8 steps to lean six-sigma culture change
Hmm, I’m not sure I agree with this post:
given that Lean/Six Sigma/Concurrent Design are really just a bag of tools from which a skilled mechanic will draw out one that is appropriate
Or even understand this post (perhaps one of my readers can translate this into English).
But I will agree that of course there are tools which are used in lean and six sigma, but you have to get into the philosophy behind lean and six sigma. Pulling tools out of a bag is great and WILL cause improvements to happen but sustainable long-term change will not occur unless driven by top management, who are committed to culture change.
The other problem with just using tools is you tend to get stuck in the Analysis phase. Too much analysis is a bad thing, for example, “the Economic analysis of leaving the toilet seat down“:
the social norm of leaving the toilet seat down in inefficient in the sense that it does not minimize the total cost of toilet seat operations per household. However, both papers fail to address an important concern: If a female finds the toilet seat in a wrong position then she will most probably yell at the male involved. This yelling inflicts a cost on the male. Based on this omission, women may argue that the analysis in these papers is suspect.
So, follow these eight steps to making culture change a reality:
- Capitalize on Propitious Moments (for example poor financial performance, making sure people actually perceive the need for change)
- Combine Caution with Optimism (create an optimistic outlook on what the change effort will bring)
- Understand Resistance to Culture Change (both at the individual level [fear of the unknown, self-interest, selective attention and retention, habit, dependence, need for security] and at the organizational or group level [threats to power and influence, lack of trust, different perceptions and goals, social disruption, resource limitations, fixed investments, interorganizational agreements]
- Change Many Elements, But Maintain Some Continuity (for example identify the principles that will remain constant) -also consider reorganising the quality function
- Recognize the Importance of Implementation (initial acceptance and enthusiasm are insufficient to carry change forward; a) adoption –> b) implementation –> c) institutionalization)
- Select, Modify, and Create Appropriate Cultural Forms (employing symbols, rituals, languages, stories, myths, metaphors, rites, ceremonies)
- Modify Socialization Tactics (because the primary way that people learn the corporate culture is through the socialization process at the beginning of their employment, if these socialization processes are changed, an organization’s culture will begin to change)
- Find and Cultivate Innovative Leadership (members are unlikely to give up whatever security they derive from existing cultures and follow a leader in new directions unless that leader exudes self-confidence, has strong convictions, a dominant personality, and can preach the new vision with drama and eloquence)
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Screwed by Sony
While Lean methods know no bounds you always find at least one company who dosen’t quite “get it”. In this case it’s Sony (via boing boing):
“God help you if you need a new screw for your Sony stuff: Sony charges 61 Euros (more than $82) for a replacement “
Perhaps Sony need to review the following presentations?
Technorati Tags: six sigma, lean manufacturing
Muda is evil and must die
Muda is any human activity which absorbs resources but creates no value. Its elimination is what lean manufacturing is all about and it is one of the most effective ways to increase the profitability of any business. Look at each step in each process: the step either add value or they don’t. A process adds value by producing goods or providing a service. A process also consumes resources. Waste occurs when more resources are consumed than are necessary to produce the goods or provide the service.
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Specifically seven types of wastes are normally quoted. These were originally developed by Toyota’s Chief Engineer Taiichi Ohno as the core of the Toyota Production System. The trick is to look at a process or work-place through “muda glasses” (look on page 10 of this excellent free pdf file for more information). Once you put these on you should be able to see the following:
- Over-production: Producing more than necessary results in consumption of raw materials before they are needed; wasteful use of manpower and utilities; additions of machinery; increased interest burdens; increased inventory (below); increased transportation and admin costs.
- Inventory or Work-in-Progress (WIP): Final products, work in progress, parts and supplies all add to the cost of operations by consuming space, facilities, manpower and admin. Their quality also deteriorates over time, and they may even be destroyed by a fire or other disaster.
- Transportation: Moving materials or products adds no value. Worse, damage often occurs during transport.
- Repair / Rejects: Rejects interrupt production and require expensive rework. Often the rejects must be discarded, thus wasting the resources and effort that went into their creation. The rejects themselves may also damage machinery.
