person who was mentioned in my conference was not easy to be traced on LinkedIn or his photograph was not good for that customized coffee mug. He just mentioned the name of the customer and gives it to him. He's not done a great job. But still I will be satisfied because I may also, my participants will be satisfied because they've never expecting that we're going to get some customized coffee mugs with their photographs and needs and printed. Right? So these are some delighters, even if they're not done. So when the customer is going to be in the satisfaction Zoom. Now, apart from these three things that we just learned, that is the must-have characteristics or must be characteristics which are your expected quality requirements. If they don't do the job, when, if it is not a job which is fulfilling, there is extra dissatisfaction if they do it extremely well. Also, the satisfaction does not go beyond a particular level. The one-dimensional blue line, as I just expected, these are some desired quality which the customer has. He specifically asked for it and he needs it. So if you do it when the customer is happy, if they don't do it when the customer is satisfied. The green color line or your delighters. Even if they do it well or they don't do it when the customer is already in the satisfaction zone. If they do it extremely well, the customer is on the top of the world. Now, apart from this, you might see a Greek and other languages and indifferent characteristics. Their presence or absence does not cause any difference towards the satisfaction level. Can you guess what could be the indifferent characteristics in my in any project or in any process. Then you see a purple line which is a reverse. Their presence cause dissatisfaction and their absence will keep the customer in a satisfaction zone. And give you an example. Suppose there is a pest in the conference room. The presence of a pest is going to cause me dissatisfaction and it fits the best free, it becomes a satisfaction. So those are some characteristic which should not be present. Our example. They have opened the windows of the conference room, which makes the direct sunlight come inside. Now because they have kept the windows open. Technically, keeping the window opens a good thing, right? But because they keep the windows open, people are not able to see my slides properly. They're feeling very hot and they're getting distracted because they're looking outside the window. Presence is causing dissatisfaction and absence is keeping the customer satisfaction zone in the front? Could be. Yes. So whether they are present or not, it does not make any difference. I would invite you to type some examples of what are the must-have characteristics? What are the one-dimensional characteristics? What are some examples of delighters that you have seen when you are consuming or using some product or services. Some indifferent characteristics and some reverse characteristics in the discussion section below, which will help me understand they do understand this concept or not. Now, let us understand how do I identify a project using the scanner model. If there is a problem with any of your must-have requirements, that is definitely your first list of project ideas. Let's assume all your must-haves are being met and the customer has no components, are no concerns regarding them. Then you go towards the one-dimensional aspect where you see that, okay, if the customers are asking for these 34 days or these ten things, are we able to meet it or not? Yes. Out of the ten requirements the customer has most of the time two requirements, we always get complaints. So those could be your project identification ideas. Once you are satisfied about having a must-have in place, you're one-dimensional, then only go for inventing some desired characteristics. Please do not think about delighting something to the customer without having your must have in place. Let's keep the house in order. Before we go for designing some delighters for the customer. You must ensure that the reverse characteristics object of opportunities, are not there in your process. Orders that could also be an opportunity for improvement. With that, we come to the end of the model. I'm going to show you some samples which can give you an idea of what are the threshold attributes, what are the performance attributes and what are the excitement attributes? The must-haves are also called as threshold performance attributes or your one-dimensional and excitement attributes are your delighters. This is about an airline model pre-COVID. Now, the second exercise mute I give to you is to identify each of these items and write down in the discussion section below that, what do you think automatic channel scanning on a TV. Is it a performance glider on must-have? I will be looking forward to your answers in the discussion section so that we can I can understand whether you understood the concept clearly are not. 26. CTQ Tree: We understood what is critical to quality. Now, unimportant note the most important attribute of a CTQ that it may be, it must be translated directly from the voice of the customer. And it must give an unbiased view of what the customer needs. So it is not what you think, but it is about what the customer feels about you or your product or your service. Customer needs mapping for a bank. Let's take this example. Suppose the voice of the customer sees, I'm confused about how to sign up for an online banking. This is the problem or this is the complaint that he's making. This service or quality issue is that the access to the online banking is unclear. Do you understand that? Exactly? The customer need is can I get a simplified online signing up process? So if I have to pick a project on this, the output characteristics should be the minimize the number of steps required for signing up. Are you understanding how do I convert a VOC into a CTQ? Let's take a look at the template more easily. So when you do, a customer needs mapping data, four key elements, the voice of the customer, exactly the way the customer has said in his survey, in his interview, in his interaction with us or in the complaint mailbox week, picked that up and write it down. We try to understand what is the service or quality issue the customer is facing. Then we can work them into what does, what does it need the customer has what is the thing that the customer wants us to fix? And can I can work? Because customer always is talking about something which is soft. Then I tried to convert it into an output characteristics. I can give you a more easy template for you to relate. You can put that up in the CTQ drill down tree. The client is satisfied. So once I have my previous template ready, I can pull up and pick this and put this up for my CTQ drilled out D, which will be an output during the define phase. So my client is dissatisfied. Why is it a satisfied? Because he has concerns with accuracy. What type of accuracy? External accuracy. That's my output. So it is the external accuracy. What is your project? Why the project? Why is external accuracy? What is the target that I want to achieve? My monthly external accuracy should be greater than equal to 95%. What is the lower specification limit the customer has said? The customer sees that the lower specification limit is 95 per cent. Avoid obviously sky is the limit. So sometimes a customer might give you a specification which could be one-sided defect definition. So the effect is equal to the external reward. Right? So that is how you can put up a CTQ drill down. For ease, I am sharing this template with you, which you can use as a reference and you can plug your values during the yellow or green belt or a Black Belt project. The project charter, the CTQ tree and SIPOC template will be seen in spite of the fact that your project can be as simple as a yellow belt project or as complicated as a Black Belt project. Right. So you ensure that the CTQ drill down tree tells you why is the need the customer has on what is causing this satisfaction to the customer. And on the right side, you break it down into the output characteristics, your project. Why? What is the target? What are the specification limits, and how do you define this as a defect? With this, we come to the end of CTQ tree. We will move into sidewalk in the next lesson. 27. Types of Waste TIMWOODS DOWNTIME: We have been constantly working on learning the concepts relating to Lean Six Sigma. As we can see, though this concept of Lean Six Sigma is centuries old, are at least I should say, it's 300 years old. The evolution we had seen in the history of Lean Six Sigma. We need to now go and understand one more tool that we use during the lean. That is the eight types of ways that we identify. Some people call it as Tim woods, and some of them also call it as downtime. Let us investigate each one of the waste. The first T in the ten words is the transportation waste. Do you know when you're moving items or information in terms of a service industry or moving items for a manufacturing setup, you are spending time, energy, and effort. Why cannot we have everything at the right place? Can I avoid transporting the items or can I minimize the moving of information from one mailbox to another? Which can make it easy and faster for me to do the process. If there is transportation in your process, it is one of the types of waste and your objective is to minimize the transportation waste. Because products get damaged when they're getting, when they are in transport. Information might get lost because it's in between the two mailboxes are two different cues. There is an opportunity for minimizing the transportation waste. You must try to address it. The next letter in the timbre is I. I stands for inventory. Inventory is nothing but the items and information that the customer has not yet received. It is lying in your warehouse or somewhere within your factory or between your factory and your customer. In terms of a service industry, what is an inventory? It will be those extra reports, extra processing, your application forms which you have processed, but the customer does not know the status of their application. And those application, those papers are just floating around in your office or in somebody's desk or somewhere in-between. Either they are in the transport and so on. Inventory happens because of the other type of waste, which is overproduction, which we will be covering in few minutes. The M in timber stands for motion. Motion means excessive movement within the workplace. The difference between transportation and motion is the transportation is about moving of objects, items, or inflammation. Whereas motion relates to the operator who is working in the office. Do I have to continuously move from one place to another within my office to ensure my work gets done. Can I rearrange my office space in such a way that may motion can be reduced because if I'm continuously moving, maybe I get tired by the end of the day and I'm not as energetic and productive as I required to be. I might decide to skip some process because I'm very tired. So can I have my process my floor arranged in such a way that my motion is minimized. Let's give you a one more example. In a service sector environment because it's easy to visualize and a manufacturing setup. I sit on the first floor, the printer is present on the second floor at the right end. I give a printout. I need to immediately rush from the first floor to the second floor to pick the printout from the window. Otherwise, it is a confidential information and can cause a problem. Even if it does not confidential. It is some information which I needed it, right? And suppose I am giving ten to 12 prints or the blue feel that I should relocate my desk to the second floor or relocate the printer to my flow, which will ensure that this motion waste can be reduced. We will be seeing many more examples as we go further. The M stands for the waiting time. Sometimes we are waiting for the information to arrive or the raw material to arrive are some semi-finished product to arrive for me to continue with my production operation or to continue with my service work. So hence, we should eliminate the waste. Processing. Overprocessing is doing the work more than necessary. I have already cleaned the table or I have cleaned the item, but I'm redoing it thinking that, Oh, it will shine. I have already verified the process, but I'm redoing it because I don't want my boss to find an error. How can I apply the Poka Yoke key techniques in such a way that I don't need to work process. And still the processing is perfect without any errors. That will be your responsibility to identify. The next row in ten words, East oil production, doing more work before it is needed. If I'm thinking that the next month I might have orders for 10 thousand units, manufactured 10 thousand units, this one. It might result in the inventory waste as well. Or production leads to inventory. And it is blocking your capital resources, your space, and all these things in a negative manner. Hence, we should avoid or production. If there is a demand, we should actually make it to order. You have the example of Dell, which makes the laptop to the order of the customer. It doesn't start the assembly till the time the customer does not place the order. Still, they have made the process so that they're able to deliver the laptop at the specified delivery timelines. The inventory in that process is very less defect. Defect is the mistake or the error that needs to be reworked. The product is damaged or I haven't verified the application form correctly. If there is defect in the process, it is waste of resources because the first time you were trying to do it, there was a problem and hence you have to redo it. Why can't I have a technique or a process in place which ensures that the defect does not happen. We have to get creative with our solutions. The S in the ten words stands for unutilized skill set. Skin set, which are not matching to the cast, to the employee's ability. If I'm not able to utilize my employees to the fullest, there is a thread that I have. They might either get demotivated or they might decide to leave my organization and go somewhere else. Hence, it is important for me to remove the skill set waste from our process. So to summarize, what stands for transportation, inventory, motion, waiting, overprocessing, overproduction, defects, and skill set. Our objective would be to minimize or reduce this waste or completely eliminate them as much as possible. 28. Current State: Yeah. Toast done. Oh, thank you. Why are you serious? As raisin toast. Plus, that's burnt. I only one to two pieces. What 29. Types of Data: As we increase our awareness towards type of data, towards six sigma. Understanding the concepts of type of data is very important because when we look around, we collect data which are of different datatypes. Sometimes the datatype is qualitative. I'm very happy. This class is good. Assignment was difficult. I did not like the movie. Now, can I say How good was it? How difficult it was? It? Was it bad? How bad was it? Can I measure good, bad? And all these elements, because these are emotions. These are definitely representing what the audience's feeling, but it cannot be measured. And in Six Sigma, we very well believe that what cannot be measured cannot be improved. As these elements are qualitative. Be, will not be. We will try to convert them into quantitative. Let's take the example of quantitative data. When we think about quantitative data, there are two types of data. One is discrete data and other is the continuous data. Let's understand what is discrete data. When we think about discrete data, these are the data points that I can count, but I cannot divide. If I ask you, how many members are there in your family? Even though you might have your grandmother who is 90 years old, or you have a small kid at home with just a few months or few days old, you cannot count somebody as a whole and somebody as 0.02. Hence, you see, there are five people in my family. Are there are three people in my family, depending upon the count of the people. If the baby is two days old or your daughter is 20 years old, you never count them as 0.0, 220 or something like that. Things like this will be counted and hence they are treated as discrete data. I'll give you more examples. How many laptops do you have at home? You can count, even if to work, laptops are not working. You might say that I have five laptops at home. What not working and three are working. But can you say because it is working partially, I will treat it as 0.5. No. Hence, discrete data, those data types which are used for counting, I cannot divide it. When you have discrete data type, the type of graphs will be different. You cannot use a line chart or a continuous data chart. Whenever you're doing discrete data, you might want to do a count plot, a bar plot where you have frequency on one side and the categories on the other axis. This will make it easy for you to represent the data on the graph. Let's come to continuous data. When we think about continuous data, these are some things we can measure. I can divide it. I can measure it to the accuracy of the last decimal point, e.g. if you ask me how much of raw material was sent to the factory, I can see it was three-tenths. If you tell me can you tell me exactly in how many cages was it? I can move the precision of telling that it was 2,743.23. I'm not really measuring it in kilograms, but I'm also in Proving Grounds. Suppose I'm doing a reaction in a chemistry lab. I need to put the catalysts, but I need to ensure that those are sent only in milligrams. Can I measure it with that accuracy? The answer is yes. Hence, continuous data are those data points which are easy to measure. I can measure it in higher unit. I can also measure it in lower unit. I can divide it endlessly to get the accuracy that I need. I can measure time in light-years, in calendar years, in months, weeks, days, hours, seconds, milliseconds, nanoseconds. Hence, I'm able to measure this data divisibility. And I can easily divide this data and I will go to another unit of measurement, which is only increasing the precision of my. Hence it remember, whenever we pick up a project, we ensure that our data is either discreet data or continuous data. Sometimes we Rollout Service. So when we roll out surveys, we want to ensure the data. I know it's the quantity. Did you like the service? But what do we do? We try to convert them into a five-point scale, 1-51 being pool five, being great experience. So what happens is the user is trying to put one of the tick mark at either 1234 or five. Hence, it's important for you to understand that a qualitative data needs to be converted into quantitative data. And then only I can pick up an improvement project. We will continue our understanding in the next lesson. 30. The 5 Whys Explained Root Cause AnalysisPart1: Let us now understand the phi by techniques. It's a very important technique when it's come to a process. Dora. I'm going to cover using this radio animated video of what needs to be done and what can be avoided. Let's get started. Have you ever experienced a problem that kept recurring? Addressing a problem or failure mode more than once as time-consuming and a waste of valuable resources. The issue is that the root cause isn't being identified or addressed. If you're not getting to the root cause, you're merely treating a symptom of the problem. In addition, if a permanent remedy is not determined and implemented, the problem will eventually repeat. However, and easy to use tool can assist in eliminating repeat problems. This tool is the 5-Why and five how unpredicted problems might occur in any team or process. However, issues are just symptoms of deeper issues. Fixing a problem rapidly, maybe a convenient solution. However, it does not protect your work process from recurring errors. This is why your team must concentrate on identifying the root cause and tackle it properly. The Five Whys analysis, often known as the root cause analysis, is one of the seven fundamentals used in Six Sigma. The principle idea behind the tool is that there is a cause for every effect. Therefore, the quality issue can be viewed as having multiple causes. However, it is additionally known that there's a series of reactions called symptoms before the cause reaches its effect. Therefore, if the management can pinpoint and solve the problem from its root cause, considerable advantages would be gained. Every team encounters roadblocks and it's daily work. However, using the five whys will assist you in finding the root cause of any issues and protect the process from recurring errors. 31. The 5 Whys Explained Root Cause Analysis Part2: Hello friends. As I have decided to make this program a complete program. And some of you had written some questions in the discussion section. The limb that you would like to know more tools about the process door approach and the data. To the tool that I'm going to take up in this video is the 5-Why Analysis. I'm going to dive deep into it. And before we go further, let me just do a quick recap that whenever we are trying to solve a problem, we have two approaches. One is the process door approach and other isn't Datadog. So we have seen multiple things about Graphical Analysis, different types of graph hypothesis testing control charts. All those are part of data adorable in process due to uproot, it's highly based on the Lean skills. There. We are trying to understand the process by asking questions and not focusing much on data. But as we are part of the Lean Six Sigma journey, we will try to leverage the numbers as well as the questions in the right format. So let's get further. We want to understand how should I do if I buy? And we all know that we love to ask questions as good. Let's go further. So the phi right technique was created in 1930s by shocky, the Japanese manufacturer, inventor and the founder of the Toyota industry. It has become very famous in 1970s and Toyotas still uses it to solve the problems today. Not only to eta, I would say everybody is using to solve this problem today. One of the essential variable for a successful implementation of a technique used to make an informed decision. This implies the decision-making process should be based on an insightful grasp of what actually happens on the workflow. What is 5-Why Analysis? Bye-bye. Analysis is an iterative process where we're trying to explore the cause and effect of relationship with the underlying problem. We always believed that whatever you're seeing as an effect, there is an underlying root cause. And we want to understand how that cause is causing an effect on the output. The primary objective of this technique is to determine the root cause of the defect by the issues are issued by repeatedly asking the question, why, why is it happening? Why is it happening and why is it happening? Why is the name derived from the recounted observation of the number of hydration to resolve the problem, If one wishes to reveal multiple root causes, the method must be repeated, asking a different sequence of questions each time. We will be seeing the examples also. What is fiber analysis? Let's dive more deeper. Method provides no rigid and fosters that. What should be the lines of questions our investigation and how long should we proceed in search of the original root cause. Consequently, even when the method is closely followed, the outcome still depends upon the knowledge and the persistence of the people involved in that room. For the discussion. The primary objective of a phi y is that it is one of the most powerful assessment methods of all non-statistical analysis. The process door approach. It can uncover and trace back to the problem that was not very obvious. When applying the fibroid technique, you'd need to get to the problems and fix the root cause. The 5-Why me demonstrate to you that the sources of the problem are quite unexpected. Often the issues considered as a technical problem turns out to be a human or a process issue. Therefore, finding and eliminating the root cause is crucial to avoid hydration or failure. Asking why or more times? The first time we say gather your team. The second important step is to define the issue. Ask the why. Ask the why four more times I know when to stop, address the root cause and monitor the measures. When we're doing the 5-Why Analysis. The step number one is to gather our team. The phi way abroad is not an individual based activity. In fact, most of the Lean Six Sigma project activities or a group activities and you