Lies here within all
The finite of infinite
But searching all life long
Where am I,where am I?
When one reach far beyond
Leaving body and all mortal
Only one question asked
What not earned but what thy gave?
Expand your horizon and reach out
To see the unseen and hear the unheard
And theclose you watch you could hear
The sound of one hand's clap
Love is the real and love the truth
Truth and god are not but love
And that love is the ultimate truth that
Create you , me and what not you see
Friday, February 5, 2010
Bench marking
Benchmarking is the process of comparing the business processes and performance metrics including cost, cycle time, productivity, or quality to another that is widely considered to be an industry standard benchmark or best practice. Essentially, benchmarking provides a snapshot of the performance of your business and helps you understand where you are in relation to a particular standard. The result is often a business case and "Burning Platform" for making changes in order to make improvements. The term benchmarking was first used by cobblers to measure people's feet for shoes. They would place someone's foot on a "bench" and mark it out to make the pattern for the shoes. Benchmarking is most used to measure performance using a specific indicator (cost per unit of measure, productivity per unit of measure, cycle time of x per unit of measure or defects per unit of measure) resulting in a metric of performance that is then compared to others.
Also referred to as "best practice benchmarking" or "process benchmarking", it is a process used in management and particularly strategic management, in which organizations evaluate various aspects of their processes in relation to best practice companies' processes, usually within a peer group defined for the purposes of comparison. This then allows organizations to develop plans on how to make improvements or adapt specific best practices, usually with the aim of increasing some aspect of performance. Benchmarking may be a one-off event, but is often treated as a continuous process in which organizations continually seek to improve their practices.
Contents [hide]
1 Popularity and benefits from benchmarking
2 Collaborative benchmarking
3 Procedure
4 Cost of benchmarking
5 Technical Benchmarking/Product Benchmarking
6 Types of benchmarking
7 Metric Benchmarking
8 See also
9 References
[edit]Popularity and benefits from benchmarking
In 2008, a comprehensive survey on benchmarking was commissioned by The Global Benchmarking Network, a network of benchmarking centers representing 22 countries. Over 450 organizations responded from over 40 countries. The results showed that:
Mission and Vision Statements and Customer (Client) Surveys are the most used (by 77% of organisations) of 20 improvement tools, followed by SWOT analysis(72%), and Informal Benchmarking (68%). Performance Benchmarking was used by (49%) and Best Practice Benchmarking by (39%).
The tools that are likely to increase in popularity the most over the next three years are Performance Benchmarking, Informal Benchmarking, SWOT, and Best Practice Benchmarking. Over 60% of organizations that are not currently using these tools indicated they are likely to use them in the next three years.
[edit]Collaborative benchmarking
Benchmarking, originally invented as a formal process by Rank Xerox, is usually carried out by individual companies. Sometimes it may be carried out collaboratively by groups of companies (eg subsidiaries of a multinational in different countries). One example is that of the Dutch municipally-owned water supply companies, which have carried out a voluntary collaborative benchmarking process since 1997 through their industry association. Another example is the UK construction industry which has carried out benchmarking since the late 1990's again through its industry association and with financial support from the UK Government.
[edit]Procedure
There is no single benchmarking process that has been universally adopted. The wide appeal and acceptance of benchmarking has led to various benchmarking methodologies emerging. The first book on benchmarking, written by Kaiser Associates[1], offered a 7-step approach. Robert Camp (who wrote one of the earliest books on benchmarking in 1989)[2] developed a 12-stage approach to benchmarking.
The 12 stage methodology consisted of 1. Select subject ahead 2. Define the process 3. Identify potential partners 4. Identify data sources 5. Collect data and select partners 6. Determine the gap 7. Establish process differences 8. Target future performance 9. Communicate 10. Adjust goal 11. Implement 12. Review/recalibrate.
The following is an example of a typical benchmarking methodology:
Identify your problem areas - Because benchmarking can be applied to any business process or function, a range of research techniques may be required. They include: informal conversations with customers, employees, or suppliers; exploratory research techniques such as focus groups; or in-depth marketing research, quantitative research, surveys, questionnaires, re-engineering analysis, process mapping, quality control variance reports, or financial ratio analysis. Before embarking on comparison with other organizations it is essential that you know your own organization's function, processes; base lining performance provides a point against which improvement effort can be measured.
Identify other industries that have similar processes - For instance if one were interested in improving hand offs in addiction treatment he/she would try to identify other fields that also have hand off challenges. These could include air traffic control, cell phone switching between towers, transfer of patients from surgery to recovery rooms.
Identify organizations that are leaders in these areas - Look for the very best in any industry and in any country. Consult customers, suppliers, financial analysts, trade associations, and magazines to determine which companies are worthy of study.
Survey companies for measures and practices - Companies target specific business processes using detailed surveys of measures and practices used to identify business process alternatives and leading companies. Surveys are typically masked to protect confidential data by neutral associations and consultants.
Visit the "best practice" companies to identify leading edge practices - Companies typically agree to mutually exchange information beneficial to all parties in a benchmarking group and share the results within the group.
Implement new and improved business practices - Take the leading edge practices and develop implementation plans which include identification of specific opportunities, funding the project and selling the ideas to the organization for the purpose of gaining demonstrated value from the process.
[edit]Cost of benchmarking
Benchmarking is a moderately expensive process, but most organizations find that it more than pays for itself. The three main types of costs are:
Visit Costs - This includes hotel rooms, travel costs, meals, a token gift, and lost labor time.
Time Costs - Members of the benchmarking team will be investing time in researching problems, finding exceptional companies to study, visits, and implementation. This will take them away from their regular tasks for part of each day so additional staff might be required.
Benchmarking Database Costs - Organizations that institutionalize benchmarking into their daily procedures find it is useful to create and maintain a database of best practices and the companies associated with each best practice now.
The cost of benchmarking can substantially be reduced through utilizing the many internet resources that have sprung up over the last few years. These aim to capture benchmarks and best practices from organizations, business sectors and countries to make the benchmarking process much quicker and cheaper.
[edit]Technical Benchmarking/Product Benchmarking
The technique initially used to compare existing corporate strategies with a view to achieving the best possible performance in new situations (see above), has recently been extended to the comparison of technical products. This process is usually referred to as "Technical Benchmarking" or "Product Benchmarking". Its use is particularly well developed within the automotive industry ("Automotive Benchmarking"), where it is vital to design products that match precise user expectations, at minimum possible cost, by applying the best technologies available worldwide. Many data are obtained by fully disassembling existing cars and their systems. Such analyses were initially carried out in-house by car makers and their suppliers. However, as they are expensive, they are increasingly outsourced to companies specialized in this area. Indeed, outsourcing has enabled a drastic decrease in costs for each company (by cost sharing) and the development of very efficient tools (standards, software).
[edit]Types of benchmarking
Process benchmarking - the initiating firm focuses its observation and investigation of business processes with a goal of identifying and observing the best practices from one or more benchmark firms. Activity analysis will be required where the objective is to benchmark cost and efficiency; increasingly applied to back-office processes where outsourcing may be a consideration.
Financial benchmarking - performing a financial analysis and comparing the results in an effort to assess your overall competitiveness and productivity.
Benchmarking from an investor perspective- extending the benchmarking universe to also compare to peer companies that can be considered alternative investment opportunities from the perspective of an investor.
Performance benchmarking - allows the initiator firm to assess their competitive position by comparing products and services with those of target firms.
Product benchmarking - the process of designing new products or upgrades to current ones. This process can sometimes involve reverse engineering which is taking apart competitors products to find strengths and weaknesses.
Strategic benchmarking - involves observing how others compete. This type is usually not industry specific, meaning it is best to look at other industries.
