To install click the Add extension button. That's it.

The source code for the WIKI 2 extension is being checked by specialists of the Mozilla Foundation, Google, and Apple. You could also do it yourself at any point in time.

4,5
Kelly Slayton
Congratulations on this excellent venture… what a great idea!
Alexander Grigorievskiy
I use WIKI 2 every day and almost forgot how the original Wikipedia looks like.
Live Statistics
English Articles
Improved in 24 Hours
Added in 24 Hours
What we do. Every page goes through several hundred of perfecting techniques; in live mode. Quite the same Wikipedia. Just better.
.
Leo
Newton
Brights
Milds

# Six Sigma

Not to be confused with 5S (methodology)

Six Sigma () is a set of techniques and tools for process improvement. It was introduced by American engineer Bill Smith while working at Motorola in 1986.[1][2] Jack Welch made it central to his business strategy at General Electric in 1995. A six sigma process is one in which 99.99966% of all opportunities to produce some feature of a part are statistically expected to be free of defects.

Six Sigma strategies seek to improve the quality of the output of a process by identifying and removing the causes of defects and minimizing impact variability in manufacturing and business processes. It uses a set of quality management methods, mainly empirical, statistical methods, and creates a special infrastructure of people within the organization who are experts in these methods. Each Six Sigma project carried out within an organization follows a defined sequence of steps and has specific value targets, for example: reduce process cycle time, reduce pollution, reduce costs, increase customer satisfaction, and increase profits.

The term Six Sigma (capitalized because it was written that way when registered as a Motorola trademark on December 28, 1993) originated from terminology associated with statistical modeling of manufacturing processes. The maturity of a manufacturing process can be described by a sigma rating indicating its yield or the percentage of defect-free products it creates—specifically, to within how many standard deviations of a normal distribution the fraction of defect-free outcomes corresponds. Motorola set a goal of "six sigma" for all of its manufacturing.

## Doctrine

The common Six Sigma symbol

Six Sigma doctrine asserts:

• Continuous efforts to achieve stable and predictable process results (e.g. by reducing process variation) are of vital importance to business success.
• Manufacturing and business processes have characteristics that can be defined, 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.
• An increased emphasis on strong and passionate management leadership and support.
• A clear commitment to making decisions on the basis of verifiable data and statistical methods, rather than assumptions and guesswork.

The term "six sigma" comes from statistics and is used in statistical quality control, which evaluates process capability. 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). The 3.4 dpmo is based on a "shift" of ± 1.5 sigma explained by Dr. Mikel J. Harry. This figure is based on the tolerance in the height of a stack of discs.[3][4] Six Sigma's implicit goal is to improve all processes, but not to the 3.4 DPMO level necessarily. Organizations need to determine an appropriate sigma level for each of their most important processes and strive to achieve these. As a result of this goal, it is incumbent on management of the organization to prioritize areas of improvement.

### Finance

Six Sigma has played an important role by improving accuracy of allocation of cash to reduce bank charges, automatic payments, improving accuracy of reporting, reducing documentary credits defects, reducing check collection defects, and reducing variation in collector performance. Two of the financial institutions that have reported considerable improvements in their operations are Bank of America and American Express. By 2004 Bank of America increased customer satisfaction by 10.4% and decreased customer issues by 24% by applying Six Sigma tools in their streamline operations. Similarly, American Express successfully eliminated non-received renewal credit cards and improved their overall processes by applying Six Sigma principles. This strategy is also currently being applied by other financial institutions like GE Capital Corp., JP Morgan Chase, and SunTrust Bank, with customer satisfaction being their main objective.[23]

### Supply chain

In this field, it is important to ensure that products are delivered to clients at the right time while preserving high-quality standards from the beginning to the end of the supply chain. By changing the schematic diagram for the supply chain, Six Sigma can ensure quality control on products (defect free) and guarantee delivery deadlines, which are the two major issues involved in the supply chain.[24]

### Healthcare

This is a sector that has been highly matched with this doctrine for many years because of the nature of zero tolerance for mistakes and potential for reducing medical errors involved in healthcare.[25][26] The goal of Six Sigma in healthcare is broad and includes reducing the inventory of equipment that brings extra costs, altering the process of healthcare delivery in order to make it more efficient and refining reimbursements. A study at the University of Texas MD Anderson Cancer Center, which recorded an increase in examinations with no additional machines of 45% and reduction in patients' preparation time of 40 minutes; from 45 minutes to 5 minutes in multiple cases.[23]

## Criticism

### Lack of originality

Quality expert Joseph M. Juran described Six Sigma as "a basic version of quality improvement", stating that "there 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."[27]

### Inadequate for complex manufacturing

Quality expert Philip B. Crosby pointed out that the Six Sigma standard does not go far enough[28]—customers deserve defect-free products every time. For example, under the Six Sigma standard, semiconductors which require the flawless etching of millions of tiny circuits onto a single chip are all defective.[29]