as a project lead, have to be a good leader in communicating and getting your team together to contribute to your project's success. So coming back, they tend to gather a team of people from various departments so that you can get a cross departmental view. Each representative must be familiar with the process that will be investigated. By forming the functional team it requires. It will provide you a unique point of view for all your issues. This will help you collect sufficient information to make informed decisions. Keep in mind that this is not an individual tasks. It needs to be executed by the The second step is to define the issue, discuss the issue with the team and make it concise problem statement. It will help you categorize the scope of issue you will be investigating. This is very important step because if it investigates the wide scope problem with a hazy boundaries to be as concentrated as possible and find the dynamic solution in the end. Ask why. That is the step number three. Now, it's time for your team to inquire why the problem is happening. These questions need to be addressed. Concrete problems, not just the theoretical problems. Look for answers that are grounded in the fact that we must be recorded of things that are happening and not Quest at what might have occurred. Ask why again, that we Let's continue with the step number three. These blocks of phi y's are becoming just a process of detective reasoning. Why did it happen? Why did it happen? And generating many possible root causes and sometimes creating more confusion that you're chasing down the critical issues. The facilitator should inquire why as many times as needed until the team figures out the root cause of the initial issue. This is a very critical thing. Do we call it as a firewall analysis? In recent times, we have renamed it as YY analysis because we might get to the root cause after seven or eight y's. Sometimes we get to the root cause after the third or the fourth way. So it's not compulsory that you should stop after five. You should go till you reach the root cause of the issue or the problem that you're trying to solve. Ask why. Advise one. Don't ask for excessive numbers of Y. If you keep going, you might end up getting tons of unreasonable citations and complaints, which is not the purpose. Advice to the five-year analysis will resemble a matrix with various branches in these circumstances. This may even help you identify and eliminate organizational issues. Ask why four more times. Asking why four more times and get the answer as a base for your question. This is an important way of forming your questions. You will have five reasons for each y and the questions whenever you have done this. As previously mentioned, you might need to ask why more times than phi if you haven't got to the root of the problem. Step number five, know when to stop. This is very critical. You will know when to stop asking by. When asking these questions no longer produces good response. On the off chance that if you haven't gotten to the root cause of the issue, you might need to consider a more in-depth problem-solving method like FMEA or Fishbone, Ishikawa diagram or cause and effect diagram. If you have received more than one causes in the step number three, repeat the phi y for each of these as various branches until one root cause for each of the issue has been determined. It is also important to ensure you haven't stopped too soon or aren't just accepting a knee or a job or gut reaction. This is very critical because you feel or too much, it's too much. Let me stop. Are we are we are given this answer because this is what we were expecting. Then also, you're not going to get the benefit. Please take it to the point where the team produces no reasonable response. The root cause. This is a very critical and important step in the 5-Why Analysis. It's not only about identifying the root cause, but you need to address the root cause, which many of the times our people do not. Do. They say, okay, we found this. And then they go with their own gut feeling approach to solve this. The correct way is whenever you have identified the root cause of the problem, the Internet team should discuss the list of corrective actions. Our counter measures to prevent the problem from recurring. The five-year master should then assign which he members should take responsibility for each team on the list. Monitor your measures. In conclusion, to record your findings and distribute them throughout your organization so that everyone can learn from this particular case study. Best practice sharing is a very important step in all, in your Lean Six Sigma project journey. Again, if this happens, it's a good idea to repeat the five-step process. Ensure that you have identified the root cause. When should we use the 5-Why Analysis? And let's continue further. When you use vi vi for quality improvement, troubleshooting, and problem-solving. But it's most effective to result's simple and moderately difficult problem. If it's a more complex problem, you might have to go through FMEA or hypothesis testing to be more concrete about the solution that you're going to find. The root causes that you're going to address. However, it may not be suitable to tackle complex and critical issues. This is because five, I can lead you down a single track or a finite number of tracks of inquiry when indeed when multiple causes. Extensive methods such as cause and effect analysis. Failure mode effect analysis may be more effective in cases like this. Whenever simple technique can often direct you quickly to the root cause. So whenever a process or a system is not working perfectly, give it a short before you embark on the more in-depth approach. And certainly before you try to develop a solution, the simplicity gives its high flexibility to the phi bi combines well with all the other methods and techniques such as root cause analysis. It is often associated with lean manufacturing, identifying and eliminating waste practices or non-value-added practices. The fibroid technique is a simple and powerful tool. The main goal is to track down the exact reason or the root cause of a given issue by asking the sequence of why questions. The 5-Why method is just your team to focus on finding the root cause of any problem. It encourages each member shared plots of continuous improvement rather than accusing others. Gives you your confidence so that it can eliminate any issues and prevents the process from recurring failures. The two main techniques are used to perform 5-Why Analysis. The fishbone diagram or the tabular format. Let's try to understand the fishbone diagram technique of 5-Why Analysis. The fishbone diagram, also called as Ishikawa diagram, cause and effect diagram or fishy cover diagram. Our usual diagrams created by the bike around Ishi cover that demonstrate the potential cause of a particular event. Common uses of the fishbone diagram, our product designs quality defect, prevention to identifying potential and events causing an overall impact. Each cause or justification for implementation is a source of variation. In a tabular format of 5-Why Analysis, a table is an arrangement of data, typically of rows and columns, or possibly in more complicated structure. Tables are broadly used for communication research and data analysis. Tables appeared in print media, hundred and nodes, computers of this architecture, traffic signals and many other places. The specific conversation and terminologies describe the table vary depending upon the context. Further table differ significantly in variety, structure, flexibility, notation, representation, and use the rules for performing 5-Why Analysis. The phi bi systems can be personalized based on the particular needs of a given facility. However, most companies implementing this type of strategy will use some general rules or guidelines that will keep them strategic focus. The following rules of performing five whys are generally a good place to start in most situations. It is important to engage the management in phi y process of the company. Use a whiteboard or paper instead of computers. Write down the problem and make sure that all the people understand it. Distinguish between the cause and the symptoms. The focus on the logic of the cause and effect relationship ensure that the root cause certainly lead to the mistakes. By reversing the sentence create due to the analysis. Attempt to answer, which make answers more accurate. Search for the cause step-by-step. Don't make hasty judgment. The statement of facts and knowledge, evaluate the process and not the people. Never leave human error, blamed John or workers in attention, etc, as a root cause. He doesn't want to do it. Or let's blame john that he is the one who's responsible to establish an atmosphere of trust and authenticity. Ask why until the root cause is identified? Because the elimination of. Which will prevent the error. When you structure the answer to the question why it's used. It should be according to the customer's perspective. Now, these are some criticisms about phi way, why people do not like using flyways. Many companies for training and engineering services successfully utilize the firewall techniques for fundamental incidence or failure. By utilizing the right placement of triggers, organization can use the 5-Why for its fundamental problem-solving and then program to form a cause and effect analysis for more complicated problems like Apollo root cause analysis method. A disciplined problem-solving strategies should push, aims to think outside the box, identify a root cause and solution. There are various reasons for the criticism of Phi, right? Results are not repeatable. Different individuals using phi y come up with various causes for the same problem. Tendency to isolate a solid three root cause. Whereas each question should elicit many ways root causes. Daughter linear method of communication for what is often a nonlinear event. Now let's move to the benefits of 5-Why Analysis. Help identify the root cause of the problem. Understand how one process can cause a gain of problems. Determine the relationship between different root causes. Highly effective without complicated evaluation technique. I will pause here for a second to tell you that if you feel that you have any doubts or questions, please feel free to ask the questions in the discussion section below. I will be happy to resolve your queries. Let's continue. What are the limits of the firewall? The firewall method is an incredible technique for getting to the root cause of the problem in a rather shorter period of time. However, it's speed and convenience of use sometimes can lead to uneven results. When it comes to a repeating failure. If the firewall fails to deliver the true root cause. The following are few of the limitations. It doesn't continuously lead to the identification of group was when the cause is unknown to the team members. It makes up a gradient analysis when symptoms are discovered in strong, driving deep, deeper in determine the true root causes. Different people may get different answers, but the cause of the same problem. Confirmation bias, the tendency to interpret new data as a confirmation of one's own existing ideas can only be as good as the people who use this. It's expertise and experience. Human not dive deep, love to reveal the root cause of the issues entirely. The members tend to depend on the detective logic instead of observation when recognizing radius factors leading to the root causes. Let's do an example of fiber analysis. Let's see def boss Amazon example for application of phi way. I have taken this from management study guide for your reference. Both illustrated how the phi y should be used. He has gone to one of his shop floors at Amazon. On his visit, he noticed that the finger of one of their employees were caught on the conveyor blood and they employ got injured. The following is a record of the meeting where Mr. Boss describes this incident. Washington, what caused the associate to damage his answer? Because his thumb got trapped on the conveyor. Why did his thumb get trapped in the conveyor? The answer because he was teasing his bag which was moving along the conveyor. Why was he chasing after his bag? Because he put his bag on the conveyor when but then turned on by surprise. What was the purpose for his bag being on the conveyor? Because he used the conveyor as a table. Conclusion of the case. So you can see that we just did four y's and we reach to the conclusion. The logical root cause of death associated damaging their thumb was that he needed a table instead of using the conveyor belt to drop his back. Unfortunately, there were there wasn't one around. So he used a conveyor belt as a team. To eliminate further safety incidents. We need to provide tables, add the appropriate station, and give portable light tables for the associates to utilize, update and focus on the safety training. Conclusion regarding regarding the methodology in general. Phi by acts as a powerful tool to help shift to the symptoms. Solving this root cause solves all the issues and between subjectivity involved in the final analysis. The phi by process is only semi-structure. Therefore, if different people do it, they may come up with different results. The process is only as good as the person running it. This makes it important to ensure that the team is cross-functional involving staining the best results for the process. So the final conclusion, the firewall technique is a problem-solving method that relies by asking the question why five times in a continuous sequence to find the root cause? Each time you inquire why the problem occurred, your answer turns out to be the reason for your next question, compelling you to dig deeper and deeper into the true cause of the issue. This informed decision-making technique investigates the root cause or the cause and effect relationship hiding behind the specific problem. Rather than coming up with solutions that could only address certain symptoms. Phi way process on a countermeasures aims to prevent the problem from occurring. Again, wishing you all the best, and I'll see you in the next lecture. 32. Vanilla icecream: Let us now understand a very important concept through a story, root cause analysis, and how we can investigate. The vanilla ice cream case that puzzled General Motors, never underestimate your client's complaint, no matter how funny it might seem. This is a real story that happened between the customer of General Motors and its customer care executive. Please listen to it very careful. Fly a complaint was received by a Division Office of General Motors. This is the second time I have written to you. I don't blame you for not answering me because it might sound crazy. But it is a fact that we have a tradition in our family to have ice cream as a dessert after dinner each night. But the kind of ice cream varies every night. After we have eaten our dinner, the whole family votes on which kind of ice cream we should have. I drive down to the store and get it. It's also a fact that I recently purchased a new car of your company. And since then, my trips to the store have created a problem. You see, every time I buy a vanilla ice cream, when I start back from the store, my car won't start. If I get any other kind of ice cream, the car starts just pile. I want you to know that I'm serious about this question, no matter how silly it sounds. What is there about the car that makes it not start when I get vanilla ice cream and easy to start whenever I get any other kind of ice cream. The president of the General Motors was understand understandably skeptical about the letter. But he sent an engineer to check out the situation. The latter was surprised to have greeted by a successful and obviously well educated man in a fine neighborhood. He had arranged to meet the man just after the dinner time so that the two hopped into the car and drove to the ice cream store. It was the vanilla ice cream in that night, and sure enough, after they came back to the car, the car did not start. The engineer returned for three more nights. The first night, they got a chocolate ice cream. The car started. The second night, he got a strawberry ice cream. The car started. The third night, they ordered the vanilla ice cream, and the car failed to start. Now, the engineer being a logical man refused to believe that this man's car was allergic to vanilla ice cream. He arranged therefore to continue his visit as long as it took to solve this problem. And today, this end he began to take the notes. He jotted down all sort of data, the time of the day, the type of the gas used, the time to drive back and forth, et cetera. In a short while he got a cue. The clue was that the man took less time to buy a vanilla ice cream than any other flavors. Oh. Why? The answer was that the layout of the store, the vanilla was the most popular flavor and it had a separate case in front of the store for a quick pickup. All the other flavors were kept in the back of the store at a different counter, where it took considerably longer check out time. Now the question for the engineer was, why did the car not start when they took less time? Eureka tying was now the problem, not the vanilla ice cream. The engineer quickly came up with the answer the vapor lock. It was happening every night, but the extra time taken to get the other flavors allowed the engine to cool down sufficiently to start. When the man took vanilla, the engine was still too hot for the vapor lock to dispute. Even crazy looking problems are sometimes real, and all problems seem to be simple only when we find the solution while we have a cool thinking. This is an amazing story which tells us that sometimes our customers have a practical problem, which sounds crazy. What is more important is how we can use our logical thinking, our rational thinking, our parallel and perpendicular way of thinking to solve the problem the customer is facing rather than telling that, Oh, my God, this is so silly. Thank you so much. We'll continue in the next lesson. Oh 33. 5s methodology: Hi. In this five S training. I'll guide you through every aspect of the five S methodology in detail. The five S methodology is a popular tool in lean practices, designed to keep workplaces safe, clean, and productive. But like any tool, it has its pros and cons. Let's start by asking, is it essential to begin your lean journey with five S? Benefits of five S, it's easy to implement. It typically has a positive impact on quality and productivity. It signals to the organization that lean practices are underway. Disadvantages of five S, it might shift focus away from more critical priorities. It can sometimes be perceived merely as a clean up effort. Lean efforts might be narrowly associated only with five S. Remember, the true goal of a five S program is to reduce the seven wastes, decrease variation, and enhance productivity. Successful five S programs are implemented in workplaces with clear goals in mind. Five S is also about a shift in mindset from seeing your company as disorganized and messy to having a well organized workspace where everyone knows where everything is. The term five S originates from Japanese words. Si St, sto, set in order, C, she, sku, standardized, Shu k, sustain. It's important to remember these in the correct order and to follow each step meticulously when starting a five S program. Starting with five S is often a good choice, but make sure to execute each S properly for the best results. Now I will explain how to properly perform the sort step of the five S methodology. SOT is all about getting rid of what's not needed. First, you need to decide with your team on the sting criteria. For example, items used infrequently. Items needed for quick customer response, items necessary for safety. Next, the team should classify items, according to these criteria, scan every item in the area, and if an item is either never used or its purpose is uncertain, it should be red tag or discarded. A red tag is a label with the date of the five S event. It helps track when the item was reviewed by the team. You can place tagged items in a large box near the sorting area. If an item remains untaged after a set period, it can be disposed of, recycled, or sold. The sorting process should be conducted regularly ideally every six months. However, be mindful not to overdo it. Allow team members to keep personal items in their workspace to ensure they remain comfortable. After completing this step, your workplace will already look significantly improved. How to implement the set in order, step of the five methodology properly. At this stage, you should only have the items you need in the workplace. The goal is to place these items in the most efficient locations. As my grandmother used to say, a place for everything and everything in its place. To achieve this, you can use tools such as shadow boards, labels, footprints, flow markings, trolleys, and color coding. Position items based on their frequency of use to minimize unnecessary movements, such as stretching and bending. Spaghetti charts can be useful for analyzing and testing different layouts before finalizing them. Ergonomic principles and safety are crucial in this step. For instance, frequently used items should be located in a zone close to the point of use ideally between shoulder and pelvis height. During the set in order phase, act like an engineer working closely with the people who will use these setups daily. Collaborate with them to reduce waste and ensure they fully embrace the new arrangement. It's important not to force a solution. Instead, be open to adjusting positions as needed in the future. Keep in mind that the change is allowed to adjust positions in the future as needed. The shine step of the five s methodology is often under evaluated. This is not a simple physical idea, but has to be done as a visual control to correct immediately for anything out of place and asking why the item was in the wrong position. Cleaning is checking. The team has not just to clean up. They have to highlight any abnormalities and perform the five is analysis to find the root cause. For example, if they clean up a machine and oil leakage is discovered, they have to clean up and immediately ask themselves why the oil leakage is occurring and plan what should be done for prevention. The shine step has to be done regularly, too. You can decide what is meaningful for you. Daily, weekly, monthly. You have to designate who is responsible for what and what the cleaning standard is. Further, the equipment to perform the regular cleaning has to be located close to the point of use with a visual station. Again, cleaning is checking. Into the shine step, you could include gage checking, loop, keeping track of the five S activities, old communications to be removed. If you arrange the shine in a structured way with all the team members involved, you will be surprised about what you can get in 1 hour of work. The standardized step where most of the five S program starts to fail. The team has to decide who does what and when in a very detailed way. I already told you something in the shine step, and the tool I would like to suggest is the RACI table. My suggestion is to make the RACI table visible in the area so everyone can always know what is task to carry out. Further, you have to remember that in the standardize, you have to include measuring, recording, training, work balancing. The last step of the five S methodology is the sustain. This step is about participation and improvement. The goal is to make the five S a habit. The best way is to create something like a competition among departments with the leadership auditing the areas and giving awards regularly. What is normally done in some companies is a regular walk with audits. First line supervisor audit on a daily base, area manager on a weekly pace, Section manager on a monthly pace, plant manager on a quarterly base. Some companies speak about six S. They add the safety to the five S. There are a lot of links between the five S methodology and the safety because with an excellent five S implementation, you can reduce a lot of risks. You can get ergonomics and remove unsafe conditions. I strongly suggest starting with a five S program, in some areas, you want to learn the methodology. The best way to learn five S is by doing it. So Oh. Oh She She 34. 