Functional benchmarking - a company will focus its benchmarking on a single function in order to improve the operation of that particular function. Complex functions such as Human Resources, Finance and Accounting and Information and Communication Technology are unlikely to be directly comparable in cost and efficiency terms and may need to be disaggregated into processes to make valid comparison.
Best-in-class benchmarking - involves studying the leading competitor or the company that best carries out a specific function.
Operational benchmarking - embraces everything from staffing and productivity to office flow and analysis of procedures performed[3].
[edit]Metric Benchmarking
Another approach to making comparisons involves using more aggregative cost or production information to identify strong and weak performing units. The two most common forms of quantitative analysis used in metric benchmarking are data envelope analysis (DEA) and regression analysis. DEA estimates the cost level an efficient firm should be able to achieve in a particular market. In infrastructure regulation, DEA can be used to reward companies/operators whose costs are near the efficient frontier with additional profits. Regression analysis estimates what the average firm should be able to achieve. With regression analysis firms that performed better than average can be rewarded while firms that performed worse than average can be penalized. Such benchmarking studies are used to create yardstick comparisons, allowing outsiders to evaluate the performance of operators in an industry. A variety of advanced statistical techniques, including stochastic frontier analysis, have been utilized to identify high performers and weak performers in a number of industries, including applications to schools, hospitals, water utilities, and electric utilities.[4]
One of the biggest challenges for Metric Benchmarking is the variety of metric definitions used by different companies and/or divisions. Metrics definitions may also change over time within the same organization due to changes in leadership and priorities. The most useful comparisons can be made when metrics definitions are common between compared units and do not change over time so improvements can be verified.
[edit]See also
Sales benchmarking
Business Excellence
Best Practices
Indexing Operating Performance
[edit]References
^ Beating the competition: a practical guide to Benchmarking. Washington, DC: Kaiser Associates. 1988. pp. 176. ISBN 978-1563650185.
^ Camp, R. (1989). The search for industry best practices that lead 2 superior performance. Productivity Press.
^ Benchmarking: How to Make the Best Decisions for Your Practice[1]
^ Body of Knowledge on Infrastructure Regulation “Incentive Regulation: Basic forms of Regulation”
Also referred to as "best practice benchmarking" or "process benchmarking", it is a process used in management and particularly strategic management, in which organizations evaluate various aspects of their processes in relation to best practice companies' processes, usually within a peer group defined for the purposes of comparison. This then allows organizations to develop plans on how to make improvements or adapt specific best practices, usually with the aim of increasing some aspect of performance. Benchmarking may be a one-off event, but is often treated as a continuous process in which organizations continually seek to improve their practices.
Contents [hide]
1 Popularity and benefits from benchmarking
2 Collaborative benchmarking
3 Procedure
4 Cost of benchmarking
5 Technical Benchmarking/Product Benchmarking
6 Types of benchmarking
7 Metric Benchmarking
8 See also
9 References
[edit]Popularity and benefits from benchmarking
In 2008, a comprehensive survey on benchmarking was commissioned by The Global Benchmarking Network, a network of benchmarking centers representing 22 countries. Over 450 organizations responded from over 40 countries. The results showed that:
Mission and Vision Statements and Customer (Client) Surveys are the most used (by 77% of organisations) of 20 improvement tools, followed by SWOT analysis(72%), and Informal Benchmarking (68%). Performance Benchmarking was used by (49%) and Best Practice Benchmarking by (39%).
The tools that are likely to increase in popularity the most over the next three years are Performance Benchmarking, Informal Benchmarking, SWOT, and Best Practice Benchmarking. Over 60% of organizations that are not currently using these tools indicated they are likely to use them in the next three years.
[edit]Collaborative benchmarking
Benchmarking, originally invented as a formal process by Rank Xerox, is usually carried out by individual companies. Sometimes it may be carried out collaboratively by groups of companies (eg subsidiaries of a multinational in different countries). One example is that of the Dutch municipally-owned water supply companies, which have carried out a voluntary collaborative benchmarking process since 1997 through their industry association. Another example is the UK construction industry which has carried out benchmarking since the late 1990's again through its industry association and with financial support from the UK Government.
[edit]Procedure
There is no single benchmarking process that has been universally adopted. The wide appeal and acceptance of benchmarking has led to various benchmarking methodologies emerging. The first book on benchmarking, written by Kaiser Associates[1], offered a 7-step approach. Robert Camp (who wrote one of the earliest books on benchmarking in 1989)[2] developed a 12-stage approach to benchmarking.
The 12 stage methodology consisted of 1. Select subject ahead 2. Define the process 3. Identify potential partners 4. Identify data sources 5. Collect data and select partners 6. Determine the gap 7. Establish process differences 8. Target future performance 9. Communicate 10. Adjust goal 11. Implement 12. Review/recalibrate.
The following is an example of a typical benchmarking methodology:
Identify your problem areas - Because benchmarking can be applied to any business process or function, a range of research techniques may be required. They include: informal conversations with customers, employees, or suppliers; exploratory research techniques such as focus groups; or in-depth marketing research, quantitative research, surveys, questionnaires, re-engineering analysis, process mapping, quality control variance reports, or financial ratio analysis. Before embarking on comparison with other organizations it is essential that you know your own organization's function, processes; base lining performance provides a point against which improvement effort can be measured.
Identify other industries that have similar processes - For instance if one were interested in improving hand offs in addiction treatment he/she would try to identify other fields that also have hand off challenges. These could include air traffic control, cell phone switching between towers, transfer of patients from surgery to recovery rooms.
Identify organizations that are leaders in these areas - Look for the very best in any industry and in any country. Consult customers, suppliers, financial analysts, trade associations, and magazines to determine which companies are worthy of study.
Survey companies for measures and practices - Companies target specific business processes using detailed surveys of measures and practices used to identify business process alternatives and leading companies. Surveys are typically masked to protect confidential data by neutral associations and consultants.
Visit the "best practice" companies to identify leading edge practices - Companies typically agree to mutually exchange information beneficial to all parties in a benchmarking group and share the results within the group.
Implement new and improved business practices - Take the leading edge practices and develop implementation plans which include identification of specific opportunities, funding the project and selling the ideas to the organization for the purpose of gaining demonstrated value from the process.
[edit]Cost of benchmarking
Benchmarking is a moderately expensive process, but most organizations find that it more than pays for itself. The three main types of costs are:
Visit Costs - This includes hotel rooms, travel costs, meals, a token gift, and lost labor time.
Time Costs - Members of the benchmarking team will be investing time in researching problems, finding exceptional companies to study, visits, and implementation. This will take them away from their regular tasks for part of each day so additional staff might be required.
Benchmarking Database Costs - Organizations that institutionalize benchmarking into their daily procedures find it is useful to create and maintain a database of best practices and the companies associated with each best practice now.
The cost of benchmarking can substantially be reduced through utilizing the many internet resources that have sprung up over the last few years. These aim to capture benchmarks and best practices from organizations, business sectors and countries to make the benchmarking process much quicker and cheaper.
[edit]Technical Benchmarking/Product Benchmarking
The technique initially used to compare existing corporate strategies with a view to achieving the best possible performance in new situations (see above), has recently been extended to the comparison of technical products. This process is usually referred to as "Technical Benchmarking" or "Product Benchmarking". Its use is particularly well developed within the automotive industry ("Automotive Benchmarking"), where it is vital to design products that match precise user expectations, at minimum possible cost, by applying the best technologies available worldwide. Many data are obtained by fully disassembling existing cars and their systems. Such analyses were initially carried out in-house by car makers and their suppliers. However, as they are expensive, they are increasingly outsourced to companies specialized in this area. Indeed, outsourcing has enabled a drastic decrease in costs for each company (by cost sharing) and the development of very efficient tools (standards, software).
