Category: Lean Six Sigma
Many people have heard of 5S, however, people often think of 5S and associate it with housekeeping. So, is 5S just an extreme form of housekeeping? Certainly not!
5S was originally used in Toyota to improve performance. The ‘5S’ referred to five simple everyday Japanese words that everyone would understand. The thought process was that by keeping the words simple and grounded in day to day language, the worker could focus on the intent not remembering complex terminology. When this technique was first imported to the west, the trainers used the Japanese words and created an obstacle that should never have been part of the process. The driving force for this was seeing the task not the process. Copying the Japanese implementation across language and cultural boundaries failed to communicate the philosophy and structure behind the process. 5S is an integral part of kaizen linked to elimination of waste and focus on value. For that reason, I use five simple English words – I only teach in English.
The 5S’s are;
Another misunderstanding from the west was adding a sixth S, safety. Safety is of vital importance, however, adding safety as the sixth S misses the point. The five S’s are grounded in an assumption that everything is safe. If the process isn’t safe don’t wait for 5S, deal with the safety issues before starting 5S, after all why would you work with an unsafe process?
Preparing for 5S is vital and too often organisations don’t invest enough to ensure they create the right environment that allows employees to succeed. There are five critical steps to creating the right environment for employees to succeed at 5S.
- Create policy and a plan.
To implement 5S successfully the organisation must establish a clear policy that documents the benefits of 5S and the roles and responsibilities for implementation. The leadership team must be united on the need and purpose of 5S. The team who create the policy and plan should be drawn from all levels of the business. This is to ensure that the potential pitfalls and problems are identified and discussed. Through this discussion the business can ensure alignment between all levels of the business and significantly reduce the opportunities for conflict. The policy should explain the behaviours and standards the business will adhere to regarding 5S.
- Write the Procedure.
Document the process for implementing and managing 5S. 5S is a form of standard work and supports employees and management alike in understanding the benefits and advantage in standardising working practices. Implementing 5S without standard work will make the process much more difficult than expected.
- Create a red tag format and area.
Standard red tags used throughout the business create consistency. This consistency ensures that everyone is clear about the meaning and purpose of any red tag in the business. The red tags also contain standardised information allowing correct identification of the item, date tagged, reason for tagging and disposition of the item. This item can then be placed in a fixed area for disposal or storage.
- Create a red tag log.
Red tagging alone won’t create a clear picture of the items in the business that are not required. The red tag log allows management to track items and the decisions made regarding their disposition. The log also allows tracking of location, cost and stock level.
- Communicate the plan and train those involved.
Once all the preparation is done, communicate why 5S is important and what benefits implementing 5S will bring. Once this is communicated throughout the business select the first team to implement 5S and train them how to implement the process.
Preparing properly for 5S will increase the speed of adoption and the likelihood of success. The leadership must understand their role in the process. Leadership should not be dictating, they need to collaborate with the workforce. The most effective activity that leadership can undertake is to identify and remove obstacles to progress, ensuring that employees have the tools and resources to succeed.
Read the future posts on how to implement each of the steps of 5S
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Picture the scene; someone in your organisation comes up with a cost-saving idea. If we move the process mean to the lower limit, we can save £’000’s and still be in specification. The technical team doesn’t like it, but they can’t come up with a reason other than “it’ll cause problems”, the finance director loves the idea, and the production manager with one eye on costs says, well if we can save money and be in spec, what’s the problem?
Let me help you.
In this scenario, the technical team may be right. If we assume that your process is in control and produces items with a normal distribution (remember that is the best case scenario!) logic dictates that half of your data is below the average value and half is above. That being the case, what you really want to know is how far from the average the distribution spreads. If the spread is large and you change process to the extreme where the average value sits right on the customer specification limit, half of everything you make will be out of spec. Can you afford a 50% failure rate? What will the impact be on your customers, your reputation, your workload (dealing with complaints).