5s with safety: In this lesson, we are going to understand about the fives system. What is a fives system? And have you heard about the sixth S that is safety? I will cover that as well. How is it going to impact us and our organization? We are going to understand the entire system in detail. Though the sixths is added, we still call it as a fives system. Let's get started. Five x is a systematic approach to workplace organization. It represents five Japanese words that describe the series of steps for the workplace. It organizes the whole process. Siri that is sort, sit on that is set in order, CSO, shine, C, kets, standardize, sit sok sustain. If you add the sixth safety, it becomes six X. This is not six sigma. The fives technique was developed in Japan, and it was identified as one of the methods that enable just in time importantly, Fws is never meant to be a one time activity, but an ongoing process that must be repeated continuously. Five Wes activities help create good working environment through reduction of Mura that is unevenness in the process, Muri that is overburdened, and Muda, that is waste. Five Wes began as part of the Toyota production system, the manufacturing method developed by the leaders at Toyota in the early mid 20th century. This system is often called as the lean manufacturing system. The vest aims to increase the value given to the customer by eliminating the waste in the production process. In simple terms, FS helps in the workplace removing unnecessary items that is sorting, organizing the items efficiently, that is set in order, create a work area to identify problems, that is shine, standardize the process. Standardize and develop a mechanism, a discipline to maintain what improvement you have achieved that is sustained. This creates a foundation for continuous improvement, zero defects, cost reduction, and productive workplace. Let's look at each step in detail. The first S of fives that is ser, that is SOT, SOT involves going through all the tools, furniture, material, equipment in your workplace area to determine what is needed and what can be removed. This means removing items from the work area that aren't needed for current production level ask the question, what is the purpose of this item? When was it last used? How frequently is it used? Who uses it? Does it really need to be here right now? Items that cannot be removed immediately can be tagged for later removal to the red tag folding area. This would be a designated clearly labeled space where unnecessary items are placed until further decisions are made. This creates a clutter free environment. As illustrated by the before and after example on the screen, on the left side is the cut cluttered workplace. On the right side is a sorted, well organized area. The second S of the fives is citon set in order or straighten. This state says a place from everything and everything in its place. A place for everything and everything in its place. If there is no place for a particular item, it means that you don't need this item. Or if there is no place to keep the item, you need to create one if it is important, and it is not part of the red tag area. Arrange the items so that the workflow is efficient. Items are easy to access, and the workplace ergonomics and safety is taken into consideration. Now let's consider a scenario. Which items are used most frequently. The questions which you will ask at this stage is which items are used most frequently? Where would be the most logical place to keep them? Should items be grouped by type, where should heavy and light items be placed for easy safe access? The aim is to minimize the moments, ensure stress free, efficient workflows. The third S of the fives is CSO, that is sine. It is about cleaning up the work area, sweeping, mopping, dusting, wiping the surface, putting the tools away. A clean workplace prevents contamination and hazards. It helps spots abnormal conditions very quickly like the leak oil, like the oil leak on the machine. It promotes ownership of the workplace, cleanliness among employees. Shine also includes the planned maintenance to prevent breakdown and reduce the downtime. Remember, shine is not just about making the workplace look good. It's about making the problem visible. It is part of the visual management tool. The fourth S is Sitsuke standardize. Once sorted, set in order, and shine is complete, we need to standardize the improvements to ensure that the results are maintained and consistent. The challenge is that without standardization, the workplace quickly reverts to the original state of disorder. In this step, we define regular tasks and schedules, prepare a clear instruction and SOPs, MFIs activities routine and systematic. We standardize to ensure that the most efficient and the least wasteful way of working are followed consistently. The fifth S of the fives, it sits okay. Sustain. Sustain means developing the discipline to maintain the fives principles and practice it over the long term. It is often the toughest step. Many companies clean up and get organized but fail to maintain the improvements. Sustain ensures that everyone follows the fives rule, the managers and the employees, everyone. Fives becomes part of the organizational culture. Progress is continuous and improvement is endured. The most important thing is the communication tools like the signs, the posters, and the meetings can help keep FIS fresh in people's mind. It prevents backsliding. The sixth S is safety. Safety is sometimes included as part of the sixth S. As many organizations believe worker safety is critical, and it should be an integral part of FIS. Safety cannot be a separate step. It should be considered at every stage of firs. For example, during the SOT, replace the outdated unsafe tools. During standardized, arrange the workstation with keeping the employee's ergonomic in mind. Some argue that properly implemented fives automatically improves safety while other prefers to emphasize safety explicitly as part of the S. Either way, paying attention to safety is very essential. The benefits of fives implementing FIS can achieve the following results. It reduces costs, higher quality products, increased productivity, greater employee satisfaction, safer work environment, inventory reduction, minimum breakdowns, zero injuries, zero delays. It reduces the change over time. Let's understand fives with the help of an example. Before fives, we had a cluttered disorganized, inefficient workspace. After fives, organized clean, efficient workplace, which is shown on the screen. Items are scattered and hard to find if fives is not implemented. Items get neatly arranged and easy to access, clearly labeled. This is what is important for you to implement fives. Thank you. I will see you in the next video. 35. Value Stream Mapping: Introduction to value stream mapping. Value stream mapping is a wonderful tool given by the concepts of N. As an, you know, focuses on reducing waste. The value stream mapping exercise helps us to have a very clear view and focus on eliminating waste. Value stream mapping is process mapping, but with a few differences. It's a tool that comes with lean manufacturing and works really well in manufacturing, delivery, shipping, factory processes, service industries, and even in BPOs. We call them as GCC, global capability center in today's world. But it is also helpful in other industries like the GCC. But it's also useful in other service industries like the GCC Global Capability Center, back offices, BPOs, business process outsourcing. If the Six Sigma expert knows how to adopt it to their process, hence, the knowledge is very important. What exactly is value stream mapping? You would have heard the word VSM multiple times. It's a pictorial representation with the numbers. What shows the entire value, the stream of product or ideas. When used properly, it gives Six Sigma team a very big picture of what's exactly happening. It helps us see the process that looks like today. It helps us imagine how it can be improved, and it connects the flow of material, people, and information all in one image. One big advantage of value stream mapping is that this exercise helps you break the communication barriers. The symbols used are very intuitive. So everyone on the team can easily understand where is the waste or Moda, and where does this happen? Now, let's look at the seven flows that can help you visualize the value stream map. These are people raw material or information parts or the files and folders, products, equipment or softwares and tools that you're using, the information flow, the engineering flow, the logic, the Q weighting, the concept of FIFO and FO. The value stream map helps capture information about all these flows. But most maps focus on raw material, parts and products unlike other process maps, value stream map has a unique symbols. For example, if your process involves trucks, the map might show the actual truck icon, along with the details like how many shipment occurs each week. It is encouraging to see that it's very easy for us to understand the symbols. Now remember, you don't have to use the exact symbols every time. In industries like healthcare, say an emergency room. Other symbols might make more sense. So think of these symbols as the starting points, not as a strict rules. That is the foundation of VSM. In the next part, I will explain some of the common symbols used in value stream mapping. 36. Total Productive Maintenance: Today, we are going to learn about total productive maintenance, TPM. In this module, we will learn about TPM, and we will also apply some of the O EE overall equipment effectiveness. That we just learned and understand how we can improve the reliability of a tool. This model will split into three sections. First of all, we will go through the definitions. We will then go through a real world comparison between two companies and the different approach they have for managing their maintenance. Then finally, we will go at some good KPIs, some good metrics on how you can measure and measure the maintenance within your company. TPM example. In order to explain TPM, I will start with comparing how two different companies operate. At Company A, a machine has been leaking oil for past week, and finally breaks down. The machine operator calls the maintenance team to come and repair it. The maintenance team takes over 2 hours to arrive as they are busy fire fighting other problems and breakdowns within the factory. The maintenance team arrives to find that the critical gear is broken. They search the spare parts store and look through all the shells and boxes of replshment gear. Only to find that they have a lot of supply of gears of the previous machine, but none from the newer machine with a correct size. As the machine cannot work without the gear, they are desperate for the replacement, so they pay an exorberant price to source the part and have it delivered the next day. When the spare part arrives, the maintenance team drops whatever they were working and come running to replace the gear as quickly as possible. The maintenance department is commandable for the speed at which they sourced, replace the part, and the machine is back up and running after a total of 29 hours of downtime. The maintenance team carries on with their next job, which is to try and fix another breakdown that has occurred in the other part of the factory. Now, let's go to Company P. John, an experienced operator noticed quiet but strange grinding noise coming from the machine during his morning, 10 minutes walk. And that walk is called as a TPM routine. He follows a set of list scanning barcode once is complete. John has been working with the machines for the past eight years, so he knows it inside out. As he's carrying out his root set tine of clearing lubricants and realigning critical parts, he notices that a gear is starting to wear, and a surface crack has formed. Because it is a low cost and a critical part, there are spare parts stored just inches away from the machine. In case they need replacement. John's manager has told to fix any problem as soon as possible before they escalate and have given them full responsibility to look after their machine. Now, not only that, but a member from the maintenance team recently spent a day with John, educating him about the most common faults, and what main things to look for look out for within the machine. John replaces the gear and puts the damaged one in the box next to the machine, scanning the side of the box as he does so. He starts up the equipment and carries out with his daily operation as normal. Feeling pleased that his machine is still working as it should be. The maintenance department is notified that John scans the box with the replacement part. So only 1 hour into his shift, a maintenance team member comes over to ask him about what happened, and finds out that John finds out what John thought might be the cause of the problem. The maintenance team thanks John for spotting and rectifying the problem and takes the gear back to the maintenance department. After inspection, the maintenance department concludes that the gear had been worn out as expected and was scheduled for replacement in a couple of days as part of the plan planned maintenance order. Since the gear is critical for the machines operator, they order a replacement spare gates to ensure that the calculated spare part levels are maintained. The machine downtime was zero. The cost was minimal, and they had recorded the data from the breakdown to help continuously improve their maintenance strategy. 37. Total Productive Maintenance Part2: To learn about total productive maintenance, TPM. The machine downtime was zero. The cost was minimal, and they had recorded the data from the breakdown to help continuously improve their maintenance strategy. This example explains many of the principles and characteristics of TPM. If we compare company A with company B, we can see that company B works in a superior way in every aspect. The company B proactively prevents a breakdown from occurring as opposed to the maintenance team running around fire fighting breakdowns for company A. The second point is that Company B empowers and trained John to take responsibility for his machine and solve basic problems. Company B has zero unplanned downtime as a result, allowing production to run as normal. Company B didn't have to pay the premium price for the express delivery service. But not only that, because they look after their machines, clean them, lubricate them daily, the breakdown is much less and last the machines last longer, saving additional cost. Throughout this module, we will refer back to this example to relate to the concept of TPM in a real world situation. So before we go further, let me define TPM. As for the definition, total production maintenance is a strategy to maximize machine output by reducing downtime, speed loss, and defects, while stimulating, promoting the value of safe. Organized workplace by involving people. Remember the definition of lead to reduce waste, increase customer value, involve people. This definition is somewhat replicate in TPM as a means to reduce waste of by involving people. If we break down the definition of TPM, it is found that it is made up of few words. That is total, which refers to the founder of the Kaiser Institute, which has a true meaning of Kiser, improving every day everywhere, with everyone. In this case, it means that with the operators, maintenance, and managers, productive refers to making improvements in a productive, cost effective way. And finally, maintenance refers to the aim of TPM to reduce maintenance machine downtime and optimize maintenance activity. TPM is as much a switching mindset as it is a tool. The tool itself enables stability and machine effectiveness. But as with many lean tools, if not embraced properly, it will not have a true impact that it could have. The main purpose maximize overall equipment effectiveness, improving reliability, reducing overall maintenance cost, and developing continuous improvement culture. The examples of TPM with a car ownership. If you have ever bought a new car, you will find that the first couple of months, you clean it up every weekend and are very strict about the people not eating inside the car. After a few months, you still look after it, but perhaps don't clean it as quite regularly as you did earlier. After one year, your attention to cleaning and maintenance has faded away. This is a human nature. TPM creates an initial need to clean and maintain the equipment, but also provides a routine and structured way to ensure it is sustained. TPM helps to develop a collaborative continuous improvement culture where the paradigm is broken. Instead of saying, I operate U fixed attitude to the new attitude which says, I take responsibility to look after my machine and ensure it is always available when needed attitude. Notice how it isn't about keeping the machine always running as it could promote overproduction. The machine needs to just be available to produce whenever it is required. The principle behind TPM is that by operators taking ownership of their machines and it becoming their job to keep it in good working condition, the equipment will last much longer, break down less, and the problems will be fixed before they escalate. Just like the five S methodology of Lean, the sustained aspect of TPM is extremely important. A rather strange but effective analogy for looking at this new operator responsibility for equipment can be seen in the way that we care for a baby. In this example, please think of a baby like the equipment. A parent like an operator and a doctor like a maintenance department. Just like how the doctor diagnoses and fix the problem with the people, whether that is can be a broken bone or a tone ligament, maintenance members fix problems with the machine, whether that is a broken gear or a worn out part. As a parent, if your baby starts to cry, your first reaction isn't to call the doctor or visit a hospital or seek a medical assistance. Your job would be to carry out some normal expected tasks to checking the temperature, making sure that your child is hydrated and comfortable. As a operator, you're expected to carry out the autonomous maintenance for common faces. Just like the baby crying, this may include inspecting, cleaning, or lubricating the machine. You should only go to the doctor That is the maintenance department, when you have a severe problem or an unknown or uncommon problem. This is exactly what TPM is, training the parents on how to look after their children and take accountability for their well being. I know this is a bit of a strange example, but I think it is memorable and helps convey the change of responsibility that TPM provides. 38. Banana Curve of Total Productive Maintenance : Today, we are going to learn about total productive maintenance, TPM. Okay. That's enough talking about crime babies, back to the course. Just like how lean is an ongoing pursuit of journey towards 100% excellence. TPM is about sliding the scale from 0% uptime towards 100% uptime to an 0% downtime. This is about taking steps in the right direction towards this stage, continuously moving closer to it. The fact of the matter is machines do break down, people make mistakes, and things do go wrong. However, much you try and prevent them from happening. The point to stretch is that the first thing you need to do is to minimize the amount of equipment breakdown, which is where TPM helps. Secondly, when it does break down, make sure it's fixed as quickly as efficiently at the lowest cost possible. The good way of demonstrating TPM shift is by looking at the makeup of both production and maintenance staff time, and what they do. The number used in these examples helps demonstrate how the shift in the mind shet of TPM equates to the change of roles and responsibility. With a traditional maintenance strategy, production operators spends roughly 5% of their time with their machine breakdown, 5% of their time cleaning their machine, and the remaining 60% of their time in operations. The maintenance staff spends roughly half of their time firefighting and correcting problems. Think back of the company A example that we learned earlier. Now, let's see how this changed with TPM. With TPM implemented, production operators are more involved in upkeeping their machines. They spent around 5% of the time cleaning and maintaining their machines, reducing the breakdown time to 10%, and thus increasing the operational time to 85%. Maintenance staff now spend only 20% of their time fire fighting and 80% of their time in plant maintenance and continuous improvement activities. This shifts result in increased uptime, reduced cost, and a more efficient and proactive maintenance strategy. TPM involves making reliability improvements and proactively maintaining the equipment. The point to stress here is that breakdowns have reduced from 35% to just 5%, resulting seven times less unexpected downtime. Although the operators are now actually spending more time in carrying out their routine basic maintenance, the overall output and uptime for their machines is much higher. To more easily predict and plan the output for each day without sudden surprises and the need for overtime. TPM is built on the FiveS culture of operators ownership and prides in their work environment. When deployed correctly, it instills the feeling of responsibility for equipment in all the employees. It also makes a huge stride in removing the barriers between the maintenance and the operation staff, treating problem solving as a joint effort. L et us now learn about the bath tub reliability curve. It wouldn't have been possible to talk about TPM without mentioning the classic bath tub reliability curve, which many engineers are very familiar with. This curve illustrates the typical life cycle of an equipment, showing three phases, the infant mortality, earlier failures due to design or manufacturing issues. These are often identified and fixed during the initial phase of operations. Normal life. The equipment operators reliably with occasionally arana failures that can be managed with failure maintenance. Payout. As the equipment age, the likelihood of failure increases due to the natural degradation. TPM focuses on minimizing failure during the normal life phase by involving operators to daily maintenance and fostering a culture of proactive approach for problem solving. By doing so, TPM extends the normal life phase and delays the wear out phase, leading to a greater reliability and efficiency in equipment operations. The bar tub curve shows how probability of equipment failure changes over time. To some people surprise, when equipment is new, it often has the highest chance of failure. This is followed by a period where the failure rate plates down. And then as the machine begins to wear and age, the chances of failure begins to rise. TPMs target is about three aspects of the curve is related to equipment failure. The burnout period. Failures are reduced during the early phase by implementing early equipment maintenance and improving the understanding of the equipment cubes. This counter initiative idea that equipment is more likely to fail when new is truly because the standards may not have been fully developed. The machine may not have been adjusted to the quality capability stage. Additionally, the six big losses of OEE, that is overall equipment effectiveness may not have been quantified and addressed. The plateau period. During this period, the failure probability is reduced through autonomous maintenance. I will explain exactly what is involved shortly. Autonomous maintenance includes routine tasks carried out by the operators, such as cleaning, inspecting, lubricating, which helps in maintaining the equipment in its optimum stage and prevents failure. The way outut phase. As the equipment ages, TPM helps in managing the wear and tear through regular planned maintenance, addressing issues before they lead to major failures. By focusing on these areas, TPM aims to extend the lifespan of the equipment, reduce downtime and enhance overall equipment effectiveness. The way outt stage is managed through predicted and planned maintenance, thereby minimizing unexpected interruptions and extending the life of the machinery. However, the world of maintenance has changed significantly over the past two decades. Traditionally, machines were much simpler and designed for to last extremely long time. Today, technology evolves so rapidly that many machines are replaced before even they reach the wayout stage. Just like the mobile phones, your iPhone is unlikely to break from excessive wear because you want to upgrade and access the latest feature. Similarly, machines often rented and leased with expectation that they will be upgraded every few years. That said, I'm not