[edit]Types of benchmarking
Process benchmarking - the initiating firm focuses its observation and investigation of business processes with a goal of identifying and observing the best practices from one or more benchmark firms. Activity analysis will be required where the objective is to benchmark cost and efficiency; increasingly applied to back-office processes where outsourcing may be a consideration.
Financial benchmarking - performing a financial analysis and comparing the results in an effort to assess your overall competitiveness and productivity.
Benchmarking from an investor perspective- extending the benchmarking universe to also compare to peer companies that can be considered alternative investment opportunities from the perspective of an investor.
Performance benchmarking - allows the initiator firm to assess their competitive position by comparing products and services with those of target firms.
Product benchmarking - the process of designing new products or upgrades to current ones. This process can sometimes involve reverse engineering which is taking apart competitors products to find strengths and weaknesses.
Strategic benchmarking - involves observing how others compete. This type is usually not industry specific, meaning it is best to look at other industries.
Functional benchmarking - a company will focus its benchmarking on a single function in order to improve the operation of that particular function. Complex functions such as Human Resources, Finance and Accounting and Information and Communication Technology are unlikely to be directly comparable in cost and efficiency terms and may need to be disaggregated into processes to make valid comparison.
Best-in-class benchmarking - involves studying the leading competitor or the company that best carries out a specific function.
Operational benchmarking - embraces everything from staffing and productivity to office flow and analysis of procedures performed[3].
[edit]Metric Benchmarking
Another approach to making comparisons involves using more aggregative cost or production information to identify strong and weak performing units. The two most common forms of quantitative analysis used in metric benchmarking are data envelope analysis (DEA) and regression analysis. DEA estimates the cost level an efficient firm should be able to achieve in a particular market. In infrastructure regulation, DEA can be used to reward companies/operators whose costs are near the efficient frontier with additional profits. Regression analysis estimates what the average firm should be able to achieve. With regression analysis firms that performed better than average can be rewarded while firms that performed worse than average can be penalized. Such benchmarking studies are used to create yardstick comparisons, allowing outsiders to evaluate the performance of operators in an industry. A variety of advanced statistical techniques, including stochastic frontier analysis, have been utilized to identify high performers and weak performers in a number of industries, including applications to schools, hospitals, water utilities, and electric utilities.[4]
One of the biggest challenges for Metric Benchmarking is the variety of metric definitions used by different companies and/or divisions. Metrics definitions may also change over time within the same organization due to changes in leadership and priorities. The most useful comparisons can be made when metrics definitions are common between compared units and do not change over time so improvements can be verified.
[edit]See also
Sales benchmarking
Business Excellence
Best Practices
Indexing Operating Performance
[edit]References
^ Beating the competition: a practical guide to Benchmarking. Washington, DC: Kaiser Associates. 1988. pp. 176. ISBN 978-1563650185.
^ Camp, R. (1989). The search for industry best practices that lead 2 superior performance. Productivity Press.
^ Benchmarking: How to Make the Best Decisions for Your Practice[1]
^ Body of Knowledge on Infrastructure Regulation “Incentive Regulation: Basic forms of Regulation”
Six sigma
Six Sigma is a business management strategy originally developed by Motorola, USA in 1981.[1] As of 2009, it enjoys widespread application in many sectors of industry, although its application is not without controversy.
Six Sigma seeks to improve the quality of process outputs by identifying and removing the causes of defects (errors) and minimizing variability in manufacturing and business processes.[2] It uses a set of quality management methods, including statistical methods, and creates a special infrastructure of people within the organization ("Black Belts", "Green Belts", etc.) who are experts in these methods.[2] Each Six Sigma project carried out within an organization follows a defined sequence of steps and has quantified targets. These targets can be financial (cost reduction or profit increase) or whatever is critical to the customer of that process (cycle time, safety, delivery, etc.).[2]
Contents [hide]
1 Historical overview
2 Methods
2.1 DMAIC
2.2 DMADV
2.3 Quality management tools and methods used in Six Sigma
3 Implementation roles
4 Origin and meaning of the term "six sigma process"
4.1 Role of the 1.5 sigma shift
4.2 Sigma levels
5 Software used for Six Sigma
6 List of Six Sigma companies
7 Criticism
7.1 Lack of originality
7.2 Role of consultants
7.3 Potential negative effects
7.4 Based on arbitrary standards
7.5 Criticism of the 1.5 sigma shift
8 See also
9 References
10 Further reading
[edit]Historical overview
Six Sigma originated as a set of practices designed to improve manufacturing processes and eliminate defects, but its application was subsequently extended to other types of business processes as well.[3] In Six Sigma, a defect is defined as any process output that does not meet customer specifications, or that could lead to creating an output that does not meet customer specifications.[2]
Bill Smith first formulated the particulars of the methodology at Motorola in 1986.[4] Six Sigma was heavily inspired by six preceding decades of quality improvement methodologies such as quality control, TQM, and Zero Defects,[5][6] based on the work of pioneers such as Shewhart, Deming, Juran, Ishikawa, Taguchi and others.
Like its predecessors, Six Sigma doctrine asserts that:
Continuous efforts to achieve stable and predictable process results (i.e. reduce process variation) are of vital importance to business success.
Manufacturing and business processes have characteristics that can be measured, analyzed, improved and controlled.
Achieving sustained quality improvement requires commitment from the entire organization, particularly from top-level management.
Features that set Six Sigma apart from previous quality improvement initiatives include:
A clear focus on achieving measurable and quantifiable financial returns from any Six Sigma project.[2]
An increased emphasis on strong and passionate management leadership and support.[2]
A special infrastructure of "Champions," "Master Black Belts," "Black Belts," etc. to lead and implement the Six Sigma approach.[2]
A clear commitment to making decisions on the basis of verifiable data, rather than assumptions and guesswork.[2]
The term "Six Sigma" comes from a field of statistics known as process capability studies. Originally, it referred to the ability of manufacturing processes to produce a very high proportion of output within specification. Processes that operate with "six sigma quality" over the short term are assumed to produce long-term defect levels below 3.4 defects per million opportunities (DPMO).[7][8] Six Sigma's implicit goal is to improve all processes to that level of quality or better.
Six Sigma is a registered service mark and trademark of Motorola Inc.[9] As of 2006 Motorola reported over US$17 billion in savings[10] from Six Sigma.
Other early adopters of Six Sigma who achieved well-publicized success include Honeywell (previously known as AlliedSignal) and General Electric, where Jack Welch introduced the method.[11] By the late 1990s, about two-thirds of the Fortune 500 organizations had begun Six Sigma initiatives with the aim of reducing costs and improving quality.[12]
In recent years, some practitioners have combined Six Sigma ideas with lean manufacturing to yield a methodology named Lean Six Sigma.
[edit]Methods
Six Sigma projects follow two project methodologies inspired by Deming's Plan-Do-Check-Act Cycle. These methodologies, comprising five phases each, bear the acronyms DMAIC and DMADV.[12]
DMAIC is used for projects aimed at improving an existing business process.[12]
DMADV is used for projects aimed at creating new product or process designs.[12]
[edit]DMAIC
The DMAIC project methodology has five phases:
Define the problem, the voice of the customer, and the project goals, specifically.
Measure key aspects of the current process and collect relevant data.
Analyze the data to investigate and verify cause-and-effect relationships. Determine what the relationships are, and attempt to ensure that all factors have been considered. Seek out root cause of the defect under investigation.
Improve or optimize the current process based upon data analysis using techniques such as design of experiments, poka yoke or mistake proofing, and standard work to create a new, future state process. Set up pilot runs to establish process capability.