To work out how much we can move the process, we must first understand how much it varies, and we use a statistical value called the standard deviation to help us. Standard deviation is the average variation from the mean for a sample data set. To work it out, take 20 samples, measure them all 5 times then use a spreadsheet to work out the mean and standard deviation. If that is too much take 10 samples and measure 3 times. Keep in mind that the smaller sample size will give a larger standard deviation. Now take the mean and add 3 x standard deviation. This is the upper limit of your process spread. Subtract 3 x the standard deviation from the process mean to find the lower limit of your process spread. The difference between these two numbers is the spread of your process and will contain 99.7% of the results measured from the process output IF the process is in control and nothing changes.
If moving the mean takes the 3 standard deviation limits of your process outside of the specification, you will get complaints. It could be that the limits are already outside of the specification, in which case moving the average will make a bad situation worse.
It is possible to calculate the proportion of failures likely from a change of average, this done using z-score calculation. I’m not aiming to teach maths, so the important message is that the failure rate can be calculated.
This is the tip of the iceberg with understanding your process. If you don’t know that your process is stable and in control, the spread won’t help you because the process can jump erratically. To improve your process
1. Gain control, make sure the process is stable.
2. Eliminate errors and waste
3. Reduce variation
4. Monitor the process to make sure it stays that way.
The most significant and profitable gains are often from process stability, not from cost-cutting. All cost-cutting does is reduce the pain, think of cost-cutting as a painkiller when you have an infection. It makes it hurt less, but doesn’t stop the infection. You need to stop the infection to feel better.
Now do you want to hurt less or do you want to get better?
There are so many models out there for process improvement that I fear the reason for having the models gets lost. You can’t see the wood for the trees. How do we get back to seeing what is in front of us?
What lies at the heart of all of the improvement methodologies?
I would argue that the reason for doing any of this is the same; a basic desire to improve the business. The next question is to improve what? Why improve at all? All businesses are there to service the needs of their customers, whether that need is for doughnuts, cars, phones, accountancy services, medical aid, it doesn’t matter. If we can find a way to service the customer’s needs better, then perhaps we can find a way to make everyone’s job more secure and grow the business. If we can make more money along the way even better.
So why do we obsess about all these different methods?
Everyone tries to understand how someone else, who we perceive is better at something, does it. We all study someone, we are taught subjects in school, how to answer questions, how to solve problems, how to make things better. Unfortunately, our education systems teach us to copy, imitate rather than innovate, so we look for models and systems to copy since that is our conditioning.
Therein lie the seeds of ruin for many improvement projects. We go, we study, we focus on what, but we fail to understand why. The real question for improvement is, why do it? Many companies who engage in process improvement, lean or six sigma projects do so to reduce costs. That cost reduction is often accompanied by job losses, which works in the short terms, but destroys trust between workers and management, and makes future improvement projects almost impossible. This is because there is an internal, short term focus for the business. Management are changing every 3 to 5 years, every new set of management focus on the perceived deficiencies of their predecessor, then proceed to change the direction to make things better. W Edwards Deming identified these factors in his seven deadly diseases. Short term goals, lack of constancy of purpose, job hopping by management, performance reviews, focus on visible figures, excessive medical costs, excessive legal costs.
American Management thinks that they can just copy from Japan. But they don’t know what to copy
W Edwards Deming
How do we succeed?
As Simon Sinek observes, we must start with why. Why do we want to improve? Is it to better serve our customers or to make more money? As United Airlines have recently shown, just saying that your customers are a priority isn’t enough. If customer service was at the heart of their principles, that video of security guards dragging a paying passenger from a flight would not have been possible. To truly succeed, a business must focus on improving the aspects of their product or service their customers value most. It must not be done to simply improve margin, but to reduce the level of defects, improve customer satisfaction, eliminate the opportunity for defects, reduce lead time, reduce waste.
This focus will lead the business to look at the process for creating customer value; reducing defects, eliminating the opportunity for defects, reducing waste all deliver lower costs for the business and better service for the customer. Reducing waste and defects means that less time is wasted on defect correction and replacement, this gives a shorter lead time and lower costs. Determining a long-term strategy, and setting in place a review process to ensure the strategy is sustained will ensure constancy of purpose. Focusing on these factors and ensuring that all the changes are sustainable for the long term may be harder, but is ultimately much better for the business.