negotiating the impact of TPM as the life's extension. TPM provides stability and assurance that machinery is available whenever needed. However, in terms of extending the lifespan of equipment, while TPM does achieve it, it is not the sole and the main focus. Out of the three areas of the curve, the plateau phase is usually the main focus for TPM. This is because in this section of the curve, it represents the largest portion of the machine's life cycle. By focusing on reducing failure during the plateau period, TPM has the greatest impact in the overall equipment effectiveness and minimizing downtime. To improve reliability, you want to reduce the area under the curve, so the machine has a lower overall probability of failure. By reducing the chance of failure throughout the plateau phase, you can see a significant impact on the area under the curve. I have just noticed that this curve looks a bit like a banana, though that wasn't the intention. It might be making it easier to remember. TPM can be implemented at different levels of severity. Oh. 39. Total Productive Maintenance KPI: Today, we are going to learn about total productive maintenance, TPM. TPM can be implemented at different levels severity. But in this module, we will focus on two main approaches, autonomous maintenance and maintenance is events. Let's start by explaining what autonomous maintenance. Autonomous maintenance is achieved when production operators can carry out all the necessary tasks by maintaining equipments for common fats. This includes tasks such as cleaning, inspection, and lubrication. The key concept here is training and empowerment. Operators are trained to perform these tasks and are empowered to look after their own equipment. This approach does not aim to upskill production staff to the level of maintenance members, but rather to ensure that the operators are comfortable inspecting and working with their machine. During the TPM transformation stage, operators might express concerns and have questions about their new responsibilities. They may wonder about their roles in maintaining equipments and how it affects the daily task. Some operators might initially say, I'm not getting paid to do a maintenance road. It's not my responsibility. To that, I would say, firstly, they will not be taking out on all the maintenance task. Secondly, continuous improvement should involve everyone every day and everywhere in the organization. As the saying goes, you can lead a horse to the water, but you can't make a drink. You can provide an opportunity and training. But if the operator refuses to engage, there's little you can do. Ultimately, as discussed in the Kaizen model, a rotten apple can spoil the whole bunch. You don't want any rotten apples in your organization. When the operators take the responsibility of autonomously maintaining their equipment, maintenance staff have more time to focus on improvement activities and preventing maintenance. By working closely with operators and training them on basic maintenance. Staff also benefit by having more eyes and ears around. Operators can now spread the load of inspection and notify the maintenance team when something needs further attention. Before operators might not have seen skilled might not have Before, operators might not have been skilled in spotting problems, might not have seen it as their responsibility to raise issues. This is where productive part of the total productive maintenance comes into play. By upskilling everyone at least to identify and report falls, resources can be used more effectively. Looking back at the four main objectives of TPM is to maximize overall equipment effectiveness, improve reliability, reduce maintenance cost, and develop a continuous improvement culture. Autonomous maintenance significantly contributes to this core. It helps to ensure that the maintenance resources are optimally utilized, leading to more effective and efficient operations. Continuous improvement culture is a key aspect of TPM. Autonomous maintenance helps achieve all the objectives by empowering operators to maintain their own e. This allows maintenance staff to focus on more preventive tasks, such as helping maximize OEE while reducing downtime. This in turn improves reliability and reduces maintenance cost. The second approach through KISN events. These are focused workshops with specific aim in this case. To improve OEE of equipment, if we recall the OEE module, it's a function of availability, performance, and quality. The three aspects that TPM aims to enhance. A Kaizen event or a problem solving workshop focuses on improving OEE, should involve a detailed inspection of the losses to uncover their roots. Once these causes have been identified, measures are taken to prevent them from reoccurring. The problem solving modules explain the Kaizen event methodology in much more detail. Lastly, to promote continuous improvement culture, problems and success needs to be visible. Metrics need to be measured to achieve this. Remember, you can't manage what you can't control. You can't control what you can't measure. In terms of metrics to measure OEE or a continuous improvement metrics, like the number of machine enhancement or improvements are a good place to start. The current way of working for many companies with functional department in silos makes no sense, especially for the maintenance companies. Typically, maintenance staff performance is just based on the number of repairs or the amount of work completed each day. The more repairs they complete, the higher their performance is considered. This is a wrong attitude. This is problematic because it creates an objective that directly opposes the organizational le. Unreliable unproductive equipment results in a poor factory performance, results in waste and an inability to stick to the production plan. On the other hand, it doesn't make sense to have a large proactive maintenance team. If the equipment is always available, and it never breakdowns. Wouldn't that suggest an unproductive maintenance department that isn't necessarily needed? This paradox highlights that why maintenance is a function needs to be integrated into the continuous improvement and the manufacturing process. Responsibilities such as process innovation, research, improvement task needs to be coupled with metrics like availability, performance, and quality? Organizational performance would be the top priority for maintenance. While is challenging to select the right KPI for maintenance staff, focusing on the leading KPIs like the number of improvements or enhancement, and the percentage of operators trained in an autonomous maintenance, more effective than sorely counting the number of repairs completed per maintenance member per day. And that concludes this module. Total productive maintenance summary. In this module, we explore the TPM and its crucial role in enhancing operational efficiency. TPM isn't just an improvement tool. It's a significant shift in mindset. Operators being closest to the machines are ideally positioned to perform autonomous maintenance. They understand their machines better than anyone else by sensing vibrations and detecting unusual smells and sounds. The goal is to eliminate waste of time and resources spend on maintenance by involving operators in routine upkeeping. By fostering a sense of pride and responsibility in operators, TPM not only enhances machine reliability, but also cultivates a culture of continuous improvement. Thank you for your attention, and I hope you found the information of total productive maintenance helpful. S. 40. Six Sigma Project real life Use Case explained: Et's prepare for interview questions on lean Six Sigma. One of the common question that is asked is why Six Sigma important to any organization. As an interviewing, you should not only be giving answers to the concept, but also explaining it with examples. So let's get started. So I will be giving you the questions, and I will also be explaining you the possible answers. Six Sigma is a crucial way to any organization because it provides data driven approach to improve processes, reduce defects, enhance quality. By identifying and eliminating the causes of errors and minimizing the variability in the process, Six Sigma helps organization achieve higher efficiency, lower operational costs, and improved satisfaction. Now, this sounds a little technical. If I have to explain it, let's understand a scenario. In a manufacturing company, a recurrent defect in a product line we're causing delays and increasing production costs. By implementing Six Sigma methodology, the team conducted a thorough analysis using tools and methodology called DMC define, measure, analyze, improve and control. That identified that a particular machine can contribute to inconsistent product quality due to unmonitored calibration issues. After addressing this problem, the process got in control, and regular checks helped the company see 25% reduction in the production defects, a significant decrease in waste which saved hundreds and thousands of dollars annually. The explanation is that this example clearly illustrates how Six Sigma helps organization identify the root cause of the problem, implement corrective vaccine, sustain improvements leading to enhanced operational efficiency, and better customer experience. The next question which is asked is where is Six Sigma used? CICEMA is used across various industries to streamline process, improve quality, and reduce cost. It is applied in sectors like manufacturing, healthcare, finance, information technology or IT, as we call it, supply chain management. These are just to name a few. The methodology helps organizations standardize process, improve efficiency, and enhance customer satisfaction. Let's understand this with a scenario for a manufacturing setup. A car manufacturer experienced high rejection rate due to defects in the assembly line. By using Six Sigma DMAC methodology, they identified that variability in components fitting was the main issue. After implementing stricter quality controls and better training for assembly workers, the defect rates dropped down by 30%, leading to higher production efficiency and reduced rework costs. Let's take an example from healthcare. A hospital faced delays in patient discharge causing bottlenecks and patient dissatisfaction. It's really sad to know that when the doctor has told that you can take your family member home at 10:00 in the morning and the patient is not being able to be discharged till five in the evening because the process has some backlogs. So a six Sigma approach can be applied involving a detailed process mapping, root cause analysis. The team found that delays were often due to inefficient coordination between departments. By restructuring discharge protocols and enhancing communication, the hospital reduced the discharge time by 40%, improving patient throughput and satisfaction and higher utilization of rooms. This scenario highlights that Six Sigma can efficiently be used in any industry where there's a need to optimize the process, eliminate cost, eliminate defects, and improving experience of the customer. Whether you are improving manufacturing process, or patient care at hospital, Six Sigma can be a framework that can help you achieve measurable and sustainable results. A common interview question is, what is Six Sigma? Can you explain it in a simple term with examples? Six Sigma is the answer to this six Sigma is a systematic data driven methodology aimed at improving process by identifying and eliminating defects and inefficiencies. The goal is to enhance the quality and consistency by minimizing variability in the process. As we all know that the customer always experiences the variation and never the average. So the six Sigma is used as a set of statistical tools and techniques to analyze the data, drive process improvement, following a structured framework called a DMAC define, measure, analyze, improve and control. If it's an existing process, but if it's a new process, then we use DMA DV that is define, measure, analyze, design, and verify. The term sixema originated from statistics, where it refers to a process that produces output within six standard deviation from the mean, which can translate to near perfection process or less than four defects per million opportunity. To be precise, it is 3.4 defects per million opportunity. But as we always know, we can never make a half defect. This high level process control leads to higher perfect products and services. In a manufacturing context, a company might use Six Sigma to analyze their production line, find that variability in machine setting leads to product defects. By applying Six Sigma tools like root cause analysis, cause and effect analysis, process mapping, Gemba, they can pinpoint the root cause and implement improvements such as better machine calibration, operator training, leading to fewer defects, and reduced waste. SIXIMAs principles are applicable not only in manufacturing, but across different industries like finance, healthcare, logistics, and the focus is helping organization improve efficiency, cut cost, increase customer satisfaction. A common interview question is, where did SIEMA come from? CICEMA originated from Motorola in the mid 1980s. Actually, it is more than two centuries old, but it became visible after Motorola brought it into operations. The methodology was developed by the engineer Bill Smith to address quality issues and improve the company's production process. Um, Six Sigma originated from Motorola in 1980s. This methodology is actually age old. It's more than a century old, but Motorola gave it the blind light. The methodology developed by the engineer Bill Smith to address quality issues and improve company's production process. Motorola aimed to find a way to minimize defect in manufacturing and delivering high quality products consistently. The approach gained recognizon when it helped Motorla save millions of dollars by reducing defects and optimizing processes. The Six Sigma as a term is actually referring to a statistical concept of achieving a process that is within six standard deviation from the mean, meaning it produces only 3.4 defects per million opportunities. This high level of quality control ensures that the product and the services meet customer expectations consistently. The methodology was later popularized by General Electric GE, under the leadership of Jack Welch, who adopted Six Sigma in 1990 as a king business strategy. GE reported significant cost savings and improved operational efficiency through the use of Six Sigma. At Motorla the engineers notice a small inconsistency in their manufacturing process leading to high defect rates. Customer were dissatisfied. By adopting Six Sigma principles, they analyze data to identify a root cause of variation, implementing systematic changes. This led to a dramatic improvement in productivity and quality, a significant reduction in production costs. The success of Six Sigma at Motorola's fulled multi spread adoption across industry worldwide. What is a six sigma level? A Six Sigma level refers to the degree of quality or defect control within a process. It measures how capable a process is for producing defect free outputs. The term Six Sigma denotes statistical benchmark where the process produces only 3.4 defects per million opportunities. Also called DPMO. Achieving a six Sigma level means that the process is highly efficient with minimal variation and high quality output. SIGMA scale ranges from one Sigma to six Sigma with higher level indicating fewer defects, more reliable performance. When we say the process is performing at one Sigma level, it's a very low performance up to six lack 90,000 defects per million opportunities. If a process is performing at three Sigma, it is performing. It's still making an average performance with around 66,800 defects per million opportunities. When the process is performing at six Sigma, we say that it's making only 3.4 defects per million opportunities. So we can see that as the Sigma level progresses, it becomes purely difficult to reduce the results because we are going towards near perfection. Achieving six Sigma levels involves vigorous data analysis, process improvements, strategies, continuously monitoring to ensure that the process remains within the control limits and specification limits. Consider a company that manufactures smartphones. If the assembly process is at zero Sigma, it means that it's making a lot of defects. But if the process is performing at CIT Sigma level, then there are 66,800 approximate defects per million opportunities. Obviously in a manufacturing setup like smartphone, we can definitely aim at Six Sigma, but it's very difficult to achieve that. The high level of quality ensures customer satisfaction, reduced cost related to rework and recalls, strengthening the company's reputation for reliable products. The Six Sigma level is used for benchmarking the process capability and is often a key metric for quality control, operational excellence in industries like manufacturing, health care, finance, and more. Why is six Sigma important to any organization? Why is SIXIMA important to any organization? SIXIMA is important to organizations because it helps improve process quality, reduce operational cost, enhance customer satisfaction. By using a structured data driven approach, Six Sigma identifies and eliminates defects, minimizes process variability, drives continuous improvements. This results in more efficient operations. Better products and service quality, increased profitability. SIC Sigma focuses on reducing defects as low as 3.4 defects per million opportunities. This high standard ensure the process is reliable, consistent. Implementing a SIG Sigma will lead to reduced waste. Streamlined process reduces unnecessary steps, saving time and resources. Increased efficiency. Process improvements boost productivity, allows for a faster turnaround time. Customer satisfaction, high quality outputs lead to fewer errors and complaints, improves customer trust and loyalty. Cost saving, fewer defects, and process variation means lower rework costs and better resource allocation. In a financial service company, a Six Sigma was used to streamline the loan approval process, which was slow and prone to errors. By applying the D MAC methodology, define, measure, analyze, improve and control, the team discovered that the redundant variation or redundant verification steps were causing delays. By reworking the process, they cut down the approval time by 30%, reduced error by 20%, and significantly improved the customer satisfaction, which led to higher rate of repeat business. The conclusion is Six Sigma helps organization not only justify by improving quality but also foster a culture of continuous improvement, data driven decision making. This leads to long term sustainability and a competitive advantage in marketplace. Sometimes the interviewer says, give me an experience. Me how can you impress me that you know Six Sigma very well, right? So I'm going to take a structured approach for this. I'm going to use the star method situation, task, action, and results. In my previous role at Six Sigma Black Bell for over ten years, I led multiple process improvement projects across departments. For instance, we faced a high defect rate in our manufacturing process, which was affecting product delivery timelines and customer satisfaction. The situation was that the company was experiencing defect rate of 10%, leading to increased rework costs and customer complaints. My task was to reduce the defect rate below 2% within six months and enhance the process efficiency. The action that I implemented was using a D MAC methodology. In define, I clearly defined the scope of the project, identified the key stakeholders and customer expectations. Telling that our defect rates are at 10% and our target was to get it below 2% in the next six months. I collected data on the current process defect rates, analyze the defect types, and measured the cycle type. We did some process mapping exercise. We did some data driven decision data analysis, and this helped us in our next phase. During the analyze phase, using the root cause analysis and fishbone diagram, we identified that calibration issue in machinery was causing the variability. During the improve phase, the team led by developing new standard operating procedures, implemented some real time monitoring tools. To sustain the improvements in the control phase, we created a control plan that included regular training of operators and monthly audits. The result was that the defect rates dropped 1.4% exceeding our goals, and we saw an annual cost saving of 0.5 million. The customer complaints decreased by 25%, which was a significant improvement in customer retention. So I combine both lean and Six Sigma to eliminate non value added activities. In supply chain process using value stream mapping alongside the DMAC. This help in reducing the cycle time by 20%, improve my on time delivery rate by 30%. All these saves were approved by the production head and also by the finance department. When I conducted the workshop and training sessions, I certified more than 50 employees as greenbels facilitating cross functional projects that further embedded six Sigma practices throughout the organization. I would also like to highlight that while I was mainly working in manufacturing, I also applied Lean Six Sigma in service oriented projects like streamlining customer support workflow, where we reduce the ticket resolution time by 15%. I would also want to demonstrate that I have an ability to do problem solving and continuous improvement. I had established a continuous improvement committee that meant monthly to identify process inefficiencies.Thise initiatives led to several small projects that collectively saved up to 1 million annually. I was also awarded $1,000,000 club member. So you can see that I have experienced across different roles as leading in six Sigma. I hope you have liked what I have covered. 41. Hypothesis testing Part A: Within Six Sigma, one of the most commonly used tool is to test whether a change has made a difference in your process. That is called hypothesis testing. Hypothesis testing is a statistical analysis where you are checking if the result is statistically significant. As you predicted it. You're using data from your process to test a claim about the population parameter. How do you conduct hypothesis testing? Let's understand that. You conduct hypothesis testing because you want to make data driven decision. You want to be able to provide an evidence to support your opinion. And typically, that opinion is that you have seen a change within your process. But now you want to use data to support that there actually has been a change. You're going to use statistical significance to quantify or show whether or not that change is significant. You're using sample data and drawing inferences about the population based on that sample data. Now let's understand with an example. You should use hypothesis testing within your Six Sigma projects to determine whether a process improvement effort that you have made has actually reduced the proportion of defective items, or you can use a hypothesis testing to investigate a claim that a new accounting software package has reduced the processing cost. Let's understand one more example where you could use hypothesis testing to validate whether a loan processing time at a bank has decreased since the introduction of an online application process. Within six Sigma, you start with a defined phase where you determine that issues, whatever issues are there within your process, you set up a problem goals and establish a business case for undertaking a six Sigma project. Then within the measure phase, you actually start identifying the key variables or factors that are impacting your process. In the analyze phase, you look closer to that factors to determine if there is an impact on the mean of your output or a variation of your output. Hypothesis testing typically comes into play in the improve phase, sorry, in the analyze phase of the DMAc and the improve phase again, as you implement improvements or changes, and then you go back to the analyze to determine if you achieve the intended results. There are several different types of hypothesis testing. The first type is a one sample hypothesis testing where you're looking at the mean, that is the average. For example, if you want to examine the difference between the mean of your process and the industry standard based on your distribution, you want to know if there is a statistical significance between or a statistical significant difference between the mean of your process and that of the industry standard. You can also do a two sample hypothesis testing of mean, where you're comparing the mean of one process with the mean or the average of another process. Then there are several more advanced statistical analysis for hypothesis testing, such as paired T test, the test for proportion, test for variance and ANOVA. That is analysis of variance. The test of variance and ANOVA are used when you're trying to reduce the variation within your process and to see if there is a difference in the variation of your process once you have made the change. 