Control the future state process to ensure that any deviations from target are corrected before they result in defects. Control systems are implemented such as statistical process control, production boards, and visual workplaces and the process is continuously monitored.
[edit]DMADV
The DMADV project methodology, also known as DFSS ("Design For Six Sigma"),[12] features five phases:
Define design goals that are consistent with customer demands and the enterprise strategy.
Measure and identify CTQs (characteristics that are Critical To Quality), product capabilities, production process capability, and risks.
Analyze to develop and design alternatives, create a high-level design and evaluate design capability to select the best design.
Design details, optimize the design, and plan for design verification. This phase may require simulations.
Verify the design, set up pilot runs, implement the production process and hand it over to the process owner(s).
[edit]Quality management tools and methods used in Six Sigma
Within the individual phases of a DMAIC or DMADV project, Six Sigma utilizes many established quality-management tools that are also used outside of Six Sigma. The following table shows an overview of the main methods used.
5 Whys
Analysis of variance
ANOVA Gauge R&R
Axiomatic design
Business Process Mapping
Catapult exercise on variability
Cause & effects diagram (also known as fishbone or Ishikawa diagram)
Chi-square test of independence and fits
Control chart
Correlation
Cost-benefit analysis
CTQ tree
Quantitative marketing research through use of Enterprise Feedback Management (EFM) systems
Design of experiments
Failure mode and effects analysis (FMEA)
General linear model
Histograms
Homoscedasticity
Quality Function Deployment (QFD)
Pareto chart
Pick chart
Process capability
Regression analysis
Root cause analysis
Run charts
SIPOC analysis (Suppliers, Inputs, Process, Outputs, Customers)
Stratification
Taguchi methods
Taguchi Loss Function
Thought process map
TRIZ
[edit]Implementation roles
One key innovation of Six Sigma involves the "professionalizing" of quality management functions. Prior to Six Sigma, quality management in practice was largely relegated to the production floor and to statisticians in a separate quality department. Six Sigma borrows martial arts ranking terminology to define a hierarchy (and career path) that cuts across all business functions.
Six Sigma identifies several key roles for its successful implementation.[13]
Executive Leadership includes the CEO and other members of top management. They are responsible for setting up a vision for Six Sigma implementation. They also empower the other role holders with the freedom and resources to explore new ideas for[weasel words]breakthrough improvements.
Champions take responsibility for Six Sigma implementation across the organization in an integrated manner. The Executive Leadership draws them from upper management. Champions also act as mentors to Black Belts.
Master Black Belts, identified by champions, act as in-house coaches on Six Sigma. They devote 100% of their time to Six Sigma. They assist champions and guide Black Belts and Green Belts. Apart from statistical tasks, they spend their time on ensuring consistent application of Six Sigma across various functions and departments.
Black Belts operate under Master Black Belts to apply Six Sigma methodology to specific projects. They devote 100% of their time to Six Sigma. They primarily focus on Six Sigma project execution, whereas Champions and Master Black Belts focus on identifying projects/functions for Six Sigma.
Green Belts, the employees who take up Six Sigma implementation along with their other job responsibilities, operate under the guidance of Black Belts.
Yellow Belts, trained in the basic application of Six Sigma management tools, work with the Black Belt throughout the project stages and are often the closest to the work.
[edit]Origin and meaning of the term "six sigma process"
Graph of the normal distribution, which underlies the statistical assumptions of the Six Sigma model. The Greek letter σ (sigma) marks the distance on the horizontal axis between the mean, µ, and the curve's inflection point, in this case µ=1. The distance is equally distributed horzontally to both sides of the mean µ as: [µ - σ/2, µ + σ/2]. The greater this distance, the greater is the spread of values encountered. For the curve shown above, µ = 0 and σ = 2. The upper and lower specification limits (USL, LSL) are at a distance of 6σ from the mean. Due to the properties of the normal distribution, values lying that far away from the mean are extremely unlikely. Even if the mean were to move right or left by 1.5σ at some point in the future (1.5 sigma shift), there is still a good safety cushion. This is why Six Sigma aims to have processes where the mean is at least 6σ away from the nearest specification limit.
The term "six sigma process" comes from the notion that if one has six standard deviations between the process mean and the nearest specification limit, as shown in the graph, practically no items will fail to meet specifications.[8] This is based on the calculation method employed in process capability studies.
Capability studies measure the number of standard deviations between the process mean and the nearest specification limit in sigma units. As process standard deviation goes up, or the mean of the process moves away from the center of the tolerance, fewer standard deviations will fit between the mean and the nearest specification limit, decreasing the sigma number and increasing the likelihood of items outside specification.[8]
[edit]Role of the 1.5 sigma shift
Experience has shown that in the long term, processes usually do not perform as well as they do in the short.[8] As a result, the number of sigmas that will fit between the process mean and the nearest specification limit may well drop over time, compared to an initial short-term study.[8] To account for this real-life increase in process variation over time, an empirically-based 1.5 sigma shift is introduced into the calculation.[8][14] According to this idea, a process that fits six sigmas between the process mean and the nearest specification limit in a short-term study will in the long term only fit 4.5 sigmas – either because the process mean will move over time, or because the long-term standard deviation of the process will be greater than that observed in the short term, or both.[8]
Hence the widely accepted definition of a six sigma process as one that produces 3.4 defective parts per million opportunities (DPMO). This is based on the fact that a process that is normally distributed will have 3.4 parts per million beyond a point that is 4.5 standard deviations above or below the mean (one-sided capability study).[8] So the 3.4 DPMO of a "Six Sigma" process in fact corresponds to 4.5 sigmas, namely 6 sigmas minus the 1.5 sigma shift introduced to account for long-term variation.[8] This is designed to prevent underestimation of the defect levels likely to be encountered in real-life operation.[8]
[edit]Sigma levels
See also: Three sigma rule
The table[15][16] below gives long-term DPMO values corresponding to various short-term sigma levels.
Note that these figures assume that the process mean will shift by 1.5 sigma towards the side with the critical specification limit. In other words, they assume that after the initial study determining the short-term sigma level, the long-term Cpk value will turn out to be 0.5 less than the short-term Cpk value. So, for example, the DPMO figure given for 1 sigma assumes that the long-term process mean will be 0.5 sigma beyond the specification limit (Cpk = –0.17), rather than 1 sigma within it, as it was in the short-term study (Cpk = 0.33). Note that the defect percentages only indicate defects exceeding the specification limit that the process mean is nearest to. Defects beyond the far specification limit are not included in the percentages.
