Plan: Here you want to identify what the problem/issue is, then perform an analysis of this problem so you can test it and how it is affecting your bottom line. So if you do the preceding, you would identify the problem and understand the root cause of the problem, using data collected to decide which of the possible causes is the true root cause.

Do: This is where you will test or experiment with possible solutions and figure out which one is the best possible solution. Do small experiments to figure out quickly what changes are needed, then you can always go back on a bigger scale after you’ve gauged the improvements results on the smaller scale. Then you can measure the solution you have chosen to its full potential, and of course measure the resolved results.

Check: Here you are going to compare the results using before and after data that you have collected. Analyze the results and measure how effective the improvements were, and then make the supported hypothesis of whether or not the solutions used reached the desired objectives.

Act: Here you document the data from the results you obtained. Inform your team about the process changes, show the data if need be. Make suggestions if other process changes are needed. 

This is just a brief explanation of how to work the PDCA template. For more information on For more information on our on-demand online classes or our virtual classrooms, please visit 6sigma.com. 

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Originally implemented by Toyota with great success, Kaizen is inclusive with the entire team, from top management to line workers. Everyone is encouraged to submit suggestions in whatever area it is warranted. Success credit is given to the entire team. This is a morale booster, which encourages company loyalty and a sense of belonging.

Methods Used With Kaizen (Continuous Improvement):

Process Mapping/Flowchart: This identifies and is a visual representation of the steps, inputs, and outputs of a process. This will show how the process flows at every step of the process.

Root Cause Analysis: An in-depth method used with tools such as 5 Whys to find out the root cause of an issue or problem. Once you get to the root of the problem, the issue should go away and not be recurring. 

PDCA stands for Plan-Do-Check-Act:

Plan: Plan ahead for any change, analyze, and hypothesize the results.

Do: Implement the plan, use small steps in a controlled manner.

Check: Study the outcome.

Act: Take necessary action to improve the plan.

An excellent mindset is that with every day comes an improvement, regardless of how small. In fact, small steps equals big changes over time. 

Kaizen is also something that can be used in creating new good habits or changing a daily routine. The personal daily routine could be equated as your day-to-day process that makes the best version of “YOU” possible. 

For more information on our on-demand online classes or our virtual classrooms, please visit 6sigma.com. 

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Process: This is the day-to-day activity that must occur to produce a product or service.

Process Map/Flow Chart: This a chart that visually shows the series of steps, describes the steps and who does them to produce a product or service. This will show the flow of the process(s) or events that has to happen to produce a product or service.  

SIPOC: Stands for Suppliers-Inputs-Process-Outputs-Customers. This is used to define a process from beginning to end.

PDCA: Plan-Do-Check-Act. This is an improvement methodology that is quite easy to use and very effective.

Output: This is what is produced by a process step, the result.

Affinity Diagram: This is a tool to organize ideas and data into priorities and categories.

Benchmarking: This is used to set a standard by comparing a set of business processes and performances to the industry’s best practices and seeing if there is a gap that can be fixed.

Defect: Anything that isn’t done right the first time.

Defect Opportunity: Any task or activity that can be measured that does not fulfill the requirement for value.

Poka-yoke: Mistake proofing. This is an action you take in Six Sigma to significantly lower the opportunity for error so much so that the customer never experiences the error.

Input: This is a resource added by a supplier to the process; this can be a product, service, data, even labor.

For more information on our Lean Six Sigma courses and services please visit 6sigma.com. 

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It’s not a big secret that just about everyone has a dog, cat or multiples of both. The American Pet Products Association (APPA) gives the statistics of their latest market research for 2018/2019 as to what percentage of the U.S. population has pets:

• 68% of U.S. households have at least one pet
• U.S. pets include 90 million dogs and 94 million cats
• 81 to 85 percent of pet owners regard their pets as a reliable source for unconditional love, stress relief, and overall zen for their health.

The American Society for the Prevention of Cruelty to Animals (ASPCA) has statistics of their own:

• 6.5 million unwanted pets are surrendered to rescues annually
• Of these, 3.3 million are dogs and 3.2 million are cats
• 1.5 million pets are euthanized annually

The main reason people surrender their pets are behavior issues. Yes, there are other issues, but behavior is usually number one. Let’s talk dogs: they need consistency in their training, there’s no room for variation. Variation creates errors, mishaps, and confusion and in the case of dogs being euthanized it creates waste of a perfectly wonderful life of a once happy pet.