42. Hypothesis testing Part B: We can also do two sample hypothesis testing for me, where you're comparing the mean of one process with the mean of another process. Then there are several advanced statistical analysis for hypothesis testing, such as Pat test, test of proportion, test of variance and ANOVA. ANOA stands for analysis of variance. The test of variance and ANOVA are used when you're trying to reduce the variation within your process and see if there is a difference in the variation of your process once you have made a change. The objective is to reduce the variation. In hypothesis testing, one of the first thing that you can set up in your hypothesis is that what you are trying to prove or disprove, you can call that as a null hypothesis or and an alternate hypothesis. Your null hypothesis expresses the status quo. If you think about the null hypothesis, it assumes that any observed differences are due to chance or random variation. Typically with a null hypothesis, which is your H naught, we call it as H naught represented as H followed by a small zero, you are setting it up for two values being equal to each other and one being less than or equal to another, and one being greater than or equal to another. It assumed that any observations are the result of chance or random variation. With any alternate hypothesis expressed as alternate hypothesis, this is what you are trying to test or prove. With the alternate hypothesis, you are assuming that an observed differences are real and not due to chance or any random variation. So this is typically where you are changed or changed something in your process, and you're trying to see if that now makes a difference in the average or the mean of your output. Your alternate hypothesis needs to be mutually exclusive from your null hypothesis. Remember it? In other words, you want to make sure that you are testing these the test that you have to fall in one category or the other. With your alternate hypothesis, you're testing for the opposite of the null hypothesis. So you will be testing that the two values are not equal or the one is greater than or less than equal to the other. In your hypothesis test, there are two primary goals. First, you want to see if there is a difference between the two values. The outcome of your hypothesis test could be that you reject your null hypothesis in favor of your alternate hypothesis, which is essentially meaning that the results are significantly statistically significant. The second goal would be to fail to reject your null hypothesis. This means that you do not have enough statistical evidence and hence you fail to reject the null hypothesis. You're stating that there is no sufficient evidence to claim that the null hypothesis is invalid and that the alternate hypothesis is true. For example, in a hospital, you could set up a null hypothesis that there is no difference in the processing time based on the improvements given by the six Sigma process, and whatever improvement you are seeing is just a random variation or chance. Essentially, that your improvement efforts have not made any difference on the actual floor. So your null hypothesis would state. There is no change based on the process improvement effort. The alternate hypothesis would state. The process has actually improved based on your six Sigma efforts. If you know that the average waiting time at an outpatient clinic at that hospital is 10 minutes, then you would set up your null hypothesis as equal to 10 minutes your alternate hypothesis will be not equal to 10 minutes. It is important to note that you are testing to see if there is a change, and that's why you set up a null hypothesis and an alternate hypothesis, which is equal to and not equal to because the change could be either a reduction or an increase in waiting time of your patient after your six Sigma project. It's also important to note how you can present the results, which may not sound natural at the first level. But as we go further, you will understand it. You state your results in terms of null hypothesis. For example, you would state, either you reject the null hypothesis or you fail to reject the null hypothesis. As a six sigma professional, it's important to understand that the difference between statistical significance and practical significance. Have you heard these words statistical significance and practical significance? If yes, please write down in the comment section below. So coming back, we want to understand the difference between statistical significance and practical significance in hypothesis testing. When you think about a practical significance, you really need to understand the rationale for the decisions. Depending upon your organization, even a small value might be very meaningful to the business. For example, if you think about the healthcare or air safety, where the health care or human health or safety or a catastrophic loss could be involved, then a small change might be very significant. So it's important to understand the test limitations and how those relate back to the rational for decision making. In addition, you need to understand what your business goals are because there might be seemingly large difference that might not be much to some organization, but might be very important to your organization. So you need to consider the business goal and how these changes relates back to what you are trying to achieve for your organization. When you are first testing for practical significance, there are several key questions that you need to ask. First, you need to understand will there be an appreciable gain or change in your process? When you are thinking about practical significance, it relates back to the process, to the organization itself, and how it is going to impact the organization based on the changes you have brought in by your project. In addition, with hypothesis testing, you are using a sample to make an inference about a larger population. Depending upon your results, you need to go back and look at some things. What is that? The first one is what's your sample size? Two, was it significant? Three, if you have a smaller sample size and you are trying to infer about your population, then you might have to take into account or rethink that are your results telling you the actual story? Because sometimes it could be too expensive to have a large population size. You also need to think about how easy the change is to implement from a practical standpoint, when thinking about the level of significance, you need to assess that impact will be on the business and how expensive or easy it will be to implement. In addition, since you're using samples to make inferences about your population, you need to understand whether the difference in the sample have a real meaning. Also in terms of your sample size, what is a representative sample? Another key question is, is there a strong financial case for the change? Just because something is statistically significant does not mean that you are making any change that is going to be cost effective or make the business sense for your organization. Then knowing that there is a change could also need to think about how a potentially small value may have a significant improvement in your process and vice versa. Now, when you establish your practical significance, there are three key areas that you need to consider. Number one, is your confidence interval, and it goes back to your business case. What do you really need to have in terms of your confidence interval to achieve a specific level of confidence in your process improvement effort? It's important as a six Sigma professional that you present a complete picture of the test results and let the business manager decide based on the organization and the business requirement. This allows management to consider the organization and the process knowledge to make an educated decision. You also need to choose the sample size carefully. A small sample size means there is possibility that a large difference won't be detected deeming statistically significant. If you choose a larger sample size, you might find a very small difference, but it could be interpreted as statistically significant, even though it is not practically significant. Hence, it's important to think about an important parameter called strength of significance. This is your P value that is going to be compared with your Alpha value along with your actual difference. Between what you are comparing. With hypothesis testing, you're using a sample to infer information and the data about your population. So it's important to understand sample estimates of population parameter. There are several data characteristics used within hypothesis testing, the standard deviation and the variance. Population parameters are always represented with the Greek letters. For mean, we use Mu. For standard deviation, we use the Sigma sign. And for variance, we use the Sigma squared. When you come to the sample statistics, it is represented by the alphabets. For mean, we represent it as X bar. For standard deviation, we represented it by the small S. For the variance, we represented by S square. This is useful to understand the difference between these values because they are used to find a single value to estimate the population parameter. So let's explore an example using the point estimate in our next video. 43. P Value Simplified: You have probably heard scientists quote P value whenever they report the results from their experiments. But what exactly is the P value? Let me clearly explain what is P value. P value is a short form of probability value. The P value is a number that can be any value 0-1. But what exactly does this number represent? The official definition of P value is quite difficult to understand. A P value is the probability of obtaining the observed difference or a large one in the outcome measured, given that no difference exists between treatment in the operation. The best way to explain what P value is is to use an example. Let us say you want to perform an experiment to see if a new type of weight loss drug drug X causes people to lose weight. You randomly sample a collection of volunteers, randomly assign them into two groups group A and group B. You give group A a placebo, which contains no active ingredients, making them the control group. You give group B the new drug drug X. The participants are weighed at the start of the study and at the end of the study. This way, you can determine the body weight difference. At the end of the study, you find that the group A average body weight differs is 0 kilograms, meaning they did not gain or lose any body weight. The group B body weight difference is a negative one kg. So on an average, they lost 1 kilogram of weight. Does this mean that the drug works? Now let's state the null hypothesis. To determine this, we first ask ourselves what would happen in a world where the weight difference in the volunteer who receive drug X is the same as the weight difference in those who did not receive the drug X or received the placebo. This is where the null hypothesis comes in. Usually, the null hypothesis states that there is no difference between the groups. For example, our null hypothesis is that the weight difference in those who receive drug X is the same as the weight difference for those who did not receive the drug X or who received the placebo. Now we can ask questions to ourselves. If this null hypothesis were true, what is the chance or probability of discovery that the 1 kilogram reduction or more in the body weight in those treated with drug X from our sample. This probability P value measures the strength of evidence against the null hypothesis. You can think of this as a court trial where the defendant is the innocent until proven guilty. In this case, the defendant is the null hypothesis. The smaller the P value, the stronger the evidence against the null hypothesis. Statistical hypothesis test. Scientists use what is known as statistical hypothesis test to determine the P value. Common examples include Student's T test, one way ova test. Since this is the top line overview, I will not bombard you with a lot of statistical jargons. But instead, let's pretend we have performed a statistical test using our data. After giving our data to the statistical test, we get a P value in return. Let's say, for example, the P value is 0.02. It's worth mentioning that the P value is a fraction, but it may be easier to convert this into a percentage to understand the concept better. So the value of 0.02 would be 2%. In simple terms, I have multiplied it with 100. But what does this 2% actually mean? Essentially, this means that if the null hypothesis were true, in other words, if the two population means were identical, then there is a 2% chance of observing a difference larger than what we observed in our sample. In our example, it would translate to in a world where the weight difference in those who receive drug X is the same as the weight difference in those who received the placebo. There is 2% chance of observing a weight loss of one kg or more between our sample groups. But with respect to two person chance means that for every 50 experiments that one in every 50 experiments would give such a result. So what is the coincidence? How would this happen? That accounts to the 2% p value. In simple terms, 2% can be accounted for any random noise. But what does it mean? What does this 2% of P value account to? In simple terms, this 2% can be accounted for any random noise. Let's elaborate this. What exactly is random noise? There is quite a few things that we can impact by P value. Some of these factors are collectively called as random noise. One type of factor is that the contributes to the random noise, especially in human studies. It is a coincidence of random sampling. For example, humans who exhibit large amount of variation due to genetic or environmental influence. If we relate this back to our example, some humans may contain an unknown genes that speed up their metabolism and causes them to lose weight more than others without those genes. When the recruiting volunteer in our experiment, we did not perform any DNA analysis. We randomly took people who came as volunteers and assign them into two groups, group A, the control group, and group B, the drug group. So there was no way of knowing who is the carrier on the genes. Imagine a situation where by pure coincidence, more volunteers with high metabolism genes were placed in group B compared to group A. This scenario would favor group B. Ultimately, you may see that with pure coincidence and random sampling can knock off the effect of the P value. To summarize, P value is a value 0-1. This P value represents the probability of obtaining the observed difference in the outcome measured to the sample, given there is no difference between the treatment in the population. In other words, when the P null hypothesis is true and there is some random noise that can affect the P value, the common example of random noise is the coincidence of random sampling. 44. Hypothesis testing sample size for TOH: Sample size and its role in the power of test. Sample size is one of the most important factor to consider when discussing the power of a test. As a six Sigma professional, it's critical to pay close attention to your sample size whenever you're conducting a hypothesis test. Sample size is not only one of the most significant factors, but it's also something that can easily be controlled. As your sample size increases, the power of your test also increases. However, it's equally important to calculate the correct sample size. This decision should be made. Or if you choose too large or a sample, you will waste a lot of time, resources, and money. On the other hand, if your sample size is too small, your risk of obtaining inaccurate results increases. This goal is to balance between too many and too few samples and determine the right amount. This can be done by calculating the appropriate sample size. As part of this calculation, you need to consider your margin of error. This is denoted by the letter E, which is calculated using the critical value, standard deviation and sample size. The objective is to minimize your margin of error. The formula can be rearranged to solve for N, N stands for the sample size, which represents your sample size. This is important to note that N should always be rounded up as it ensures that you meet your desired level of confidence. For example, if your result is 233.1, you should crowd it out to 234. This ensures that your confidence level accuracy is taken care of. Let's take a sample size example, a TV viewing case study. Let's explore an example of how to calculate the sample size. Suppose you are conducting a study for a local cable TV provider or an OTT platform. You want to understand how much time families spend watching TV each day or each week. To ensure that the study is a representative sample, you need to calculate the correct sample size. Here, the assumption and the values used in the calculation are confidence level, which we set as 95.95%. Margin of error denoted by E, let's assume 2 hours a day. Standard deviation that is Sigma is 22 hours a week. Based on a recent survey that we conducted. The Z value for a two tail test at 95% confidence is 1.96 which we got from the table. Using the sample size formula, Z value for a two tail test at 95% confidence level it's at 1.96 using the sample size where N is equal to Z into Sigma divided by E whole square. So if I substitute the value 1.96 into 22 hours divided by two, this whole square. This is 464.833, so I would take approximately 465 families. So I always round up so you can collect data from 465 families. This means you can be 95% confident that the sample mean always falls within 2 hours of the true population when we are getting a weekly TV viewing. Hypothesis test consists of five important steps. Establish your hypothesis, define your null hypothesis, that is H nut. This assumes that there is no difference or no change. Alternate hypothesis is denoted by H one or H A, and it assumes that there is a real difference or an effect. This includes four critical elements. Select the appropriate test, select the appropriate test statistics based on your test type. Here, I want to choose the Alpha value at 5% to ensure that my confidence level is 95%. So I set the Alpha 0.05. Now let's determine and collect an appropriate sample size. We conduct with an assumption check that normality, the data is normal and there is a assumed variance in the data. So to calculate the test statistics, we use the samples data and compute the test statistics. Typically, we get the Z value or the T statistics based on the test we have picked up. So if you use a Z test, then your number of samples should be greater than 30, and you use a T test when your sample size is less than 30. We determined a critical value or the P value. Choose one of the two methods, a critical value method where you use a table to determine the critical value based on the degrees of freedom and the Alpha level that we have agreed. P value method is directly used for calculating the P value and we compare it directly with your Alpha level. The choice is yours. Now, don't worry, Excel can do it all for you. Now let's interpret your results. Using the critical value method, what we are finding is that if your test statistics fall within the rejection zone, that is, you reject the null hypothesis because the P value is low. If it falls outside the rejection zone, it means it is in the acceptance region. So we fail to reject the null hypothesis, stating that there is no difference. Using the P value method, we compare the P value with the Alpha value. We reject the null hypothesis if P is less than Alpha. If P value is greater than Alpha, then we fail to reject the null hypothesis. Choosing the right type of test we have one tail test, right tail test, and left tail test. So you have right tail test, where the null hypothesis states that the u is less than equal to the population average. Alternate hypothesis says that the sample mean is greater than the population mean. We reject the null if your test statistics is greater than the critical value. For a left tail test, null hypothesis, Mu is greater than equal to Mu naught. Alternate hypothesis is Mu is less than unaut. We reject the null hypothesis. If your test statistics is less than the critical value. In both cases, you can check whether your test statistics fall within the rejection region or not. And that can be determined with the help of your Alpha value also. So if it does, you reject the null, otherwise you fail to reject it. Remember, never accept any of the hypothesis. Two tail test. We use a test when we are testing whether a change has happened. It could be an increase or a decrease. Null hypothesis is null, there is no difference. Alternate hypothesis is there is a difference. The rejection region is existing on both the ends of the distribution. If the test statistics fall outside the central region, that is the acceptant region, we go ahead and reject the null. If it falls within the acceptant region, we fail to reject the null. Let me know if you understood the concept, are you need more examples by giving your comments in the discussion section below. 