Sigma level DPMO Percent defective Percentage yield Short-term Cpk Long-term Cpk
1 691,462 69% 31% 0.33 –0.17
2 308,538 31% 69% 0.67 0.17
3 66,807 6.7% 93.3% 1.00 0.5
4 6,210 0.62% 99.38% 1.33 0.83
5 233 0.023% 99.977% 1.67 1.17
6 3.4 0.00034% 99.99966% 2.00 1.5
7 0.019 0.0000019% 99.9999981% 2.33 1.83
[edit]Software used for Six Sigma
Main article: List of Six Sigma software packages
[edit]List of Six Sigma companies
Main article: List of Six Sigma companies
[edit]Criticism
[edit]Lack of originality
Noted quality expert Joseph M. Juran has described Six Sigma as "a basic version of quality improvement", stating that "[t]here is nothing new there. It includes what we used to call facilitators. They've adopted more flamboyant terms, like belts with different colors. I think that concept has merit to set apart, to create specialists who can be very helpful. Again, that's not a new idea. The American Society for Quality long ago established certificates, such as for reliability engineers."[17]
[edit]Role of consultants
The use of "Black Belts" as itinerant change agents has (controversially) fostered a cottage industry of training and certification. Critics argue there is overselling of Six Sigma by too great a number of consulting firms, many of which claim expertise in Six Sigma when they only have a rudimentary understanding of the tools and techniques involved.[2]
Some commentators view the expansion of the various "Belts" to include "Green Belts," "Master Black Belts" and "Gold Belts" as a parallel to the various "belt factories" that exist in martial arts.[citation needed]
[edit]Potential negative effects
A Fortune article stated that "of 58 large companies that have announced Six Sigma programs, 91 percent have trailed the S&P 500 since". The statement is attributed to "an analysis by Charles Holland of consulting firm Qualpro (which espouses a competing quality-improvement process)."[18] The gist of the article is that Six Sigma is effective at what it is intended to do, but that it is "narrowly designed to fix an existing process" and does not help in "coming up with new products or disruptive technologies." Many of these claims have been argued as being in error or ill-informed.[19][20]
A BusinessWeek article says that James McNerney's introduction of Six Sigma at 3M may have had the effect of stifling creativity. It cites two Wharton School professors who say that Six Sigma leads to incremental innovation at the expense of blue-sky work.[21] This phenomenon is further explored in the book, Going Lean, which provides data to show that Ford's "6 Sigma" program did little to change its fortunes.[22]
[edit]Based on arbitrary standards
While 3.4 defects per million opportunities might work well for certain products/processes, it might not operate optimally or cost effectively for others. A pacemaker process might need higher standards, for example, whereas a direct mail advertising campaign might need lower standards. The basis and justification for choosing 6 (as opposed to 5 or 7, for example) as the number of standard deviations is not clearly explained. In addition, the Six Sigma model assumes that the process data always conform to the normal distribution. The calculation of defect rates for situations where the normal distribution model does not apply is not properly addressed in the current Six Sigma literature.[2]
[edit]Criticism of the 1.5 sigma shift
The statistician Donald J. Wheeler has dismissed the 1.5 sigma shift as "goofy" because of its arbitrary nature.[23] Its universal applicability is seen as doubtful.[2]
The 1.5 sigma shift has also become contentious because it results in stated "sigma levels" that reflect short-term rather than long-term performance: a process that has long-term defect levels corresponding to 4.5 sigma performance is, by Six Sigma convention, described as a "6 sigma process."[8][24] The accepted Six Sigma scoring system thus cannot be equated to actual normal distribution probabilities for the stated number of standard deviations, and this has been a key bone of contention about how Six Sigma measures are defined.[24] The fact that it is rarely explained that a "6 sigma" process will have long-term defect rates corresponding to 4.5 sigma performance rather than actual 6 sigma performance has led several commentators to express the opinion that Six Sigma is a confidence trick.[8]
[edit]See also
Business process
Design for Six Sigma
[edit]References
^ Tennant, Geoff (2001). SIX SIGMA: SPC and TQM in Manufacturing and Services. Gower Publishing, Ltd.. p. 6. ISBN 0566083744.
^ a b c d e f g h i j k Antony, Jiju. "Pros and cons of Six Sigma: an academic perspective". Retrieved May 1, 2008.
^ "Motorola University - What is Six Sigma?". Retrieved 2009-09-14. "[...] Six Sigma started as a defect reduction effort in manufacturing and was then applied to other business processes for the same purpose."
^ "The Inventors of Six Sigma". Retrieved January 29, 2006.
^ Stamatis, D. H. (2004), Six Sigma Fundamentals: A Complete Guide to the System, Methods, and Tools, New York, New York: Productivity Press, p. 1, ISBN 9781563272929, OCLC 52775178, "The practitioner of the six sigma methodology in any organization should expect to see the use of old and established tools and approaches in the pursuit of continual improvement and customer satisfaction. So much so that even TQM (total quality management) is revisited as a foundation of some of the approaches. In fact, one may define six sigma as "TQM on steroids.""
^ Montgomery, Douglas C. (2009), Statistical Quality Control: A Modern Introduction (6 ed.), Hoboken, New Jersey: John Wiley & Sons, p. 23, ISBN 9780470233979, OCLC 244727396, "During the 1950s and 1960s programs such as Zero Defects and Value Engineering abounded, but they had little impact on quality and productivity improvement. During the heyday of TQM in the 1980s, another popular program was the Quality Is Free initiative, in which management worked on identifying the cost of quality..."
^ "Motorola University Six Sigma Dictionary". Retrieved January 29, 2006.
^ a b c d e f g h i j k l Tennant, Geoff (2001). SIX SIGMA: SPC and TQM in Manufacturing and Services. Gower Publishing, Ltd.. pp. 25. ISBN 0566083744.
^ "Motorola Inc. - Motorola University". Retrieved January 29, 2006.
^ "About Motorola University". Retrieved January 29, 2006.
^ "Six Sigma: Where is it now?". Retrieved May 22, 2008.
^ a b c d e De Feo, Joseph A.; Barnard, William (2005). JURAN Institute's Six Sigma Breakthrough and Beyond - Quality Performance Breakthrough Methods. Tata McGraw-Hill Publishing Company Limited. ISBN 0-07-059881-9.
^ Harry, Mikel; Schroeder, Richard (2000). Six Sigma. Random House, Inc. ISBN 0-385-49437-8.
^ Harry, Mikel J. (1988). The Nature of six sigma quality. Rolling Meadows, Illinois: Motorola University Press. p. 25. ISBN 9781569460092.
^ Gygi, Craig; DeCarlo, Neil; Williams, Bruce (2005). Six Sigma for Dummies. Hoboken, NJ: Wiley Publishing, Inc.. pp. Front inside cover, 23. ISBN 0-7645-6798-5.
^ El-Haik, Basem; Suh, Nam P.. Axiomatic Quality. John Wiley and Sons. p. 10. ISBN 9780471682738.
^ Paton, Scott M. (August 2002). Juran: A Lifetime of Quality. 22. pp. 19–23. Retrieved 2009-04-01.
^ Morris, Betsy (2006-07-11). "Tearing up the Jack Welch playbook". Fortune. Retrieved 2006-11-26.
^ Richardson, Karen (2007-01-07). "The 'Six Sigma' Factor for Home Depot". Wall Street Journal Online. Retrieved October 15, 2007.
^ Ficalora, Joe; Costello, Joe. "Wall Street Journal SBTI Rebuttal" (PDF). Sigma Breakthrough Technologies, Inc.. Retrieved October 15, 2007.
^ Hindo, Brian (6 June 2007). "At 3M, a struggle between efficiency and creativity". Business Week. Retrieved June 6, 2007.
^ Ruffa, Stephen A. (2008). Going Lean: How the Best Companies Apply Lean Manufacturing Principles to Shatter Uncertainty, Drive Innovation, and Maximize Profits. AMACOM (a division of American Management Association). ISBN 0-8144-1057-X.
^ Wheeler, Donald J. (2004). The Six Sigma Practitioner's Guide to Data Analysis. SPC Press. p. 307. ISBN 9780945320623.
^ a b *Pande, Peter S.; Neuman, Robert P.; Cavanagh, Roland R. (2001). The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance. New York: McGraw-Hill Professional. p. 229. ISBN 0071358064.
[edit]Further reading
Adams, Cary W.; Gupta, Praveen (2003). Six Sigma Deployment. Burlington, MA: Butterworth-Heinemann. ISBN 0750675233.
Breyfogle, Forrest W. III (1999). Implementing Six Sigma: Smarter Solutions Using Statistical Methods. New York, NY: John Wiley & Sons. ISBN 0471265721.
De Feo, Joseph A.; Barnard, William (2005). JURAN Institute's Six Sigma Breakthrough and Beyond - Quality Performance Breakthrough Methods. New York, NY: McGraw-Hill Professional. ISBN 0071422277.