The Six Sigma tool that dog trainers would benefit from would be PDCA, or Plan-Do-Check-Act. If the dog trainer is consistent, clear and knowledgeable in the process used to train the canine, perhaps euthanizing an animal for behavioral reasons would be eliminated completely. 

If a dog isn’t trained properly, it has to do with the trainer, not the dog. If both dog trainers and owners used the DMAIC template to improve their current dog training process (or DMADV to create one), once again Six Sigma would have come to the rescue…literally.

For more information on our Lean Six Sigma courses and services, please visit 6sigma.com. 

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Think of it like one huge box. You open it and there is another box, open that box and there is another box and so on. The boxes are all just boxes, the contents you put in them is what will define them. 

Whether the word you use is Define as in the Define phase of the DMAIC template, or the word Plan, as in the acronym PDCA which stands for Plan-Do-Check-Act, the information you put into that box will be of a specific nature, but with a slight variance. 

The reason is that every core of Lean Six Sigma’s existence is for perfection and systematic problem solving, so the DMAIC gene will be woven into all of its family members.

Do as You Would Do in Real Life

Let’s take the concept of the boxes we just used. In the Define phase, in the first box Define the problem. While still in the Define phase, in each smaller box define specific details but keep them in separate boxes under the same Define phase. This keeps things organized. In real life if you were to put a book in a box that you have labeled shoes, you won’t remember where your favorite book is. Think of this book as a loss of valuable information. By applying the DMAIC template correctly, problem solving will be much easier. 

For more information on our Lean Six Sigma classes and services, please visit 6sigma.com. 

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Walter A Shewhart and His Contributions to Statistical Quality Control

Walter A Shewhart is a name highly revered amongst modern engineers as a man who married statistics, quality control, and process improvement in an era when quality control involved discarding defective items post-manufacture.

He is often regarded as the grandfather of total quality management and process improvement. Not only that, his concepts serve as a primer for quality engineers to this day.

Early Life, Work, and Contributions

Shewhart attended the University of Illinois at UrbanaChampaign before pursuing his doctorate in physics from the University of California, Berkeley in 1917. He worked for the Western Electric Company and was with the Inspection Engineering Department until 1925 when he joined the newly established Bell Telephone Laboratories.

Whilst at Bell Labs, Shewhart revolutionized the production process followed at the time. He leveraged schematic control charts of his creation to bring down the number of defective pieces being manufactured. This not only brought down costs for the company but also helped in building credibility among consumers.

Today, he is one of the most revered and well-respected personalities in the field of process improvement and quality. His contributions to process adjustments in manufacturing are still considered the founding stones for modern industry six sigma quality guidelines.

Shewhart’s contributions to Process Improvement Reducing variation

Shewhart is best known for his simple schematic control chart which changed the manufacturing industry forever. This chart outlined principles essential to modern process quality control. These are followed to this day with certain improvements as production processes became more complicated.

A key thing to remember in any process is that no two products will ever be the same. Reducing these variations to improve quality has always been one of the manufacturing industry’s greatest challenges. Dr. Shewhart’s acknowledgment of two classes of variation, namely special-cause’ and common-cause’ led him to improve his control chart mentioned above.

He proposed variables which would reduce common-cause’ variations. According to him, to distinguish between the two, every manufacturing process would need to be brought under statistical control. This and other principles of Shewhart helped pave the way for modern analysis of manufacturing processes.

Deming Wheel Cycle and Six Sigma

One of Shewhart’s other well-known accomplishments included a simple plan termed PDCA or plan-do-check-act, an iterative four-step management method for the continual improvement of processes. This is also known famously as the Deming Wheel cycle.

In six sigma programmes, the above-mentioned cycle is renamed as DMAIC or define-measure-analyze-improve-control. A guiding principle of the PDCA/DMAIC is the iterative nature of the processes. More the number of iterations a product is subjected to, the better the end output.

To illustrate and highlight his contribution to six sigma and the PDCA cycle, the latter needs to be looked at from the perspective of a company which isn’t experiencing profits.