- Motion: Any motion of a person’s body not directly related to adding value is unproductive. Unnecessary or awkward operator motions put undue stress on the body and cause waste.
- Over-processing: Sometimes inadequate technology or design leads to muda in the processing work itself. For example, the apparent need to wrap WIP in bubble-wrap for transportation to another machine could be eliminated by re-designing the assembly line.
- Waiting: Waiting occurs when the hands of the operator are idle; when an operator’s work is put on hold because of line imbalances, lack of parts or machine downtime; or when the operator is simply monitoring the machine as it adds value.
Simplified view of muda is:
- Wasting time.
- Wasting a consumable resource, such as materials.
- Causing dissatisfaction (including incomplete satisfaction).
Muda is one of the ’3Ms’: muda, or waste, mura, meaning irregular, uneven or inconsistent, and muri, meaning unreasonable or excessive strain. Basically, Muda is the waste in a process; these are the seven production wastes that Taiichi Ohno references. Transportation, Inventory, Movement, Waiting, Overproduction, Over-processing, and Defects; Mura is the unevenness or fluctuation of the schedule: Variability; and Muri is the overburdening of your people or equipment.
Curious Cat also has a good article on muda here and so does the lean six-sigma academy here.
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The super-quick guide to Lean Manufacturing
The Lean philosophy was developed by Toyota in the 1950s and 1960s to improve the efficiency of car production. It was used to ensure the 10,000 components of a car were ready at the right time of the production line to allow the fastest possible production of motor vehicles. Lean encourages managers to look at how customers and goods flow through their systems to unlock bottlenecks and inefficiencies. In doing so it defines value-adding activity solely as those which affect the customer and estimates 90% of all actions within organisations are wasted because they add no value. The principles have been adopted by organisations as diverse as Tesco and the NHS.
Lean manufacturing refers to the systematic identification and elimination of waste (muda) from a process while increasing responsiveness to change. While there are a number of specific tools that organizations use to implement lean production systems, the six core methods listed below are most typically used. Most of these lean methods are interrelated and some can occur concurrently. Implementation is often sequenced in the order presented below. Most organizations begin by implementing lean techniques in a particular production area or at a pilot facility and then expand use of the methods over time.
- Kaizen
- 5S
- Total Productive Maintenance (TPM)
- Cellular Manufacturing / One-piece Flow Production Systems
- Just-in-time Production / Kanban
- Six Sigma
Other tools such as value stream mapping (click here to download a file from my website) can also be deployed.
Click here for a typical lean production implementation roadmap.
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The Ultimate Short Guide to Value Stream Mapping
A value stream map is a simple diagram of every step involved in the material and information flows needed to bring a product from order to delivery. The first step is to draw a visual representation of every step in a process, including key data, such as the customer demand rate, quality, and machine reliability. Next, draw an improved future-state map showing how the product or service could flow if the steps that add no value were eliminated. Finally, create and implement a plan for achieving the future state.
It’s important to make the distinction between process mapping and value stream mapping as the two are not the same. What makes value stream mapping different? On a value stream map you get both the material and information flow. By doing this we can see the relationship between these two flows and it allows us to understand where the sources of waste actually are.
A consideration of cycle time is critical. Cycle time is the total elapsed time to move a unit of work from the beginning to the end of a physical process. However, the overall cycle time may include non-value added tasks which do not add value to the end result; this is known as muda or waste.
The key to mapping a value stream is flexibility. Although there are many excellent books such as:
- Learning to See: Value Stream Mapping to Add Value and Eliminate Muda
- Creating Continuous Flow: An Action Guide for Managers, Engineers and Production Associates
- Making Materials Flow: A Lean Material-Handling Guide for Operations, Production-Control, and Engineering Professionals
- Seeing the Whole: Mapping the Extended Value Stream
you should always be prepared to amend the tools to fit your company. Initially, it will be difficult to do this but you will end-up with a set of mapping icons and methodology which is specific to the way your company operates.