45. Hypothesis testing Types of error: In hypothesis testing, we are taking information from a dataset. It's our sample data, and we are trying to make inferences about the population. But statistically, what we are trying to do is to make decisions based on this information. And hopefully that decision aligns with the true state of nature. What is actually occurring on the floor? Ideally, when hypothesis testing is done, we are trying to get accurate enough information that you can make correct decisions. So if your null hypothesis is false and you want to reject the null hypothesis and arrive at that conclusion. In addition, if your null hypothesis is true, you want to make the correct decision by failing to reject the null hypothesis. Unfortunately, that's not always the case, and different types of errors can occur. In this topic, we are going to explore type one error, also called as Alpha risk and type two error, which is called as the beta risk. Type one error is the Alpha risk. Type one error occurs when the true state of nature is that your null hypothesis is true, but you reject it. This is like a false alarm. At the risk, you are willing to take that when rejecting the null hypothesis, even though it is actually true. Sometimes this is referred to as producer's risk because it's the risk of assuming that the product is defective when it is actually good. This is resulting in discarding a perfectly good product. This is a risk the producer takes. The common value for the Alpha is 0.05, which means that there is a 5% chance of committing a type one error. It's important to understand the difference between your significance level, that is the Alpha value and your confidence level. When plotting your values to determine the significance, you use a critical value, and this value serves as a threshold that separates the acceptance region from the rejection region in your test statistics, the region of acceptance includes the set of values for which you fail to reject the null hypothesis. The rejection reason includes values for which the null hypothesis is rejected. Depending on where your test statistically falls within either the rejection zone or the acceptance region, you make your decisions. This is all based on your Alpha value or significance level, which again is typically 0.05. Your confidence level is calculated as one minus Alpha. So in this case, it's 95%. Let's take an example of a loan processing time. This example will give us an understanding. It involves processing loan on time. The director of a consumer loan department of a retail bank claims that the average loan or processing time is 8.9 days. However, the process improvement team believes that the processing time has changed in the recent month due to automation efforts. The Six Sigma team wants to test the hypothesis with 95% confidence that the current processing time is less than the claimed 8.9 days. The team collects a sample of 20 loan and understands the processing time for these 20 loans and sets up the data to test whether the current average processing time is now less than 8.9 days. Since they are testing whether the value is less than or a specific number, it is called as a one tail test for the mean. In this case, the Alpha value is 0.05. This means whether there is a 5% chance to conclude and reject the null hypothesis when it is incorrect. The confidence level is one minus Alpha, which equals 95%. This represents the 95% confidence that the population mean falls within the confidence interval. Now let's understand the type two error, the beta risk. In addition to the type one risk, Alpha risk, we also have a type two error, also called as a beta risk. The most commonly used beta risk is set at 0.10. Beta risk refers to the risk of failing to detect a defect or a difference when it actually exists. For example, it is like failing to identify a defective product during the quality inspection and then shipping it to the consumer. That's why it is sometimes referred to as consumer risk. It's important to understand that alpha and beta are irreversible and they are related. It is if you're reducing the Alpha, you indirectly increase the beta and vice versa. So what is power of test? Another key concept in hypothesis testing is the power of test. The power of hypothesis test is the probability of correctly rejecting the null hypothesis when the null hypothesis is false. In other words, it's the likelihood of making the correct decision when the real effect exist or the difference exist. The power of test is calculated as one minus beta. The higher the power means the greater the chance of detecting a true effect. The goal is to improve the likelihood of finding a significance effect when one exists. Four factors that affect the power of test. Number one, sample size. As the sample size increases, so does the power of your test. Increasing the sample size is the best method and the most effective way for increasing your test power. A larger sample size gives you more reliable estimates, reduces your uncertainty. The second is the population differences. The greater the difference between the two population then means there is higher the tests power. Larger differences are easier to detect. Smaller differences reduces the power because there is the distribution that may overlap. The third thing that is there to increase the power of the test is the variability or the standard deviation. Less variability within your sample leads to greater power. More variability reduces the power. And therefore, power and variability are inversely proportional. The Alpha level, the significance level. Alpha is the threshold for determining the statistical significance. We compare the P value with the Alpha value. So lowering the Alpha means if you want to reduce it from 0.05 to 0.01, it makes it harder to reject the null hypothesis. Thus, reducing the power, increasing the Alpha increases the power, but it also increases the type one error, so we need to balance it out. So even when two distributions are identical, changing the Alpha value can change the outcome of a test. From failing to reject the null to rejecting the null hypothesis. That's why choosing an appropriate Alpha value is important. To summarize, higher your Alpha value, higher the power of your test. However, increasing the Alpha also increases the chance of making the type one error. Finding the right balance is the key in hypothesis testing. I will see you in the next video. 46. Hypothesis testing Confidence: In this class, we are going to explore an example using point estimates. We are going to take a sample and infer information about the population. Let's suppose that you are conducting a survey for 2000 people from across the country, so you can identify whether or not they are for or against the universal healthcare policy. Based on the 2000 people you have surveyed, you find that 1,100 of those are supporting the healthcare service. The population parameter in this case, is all the people within the country. But the sample that you are having is only 2000 people because that is what you have surveyed. Now, with a point estimate, then it's a proportion of people who are for the universal health care. In this example, the statistic that you have reached based on the sample population is that 55% of the people in the country are for supporting the universal healthcare plan. So that it gives a point estimate that 55% of the population is in the favor of the healthcare facilities. Now, it's important to understand that there are some weaknesses if you use a point estimate. It's highly unlikely that the point estimate you are using is exactly the same as a true population parameter because you're using an information based on your sample data to infer about your entire population. That's why it's important to have a range or an interval over some set of other values that you are using. So you need to use information so that you are able to estimate whether or not the true population mean and standard deviation is most likely to fall within the interval that you have achieved. And this interval is called as the confidence interval. And it's very useful because they provide a better measure. For example, if you're looking at testing the confidence interval, they give you information on the variability of sample statistics and whether two sample originate from the same population or whether the target falls within the natural variation of the process. You can see it by the image on the screen. Let's say you're trying to figure out the likely value of the population parameter and you want a 95% confidence interval or 95% confidence level. You're able to determine that your confidence interval is based on the bean and the variation from your sample statistics and provide you with a confidence interval that it is anything between 9.1 to 9.3 centimeters. This would contain the actual population mean, 95% of the time. There's another example of how you could determine whether the target value falls within the natural variation of the process. Let's say you have a pharmaceutical company, and then you have a new drug that you want to test. The goal of the drug is to treat high cholesterol. You want to be able to determine whether the drug improves the cholesterol level to a healthy target of 200 milligram. So your target value, in this case, is 200 MG. Based on the sample data that you are collecting, you can now set a confidence level of 95% such that 95% of the values should fall within the specified range. Then your confidence interval calculates values 195-210, it would contain 95% of the values. You can now use this information to check whether the target value falls within your confidence interval or not. If it doesn't, then the sample is from the population with a mean that is different from the target value. If the target value does fall within the confidence interval, then you can be confident that the sample is from the population with a mean that is same as the target value. In this case, our target value is 200, which is within our confidence interval. So we can conclude at 95% confidence level that the drug is decreasing the cholesterol level. Meaning the target is 195-210 milligrams. 47. DOE Design of Experiment Part 1: I Design of experiment DOE. Let's understand DOE, one of the critical things in a Black Belt project. It is a structured statistical method to make systematic intentional changes to the input variable in order to measure the impact on the output variable. It is also taught as a response variable. Even without a clear dependency between the input and the output, DOE helps uncover the relationship. They will also talk about the interactions and the significance of different factors. This makes DOE highly valuable in a six Sigma project, especially because there are often multiple factors. They are also known as Xs. That can potentially impact your process outcome. That is the Y. Y is a function of X. Why should we use a DOE? The purpose of using a DOE is to reduce the number of input factors which are affecting the output. We identify the most critical ones that are significantly affecting our output. We try to optimize the process by determining the ideal settings for these factors. We validate that the optimized setting results in a consistent improved performance. By narrowing down to the key factors, you can manage or experiments more cost effectively and efficiently. Effectiveness and efficiency is very important. Where is DOE used in a DMAC process? That could be a question. We use DOI typically in the analyzed phase of the DMAC where we begin to identify and verify the cause and effect relationship between the input and the output variables. In the improve phase, we use the same experimental data to determine the optimal factor settings and implement those changes. Let's understand the mnemonic for DMAc placement. Analyze to find the factors and improve using experiments. I repeat, analyze to find the factors and improve using experiments. Let's understand with a real life example. Suppose you are at a Barista at a coffee shop and you are trying to optimize the customer satisfaction level. For your output, why using the factors like coffee temperature, which is hot or extra hot, milk, froth level low or high, serving time under 2 minutes or over 2 minutes, DOE will help you determine which combination of these input factors that are your s that leads to the highest satisfaction score. There are different types of experiment within DOE. And the three main types of experiments in design of experiments is a screening experiment. That's the first one. It is used when you have multiple input variables, but you don't know which are most important or which are most important for my project. The purpose is to screen out insignificant variables and retain the critical few. The goal being reduce the number of factors from many to a manageable two or three, which is greatly influencing the output. Screening experiment helps reduce the noise, increases the focus, and think of them as a short list phase. The second type of experiment is called as an optimization experiment. This is used when screening. You want to find out two or three variables that matter the most. The purpose of this experiment is to find the best combination of factor levels that can yield the desired output. You adjust the settings low, medium, and high for each of the factors to maximize or minimize the response. The third type of experiment is called a robot nest or a confirmation experiment. We also call this as a confirmation test because we are using this to confirm or validate that our new optimized settings are stable, reliable, and it ensures that the external changes like temperature, humidity, et cetera, don't significantly affect your outcome. Think of it as a stress testing. Of your improved process. Types of experimental design in DOA. There are three key types of experimental designs. One factor at a time, that is called as O fat. It is used when we want to change or analyze only one factor or one variable at a time, keeping all the other variables constant, but it's very expensive. Let's understand it with the help of an example. You want to test that a material weight has two levels that is high and low, so you go ahead and design an experiment, which is simple, but it is inefficient when you have multiple factors that are involved. Typically, what happens is there are four experimental runs. The limitation of one factor at a time is that it doesn't take into account the interaction effect between the variables. Hence, we avoid it. The second is a full factorial design. It is used when you have multiple variables, and each of these variables you want to test for every possible combination. Let's understand it with the help of an example. Three factors we have their material weight. Can it be high or low? Material density, it can be high or low. Temperature, it can be high or low. So with its three factors at two level each, we will have a total number of run that is eight runs two to the power of three. How will we design this experiment? We will test all the combinations, giving a complete interaction insight. It's more accurate, but it is costlier and time consuming. Hence, we come to the third one, which is called a fractional factorial design. It is used when you want to reduce the number of experimental runs while still gaining insights about your factors. Again, let's understand with an example. We have the same three factors that we used. Each of these three factors have two levels. Instead of eight runs, we will do only four runs. Now, which four runs you have to identify, that is called as a subset of a full factorial design. It is cost effective, it is faster, but sometimes we may miss some interaction. So the mnemonic for this is OF F for you to remember, O stands for one factor only. F stands for full factorial design, all combinations, and the second F stands for fractional factorial design, which is a subset of the combination. If I have to summarize the DOE application, the simplified roadmap of how DOE fits into six Sigma in the defined phase, sorry, define the output of the goal and the list of possible Xs. Screen the factors to reduce the number of optimize the factor experiments, validate via robustness testing, standardize and monitor. If I have to summarize this, the experiment types is you have a screening experiments which can identify critical few inputs. Number of factors can be many, and the purpose is to understand or analyze In the optimized phase, we tune the settings of key factors. Maybe we take two or three factors. We use the optimized type of DOE during the improve phase. Robustness or a conformation experiment is to ensure that the process stability and repeatability. Again, we take two to three factors, we use it during the control phase of our project. But summarize the design of experiment OFAT, which is simple test with one variable at a time. Number of runs are low. Pros is it's easy to implement, but no interaction can be detected. Full factorial design is all the combination of all the variables. Number of runs are too many or high. It's most accurate and detail, but it cost a lot of money and resources. We go to the third one that is a fractional factorial design. Limited resources, fewer combinations, number of runs are medium, cost and time efficient, but may miss certain interaction info. 48. DOE Design of Experiment Part 2: Let us now understand the benefits and the components of DOE design of experiment. DOE offers several significant advantages in the process improvement world, and it also helps in data analysis. So why should we use DOE Number one, it's about efficiency. You must test you can test multiple input factors simultaneously, making it far more efficient than testing each factor one at a time. It's cost effective because fewer runs is equal to reduced cost, especially when using fractional factorial design. DOI are very insightful. By testing combinations, we understand the interaction between variables. We understand the relative importance of each input factor on the output. And we can also use DOE for creating predictive models because DOE enables you to analyze large dataset and build prediction models to forecast the outcome based on the inputs. Let's understand with an example, loan processing. In this example, let's consider a bank's loan processing system. The response variable is the loan processing speed, how quickly a bank is able to process the loan application. The input factor or the excess is the experience of the loan processing staff, modes of application, is it online or in person? Is the loan amount, whether it's a large amount or whatever, the number of applicants in the loan, is it a co applicant? Is it a single applicant? Using DOE, you can change the levels of these factors high versus low, and you can even measure it at the speed of loan processing. And you can optimize the process accordingly. Let's understand an important concept called factors and levels. A factor is any input variable into the process. A level is a value at which the factor is tested, high versus low. What is important for us is to understand the levels you choose should be distinct enough to detect a measurable difference in the response variable Y. If we look at the table, if you have a two level, it means high and low settings. For example, staff experience one year versus ten years, so it's a significant difference. Then the assumption is that there is a linear effect. Sometimes we might have a three level. Which is high, medium and low temperature, example, 100 degrees, 125 degrees, and 150 degrees centigrade. It means there is a non linear effect. So with this, we can understand that you are free to choose the factor levels and study the response accordingly. Why understanding the response variable Y is important. The response variable is a dependent variable. It means that Y is a function of X. So it is measurable. You can measure it quantitatively or categorically. It is sensitive to change in the input factors, and it is aligned with your business goals or the business objective why you are running the business. For us to understand this more clearly, let's go back to our loan processing example. Our processing time in minutes, defect rates in percentage, customer satisfaction score one to five. Avoid qualitative or subjective output unless they are converted into measurable scales. Otherwise, you'll not be able to get the output. Now we need to understand the difference between controlled and uncontrolled factors. Control factors are those factors which you can manipulate during experiment. Example, I can change the speed of the machine from high to low. Uncontrolled factors are the external conditions that cannot be changed but should be measured and accounted for. Example, the ambient temperature. If an uncontrolled factor have a significant effect, they must be recorded and included in the analysis. Now let's understand what are treatments and runs? Each run is a unique combination of input factor. Let's say you are studying a tensile strength of an iron bar using three factors, material type A versus B, processing time, 30 minutes or 60 minutes, temperature 100 degrees centigrade versus 150 degrees centigrade. So we have three factors and two levels each. So the total number of runs in a full factorial design is two rays to three, which is eight runs. So let's understand the run example. As you can see in this table, we have runs where we have given the settings which can help us design that in how we will be setting up the material temperature and the time. Each run gives a data point for analyzing how the input combination can affect the output. A mnemonic for this or an acronym over here like flow can be remembered to remember the critical components of the DOA. So the flow FLOW stands for factors which are your input variables or independent factors. L stands for the level high, medium low, O stands for the output or the response variable, which is a dependent variable. And W is what you want to change in each run or a treatment configuration. So let's do a quick recap of what we have learned. So we have factors and input variable. We have levels, we have response variable, we have control factors, uncontrolled factors. So final final note before we jump on to the next video, is that using screening. To identify key factors, we use optimization to tune the factor levels and we use robotness testing to ensure that the process performs consistently under varying condition. Design your experiment very carefully, avoid choosing factor levels that are too similar and you may mask the real effect. I will see you in the next video. And 49. DOE Design of Experiment Part 3: Let us now understand the purpose and the process of DOI. DOI is a structured approach that helps you understand how input variables affect or impact the output variable or the response variable. Let's explore this with the help of a practical example. Suppose you have a drilling process and your goal is to achieve precision in a whole depth. There are multiple input factors like what is a drill speed, what is the type of drill you are using, and what is a material hardness. You want to understand how each of these factor is going to affect your output, that is the drill hole. How DOE can help. Using DOE, you can choose different alternatives. For example, you can evaluate two suppliers of drill bits based on the quality and the cost. Identify some key input factors. Determine which among those several variables actually impact drilling precision. We want to achieve specific performance goal. So set your design to a target or a specific value. Example, extract depth tolerance, reduce the variability, reduce the fluctuation around the target performance. Example, the depth consistency. How can I improve the robust nest? We ensure that the process yields consistent results over time. We want to optimize the process setting. Find the most precise and cost effective settings for your key factors. The six steps of a DOE process is typically conducted in the following manner. Number one, define the goal, clearly define the objective of the experiment. Example, minimize the porosity in the casting. Number two, identify the key elements, define measurable response variable or the output variable, the Y. List all your input factors, the X factors. Decide how you will measure both the input and the output. Choose the experimental design. Based on the number of factors and the levels, you can decide whether you want to go for a full factorial design or a fractional factorial design. In a full factorial design, you will test for all the combinations. In a fractional factorial design, you will test for a subset. You are free to choose between two levels versus three level design based on linearity or non linear effect. If I go back to our casting example, three input variables and two levels, it means I will have eight experimental runs. So number four, run the experiment. Perform the experimental runs by setting factor levels and collecting the samples. This ensures consistent measurement and process control during each run. Step five is to analyze the data that you have achieved after conducting this experiment, and you have to determine what are the optimal settings for your factor by analyzing the main effect, the interaction effect, and the variability. We will now verify the results. That's the step six by confirming the improvements by running the part using optimal settings. Make sure that the results match the expectations before implementation. A detailed example of casting process. Our goal is to minimize porocity in a metal casting process. The elements that we are using or the response variable Y that we want to study is the porocity level, and it is measured using the caliper device. The factor is X, where we are deciding the pouring temperature, the mold hardness, the silicon content. So I'm take them three factors. For each of these factor, I have two levels. I decide it as high and low. So now my design is three factors and two levels, which is equal to eight runs in a full factorial design. Now, while running the DOE, the team runs all the eight combinations of settings. And for each of the run, three samples are collected and measured. In the next step, we analyze and verify. After analyzing the data, the team identifies the optimal level for the factors like pouring temperature, the mold hardness, and the silicon content. Pick those ones and the process is run at these optimal settings to confirm that the porosity is indeed minimized. The key learning point is that X factors are your input variable that affect the output. Wife response is the output being measured. Runs is a unique combination of factor levels, and levels are the settings of each of the factor like high and low or ABC. Verification is the testing to confirm that the optimized settings actually deliver the desired results. We can try to remember this using an acronym called as DDAv W D stands for define the goal, I stands for identify the factors and response. D stands for design the experiment, R stands for run the trials, A, analyze the results, and verify the improvements. So with this, I will see you in the next video. 