The company would brainstorm ideas for improvement which is the plan’ phase of the cycle. Next, the company chooses an actionable course, then pursues it, which constitutes the “do” phase. The next phase check’ constitutes studies conducted to test the results of the actions taken prior. This phase also quantifies the efficacy of the prior phase and serves as the foundation stone for the next step. In the act phase, the company analyses the observed results. If the results are up to the mark, the process is set in stone until further improvements are needed. If they are not, this phase instructs the company to circle back to the original brainstorming pool to start the process over again and repeat the cycle until the company is pleased with the results.

This plan illustrates Shewhart’s brilliance and the thought process that the continuous evaluation of management procedures and the consideration of new ideas are vital in streamlining “common causes” and mitigating “special causes” in variation.

Conclusion

In conclusion, Shewhart is one of the most eminent contributors in Six Sigma and process improvement. His work and contributions help organizations identify unique attributes in their processes which influence customer experience and quality.

They will always be leveraged by organizations operating on the bleeding edge and wanting to re-define the way things are done.

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It’s broken down as follows:

P (Plan): Identify your problem and find the root cause using the 5 Whys.

D (Do): After you’ve identified your problem and found the root cause, now brainstorm possible solutions. Test the solution you believe has the most potential. Do a small pilot test.

C (Check): Now you must assess your findings on that small pilot test. If you find that improvement is needed, then go ahead and make the necessary changes and repeat the “check” phase once again.

A (Act): This is the last step when you implement the solution in its entirety.

The advantages of using the PDCA cycle are:

• Encourages continuous improvements
• Less wasted time
• Fosters working as a team
• Cost effective

This simple template can be a great help on Thanksgiving while preparing the family dinner. Since most of the preparation usually falls on one person, this simple tool can make this interactive and fun!

Happy Thanksgiving 2018 from all of us at 6Sigma.com. For more information on our Lean Six Sigma Green belt Training courses and services, please visit 6sigma.com. 

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In its most general sense, process improvement is an analysis of a series of set actions, especially in business, that is aimed at both improving quality and decreasing costs. The theory and practice of process improvement have increasingly been applied in various industries and corporate sectors for over two centuries.

During this period, there have been many prominent process improvement gurus, both in the industry and within the academic sphere, but a few stand out as key names in the movement to achieve efficiency, quality, waste reduction, customer satisfaction and elimination of variance.

Although most of them have passed on, their memory continues to live on in the revolutionary and innovative methods and concepts that are now so pervasive within the business environment today. We look at these individuals, how their work relates to each other and how their ideas continue to contribute to process improvement.

The Pioneers

The quality revolution kicked off in the late 18^th and early 19^th centuries, with Eli Whitney among the movement’s leaders. Eli came up with the idea of manufacturing using interchangeable parts. He believed that assembly of identical parts to create one finished product sped up the process and allowed for uniform quality of finished products during mass production. This method of assembly also lowered costs, since the interchangeable parts could be put together even by unskilled workers.

As experts began to look closer at different work processes to see where more efficiency and cost savings were to be gained, one of the greatest husband-wife teams in science and engineering history stepped up to the plate. In the early 1900s, Frank and Lillian Gilbreth collaborated to develop the study of motion as a technique for use in both engineering and management. Until his death in 1924, Frank Gilbreth examined the relationship between people and human effort. His observation that people did the same jobs in different ways led him to try and find the most efficient of these ways that would require the least effort.

Development and Improvement of Specialized Manufacturing Processes

If there is one name that encompasses the global view of American business success in the 20^th century, it would have to be Henry Ford. His manufacturing processes were so efficient and effective in reducing waste that even Toyota, the Japanese automotive giant, studied them. Besides encouraging his employees to build better cars, he also drove them to remedy any operational deficiencies that they found.

For instance, he introduced the moving car assembly line in 1913 and ensured that the necessary parts were readily available at each stage to ensure that there was no need for the line to stop or slow down to allow a worker to sift through a pile of parts to find the one that was needed.

With the American manufacturing sector growing quickly in the early 1900s as evidenced by the success of companies like Ford’s, and as products and markets became segmented and complex, organizations needed to develop ever more specialized business functions. As the new functions brought new capabilities and ways to work, it became necessary to find new ways to improve them.

Frederick Winslow Taylor established himself as a major player in the effort to improve engineering processes during this period. Specifically, Taylor focused on the standardization of work, the study of processes, systematic training and the employee-management structure of manufacturing organizations.