Value Stream Mapping Process Step Templates/Symbols
Here are some templates and symbols you can use for tracking your value stream map tasks:
- Value Stream Map Process Step Templates: Excel, PDF
- Value Stream Map Symbols: VSM symbols #1, VSM symbols #2
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One sample z-test using Minitab
Using an example from The Practice of Business Statistics Minitab Manual
A manufacturer of pharmaceutical products. The laboratory verifies the concentration of active ingredients by analysing each specimen three times. The standard deviation of this distribution is known to be σ = 0.0068 grams per litre. Three analyses of one specimen give concentrations: 0.8403, 0.8363, 0.8447.
One-Sample z-Test
A hypothesis test for a population mean μ, with σ known, can be undertaken by selecting:
Stat > Basic Statistics > 1-Sample Z
from the menu. In the dialogue box, enter the column containing the variable that you want to calculate the hypothesis test for and enter a value for σ in the Sigma box. In the Test mean box, specify the null hypothesis test value.
In this example, we want to determine if there is significant evidence at the 1% level that the true concentration is not 0.86%. This calls for a test of the hypothesis that μ = 0.86 against the alternative μ ≠ 0.86.
Click on the Options button. In the Options sub-dialogue box, specify the alternative hypothesis. You can choose less than (lower-tailed), not equal (two-tailed), or greater than (upper-tailed) and click OK.
If instead we wish to test the hypothesis that μ = 0.86 against the alternative μ. The P-value given is always smaller for the one-sided test. In fact, it is equal to half the P-value computed for the two-sided test. In both tests, the P-value is 0 and the null hypothesis should be rejected.
Related Resources:
- Wikipedia entry
- A nice worksheet of the main concepts (doc file)
- Another useful overview (pdf file)
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One sample t-test
To undertake hypothesis testing it is necessary to go through these following stages:
1. Decide on the null hypothesis, H0.
2. Decide on the alternate hypothesis, H1.
3. Decide on the significance level.
4. Calculate the appropriate test statistic, using the sample data.
5. Calculate the p-value.
6. Compare the p-value with the significance level, and decide whether to reject or accept the null hypothesis, H0.
The null hypothesis is a statement about the population value that will be tested – “no change” statement. The alternative hypothesis is the hypothesis that includes all population values not covered by the null hypothesis – “some change” statement
There are several different types of hypothesis tests. Specifically, this post concentrates on the one sample t-test.
What is a one sample t test?
The one sample t-test is used to test the null hypothesis that the mean of the population from which the data sample is drawn is equal to a hypothesized value.
Hypotheses:
- Null: There is no significant difference between the sample mean and the population mean.
- Alternate: There is a significant difference between the sample mean and the population mean.
Assumptions
Before running a one sample t-test you need to establish if the data violates any assumptions by using these tests. Generally, the test assumes that the sample values are independent and are all identically normally distributed (same mean and variance). If your data do not come from a normal distribution:
- transform the values to make the distribution more normal
- use a nonparametric test instead, for example, a one-sample sign test. This is potentially the best option if the distribution is highly skewed
- use the t test anyway, knowing that the t test still works well if the underlying distribution
is symmetric, unimodal, and continuous.
A fuller description of the possible alternatives can be found here.
One of the advantages of the t-test is that it can be applied to a relatively small number of cases. It was specifically designed to evaluate statistical differences for samples of 30 or less. However, although the assumption of normality is not too important with large samples, it is important with small sample sizes, for example less than 10.
You also need to be aware that statistically significant does not mean the same as practically significant.
Minitab
To run a one sample t-test for a hypothesis concerning a single mean in Minitab:
Stats -> Basic Statistics -> 1 sample t -> Variables (enter data columns)-> Check “Test of Mean” (enter value in the box).
Minitab will respond with Test of mu = (value you entered) vs mu not = (value you entered). Below this will be printed the N, mean, standard deviation, standard error, T statistic, and P value.
This link takes you to the Minitab training material for a one-sample t-test. Alternatively, this or this provide a nice summary. If you don’t have Minitab use this site.
P-value
P is the probability that the mean for the data equals the value you were comparing it to. The Prism site has a great summary about how to think about results from the one-sample t test.
Technorati Tags: six sigma, lean manufacturing
Integration of A3 into the DMAIC framework
Although it’s easy to focus on other things at this time of year, it appears that even Santa uses Six Sigma to help him meet his toy related delivery objectives, despite what the naysayers may have you believe. So last week during a break in the festivities, my mind wandered to the use of A3. A3 – what the heck is that?