Hahn, G. J., Hill, W. J., Hoerl, R. W. and Zinkgraf, S. A. (1999) The Impact of Six Sigma Improvement-A Glimpse into the Future of Statistics, The American Statistician, Vol. 53, No. 3, pp. 208-215.
Harry, Mikel J.; Schroeder, Richard (1999). Six Sigma: The Breakthrough Management Strategy Revolutionizing the World’s Top Corporations. New York, NY: Doubleday. ISBN 0385494378.
Keller, Paul A. (2001). Six Sigma Deployment: A Guide for Implementing Six Sigma in Your Organization. Tucson, AZ: Quality Publishing. ISBN 0930011848.
Pande, Peter S.; Neuman, Robert P. (2001). The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance. New York, NY: McGraw-Hill Professional. ISBN 0071358064.
Pyzdek, Thomas and Paul A. Keller (2009). The Six Sigma Handbook, Third Edition. New York, NY: McGraw-Hill. ISBN 0071623388.
Snee, Ronald D.; Hoerl, Roger W. (2002). Leading Six Sigma: A Step-by-Step Guide Based on Experience with GE and Other Six Sigma Companies. Upper Saddle River, NJ: FT Press. ISBN 0130084573.
Taylor, Gerald (2008). Lean Six Sigma Service Excellence: A Guide to Green Belt Certification and Bottom Line Improvement. New York, NY: J. Ross Publishing. ISBN 978-1604270068.
Tennant, Geoff (2001). SIX SIGMA: SPC and TQM in Manufacturing and Services. Aldershot, UK: Gower Publishing, Ltd. ISBN 0566083744.
Six Sigma seeks to improve the quality of process outputs by identifying and removing the causes of defects (errors) and minimizing variability in manufacturing and business processes.[2] It uses a set of quality management methods, including statistical methods, and creates a special infrastructure of people within the organization ("Black Belts", "Green Belts", etc.) who are experts in these methods.[2] Each Six Sigma project carried out within an organization follows a defined sequence of steps and has quantified targets. These targets can be financial (cost reduction or profit increase) or whatever is critical to the customer of that process (cycle time, safety, delivery, etc.).[2]
Contents [hide]
1 Historical overview
2 Methods
2.1 DMAIC
2.2 DMADV
2.3 Quality management tools and methods used in Six Sigma
3 Implementation roles
4 Origin and meaning of the term "six sigma process"
4.1 Role of the 1.5 sigma shift
4.2 Sigma levels
5 Software used for Six Sigma
6 List of Six Sigma companies
7 Criticism
7.1 Lack of originality
7.2 Role of consultants
7.3 Potential negative effects
7.4 Based on arbitrary standards
7.5 Criticism of the 1.5 sigma shift
8 See also
9 References
10 Further reading
[edit]Historical overview
Six Sigma originated as a set of practices designed to improve manufacturing processes and eliminate defects, but its application was subsequently extended to other types of business processes as well.[3] In Six Sigma, a defect is defined as any process output that does not meet customer specifications, or that could lead to creating an output that does not meet customer specifications.[2]
Bill Smith first formulated the particulars of the methodology at Motorola in 1986.[4] Six Sigma was heavily inspired by six preceding decades of quality improvement methodologies such as quality control, TQM, and Zero Defects,[5][6] based on the work of pioneers such as Shewhart, Deming, Juran, Ishikawa, Taguchi and others.
Like its predecessors, Six Sigma doctrine asserts that:
Continuous efforts to achieve stable and predictable process results (i.e. reduce process variation) are of vital importance to business success.
Manufacturing and business processes have characteristics that can be measured, analyzed, improved and controlled.
Achieving sustained quality improvement requires commitment from the entire organization, particularly from top-level management.
Features that set Six Sigma apart from previous quality improvement initiatives include:
A clear focus on achieving measurable and quantifiable financial returns from any Six Sigma project.[2]
An increased emphasis on strong and passionate management leadership and support.[2]
A special infrastructure of "Champions," "Master Black Belts," "Black Belts," etc. to lead and implement the Six Sigma approach.[2]
A clear commitment to making decisions on the basis of verifiable data, rather than assumptions and guesswork.[2]
The term "Six Sigma" comes from a field of statistics known as process capability studies. Originally, it referred to the ability of manufacturing processes to produce a very high proportion of output within specification. Processes that operate with "six sigma quality" over the short term are assumed to produce long-term defect levels below 3.4 defects per million opportunities (DPMO).[7][8] Six Sigma's implicit goal is to improve all processes to that level of quality or better.
Six Sigma is a registered service mark and trademark of Motorola Inc.[9] As of 2006 Motorola reported over US$17 billion in savings[10] from Six Sigma.
Other early adopters of Six Sigma who achieved well-publicized success include Honeywell (previously known as AlliedSignal) and General Electric, where Jack Welch introduced the method.[11] By the late 1990s, about two-thirds of the Fortune 500 organizations had begun Six Sigma initiatives with the aim of reducing costs and improving quality.[12]
In recent years, some practitioners have combined Six Sigma ideas with lean manufacturing to yield a methodology named Lean Six Sigma.
[edit]Methods
Six Sigma projects follow two project methodologies inspired by Deming's Plan-Do-Check-Act Cycle. These methodologies, comprising five phases each, bear the acronyms DMAIC and DMADV.[12]
DMAIC is used for projects aimed at improving an existing business process.[12]
DMADV is used for projects aimed at creating new product or process designs.[12]
[edit]DMAIC
The DMAIC project methodology has five phases:
Define the problem, the voice of the customer, and the project goals, specifically.
Measure key aspects of the current process and collect relevant data.
Analyze the data to investigate and verify cause-and-effect relationships. Determine what the relationships are, and attempt to ensure that all factors have been considered. Seek out root cause of the defect under investigation.
Improve or optimize the current process based upon data analysis using techniques such as design of experiments, poka yoke or mistake proofing, and standard work to create a new, future state process. Set up pilot runs to establish process capability.
Control the future state process to ensure that any deviations from target are corrected before they result in defects. Control systems are implemented such as statistical process control, production boards, and visual workplaces and the process is continuously monitored.
[edit]DMADV
The DMADV project methodology, also known as DFSS ("Design For Six Sigma"),[12] features five phases:
Define design goals that are consistent with customer demands and the enterprise strategy.
Measure and identify CTQs (characteristics that are Critical To Quality), product capabilities, production process capability, and risks.
Analyze to develop and design alternatives, create a high-level design and evaluate design capability to select the best design.
Design details, optimize the design, and plan for design verification. This phase may require simulations.
Verify the design, set up pilot runs, implement the production process and hand it over to the process owner(s).
[edit]Quality management tools and methods used in Six Sigma
Within the individual phases of a DMAIC or DMADV project, Six Sigma utilizes many established quality-management tools that are also used outside of Six Sigma. The following table shows an overview of the main methods used.
5 Whys
Analysis of variance
ANOVA Gauge R&R
Axiomatic design
Business Process Mapping
Catapult exercise on variability
Cause & effects diagram (also known as fishbone or Ishikawa diagram)
Chi-square test of independence and fits
Control chart
Correlation
Cost-benefit analysis
CTQ tree
Quantitative marketing research through use of Enterprise Feedback Management (EFM) systems
Design of experiments
Failure mode and effects analysis (FMEA)
General linear model
Histograms
Homoscedasticity
Quality Function Deployment (QFD)
Pareto chart
Pick chart
Process capability
Regression analysis
Root cause analysis
Run charts
SIPOC analysis (Suppliers, Inputs, Process, Outputs, Customers)
Stratification
Taguchi methods
Taguchi Loss Function
Thought process map
TRIZ
[edit]Implementation roles
One key innovation of Six Sigma involves the "professionalizing" of quality management functions. Prior to Six Sigma, quality management in practice was largely relegated to the production floor and to statisticians in a separate quality department. Six Sigma borrows martial arts ranking terminology to define a hierarchy (and career path) that cuts across all business functions.