Improvement of Quality Assurance and the Birth of Statistical Quality Control

In the 1920s during his time working at Bell Labs, Walter Shewart devised the concept of statistical process control, allowing for improved planning and implementation of mass production processes. During this period, Shewart also developed PDCA Planning (what needs to change); Doing (making and testing the change); Checking (seeing whether the desired outcome has been achieved) and Acting (making changes a permanent part of the manufacturing process).

Yet another pioneer in the field of statistical quality control was Harold F. Dodge. He also worked at the Quality Assurance Department of Bell Labs alongside Harry Romig, where the pair was also responsible for the development of sampling plans. Dodge and Romig designed standardized schemes for use in sampling and published tables which related risks to sample sizes.

Scientific Analysis of Processes and Quality

Process improvement has proven most effective when carried out with data and metrics behind the identification of any areas of waste, poor quality or inefficiency. Eugene Grant became well known for his work in the field of engineering economics after publishing a book on the subject in 1930. He also taught at Montana State University in the 1920s and at Stanford University’s School of Engineering in 1930 on how to improve processes through problem-solving and decision making at the operational level.

Another process improvement guru responsible for important and enduring contributions to statistical quality control and the related sciences was George E.P. Box. However, he initially got into the field of statistics by happenstance rather than design. As a chemistry student carrying out scientific experiments during World War II, he needed the help of a statistician to help him make sense of the varied results he obtained. As there was no statistician available, he worked on his master’s degree in statistics, later taking up a job at Imperial Chemical Industries (ICI). In addition to research experimentation, he also helped ICI to improve its chemical and mechanical processes.

Putting People First

In contrast to Frederick Winslow Taylor, Peter Drucker decided to take an approach that was much more sympathetic to employees, whom he termed as knowledge workers. This was a stark contrast to Taylor’s highly structured and often inflammatory treatment of the common worker. By focusing on decentralization and simplification, Drucker pioneered the concept that we recognize today as outsourcing.

The key influences on business process improvement in the 1940s and 1950s were W. Edwards Deming and Joseph Juran, who made enormous contributions to the idea of Total Quality Management (TQM), which places the human aspect at the forefront of quality management. Deming and Juran were also responsible for many of the statistical quality control methods in use for the improvement of manufacturing processes.

Japanese Manufacturing Efficiency Comes to the Fore at Toyota

Much of the process improvement methodologies and tools that have become so popular today were developed in the period between 1950 and 1080, when Japan quickly emerged as the leader in manufacturing efficiency and quality. In 1950, engineer and statistician Genichi Taguchi joined the Nippon Telegraph and Telephone Corporation’s Electrical Communications Laboratory (ECL), at a time when the ECL was embroiled in a heated rivalry with America’s Bell Labs for the development of telephone switching systems. Taguchi also consulted widely with Toyota and other top manufacturers in Japan. His ideas on the loss function, experimental design and the reduction of variation have had a huge influence on fields beyond manufacturing and process engineering.

At the end of the Second World War, productivity at Toyota was way lower than the mighty American car industry based out of Detroit. The president of Toyota declared that his company must catch up with the Americans in three years and tasked Taiichi Ohno as part of the team to achieve this vision. He quickly deduced that the only reasons why the company was unable to match Detroit’s motor industry were waste and inefficiency. The strategy and methodologies that he and his team developed from the mid-1940s to the mid-1970s formed the basis of the famous Toyota Production System (TPS).

Another notable name in the practice of process improvement to have had an impact at Toyota during this period was Shigeo Shingo. A leading consultant on the improvement of manufacturing operations, he was greatly influenced by the work of Fredrick Taylor. In 1955, he joined Toyota and quickly developed the SMED system and error proofing. It is said that he managed to cut down the set-up time of a press from four hours to only three minutes. Throughout his life, he traveled around the world giving memorable talks on process improvement and carrying out remarkable projects as a consultant.

Japanese Efficiency Meets Quality Management

Kaoru Ishikawa is widely considered to be the Father of Japanese Quality. He not only invented the cause and effect diagram (Fishbone diagram), but was also responsible for the development of the Company Wide Quality Control (CWQC) method. In order to reduce workplace conflict, he also devised the next operation as the client concept. His belief was that management should not only be satisfied with offering the customer a quality product, but should also offer service to the customer after they had purchased the product.