Well, it not a trunk road in Southern England, connecting London to Portsmouth neither is it a motorway in Switzerland. It is in fact a problem solving report developed as part of the Toyota Production System which is written/sketched on an A3 piece of paper (A3 being a paper size defined by ISO 216.
Last week I initiated a thread over at iSixSigma discussing the feasibility of integration of DMAIC with the A3 problem solving methodology. In essence A3 uses the Plan-Do-Check-Act approach as follows:
- Theme & Background, including problem statement
- Current Condition (process map)
- Root Cause Analysis
- Target Condition
- Implementation Plan
- Follow-up Plan
- Results Report
However, overlaying the DMAIC framework gives us:
DEFINE:
- Theme & Background, including problem statement
MEASURE:
- Current Condition (process map)
ANALYZE:
- Root Cause Analysis
IMPROVE:
- Target Condition
- Implementation Plan
CONTROL:
- Follow-up Plan
- Results Report
I believe that this gives you a much more powerful approach than merely A3 alone. You can now use the DMAIC tools in the correct context and most appropriate stage. It also allows you to overcome some of the limitations which have been leveled at the DMAIC approach.
More information on A3 can be found here and here.
What do you think? Can the approaches be integrated or are they dealing with different types of improvement: continual and breakthrough? Post a comment below.
Technorati Tags: six sigma, lean manufacturing
Statistical Software is not Six Sigma
Six Sigma is about numbers. Six Sigma produces a flood of data about your process that are critical to your success. If you don’t measure it and understand what you are measuring, you can’t manage it. Six Sigma’s clear strength is a data-driven analysis and decision-making process not someone’s opinion or gut feeling.
The value of statistical analysis cannot be underestimated. Through an analysis of all of that data, you begin to understand your process and develop methodologies to identify and implement the right solutions to improve your process. Statistical evaluation of the data identifies key areas which can have an adverse effect on product quality if not controlled. Once you have identified these key areas you can focus your process improvement efforts.
Given the importance of intelligently handling all of this data, you need to find an efficient and powerful method of crunching the numbers. Naturally, you want to avoid the drudgery of manual calculations and save a whole lot of time by using a statistical software application. You may be tempted to use Excel or another spreadsheet application as a calculator and database to store your statistical process control data. However, you will quickly find out that a basic spreadsheet is too cumbersome to handle the volume and sophistication of the data keeping and analysis you need to perform in a Six Sigma project.
Advanced statistical software such as Minitab, Statgraphics, or Dataplot (free!)are very useful if not essential for gathering, categorizing, evaluating, and analyzing the data collected throughout a Six Sigma project. Both Minitab and Statgraphics are powerful full standalone statistical process control software applications for performing statistical analysis. Both are highly recommended for Six Sigma use as they are tools that can help you utilize one of Six Sigma’s biggest advantages: the ability to make better decisions based upon data.
However in the Six Sigma arena, software is like a crutch. Six Sigma practitioners must realize that numbers don’t represent the total information about an event and statistical software doesn’t solve problems.
I’ve seen practitioners who have mastered Six Sigma statistical software. They know the software inside-out. If you give them some numbers, they spit out a solution in no time while convincing you of the correctness of their solution. These people may actually be dangerous because they can initiate a process change based on software, and produce no gain whatsoever for their company. They can use statistical software to justify anything.
I’ve seen people performing process analysis without even knowing what the process is all about. Statistics is about correlation, while engineering is about causation. Correlation doesn’t mean causation, although causation may lead to stronger correlation. Therefore, Six Sigma practitioners must gain process knowledge before they can interpret a statistical analysis correctly. Besides, statistical software can analyze the data using many techniques and produce an analysis summary that can give a false perception of one’s process expertise.
With a good understanding of the process at hand, practitioners can solve many problems using statistical software. However, if there’s a lack of process knowledge, it’s hard to be sure of what’s going on in the process, or what the statistical analysis is revealing. Process knowledge also expedites statistical analysis, because it allows for Six Sigma experts to know which tool would be effective for performing the desired statistical analysis.