Six Sigma identifies several key roles for its successful implementation.[13]
Executive Leadership includes the CEO and other members of top management. They are responsible for setting up a vision for Six Sigma implementation. They also empower the other role holders with the freedom and resources to explore new ideas for[weasel words]breakthrough improvements.
Champions take responsibility for Six Sigma implementation across the organization in an integrated manner. The Executive Leadership draws them from upper management. Champions also act as mentors to Black Belts.
Master Black Belts, identified by champions, act as in-house coaches on Six Sigma. They devote 100% of their time to Six Sigma. They assist champions and guide Black Belts and Green Belts. Apart from statistical tasks, they spend their time on ensuring consistent application of Six Sigma across various functions and departments.
Black Belts operate under Master Black Belts to apply Six Sigma methodology to specific projects. They devote 100% of their time to Six Sigma. They primarily focus on Six Sigma project execution, whereas Champions and Master Black Belts focus on identifying projects/functions for Six Sigma.
Green Belts, the employees who take up Six Sigma implementation along with their other job responsibilities, operate under the guidance of Black Belts.
Yellow Belts, trained in the basic application of Six Sigma management tools, work with the Black Belt throughout the project stages and are often the closest to the work.
[edit]Origin and meaning of the term "six sigma process"
Graph of the normal distribution, which underlies the statistical assumptions of the Six Sigma model. The Greek letter σ (sigma) marks the distance on the horizontal axis between the mean, µ, and the curve's inflection point, in this case µ=1. The distance is equally distributed horzontally to both sides of the mean µ as: [µ - σ/2, µ + σ/2]. The greater this distance, the greater is the spread of values encountered. For the curve shown above, µ = 0 and σ = 2. The upper and lower specification limits (USL, LSL) are at a distance of 6σ from the mean. Due to the properties of the normal distribution, values lying that far away from the mean are extremely unlikely. Even if the mean were to move right or left by 1.5σ at some point in the future (1.5 sigma shift), there is still a good safety cushion. This is why Six Sigma aims to have processes where the mean is at least 6σ away from the nearest specification limit.
The term "six sigma process" comes from the notion that if one has six standard deviations between the process mean and the nearest specification limit, as shown in the graph, practically no items will fail to meet specifications.[8] This is based on the calculation method employed in process capability studies.
Capability studies measure the number of standard deviations between the process mean and the nearest specification limit in sigma units. As process standard deviation goes up, or the mean of the process moves away from the center of the tolerance, fewer standard deviations will fit between the mean and the nearest specification limit, decreasing the sigma number and increasing the likelihood of items outside specification.[8]
[edit]Role of the 1.5 sigma shift
Experience has shown that in the long term, processes usually do not perform as well as they do in the short.[8] As a result, the number of sigmas that will fit between the process mean and the nearest specification limit may well drop over time, compared to an initial short-term study.[8] To account for this real-life increase in process variation over time, an empirically-based 1.5 sigma shift is introduced into the calculation.[8][14] According to this idea, a process that fits six sigmas between the process mean and the nearest specification limit in a short-term study will in the long term only fit 4.5 sigmas – either because the process mean will move over time, or because the long-term standard deviation of the process will be greater than that observed in the short term, or both.[8]
Hence the widely accepted definition of a six sigma process as one that produces 3.4 defective parts per million opportunities (DPMO). This is based on the fact that a process that is normally distributed will have 3.4 parts per million beyond a point that is 4.5 standard deviations above or below the mean (one-sided capability study).[8] So the 3.4 DPMO of a "Six Sigma" process in fact corresponds to 4.5 sigmas, namely 6 sigmas minus the 1.5 sigma shift introduced to account for long-term variation.[8] This is designed to prevent underestimation of the defect levels likely to be encountered in real-life operation.[8]
[edit]Sigma levels
See also: Three sigma rule
The table[15][16] below gives long-term DPMO values corresponding to various short-term sigma levels.
Note that these figures assume that the process mean will shift by 1.5 sigma towards the side with the critical specification limit. In other words, they assume that after the initial study determining the short-term sigma level, the long-term Cpk value will turn out to be 0.5 less than the short-term Cpk value. So, for example, the DPMO figure given for 1 sigma assumes that the long-term process mean will be 0.5 sigma beyond the specification limit (Cpk = –0.17), rather than 1 sigma within it, as it was in the short-term study (Cpk = 0.33). Note that the defect percentages only indicate defects exceeding the specification limit that the process mean is nearest to. Defects beyond the far specification limit are not included in the percentages.
Sigma level DPMO Percent defective Percentage yield Short-term Cpk Long-term Cpk
1 691,462 69% 31% 0.33 –0.17
2 308,538 31% 69% 0.67 0.17
3 66,807 6.7% 93.3% 1.00 0.5
4 6,210 0.62% 99.38% 1.33 0.83
5 233 0.023% 99.977% 1.67 1.17
6 3.4 0.00034% 99.99966% 2.00 1.5
7 0.019 0.0000019% 99.9999981% 2.33 1.83
[edit]Software used for Six Sigma
Main article: List of Six Sigma software packages
[edit]List of Six Sigma companies
Main article: List of Six Sigma companies
[edit]Criticism
[edit]Lack of originality
Noted quality expert Joseph M. Juran has described Six Sigma as "a basic version of quality improvement", stating that "[t]here is nothing new there. It includes what we used to call facilitators. They've adopted more flamboyant terms, like belts with different colors. I think that concept has merit to set apart, to create specialists who can be very helpful. Again, that's not a new idea. The American Society for Quality long ago established certificates, such as for reliability engineers."[17]
[edit]Role of consultants
The use of "Black Belts" as itinerant change agents has (controversially) fostered a cottage industry of training and certification. Critics argue there is overselling of Six Sigma by too great a number of consulting firms, many of which claim expertise in Six Sigma when they only have a rudimentary understanding of the tools and techniques involved.[2]
Some commentators view the expansion of the various "Belts" to include "Green Belts," "Master Black Belts" and "Gold Belts" as a parallel to the various "belt factories" that exist in martial arts.[citation needed]
[edit]Potential negative effects
A Fortune article stated that "of 58 large companies that have announced Six Sigma programs, 91 percent have trailed the S&P 500 since". The statement is attributed to "an analysis by Charles Holland of consulting firm Qualpro (which espouses a competing quality-improvement process)."[18] The gist of the article is that Six Sigma is effective at what it is intended to do, but that it is "narrowly designed to fix an existing process" and does not help in "coming up with new products or disruptive technologies." Many of these claims have been argued as being in error or ill-informed.[19][20]
A BusinessWeek article says that James McNerney's introduction of Six Sigma at 3M may have had the effect of stifling creativity. It cites two Wharton School professors who say that Six Sigma leads to incremental innovation at the expense of blue-sky work.[21] This phenomenon is further explored in the book, Going Lean, which provides data to show that Ford's "6 Sigma" program did little to change its fortunes.[22]
[edit]Based on arbitrary standards
While 3.4 defects per million opportunities might work well for certain products/processes, it might not operate optimally or cost effectively for others. A pacemaker process might need higher standards, for example, whereas a direct mail advertising campaign might need lower standards. The basis and justification for choosing 6 (as opposed to 5 or 7, for example) as the number of standard deviations is not clearly explained. In addition, the Six Sigma model assumes that the process data always conform to the normal distribution. The calculation of defect rates for situations where the normal distribution model does not apply is not properly addressed in the current Six Sigma literature.[2]
[edit]Criticism of the 1.5 sigma shift
The statistician Donald J. Wheeler has dismissed the 1.5 sigma shift as "goofy" because of its arbitrary nature.[23] Its universal applicability is seen as doubtful.[2]
The 1.5 sigma shift has also become contentious because it results in stated "sigma levels" that reflect short-term rather than long-term performance: a process that has long-term defect levels corresponding to 4.5 sigma performance is, by Six Sigma convention, described as a "6 sigma process."[8][24] The accepted Six Sigma scoring system thus cannot be equated to actual normal distribution probabilities for the stated number of standard deviations, and this has been a key bone of contention about how Six Sigma measures are defined.[24] The fact that it is rarely explained that a "6 sigma" process will have long-term defect rates corresponding to 4.5 sigma performance rather than actual 6 sigma performance has led several commentators to express the opinion that Six Sigma is a confidence trick.[8]
[edit]See also
Business process
Design for Six Sigma
[edit]References
^ Tennant, Geoff (2001). SIX SIGMA: SPC and TQM in Manufacturing and Services. Gower Publishing, Ltd.. p. 6. ISBN 0566083744.