During the late 1970s and into the early 1980s, Noriaki Kano, a consultant and professor of quality management, set up the foundation for a radically new approach to customer satisfaction. He challenged the belief that to achieve customer satisfaction, it was necessary to improve all attributes of a product or service. Kano instead stated that only certain attributes need to be improved. The Kano model for customer satisfaction puts customer preferences in five quality categories.

America and Europe’s Soul Searching

With Japan’s eminence in manufacturing based largely on its automotive industry, it came as little surprise that the US would try to find out how America’s car makers performed in comparison. James P. Womack and Daniel Jones carried out a study on American car manufacturing efficiency titled The Future of the Automobile. It indicated a 3:1 productivity ratio in favor of the Japanese, in contrast to Taiichi Ohno’s estimate in the 1950s which showed that Detroit’s worker productivity was nine times higher than that of Japan’s car manufacturers’. Womack’s book, The Machine That Changed the World used the study’s findings to conclude that Lean manufacturing in Japan produced higher quality products by using half the resources required by American car makers.

The GPRI model was initially mooted by Richard Beckhard in 1972. An acronym for Goals, Roles, Processes and Interpersonal Relationships, it represents the critical and interrelated aspects required for effective teamwork. The model, which started out in social science but has since been adapted for the change acceleration process (CAP) toolkit for Six Sigma, helps team leaders to ensure efficiency, quality and productivity.

As the 1970s drew to a close, it was apparent that North America and Western Europe were losing out to Japan’s more efficient manufacturers who produced reliable, affordable and high-quality goods at a fraction of the cost. Armand Feigenbaum, a process improvement consultant, estimated that as much as 40% of the capacity of manufacturing plants that do not follow lean principles is wasted.

Finally, a Way Back for the West?

By the time Philip Crosby‘s book Quality Is Free hit the market, the US manufacturing industry was slogging through a recession and struggling with foreign competition. Crosby provided a 14-step blueprint for the improvement of quality, and introduced the manufacturing world to the zero defect concept, which many considered to be a sure recipe for success.

Eliyahu M. Goldratt, an Israeli businessman, took an unorthodox approach to publish his theory of constraints by having it as the central theme of a novel called The Goal. His theory states that the weakest link in a business process a constraint – needs to be identified since it keeps the rest of the process from successfully achieving its goals. When constraints have been identified, they can be fixed or eliminated.

One of the most celebrated methodologies in use by process improvement professionals in the world today is Six Sigma. The name of this framework was coined by an engineer at Motorola known as Bill Smith. In the early 1980s, under the chairmanship of Bob Galvin, engineers at Motorola felt that traditional measures of quality, which measured defects in terms of thousands of opportunities, were not granular enough. They instead measured defects that occurred per million opportunities, created a culture that supported it and gave it the now iconic name. Because of the incredible bottom-line results that Bill Smith’s methodology achieved for Motorola, it has been adopted by tens of thousands of organizations from across the globe.

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The word Kaizen essentially breaks down like this: “kai” means change, and “zen” means good, so good change or improvement. What is not included in the name is that it is continuous; meaning it doesn’t happen just one time, it is small little improvements continuously. 

In Kaizen, everyone in the company is involved, from the management on down. Everyone works as a team; in other words, success depends on everyone.  

With this mindset, a Toyota facility in the United States had over 75,000 suggestions from their team in just one year. They estimated approximately 7,000 employees gave their input, and 99% of their suggestions were implemented. They used the PDCA cycle, or Deming Cycle.

Plan-Do-Check-Act

Plan: Use data or develop a hypothesis to identify issues that need improvement as a team, and decide which one has the priority. Also determine the end result or goal and possible ways of getting there.

Do: Test on a small scale a suggestion from a team member for a promising solution and measure the results.

Check: Study the results and see if the level of effectiveness matches your goal or hypotheses.

Act: If the results were successful, then implement the solution.

The mindset of the team is very important. When the team is included in the success of the company, their intention becomes the secret sauce to your company’s success. This could be akin to the fans at a ballgame; it has been said that the fans are just as important as the actual players, or perhaps they are even more important, for the fans give the impetus to the players. The inclusiveness and appreciation gives the employees the impetus for the company to succeed.