In summary, focus on your customer needs, plan for long term success, and make changes that are consistent with your long-term goals. Don’t copy what others have done, understand the link between their long-term goals and improvement activities. Once this is understood for their business, focus on your own business and use only the tools and techniques that support your own long-term goals AND your customer’s needs. If you ever find a conflict between these demands, always choose your customer’s needs; long-term success can only come from repeat business, and repeat business only comes from satisfied customers.
Profit in business comes from repeat customers, customers that boast about your project or service, and that bring friends with them.
W. Edwards Deming
I regularly see posts and discussion points asking what are the differences between Lean and Six Sigma, should Lean or Six Sigma be used first, and if Lean is better than Six Sigma. I find it really puzzling that people involved in continuous improvement still have this debate, especially since the two techniques are not alternative approaches, but are complementary techniques.
Let’s take a quick look at these three questions
- What are the differences between Lean and Six Sigma?
Lean is the practical application of the Toyota Production System. Lean started out as a simple way to ensure that business were focused on the things that customers value and ensuring the activities in the business are as efficient as possible at delivering customer value. Lean focuses on process velocity, reducing waste in all forms and eliminating non value added activities. There is a bias to immediate action Lean, to ensure that waste is removed in the shortest possible time.
Six Sigma was developed by Motorola to enable effective competition against high quality imports from Japan. Six Sigma is a highly structured process aimed at understanding and reducing variation to ensure that the process always delivers the product or service required by the customer. Six Sigma requires statistical evidence and proof of performance, with a mantra of show me the evidence, the ultimate aim of which is to ensure the product delivered is absolutely consistent and within specification. Six Sigma has a bias to understanding the customer and only acting on statistically valid evidence.
The aim of both Lean and Six Sigma is to reduce waste, particularly defects, improve process performance and thereby increase customer satisfaction. Lean aims to achieve this by identifying and removing waste and non-value added activities. Six Sigma aims to achieve this by ensuring the customer needs are fully understood and the process is capable of delivering the required product consistently.
- Which Should be used first, Lean or Six Sigma
My perception is that if a practitioner is more comfortable with Lean they will use the lean tools first and if they are more comfortable with Six Sigma they will apply Six Sigma first. Let’s phrase that question differently and see if it still makes sense.
Do you want to reduce waste, defects, and lead time for your process through Lean, or do you want to reduce waste, defects and lead time for your process through Six Sigma? I believe almost every production manager and senior executive would ask one more question; why do I have to choose?
Lean and Six Sigma processes are valuable and there is a strong crossover in the skills. For example if final checking of a process is unnecessarily complicated and yielding too many defects, would you want to be certain that the test method was correctly identifying defects? Of course, therefore we should use Six Sigma first right, because that is where we find Gauge reproducibility and repeatability tools? However, would you want to eat until that was done before simplifying the process? If we give in to the tyranny of “or” we have to choose. What if we choose and instead, and use different groups in the team for both exercises. We need to make sure they communicate effectively, but if the tasks are perceived as of equal importance and we promote a collaborative approach, we can get both done in parallel. That way we eliminate the non-value added steps and ensure that we can separate good parts from bad parts.
If we start with Lean we end up with a simple process (good) without knowing if our output performance is due to the test method, operator or parts (bad). If we start with Six Sigma, we know where the variation finished part performance comes from (good), but the process is still very complicated and we still can’t clearly see what needs to change (bad). If we apply both techniques in parallel we get a simplified process (good) with clarity of process performance (good). Applying both in parallel gives the best results.
- Is Lean better than Six Sigma?
Is your car engine more important than the steering? Neither works well without the other, having a car that can go fast, but is hard to direct is not going to work, equally having an excellent capability to direct the car, but nothing to make it move is also going to fail.