^ a b c d e f g h i j k Antony, Jiju. "Pros and cons of Six Sigma: an academic perspective". Retrieved May 1, 2008.
^ "Motorola University - What is Six Sigma?". Retrieved 2009-09-14. "[...] Six Sigma started as a defect reduction effort in manufacturing and was then applied to other business processes for the same purpose."
^ "The Inventors of Six Sigma". Retrieved January 29, 2006.
^ Stamatis, D. H. (2004), Six Sigma Fundamentals: A Complete Guide to the System, Methods, and Tools, New York, New York: Productivity Press, p. 1, ISBN 9781563272929, OCLC 52775178, "The practitioner of the six sigma methodology in any organization should expect to see the use of old and established tools and approaches in the pursuit of continual improvement and customer satisfaction. So much so that even TQM (total quality management) is revisited as a foundation of some of the approaches. In fact, one may define six sigma as "TQM on steroids.""
^ Montgomery, Douglas C. (2009), Statistical Quality Control: A Modern Introduction (6 ed.), Hoboken, New Jersey: John Wiley & Sons, p. 23, ISBN 9780470233979, OCLC 244727396, "During the 1950s and 1960s programs such as Zero Defects and Value Engineering abounded, but they had little impact on quality and productivity improvement. During the heyday of TQM in the 1980s, another popular program was the Quality Is Free initiative, in which management worked on identifying the cost of quality..."
^ "Motorola University Six Sigma Dictionary". Retrieved January 29, 2006.
^ a b c d e f g h i j k l Tennant, Geoff (2001). SIX SIGMA: SPC and TQM in Manufacturing and Services. Gower Publishing, Ltd.. pp. 25. ISBN 0566083744.
^ "Motorola Inc. - Motorola University". Retrieved January 29, 2006.
^ "About Motorola University". Retrieved January 29, 2006.
^ "Six Sigma: Where is it now?". Retrieved May 22, 2008.
^ a b c d e De Feo, Joseph A.; Barnard, William (2005). JURAN Institute's Six Sigma Breakthrough and Beyond - Quality Performance Breakthrough Methods. Tata McGraw-Hill Publishing Company Limited. ISBN 0-07-059881-9.
^ Harry, Mikel; Schroeder, Richard (2000). Six Sigma. Random House, Inc. ISBN 0-385-49437-8.
^ Harry, Mikel J. (1988). The Nature of six sigma quality. Rolling Meadows, Illinois: Motorola University Press. p. 25. ISBN 9781569460092.
^ Gygi, Craig; DeCarlo, Neil; Williams, Bruce (2005). Six Sigma for Dummies. Hoboken, NJ: Wiley Publishing, Inc.. pp. Front inside cover, 23. ISBN 0-7645-6798-5.
^ El-Haik, Basem; Suh, Nam P.. Axiomatic Quality. John Wiley and Sons. p. 10. ISBN 9780471682738.
^ Paton, Scott M. (August 2002). Juran: A Lifetime of Quality. 22. pp. 19–23. Retrieved 2009-04-01.
^ Morris, Betsy (2006-07-11). "Tearing up the Jack Welch playbook". Fortune. Retrieved 2006-11-26.
^ Richardson, Karen (2007-01-07). "The 'Six Sigma' Factor for Home Depot". Wall Street Journal Online. Retrieved October 15, 2007.
^ Ficalora, Joe; Costello, Joe. "Wall Street Journal SBTI Rebuttal" (PDF). Sigma Breakthrough Technologies, Inc.. Retrieved October 15, 2007.
^ Hindo, Brian (6 June 2007). "At 3M, a struggle between efficiency and creativity". Business Week. Retrieved June 6, 2007.
^ Ruffa, Stephen A. (2008). Going Lean: How the Best Companies Apply Lean Manufacturing Principles to Shatter Uncertainty, Drive Innovation, and Maximize Profits. AMACOM (a division of American Management Association). ISBN 0-8144-1057-X.
^ Wheeler, Donald J. (2004). The Six Sigma Practitioner's Guide to Data Analysis. SPC Press. p. 307. ISBN 9780945320623.
^ a b *Pande, Peter S.; Neuman, Robert P.; Cavanagh, Roland R. (2001). The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance. New York: McGraw-Hill Professional. p. 229. ISBN 0071358064.
[edit]Further reading
Adams, Cary W.; Gupta, Praveen (2003). Six Sigma Deployment. Burlington, MA: Butterworth-Heinemann. ISBN 0750675233.
Breyfogle, Forrest W. III (1999). Implementing Six Sigma: Smarter Solutions Using Statistical Methods. New York, NY: John Wiley & Sons. ISBN 0471265721.
De Feo, Joseph A.; Barnard, William (2005). JURAN Institute's Six Sigma Breakthrough and Beyond - Quality Performance Breakthrough Methods. New York, NY: McGraw-Hill Professional. ISBN 0071422277.
Hahn, G. J., Hill, W. J., Hoerl, R. W. and Zinkgraf, S. A. (1999) The Impact of Six Sigma Improvement-A Glimpse into the Future of Statistics, The American Statistician, Vol. 53, No. 3, pp. 208-215.
Harry, Mikel J.; Schroeder, Richard (1999). Six Sigma: The Breakthrough Management Strategy Revolutionizing the World’s Top Corporations. New York, NY: Doubleday. ISBN 0385494378.
Keller, Paul A. (2001). Six Sigma Deployment: A Guide for Implementing Six Sigma in Your Organization. Tucson, AZ: Quality Publishing. ISBN 0930011848.
Pande, Peter S.; Neuman, Robert P. (2001). The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance. New York, NY: McGraw-Hill Professional. ISBN 0071358064.
Pyzdek, Thomas and Paul A. Keller (2009). The Six Sigma Handbook, Third Edition. New York, NY: McGraw-Hill. ISBN 0071623388.
Snee, Ronald D.; Hoerl, Roger W. (2002). Leading Six Sigma: A Step-by-Step Guide Based on Experience with GE and Other Six Sigma Companies. Upper Saddle River, NJ: FT Press. ISBN 0130084573.
Taylor, Gerald (2008). Lean Six Sigma Service Excellence: A Guide to Green Belt Certification and Bottom Line Improvement. New York, NY: J. Ross Publishing. ISBN 978-1604270068.
Tennant, Geoff (2001). SIX SIGMA: SPC and TQM in Manufacturing and Services. Aldershot, UK: Gower Publishing, Ltd. ISBN 0566083744.
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