For more information on our Six Sigma training courses and services, please visit 6sigma.com. 

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PDCA (Plan-Do-Check-Act) and PDSA (Plan-Do-Study-Act) are two techniques aimed at promoting continuous improvement and extending a company’s ability to stay ahead of a rapidly changing environment. However, while some people confuse them and even use them interchangeably, there are some big differences that are important to observe.

Sure, on the surface, they might look quite similar but once one digs down beneath the surface, various differences start to present themselves, even in steps that have the same name. Understanding those differences and knowing how they affect the application of each method is a critical first step in using them correctly.

PDSA Provides an In-Depth Overview of the Situation

An important difference between the two methodologies is that PDSA attempts to study the consequences of the applied changes more closely and in more detail compared to PDCA. The meaning of the check phase often boils down to running some basic tests to ensure that the new state of the system corresponds to some baseline measurements. However, that may not be enough to get the full picture and ensure that the changes will actually lead to an improvement in the long run.

By replacing this step with the study one from PDSA, you can often see much better results from the analysis of each step’s impact, and therefore see better long-term improvements. Keep in mind that there may not always be a very good opportunity for studying the effects of your change in that much detail, which could call for the use of PDCA instead. But more on that a little below.

Differences in Other Steps

The other three steps seem similar in both methods, but there are in fact some intricate differences to be aware of. The important thing to remember here is that both methods are iterative and cyclic, meaning that you’ll come back to step one after finishing the cycle, and will repeat the whole process with the new knowledge you’ve obtained.

This means that you will sometimes see a real difference in the way the planning and action phases are carried out between the two methods, because you’ll be working with two different sets of data. Whether this will make any impact on the way you’re actually carrying out both improvement systems depends on the context of your own organization’s work style, but in most cases there will indeed be some differences.

Recognizing the Right Use for Each Method

Don’t make the mistake of thinking that either PDCA or PDSA is better than the other one in some way. In the end, they’re both tools, and they were both created with a specific purpose. You must recognize the correct application of each of the two, and know when a situation calls for either of them.

As we said above, sometimes you might not have that much information to work with in the first place, making the use of PDCA more appropriate. Indeed, the short-running cycles often associated with it can often prove much more beneficial when trying to realize quick, to-the-point improvements in your organization. On the other hand, if you need to ensure that you’re looking into the results of your change in an in-depth manner, then you should definitely go with PDSA.

Conclusion

PDSA and PDCA are somewhat similar, yet quite different. It’s important to understand what sets them apart, and realize when a situation calls for either one of the two. With time, you should develop some intuition about the correct use of both, and you will find them to be very viable parts of your arsenal as a lean leader seeking to improve their organization.

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The Tools and Methodologies Used by Both TPS and Lean

5S: This is a system to organize the workplace and then maintain it. This system originated from the Toyota Production System.

• Sort (Seiri): Only keep what is needed and discard the rest.
• Straighten (Seiton): Make sure everything needed for work as its own place.
• Shine (Seiso): Make sure everything is clean free of dirt, dust and contaminates so that problems can be easily noted and taken care of.
• Standardize (Seiketsu): Create a process of standards; make things visible so that it is easy to identify what are normal conditions and what isn’t.
• Sustain (Shitsuke) implement protocols for maintaining established desired standards.

Kaizen: This Japanese philosophy focuses on the mindset of continuous small improvements over the long haul.

Kanban: A method (could be a board) for managing the actual process of a product or service.

P.D.C.A: Plan-Do-Check-Act  — this is used for implementing improvements

• Plan: Create the plan and expected results
• Do: Carry out the plan
• Check: Confirm the results you achieved
• Act: Review estimated expected results and repeat again

Poke-Yoke: Mistake proofing, when you design the product with the mindset of avoiding specific errors in the actual design.

Root Cause Analysis (RCA): Conducting RCA will ensure that the issue won’t happen again. One great tool for RCA is the 5 Whys.

5 Whys: Keep asking why to the previous answer until a satisfactory answer is achieved.

As you can see, the same tried and true methods still work today. The tools or methods need not be complicated to achieve great results. Want to learn more about these Six Sigma tools and methodologies? For more information on our Six Sigma training courses or services, please visit 6sigma.com.