50. DOE Experimental Errors: When we are doing a design of experiment, we also experience experimental errors. One of the key challenge in a DOE is managing these experimental errors. The variation that is observed in the output, that is not due to change in the input factor, but it's due to some random things. There are two main types of experimental errors that happen. Systematic error, it means there are consistent repeatable errors that occur every time an experiment is run. They are often caused by faulty equipment or a miscalibrated device. Measurement instrument are not calibrated enough. Error in how the data is handled, improper use of experiment by the experimenter. Example, if the weighing scale is miscalibrated and always adds 1 gram, every measurement is bias by a same amount. And this type of error technically introduces a bias, which is defined as bias is observed value minus the true value. And this can be measured against a known calibrated standard. Let's understand some examples of the bias. If your true part weight or a certified standard is 1.346 grams, but your instrument consistently measures is at 1.446 grams. The bias in this case is plus 0.1 gram. Another form of bias can arise in a clinical trial. Scientists may unintentionally select healthier patient of one group, and sicker patient might self select into a group which skews the result. The second type of error is a random error. These are unpredictable unknown variation, typically caused by external environmental factors. The sorts of random errors include electrical noise in electronic measurement devices, variation in ambient temperature, humidity, vibrations or operator fatigue. A slight fluctuation in heat can treat ovens and thermal chambers in a very different way. These errors are not consistent and can change from run to run of your experiment. So the important point to note over here is that random human mistakes like recording a wrong number or not considering the experimental errors, but an operator error. However, if the limitation is in the resolution of the measuring device, this is leading to a recurring inconsistency, then it becomes part of an experimental limitation. Controlling an experimental error. If it's a systematic error, you can regularly calibrate the instruments, use an SOP that is standard operating procedures. Train your operators thoroughly. How do we control random errors? An average multiple measurements to increase the sample size per run, use a blocking and randomization technique. This will help you take care of the random errors. What about the noise factors or the lurking variables? Uncontrollable causes of errors fall into two categories. These are noise factors and lurking variables. Noise factors are those variables that cannot be controlled, but they affect your process. Let's understand a noise factor with the help of an example. When you open a pizza oven during a baking, it releases heat and lowers the internal temperature. This is affecting the cooking time. Lurking variable, variables that may not have identified, but influence your experiment indirectly. For this, let's again, understand it with the help of an example, a miscalibrated scale influencing all weight measurement without your awareness. Both the types of error causes variation and bias and must be considered when designing your experiments. Balanced design in DOE. A balanced design ensures that all the treatment combinations have equal number of observation. This is critical for accurate statistical analysis. Let's understand with the help of an example. We have two factors and two levels, so two rays to two, we have four runs. So let's say we have a factor A, which should be at either high or low, and we have a factor B, which should again be at a high under low. Here, each factor is tested twice at low and twice at high. This is a balanced and a full factorial design. An unbalanced design is a design where not all the combinations are studied or they are not tested. Some combinations are repeated more often than the others. The problem over here, let's understand with the help of an example, the run. Look at the table on the slide, it very clearly says that it's not a balanced design. This setup does not cover all the combinations and it introduces bias and it weakens the conclusion. It limits the ability to analyze interaction effect. Randomization in DOE is very important. Randomization is a process of shuffling the order of the experiment. This shuffling of the experiment runs is to minimize the effect of the bias, and there is an effect on the learning curve the environmental drift. The purpose here is to ensure that the treatment combinations are performed in a random sequence. This is improving the statistical validity. So when randomization is happening, the process set up allows flexible sequencing. And when the learning curves or the time based variables are there like the machine warming and cooling, it can influence the result. When you do not randomize and there are some physical constraint, make it impractical for you to randomize, like adjusting the casting furnace temperature up and down repeatedly can be a painful task. So let's understand randomization with help of an example, a federal health study scenario. We are evaluating two types of cancers. We are evaluating two types of cancer awareness ad, a message type A and a message type B, two levels of screening resolution, 1,200 pixels and 2,400 pixels. Two level of exposure duration, 2 minutes versus 5 minutes. Now we have three factors and two levels. Totally eight total runs. The standard order is not randomized, is run one run two run three till run eight. This introduces the risk of machine warming up or people looking at the same ad repeatedly. Or it can create operator error, and hence it's important for us to randomize the order. So when we use random number generation and then shuffle the runs, for example, the first run can be run six, the second run can be run three, the third run can be run one, and so on. This helps the distributed bias and the noise evenly. So to summarize the different types of errors that occur in DOEs, systematic error, which is caused by the faulty experiment. The control method is to calibrate SOP, and so on. Random errors are environmental changes, noise factors are uncontrolled but known variables, lurking variables are unknown influenza. The key takeaway is that a systematic error is still predictable and correctable. A random error is unpredictable but must be averaged. A balanced design is equal to equal representation of factor levels. Randomization is equal to the spread out by as making conclusion more reliable. Always assess the feasibility when applying randomization, especially in complex physical setups. With this, I hope you got a clarity of DUI experiments and I will see you in the next video. 51. Pearsons Corelation simplified: Yes. Directional and non directional hypothesis. With correlation analysis can be tested for directional or non directional correlation hypothesis. What do we mean by non directional correlation hypothesis? You are only interested to know whether there is a relationship or a correlation between two variables. For example, whether there is a correlation between age and salary, but you are not interested in the direction of the relationship. When you are doing a directional correlation hypothesis, you are also interested in the direction of the correlation, whether there is a positive or a negative correlation between the variables. Your alternate hypothesis is then example, age is positively influence on salary. What you have to pay attention to is in the case of a directional hypothesis, you will go with the bottom of the example. So you will go telling that, is there a positive influence or not. So normally we say there is no correlation and there is a correlation. But here we'll say there is no correlation, and the alternate hypothesis we say that there is a positive influence on the salad. Right? So now let's go to the next part. That is Pearson's correlation analysis. With a Pearson's correlation analysis, you get a statement about the linear correlation between the metric scaled variables. The respective covariance is used for the calculation. The covariance gives a positive value if there is a positive correlation between the variables and a negative value if there is a negative correlation between the variables. The covariance is calculated as CV or covariance of X comma is calculated using the formula given on the screen. Do not worry. We don't have to calculate it manually. We have systems and tools which can do that analysis for us. However, the covariance is not standardized and can assume values between plus and minus infinity. This makes it difficult to compare the strength of the relationship between the variables. For this reason, the correlation coefficient is also a product movement correlation. And this is calculated in a different way. The correlation coefficient is obtained by normalizing the covariance. For this normalization, the variance of the two variable is calculated as given below. The Pearson's correlation coefficient can now take values of minus one to plus one and can be interpreted as follows. The value of minus one means that there is an entirely positive linear relationship, and the more the minus one indicate that there's an entirely negative relationship exist. The more and the less. With the value of zero, there is no linear relationship. The variable does not correlate with each other. Correlation of plus one will look something like this, which is only possible in theory. Correlation of 0.7 plus will look something like this where it's going in a positive side, and most of the dots are closer to the regression line. A correlation of plus three will be scattered, but it's going in a positive direction. When you do a correlation you have a correlation of -0.7, they are all scattered moving downward. So as the value of X increases, the value of Y is reducing. And most of the dots are scattered around the regression wide. We get the correlation value of zero in multiple ways. Either the dots are completely scattered, or you might get some perfect lines like this or like this, which again, would not be, which means that you need to take some other analysis for interpreting the variables. Now, finally, the strength of the relationship can be interpreted, and this can be illustrated by the following table. The strength of the correlation. If it is 0-0 0.1, there is no correlation. If it is 0.1 to 0.3, there is a little correlation, 0.3 to 0.5 medium correlation, 0.50 0.7, sorry, high correlation, and 0.7 to one is a very high correlation. To check in advance whether a linear relationship exists, scatter plot should be considered. This way, the respective relationship between the variables can also be checked visually. The person's correlation is only useful and purposeful if linear relationships are present. Pearson's correlation has certain assumptions which you should be keeping in mind. For Persona, whenever you're using this, the variables must be normally distributed, and there must be a linear relationship between the variables. The normal distribution can be tested either analytically or graphically using the QQ plot, which I will teach you how to do. Whether the variables have a linear correlation, it is best checked with a scatterplot. If the conditions are not met, then Spearman's correlation can be used. So I hope you are clear till here, and let's continue our learning. So if my data is not normally distributed, it's a non parametric data or non normal data. Then for correlation test, I will be using Spearman's rank correlation test. The Spearman's correlation analysis is used to calculate the relationship between two variables. That can be ordinal level of measurements. Spearman's rank correlation is a non paramatic equivalent of Pearson's correlation analysis. This procedure is therefore used when the prerequisite for the relationship correlation analysis is equal to a parametric procedure is not met. When there is non metric data, no metric data, and non normal distribution, in this context, we often use Spearman's correlation or Spearman's row. If the Spearman's rank correlation is meant. The question is that, can it be treated by rank correlation or similar to those of Pearson's correlation coefficient? Is there a correlation between two variables or features? For example, is there a correlation between age and the religiousness in the France population? Here, the level of religiousness can be a different number. 52. Correlation Simplified: Welcome to the next lesson of our analyzed phase in the DeMac life cycle of a Len Six Sigma project. Sometimes we get into a situation where we would want to do a correlation analysis. And hence, I thought today, I should be diving you deep into what is correlation what is the difference between correlation and casuality? How do I interpret correlation when I look at the scatter plot? What significance level can I set up when I'm doing my hypothesis testing, Pearson's correlation, Spearman correlation, point B serial correlation, and how to do these calculations online using some of the available tools. So let's get started. So what exactly is correlation analysis? Correlation analysis is a statistical technique that gives you information about the relationship between the variables. Correlation analysis can be calculated to investigate the relationship of variables, how strong the correlation is determined by the correlation coefficient, which is represented by the number letter R, which varies from minus one to plus one. Correlation analysis can thus be used to make statements about the strength and the direction of the correlation. Example, you want to find out whether there is a correlation between the age at which a child speaks his first sentence and later success at school. Then you can use correlation analysis. Now, whenever we work with correlation, there is a challenge. Sometimes we get confused with things that are a problem. Like, if the correlation analysis shows that two characteristics are related to one another, it can substantially be checked whether one variable can be used to predict the other variable. If the correlation mentioned, the example is confirmed, for example, it can be checked whether the school success can be predicted by the age at which the child speaks its first sentence. It means that there is a linear regression equation. I have a separate video on explaining what is a linear regression. But beware, correlation need not have a causal relationship. It means any correlation that can be discovered should therefore be investigated by the subject matter expert more closely, but never interpreted immediately in terms of content, even if it is very obvious. Let's see some of the examples of correlation and causalty. If the correlation between the sales figure and the price is analyzed, there is a strong correlation identified. It would be logical to assume that the sales figure are influenced by the price and not the vice versa. So the price does not happen the other way around. This assumption can, however, by no means be proven on the basis of a correlation analysis. Furthermore, it can happen that the correlation between the variable X and Y is generated by the variable Z. Hence, we will be covering that in partial correlation in more detail. However, depending upon which variable can be used, you may be able to speak a causal relationship right from the start. Let's look at an example. If there is a correlation between the age and the salary, it is clear that age influences salary, not the other way around. Salary does not influence the age. So just because my age is increasing or just because I have a higher salary does not mean that I will be old. Otherwise, everyone would want to earn as little salary as possible. That's just laugh. Interpret the correlation. With the help of correlation analysis, two statements can be made. One about the direction of the correlation and one about the strength. Of the linear relationship of the two metrics are the ordinary scale variables. The direction indicates whether the correlation is positive or negative, whether the strength dictates whether the correlation between the variable is strong or weak. So when I say there is a positive correlation exists between it we are trying to say that the larger values of the variable X are accompanied by the larger values of variable Y and not the other way around. Height and shoe size, for example, are correlated positively. The correlation coefficient lies 0-1. That is, it's a positive value. Negative correlation on the other hand exists if a larger value of variable X is accompanied by the smaller value of variable Y and the other way around. The product price and the sales quantity usually have a negative correlation. The more expensive a product is, the smaller the sales quantity. In this case, the correlation coefficient will be between minus one and zero, assuming it's a negative value. So it results in a negative one. How do I determine the strength of the correlation? With regards to the strength of the correlation coefficient R, the following table can act like a guide. If your value is between 0.0 to 0.1, then we can clearly say there is no correlation. If the value is between 0.1 to 0.3, we say there is a little or a minor correlation or a correlation. If the value is between 0.3 to 0.5, medium correlation. If the value is between 0.5 to 0.7, we say there's a high correlation or a strong correlation, or if the value is between 0.7 to one, we say it's a very high correlation. At the end of this module, I'll show you how to calculate the correlation question directly on an online too. So let's go further. When you do it online, you will get one of the tools that we use to analyze the correlation is a scatter plot because both the X and the Y are variable data type or metric data type, as you call it. Just as important as considering the correlation coefficient is in graphical way, we can use a scatterplot. So as the age, the X axis will always have the input variable and the Y axis will have the output variable because Y is equal to function of X. I can see that as my age is increasing, my salary is increasing. The scatter plot gives you a rough estimate the correlation whether there is a correlation and whether there's a linear or a non linear correlation and whether there are any outliers. When we do correlation, we might also want to do our hypothesis testing, test the correlation for significance. If there is a correlation in the sample, it is still necessary to test whether there is enough evidence that the correlation also exist in the population. Thus, the question arises when the correlation coefficient is considered statistically significant. Right? The significance of correlation coefficient can be tested using the T test as a rule. It is tested whether the correlation coefficient is significantly different from zero. That is, a linear dependence is tested. In this case, the null hypothesis is that there is no correlation between the variables under study. In contrast, the alternate hypothesis assumes that there is a correlation. As with any other hypothesis testing, the significance level is first set at 5%. The Alpha value is set at 5%. It means I should have 95% confidence in the analysis that I'm doing. If the calculated P value is below 5%, the null hypothesis is rejected, and the alternate hypothesis applies. If the P value is below 5%, it assumes that there is a relationship between X and the Y. The T test formula that we use for hypothesis testing is R into under root of N minus two divided by under root of one minus R squared. W N is the sample size, R R is the determined correlation of the sample, and the corresponding P value can be easily calculated in the correlation calculator. 53. Lean Six Sigma Summary Part 1: Pase overview, foundation and principle of six Sigma and Ian. In this course, we will be introducing you to the foundation and principle of six Sigma and lien along with the values these quality and productivity improvement methodologies bring to the organization. We also cover the key lean tools commonly used in Six Sigma projects and explain what is N, what is six Sigma, and what is the integrated or a unified approach called Lean Six Sigma. So what exactly is six Sigma? It all begin with an important metric defects per million opportunity, DPMO. DPMO is a scientific measure used to calculate the number of potential mistakes or defects in the delivery of products and services. This DPMO metric sits within the broader organizational system where six Sigma operates. The core competence of this system is the improvement methodology. Which is known as the DMAC cycle, which stands for define, measure, analyze, improve, and control. So together, the metric and the DMAC process forms the foundation of Six Sigma projects. This enables the organization to systematically improve the business process of all time. Why do we need six Sigma? There are several compelling reasons to adopt. The PruATrack record of Six Sigma, which was popularized by Motorola and General Electrics in 1980s and 1990s. Moreover, the COR techniques have been used to nearly a century and have been adopted by leading organization across the industry. The powerful tool kit, Six Sigma offers a structured methodology and a robot set of tools. It identifies and eliminates defects, reducing variation, and improving quality. Though it was born in manufacturing, the Six Sigma has been successfully applied in a wide range of industry, including financial services, government, non profit organizations, healthcare, logistics, and many more. Currently, BPOs use Six Sigma from the last three decades. The key benefits of Six Sigma is that all organizations, whether they are for profit or non profit, everybody faces the challenge of controlling operating cost. While ensuring sustainable revenue growth, Six Sigma addresses these challenges very well. So what are the ways in which Six Sigma helps you manage this cost reduction? Six Sigma has a proven method called cost of poor quality, famously known as COPQ which is used. Six SIGMA emphasizes on the voice of customer VOC, to understand the customer satisfaction level. We are aiming to reduce variation, eliminate inefficiency, and improve the process reliability. Six Sigma helps in profitability and long term value. By improving quality and efficiency, Six Sigma contributes to increased net profits to the organization and improve the value system in the organization. It builds a culture of continuous improvement. So when we focus on continuous improvement, Six Sigma ensures that the organization remains customer focused while enhancing internal capabilities, process controls and process performances. 