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Free Six Sigma Files
Files containing more on the topics below can be found here:
The Balanced Scorecard (BSC): The BSC is a performance measurement tool that allows organizations to consider all the factors that influence overall performance to get a balanced view. They urged companies to ask and to measure, “If we’re going to succeed financially (the overall mission for businesses), what is it that we’re doing well from our customers’ perspective?” and “If we are to meet these customer needs, what is it that we must do well internally?” By answering such questions, organizations would be considering their performance from all perspectives – financial, customer, and internal. The answers to the questions would define for a company what is most important to be done in achieving the overall goal of financial success. Once an organization identified what was most important to do, it could then develop measures to keep track of how the company was doing at those things. Today over half of Fortune 1,000 companies in North America are using the Balanced Scorecard, which has become the hallmark of a well-run organization. Many organizations say the scorecard is the foundation of their measurement and management systems.
An introduction to basic quality tools: day-to-day we are facing with different problems and understanding and being able to apply basic quality control tools, we can solve these issues in the shortest possible time. The basic tools are:
1 . Flow Chart
2 . Ishikawa diagrams (cause and effect diagram)
3 . 5-why analysis
4 . Check lists
5 . Pareto Chart
6 . Histogram
7 . Scatter diagrams
8 . Control Chart
9 . Brainstorming
A DMAIC project template: This is a very comprehensive template which guides you through the DMAIC framework. It contains several embedded tools that may help you to follow the steps below:
Technorati Tags: six sigma, lean manufacturing
About
Blog objectives
This blog is about quality assurance, six sigma and the Toyota Production System. Hopefully you’ll gain a deeper understanding of this subject by reading the articles, conversations, images, links, thoughts and video clips I post regularly?
About me
I sometimes post comments on other blogs:
You can view my LinkedIn profile and online resume by clicking here:
I’m an engineer and manager by education; quality, safety and environmental professional by experience and statistical enthusiast out of necessity. I believe that although it is easy to lie with statistics it is hard to tell the truth without them. I hold a Bachelor of Engineering (Hons) degree from the University of Northumbria, a Master of Science degree in Total Quality Safety & Environmental Management from the Open University & a Master of Business Administration degree from the University of Durham along with several other qualifications.
After completing a mechanical and production engineering apprenticeship with a turbine-generator manufacturer, I moved into planning for the offshore industry, followed by a move into quality for a consulting firm which specialised in the turnkey construction of combined cycle gas turbine power stations across Europe. Next I helped to establish a high-volume electronics company as a manager responsible for all aspects of quality, safety and environmental issues and then finally to a filter manufacturing company in NE England.
I am a European Foundation For Quality Management Business Excellence Assessor, Six Sigma Black Belt, Member of the Chartered Institute of Quality Assurance, Institute of Occupational Safety and Health, Senior Member of the American Society for Quality, Lead Environmental and Quality Systems Assessor and also a Member of the Chartered Institute of Management.
My favourite work related quote comes from Sir Henry Royce (1863-1933) :
“Strive for perfection in everything you do. Take the best that exists & make it better. If it doesn’t exist create it. Accept nothing as nearly right or good enough”.
Disclaimer
Come on guys …. please take everything I say in the spirit it’s intended. I’m not offering professional advice just my personal opinions – you can take them or leave them! The quality profession is a journey and as such my thoughts and opinions change from time to time as I come to learn more and develop my understanding about the things and issues that I am blogging about. This blog just provides a snapshot of the knowledge, views, and opinions that I hold at a particular point of time and these might most probably change over a period of time.
I reserve the right to evolve my knowledge, thoughts, and viewpoints over time and to change them without assigning any reason. My blog includes links to other sites/blogs operated by third parties. These are provided as a means of convenient access to you to the information/opinion contained therein. I am in no way responsible for the content of any other sites or any products or services that may be offered through other sites. The information in this weblog is provided “AS IS” with no warranties, and confers no rights.
This weblog does not represent the thoughts, intentions, plans or strategies of my employer. Feel free to challenge me, disagree with me, or tell me I’m completely nuts in the comments section of each blog entry, but I reserve the right to delete any comment for any reason whatsoever (abusive, profane, rude, or anonymous comments) – so keep it polite, please!
Remember: Taking Ex-Lax and sleeping tablets on the same night is rarely a good idea.
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