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So we are going to go down a few of these Lean Six Sigma tools and terms and what they are used for. Remember these are just some examples; how these tools can be used is only limited by your creativity.

Tools and Terms of Lean Six Sigma

1. Cause and Effect Diagram: this tool is a great tool for visually seeing the relationships between multiple causes and the effects they produce.
2. Fishbone Diagram: this diagram resembles a fish and can be used as a cause and effect diagram. The spine represents the effect and the branches can represent various causes.
3. The 5 Whys: this is an excellent tool where you keep asking why as you get deeper until you get to the root cause of the problem. This way you can implement the proper countermeasures to fix the issue.
4. Kaizen: an honorary lean tool that was adopted into Lean Six Sigma. It is a Japanese word meaning “change for the better” and it is used for continuous small improvements, involving all staff members.
5. Value Stream Analysis: this is an analytical tool that monitors all activities done and is depicted visually in a Value Stream Map. Here you can see what activities don’t add value and which ones are necessary, meaning they add value to the product or service.
6. Root Cause: this is the ultimate cause of the problem/issue.
7. PDCA Cycle (Plan-Do-Check-Act): this is a 4-step plan used to solve issues in quality control. It is also known as the Deming Cycle, Shewhart Cycle or Deming Wheel.

This is just a partial list. Interested in learning more about these tools and terms? Why not enroll in one of our Six Sigma training classes? For more information on our courses or services, please visit 6sigma.com.

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The PDCA (Plan-Do-Check-Act) cycle is a very powerful tool for driving your organization towards continuous improvement, and when applied correctly, it can result in huge boosts to the company’s overall productivity. However, care must be taken that each step is carried out correctly and with regards to the company’s current context. While the PDCA system is a rather flexible one, it has to be adapted correctly to each implementation, otherwise you’re going to see poor results in the long run.

Plan

This is the stage where you have to determine the exact objectives of the organization, and what results you expect to achieve with the implementation of PDCA in the short and long term. It’s important that expectations are established clearly and in a way that you can take concrete steps towards realizing each one, instead of aiming for vague, abstractly defined goals.

The planning phase must also take any previous PDCA iterations into account, ensuring that you don’t repeat the same mistakes as last time. This makes it important to have proper data collection systems in place, although how exactly you’re going to do that depends on the specific work your organization does.

Do

Now it’s time to put those plans into action. This step is relatively straightforward, and as long as you’ve designed your plans with attention to detail and with enough flexibility to account for possible last-minute changes in requirements, you should be able to simply follow the list step by step and move through it.

There should be no unexpected complications here, but this of course depends on how well you’ve developed your plans in the first place.

Check

It’s crucial that the results of the PDCA cycle are verified according to the initial expectations outlined in the plan, as well as old data gathered from previous cycles if appropriate. You can also verify your findings against third-party data sets, if you have access to those, although this is a highly individual factor and depends on the industry you’re working in. But if you have access to additional data sets that can help you make a more informed decision, it’s definitely something you should use in the Check phase.

Make sure to get as much input as possible from all levels of the company at this stage, not just from high-level executives or people from those circles. All employees will likely have some valuable input to provide about the current iteration of the PDCA cycle, and ignoring the additional information you can obtain in this manner is one of the fastest ways to kill progress in your company completely.

Act

Now that you’ve gone through the first three steps of the PDCA cycle and you’ve collected some data about the way it was realized, it’s time to make appropriate changes to the whole organization in preparation for the next PDCA run. This is why it’s so important to collect as much data as possible during the Do phase, and to put it through a thorough enough analysis in the Check phase. Failing to do either of those will leave you in a situation where you have far too little information to make an informed decision in the Act phase, and that can make the whole PDCA process unnecessary.

Keep in mind that some of the actions you take here may need to be reverted later on, depending on how they impact the whole organization. Just because a certain change in the company structure makes sense on a local level when running the current project, this doesn’t mean that you’ll get good results across the board from implementing it.

Conclusion

The PDCA cycle is one of the most powerful tools for rapid iteration and ensuring that you’re always moving towards improvement. It’s flexible and can be easily adapted to multiple different working environments, but it relies heavily on working with the right data sets and having the ability to see the big picture with regards to the organization as a whole. As long as you make sure to get enough input from all levels, you should see great results from implementing PDCA in your own company.

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