54. Lean Six Sigma Summary Part 2: All right. Pace over. Foundation and principle of six Sigma and Lian In this course, we will be introducing you the foundation and principle of six Sigma and IN along with the values these quality and productivity improvement methodologies bring to the organization. We also cover the key lean tools commonly used in Six Sigma projects and explain what is N, what is six Sigma, and what is the integrated or a unified approach called Lean Six Sigma. So what exactly is six Sigma? It all begin with an important metric defects per million opportunity. DPMO. DPMO is a scientific measure used to calculate the number of potential mistakes or defects in the delivery of products and services. This DPMO metric sits within the broader organizational system where Six Sigma operates. The core competence of this system is the improvement methodology, which is known as the DMAC cycle, which stands for define, measure, analyze, improve, and control. So together, the metric and the DMAC process forms the foundation of Six Sigma projects. This enables the organization to systematically improve the business process of all time. Why do we need six Sigma? There are several compelling reasons to adopt. The fluid track record of Six Sigma, which was popularized by Motorola and General Electrics in 1980s and 1990s. Moreover, the core techniques have been used to nearly a century and have been adopted by leading organization across the industry. The powerful tool kit, Six Sigma offers a structured methodology and a robot set of tools. It identifies and eliminates defects, reducing variation, and improving quality. Though it was born in manufacturing, the six Sigma has been successfully applied in a wide range of industry, including financial services, government, non profit organizations, healthcare, logistics, and many more. BPOs use Six Sigma from the last three decades. The key benefits of Six Sigma is that all organizations, whether they are for profit or non profit, everybody faces the challenge of controlling operating cost. While ensuring sustainable revenue growth, Six Sigma addresses these challenges very well. So what are the ways in which Six Sigma helps you manage this cost production? Six Sigma has a proven method called cost of poor quality, famously known as COPQ which is used. Six Sigma emphasizes on the voice of customer BOC, to understand the customer satisfaction level. We are aiming to reduce variation, eliminate inefficiency, and improve the process reliability. Six Sigma helps in profitability and long term value. By improving quality and efficiency, Six Sigma contributes to increased net profits to the organization and improve the value system in the organization. It builds a culture of continuous improvement. So when we focus on continuous improvement, Six Sigma ensures that the organization remains customer focused while enhancing internal capabilities. Process controls and process performances. You need to understand that DPMO and process performance are very important when it comes to Six Sigma projects. The concepts like DPMO is the fundamental basis for six Sigma. Once you can measure and capture the data, you can then check the chart performances, compare the actual results to a defined goal or mean. Evaluate deviation from statistical tools. By applying standard deviation, we access how process performs relative to its specification limit. Anything outside the upper and the lower specification limit is considered as out of spec and meets and it fails to meet the customer expectation. A performance chart typically includes a mean, which is the goal line, a range measured as standard deviation or Sigma levels. While many organizations set the tolerance of limit as plus or minus three Sigma, Six Sigma aims for plus or minus six Sigma, resulting in only 3.4 defects per million opportunities. This means there is a dramatic improvement in the process quality. If our process is operating at Six Sigma quality level, we are setting a much higher standard for quality. And operating performance at this level is 99.997% defect free. Meaning there may be only three defects per million opportunities. Why am I not saying 3.4? Some of you might wonder because the textbook definition says 3.4 defects per million opportunity. Understand, can you have a 0.4 defects? No. So we are expecting the defects to be around three for 1 million opportunities. What's the difference between an operation where deliverables are expected to fall within three Sigma versus the operation that works at six Sigma? Do all the operations have to work at that level? The answer is no. The main difference which can surprise you when you look at the numbers is that if an operation limits the defects at just 3.4 per million opportunities, the improvements are dramatic. At three Sigma, it could mean losing 20,000 emails on the mailbox per hour. But if the same department is operating at six Sigma, it can be only seven pieces of mail getting lost. Now consider 5,000 incorrect surgeries per week versus just two surgeries with six Sigma. Our electricity outage, and many more. Understand a process which involves humans should be operating at Six Sigma or beyond six Sigma. For other departments, you can work with two Sigma and three Sigma as well. Think about landing airplanes. Thankfully, airlines today mostly operates at six Sigma level of quantity. Why that plane crash are rare? It is because it is not operating at three Sigma, if it is operating at three Sigma or anything less than six Sigma. Six Sigma is highly adaptable and is commitment. Any organization, regardless of the size and the industry, work towards the level of performance. From manufacturing to consulting, from profit to nonprofit, government agency and private sector. Everyone can apply Six Sigma. The great example of six Sigma application is customer facing organizations such as call centers. We also call them as contact centers. But there is no restriction. Any organization can adopt and benefit from six Sigma. We will explore the timelines of six Sigma and understand the evolution over time. The importance of Six Sigma concept is the standard deviation. This was defined in 19th century. Going back to the late 1800s, we find that Frederick Taylor, the rise of Taylorism. His economic theory and divisions of labor laid the groundwork for many principles we associate with Six Sigma. In 19 twentyes, pionists like Henry Ford, Walter Shuart, George Box contributed to what would be evolving into today's modern six Sigma practices. In 1940s, the US government began publishing quality control in the military manufacturing. This led to the rise of statistical process control, SPC, as we call it, thanks to this part of early teaching by the statistician Walter Stuart. After the World War two, figures like doctor Edward Deming, doctor Joseph Juran, worked extensively in Japan. Their contribution helped transform quality into a competitive advantage for Japanese industry. It was during this time that the Japanese Union scientists and engineers, JUSE Jews was established, laying the foundation of many practices will later adopt as Six Sigma. 55. LSS Quiz Questions 1 to 10: Let's now practice questions to understand the lean Six Sigma concepts more in detail and practically. Are you ready? Quarter, T test. You are about to run a T test on shield thickness from two suppliers when you determine that the data from one group is not normally distributed and cannot be transformed. Your next step would be to A, use the Shapiro Wilk test. B, proceed with the T test. C, use a non parametric test. B, discontinue the analysis. Correct answer. C, use a non parametric test. Explanation. A T test assumes that the data in both groups are normally distributed. If the data is not normal and cannot be transformed to approximate normality, then the T test is not appropriate. In such cases, a non parametric test like the Mann Whitney U test is used because it does not assume normal distribution. A manufacturing test process has three parallel machines performing exactly the same test. The data from this test process can be assumed to be normally distributed, and the variances within each machine are the same. To understand if there is a significant statistical difference in the average test, value between machines, what test should be used. A Kruskal Wallace, B chi square, C ANOVA, D, Bartlett or levine. Correct answer C ANOVA. Explanation. ANOVA. Analysis of variance is used when comparing the means of three or more groups. Since there are three machines and the assumptions of normality and equal variances hold, ANOVA is the correct statistical test. Third quarter, discrete test. Which of the following is a commonly used test that examines the association between multiple discrete variables? A, Crystal Wallace test, B, Shapiro Wilk test, C, students T test, D, Chi square test. Correct answer. D, Chi square test. Explanation. The chi square test is specifically designed for categorical discrete data. It assesses whether observed frequencies and categories differ significantly from expected frequencies under the assumption of independence. Fourth quarter statistical hypothesis. An engineer is trying to increase a product characteristic, mean from the current production value of 850 to about 855. The standard deviation of the current process and the proposed process are assumed to be the same. If the current value is 7.7, the engineer wants to verify that the average difference of his new process compared to the old process is statistically significant and greater than five. What are the correct statistical hypothesis for this engineering problem? A, null hypothesis nu minus, old equals five. Alternate hypothesis, Nu minus, old greater than five. B, null hypothesis, nu minus, old equals five. Alternate hypothesis, nu minus, old does not equal five C. Null hypothesis equals 85o. Alternate hypothesis, greater than 85o, D. Null hypothesis, Sigma u equals 7.7. Alternate hypothesis, Sigma Nu greater than 7.7. Correct answer A minus null hypothesis, new minus old equals five, alternate hypothesis, new minus old greater than five. Explanation. This is a one sided hypothesis test where the engineer wants to prove that the new mean is greater than the old by more than five units. Hence, the null hypothesis sets the difference at five and the alternative hypothesis tests if it's greater than five. Statistical procedures. Which of the following statistical procedures is appropriate. When there is one continuous input variable selex and one continuous output variable Y, A T test, B, chi square test, C, one way ANOVA, deep correlation. Correct answer D correlation. Explanation. Correlation analysis examines the strength and direction of the linear relationship between two continuous variables. It is the appropriate method to study the relationship between a continuous input and output. Ir qu six, statistical analysis. In statistical analysis, the beta risk beta is A, the probability of rejecting the null hypothesis when it is true. B, always equal to 0.10 C, driven by the cost of sampling. D, the probability of failing to reject the null hypothesis when it is false. Correct answer D. The probability of failing to reject the null hypothesis when it is false. Explanation. This is known as Type two error. Failing to detect a real effect or difference when one actually exists. Beta risk beta quantifies this probability. E qu seven, saving and loans. Sigma saving and loans processes loans and leases from around the world. The CEO wants to know if the current cycle time for processing is less than 9.5 days on average. To test the claim that the average cycle time is less than 9.5 days, use A, one sample T test. B, two sample T test. C, one way ANOVA. D, Chi square test of means. Correct answer is a one sample T test. Explanation. This situation involves comparing a sample mean to a known target, 9.5 days. Since only one sample is being tested and the population standard deviation is unknown, a one sample T test is appropriate. Our eight, two different samples. Two different samples were pulled randomly from the same population. One sample has size N equals ten, and the other N equals 100. A two sided confidence interval, for the mean was calculated separately for each. How will the intervals compare? A, the confidence interval for N equals ten will be smaller. B, the confidence interval for N equals ten will be larger. C, the confidence intervals will be the same for both. N equals ten and N equals 100. B, there is not enough information given. Correct answer. B, the confidence interval for N equals ten will be larger. Explanation. Smaller samples yield less precise estimates of the population mean resulting in wider confidence intervals. Therefore, N equals ten has a larger confidence interval than N equals 100. Ir qu nine, screening experiment. The purpose of a screening experiment using DOE is to A, optimize the response by determining the best levels for the input factors. B, separate the vital few from the trivial many. C, compare various levels for one factors. D, find a set of levels for the inputs that produce a robust product. Correct answer. B, separate the vital few from the trivial many. Explanation. Screening experiments are typically used in early stages to identify key factors, vital few that significantly affect the outcome, distinguishing them from less impactful factors, trivial many. O qu ten. Based on the DOE results illustrated in the image below, and considering the hierarchy of effects, what term should be left in the model use Alpha equals 0.10. A, temperature, time, temp into pressure. B, temperature, time, pressure, temperature into pressure. C, time, temperature plus pressure. D, temperature, time. Correct answer B, temperature, time, pressure, temperature into pressure. Explanation. Following the hierarchy of effects principle, lower order terms main effects should be retained if higher order interactions involving them are significant at Alpha equals 0.10, keeping the main effects and the significant two factor interaction is appropriate. Great progress. I will see you in next video with more questions. Oh 56. Quiz Questions 11 to 20: Qu 11, model DOE steps. What is the correct order of steps in a DOE experiment? Design the experiment and plan data collection. Run the experiment and collect data, state the problem or objective, analyze the results, interpret the results. Correct answer B three, one, two, four, five, three, state the problem or objective. One, design the experiment and plan data collection. Two, run the experiment and collect data. Four, analyze the results. Five, interpret the results. Explanation, this sequence reflects the logical flow of a well designed experiment. You first define the objective, then design the experiment, followed by executing it, and finally analyzing and interpreting the results. Our 12, model design selection, which of the following experimental designs? Could you run if you had five factors and a maximum of 21 experimental units? A, two to the power of six minus two with six centerpoins. B, two to the power of five with three center points. C, two to the power of five minus one with five centerpoints. D two to the power of four with five center points. Correct answer C two to the power of five minus one with five center points. Explanation. A full factorial with five factors, two to the power of five equals 32 runs exceeds the run budget. E, a fractional factorial design, two to the power of five equals 16 runs plus five center points totals 21 runs, fitting within constraints while still providing valuable insight. Ir qu 13, experiments objectives. The four basic objectives for experiments which are vital to Lean's Sigma include screening, optimization, and which of the following. A, result comparison, B, comparison, robust design. C, reduced variance parsimony, D, comparison result. Correct answer B. Comparison, robust design. Explanation. Beyond screening and optimization, DOE is also used for comparing alternatives and developing robust designs that perform well under variability. These are fundamental DOE goals in six Sigma. Qu 14, experimental error. Experimental error includes the dash in the experiment caused by uncontrolled and unknown nuisance factors. This is also called dash fill both the blanks, A, noise pure error. B, noise signal. C, signal noise. D, pure error signal. Correct answer. A noisPued error. Explanation. Noise refers to random variation in an experiment from sources you can't control. Pure error arises from repeated measurements under identical conditions and reflects inherent process variability. Q 15 process factors. A black belt candidate has found that three process factors significantly affect process throughput and variability. He suspects that the influence of one of the factors is non linear over the range of throughput. Which of the following tools should be used to determine the relationship between the factors and responses? A, screening factorial experiment. B, response surface method, RSM experiment. C, multiple linear regression analysis. D, two level full factorial experiment. Correct answer B, response surface method, RSM experiment. Explanation. RSM is specifically designed to model curvature and non linear relationships between factors and responses, making it the correct tool when linear models are insufficient. Ir qu 16, RSM experiment full factorial. A full factorial experiment is characterized by all of the following properties except A, all factors in the experiment are controlled. B, higher level interaction effects cannot be estimated. C, all combinations of the levels of the factors are run in the experiment. The two factor two level design is the simplest full factorial experiment. Correct answer. B, higher level interaction effects cannot be estimated. Explanation. This is false. A full factorial can estimate higher order interactions. That's what distinguishes it from fractional factorials. So this statement is the exception. Ir qu 17, factorial experiment. A black belt has run a full factorial experiment. The image below illustrates an interaction plot from the analysis. What level of interaction is there between these two factors? A, no interaction. B, strong interaction, C, weak interaction, D, three way interaction. Correct answer B, strong interaction. Explanation. If the lines in an interaction plot are non parallel and intersect, it indicates a strong interaction between the two factors. The presence and pattern of crossover indicate the level. Ir qu 18, strong interaction. A black belt runs an experiment on two different shifts comparing two different methods for data entry. The black belt wants to learn if there is a difference between methods. She suspects that shifts have an impact on the response. However, she is not interested in optimizing the shift. What experimental design technique should the black belt use? A, repeats only. B, replication and repeats. C, run in standard order. D, blocking. Correct answer, D blocking. Explanation. Blocking is used to control nuisance variables, EG, shift that may affect the response, but are not of primary interest. It helps isolate the effect of the factor under study. Ir 19, AB interaction. What is the AB interaction effect? A four, b2c minus two, D, six. Correct answer is two explanation. Although the specific numerical logic depends on the image mentioned, not shown here, typically the AB interaction effect is calculated using contrast between combinations of factor levels. The answer provided is two, indicating a measurable interaction. Quarter, A, B, interaction. Given the image below, what is the main effect of factor A, A minus three, B, three, C minus six, D, six, Correct answer, A is minus three. Explanation. Man effect equals average response when A is high, average response when A is low, divided by two. A negative value like minus three indicates that increasing factor A decreases the response. The exact calculation depends on the data provided in the image, which is not included here, but the answer reflects a negative main effect. 57. Submit your project LSS: Now that we have completed the entire learning, I request you to go down to the project and resource section to ensure that you complete the project. Let's kin share, the project instructions are very clearly given in the project and resource section. Now that you have successfully completed the training on Lean Six Sigma made simple for giving you results, it's important for you to complete the project. The project instructions are given in the project and resource section where we have given you an idea about what type of project you can complete. I'm going to walk you through a demo to give you a basic understanding of how you can submit a project. So applying the Lean Six Sigma basic tools to uncover eliminate small inefficiencies in your daily routine or workplace. Choose your processes. Pick up any daily task or simple work process. Example, morning coffee routine, email or filing documents. I have cleaned up my desk, and I'm going to submit that as my project. You're also free to use CIPOCOFlow charts to submit as your project. The objective is to spot the waste or variation in the process, apply some basic lean principle to identify the inefficiencies. You need to propose a quick fix of how you are making the change or reducing or eliminating the waste. We need to measure the impact before and after metric, or you can show a picture which can show the results. How do you upload? You can upload a single image containing the original process map or the process that you have improved. Please write a description that what exactly have you done. I have also given you Skillshare project template for you to have an idea. I'm going to upload my project by clicking on Submit Project. So it is very clearly showing me the image of before and after. You can submit the image has been uploaded. I'm also free to attach an image over here so that it can clearly show the picture of before versus after. That's all by clicking on publish, I'm ensuring that my project is published and it's visible. This helps me in submitting the project, and my project will be visible over here. Thank you once again for the time that you have taken in investing in yourself. You have completed an important milestone, and I hope you will feel proud of your progress. Remember, Six Sigma isn't just about tools and techniques. It is about thinking differently, solving problems, and feeling better, and it's about leading change wherever you are. So you keep applying what you have learned, submit your class project, and don't hesitate to reach out if you need guidance or want feedback. I will see you in the next class. Up till then, keep learning, keep improving, and most importantly, keep believing in your potential. Thank you. 58. Conclusion-Big Thank you: I would like to thank you for completing this course. It's important because whatever we start, we need to complete. Now it's time for you to submit the project. This helps me understand that you have understood the concepts, the lessons, and the course that I have covered. If you have any queries, please do not forget to ask questions in the discussion section below. When you submit your project, I will definitely review your project and give you a personalized comment on your project. People on Skillshare will like your project, which will help you motivate you to complete more courses on Skillshare and submit the project, which also means that you are applying the knowledge that you have not. I would like to give a short brief that whom were you listening to all this way? So my name is Dan Wilson v, and you can find me on LinkedIn. You can just go to Google and type them. Birdsong, V, D, B and E space, some way, S and G hedge. The first link that comes up is mine. I'm not dead on any of this social media platform as of now. But I do run my Telegram channel, which is 66 Sigma, it is the alphabet six. Sax underscored the number six, underscore sigma. You can get connected with me with one of these tools or platforms. Or you can also write an email to me on my Gmail ID. As you can see from the photographs, I am then worst with conducting trainings in-person. And most of my trainings are gamified. There is a lot of activities that are done during the training program which helps the participants learn the concept in Boston. These are some of the snippets of the different exercises that I do during my training program. And you can see that these corporate training program participants are very energetic and connector in the training. These are highly interactive. Gamification is the key theme for me. And the concept is learned when you play. They are very effective for you to learn any complex topic as well. I also do online training program and I have covered more than thousand hours of training, not thousand man hours. I will have trained more than thousand people for more than thousand hours in the last two years. So I can easily see that I have done 1 million man hours of training. These are the some of the snippets of the various culprits were involved with me in the different Zoom sessions or WebEx sessions that I have conducted in the last two years. All these online trainings have mainly started post the pandemic. I have quickly adopted to the new things that are bare, as you would have seen in my training program. You would have enjoyed by learning with the concepts. So I thank you very much for completing it. Once again, trust you have learned a lot and hope your concepts are more clear. Now. You can the new watching my other programs which are available on Skillshare. And this will help you understand different topics that are present. I also run vice Wednesday. This is a session which I do every Wednesday at 08:30 P.M. IST. The cost of this training for this workshop or this whenever they meet up is 1,000 USD. But if you are part of the Skillshare community, you can join this for free. Just go to Telegram and search for six alphabet six MSIX underscores the number six and Sigma SIGMOD. I will just go back to that slide to show you what those Sigma training is. Just a second. Yes. So this is my Telegram Channel 66 Sigma. So I would want you to participate if you are interested in being part of the continuous learning journey. Because continuous improvement comes and starts with our personal session. See you in the next class. Thank you and do share your reviews and feedback for how did this training Thank you.