Lean and Six Sigma are complementary and whilst each is an excellent tool in it’s own right, when used together these two tools yield results far in excess of what each can give alone. Neither is better than the other, they are different and they are complimentary. Lean or six sigma is not a binary choice, it is a comprehensive toolkit for solving problems.
Just as an engineer uses different tools and techniques for different structures, so Lean and Six Sigma should be applied when the tools and techniques are appropriate to the task in hand.
So my final message on this would be don’t worry about whether the improvement process should be lean or six sigma, instead worry about whether the tool selected to improve the process will yield the most effective solution. In other words don’t get trapped by the tyranny of “or” instead be empowered by the freedom of “and”.
A behaviour I suspect many lean six sigma mentors have seen with new belts is paralysis by analysis. Newly qualified, with access to powerful statistical analysis software and on their own for the first time, their first reaction is to conduct every statistical test they can think of, working on the principle that they are looking at the data from every perspective. What they are actually doing is in part showing off their new found skills and in part showing off their unconscious incompetence. That is not to say they are incapable, only that they lack experience.
When mentoring new belts I always start them out with three simple questions.
The reason for these questions is to make sure that they learn what I believe is one of the most important skills in lean six sigma; focus. I have noticed over many years that when belts who are new to statistical analysis gain access to a powerful statistical analysis package.
So back to the questions. The first question is this;
1. Can you write a simple statement of what you want to know?
It may seem obvious, but often people forget the first discipline of six sigma – DEFINE.
Starting analysis without actually stating what you want to know leads to confusion. It is all too easy to conduct a series of statistical tests then when the results are available find you can’t remember what you originally set out to discover. Let’s be honest, most of us have done it and had to start again, that’s how we learned not to do it.
It is for this reason that I tell anyone starting to do statistical analysis, do nothing until you can write a simple statement of what you are trying to discover. If you don’t know what difference or correlation you are trying to discover, how can you possibly choose a suitable test? We all suffer from a cognitive bias that makes it easy to believe we know what is required. However, if we can’t write it down simply, and in plain language, do we really know what we are trying to discover?
Having written down our question in plain language we need a way to answer our question. This leads to the second question;
2. How will this test answer the question posed above?
There must be a direct link between the analysis undertaken and the purpose of the test. For example if we want to know if changing a pigment gives the same colour for a particular application, we should consider how the testing has been done. If the tests are done side by side in a laboratory on the same piece of substrate and the results are normally distributed without outliers, a paired t-test would be appropriate. However if the testing occurs in different factories on different batches of substrate and the results are not normally distributed with outliers, Moods median test should be used.
The context of the data has to be considered when deciding which test to use. Again, the test selection and the logic for selecting the test should be written down in plain language. If you cannot do that, you have not adequately considered your test selection and should revisit your thought process.
So now we have a clear picture of what we want to know and what test should be done to answer that question. What else is required?
3. Write down the rules for interpreting the test.
It is vital that the rules for interpreting results are written down before the analysis is done. If an alpha level of 0.05 is selected and the p-value from the test result is 0.93, the test fails.
Remember the cognitive bias from the problem definition? It appears here again; if we write the p value after conducting the test, we may decide that an alpha level of 0.1 is adequate. The interpretation of the test is different, because our decision making has been influenced by the results, the test acceptance hers hold is no longer objective. For example, if failure resulted in an expensive process change in a business with limited finance, going back to the pigment example, if the new pigment is lower cost it would be easier to accept a larger difference to push the change through. That may not satisfy the customers’ needs and may result in higher complaints and potentially higher costs in the long term. the combination of a desire to save money and an apparently small difference in performance will have seduced the operator into unconsciously compromising their standards.
How should the decision criteria be documented? That is the whole point and purpose of null and alternate hypothesis, but that is for another time.
Following these three simple rules will ensure clarity of purpose, that there is a rational link between the desired information and technique applied and that the pass / fail criteria are set objectively. Following these simple rules for data analysis will save a lot of time and help the practitioners to become confident and productive in a shorter time.