### Role of consultants

The use of "Black Belts" as itinerant change agents has fostered an industry of training and certification. Critics have argued there is overselling of Six Sigma by too great a number of consulting firms, many of which claim expertise in Six Sigma when they have only a rudimentary understanding of the tools and techniques involved or the markets or industries in which they are acting.[30]

### 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 was attributed to "an analysis by Charles Holland of consulting firm Qualpro (which espouses a competing quality-improvement process)".[31] The summary 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."[32][33]

#### Over-reliance on statistical tools

A more direct criticism is the "rigid" nature of Six Sigma with its over-reliance on methods and tools. In most cases, more attention is paid to reducing variation and searching for any significant factors and less attention is paid to developing robustness in the first place (which can altogether eliminate the need for reducing variation).[34] The extensive reliance on significance testing and use of multiple regression techniques increases the risk of making commonly unknown types of statistical errors or mistakes. A possible consequence of Six Sigma's array of P-value misconceptions is the false belief that the probability of a conclusion being in error can be calculated from the data in a single experiment without reference to external evidence or the plausibility of the underlying mechanism.[35] One of the most serious but all-too-common misuses of inferential statistics is to take a model that was developed through exploratory model building and subject it to the same sorts of statistical tests that are used to validate a model that was specified in advance.[36]

Another comment refers to the often mentioned Transfer Function, which seems to be a flawed theory if looked at in detail.[37] Since significance tests were first popularized many objections have been voiced by prominent and respected statisticians. The volume of criticism and rebuttal has filled books with language seldom used in the scholarly debate of a dry subject.[38][39][40][41] Much of the first criticism was already published more than 40 years ago (see Statistical hypothesis testing § Criticism).

Articles featuring critics have appeared in the November–December 2006 issue of USA Army Logistician regarding Six-Sigma: "The dangers of a single paradigmatic orientation (in this case, that of technical rationality) can blind us to values associated with double-loop learning and the learning organization, organization adaptability, workforce creativity and development, humanizing the workplace, cultural awareness, and strategy making."[42]

Nassim Nicholas Taleb considers risk managers little more than "blind users" of statistical tools and methods.[43] He states that statistics is fundamentally incomplete as a field as it cannot predict the risk of rare events—something Six Sigma is specially concerned with. Furthermore, errors in prediction are likely to occur as a result of ignorance for or distinction between epistemic and other uncertainties. These errors are the biggest in time variant (reliability) related failures.[44]

#### Stifling creativity in research environments

According to an article by John Dodge, editor in chief of Design News, use of Six Sigma is inappropriate in a research environment. Dodge states[45] "excessive metrics, steps, measurements and Six Sigma's intense focus on reducing variability water down the discovery process. Under Six Sigma, the free-wheeling nature of brainstorming and the serendipitous side of discovery is stifled." He concludes "there's general agreement that freedom in basic or pure research is preferable while Six Sigma works best in incremental innovation when there's an expressed commercial goal."

A BusinessWeek article says that James McNerney's introduction of Six Sigma at 3M had the effect of stifling creativity and reports its removal from the research function. It cites two Wharton School professors who say that Six Sigma leads to incremental innovation at the expense of blue skies research.[46] This phenomenon is further explored in the book Going Lean, which describes a related approach known as lean dynamics and provides data to show that Ford's "6 Sigma" program did little to change its fortunes.[47]

### Lack of systematic documentation

One criticism voiced by Yasar Jarrar and Andy Neely from the Cranfield School of Management's Centre for Business Performance is that while Six Sigma is a powerful approach, it can also unduly dominate an organization's culture; and they add that much of the Six Sigma literature – in a remarkable way (six-sigma claims to be evidence, scientifically based) – lacks academic rigor:

One final criticism, probably more to the Six Sigma literature than concepts, relates to the evidence for Six Sigma’s success. So far, documented case studies using the Six Sigma methods are presented as the strongest evidence for its success. However, looking at these documented cases, and apart from a few that are detailed from the experience of leading organizations like GE and Motorola, most cases are not documented in a systemic or academic manner. In fact, the majority are case studies illustrated on websites, and are, at best, sketchy. They provide no mention of any specific Six Sigma methods that were used to resolve the problems. It has been argued that by relying on the Six Sigma criteria, management is lulled into the idea that something is being done about quality, whereas any resulting improvement is accidental (Latzko 1995). Thus, when looking at the evidence put forward for Six Sigma success, mostly by consultants and people with vested interests, the question that begs to be asked is: are we making a true improvement with Six Sigma methods or just getting skilled at telling stories? Everyone seems to believe that we are making true improvements, but there is some way to go to document these empirically and clarify the causal relations.

— [34]

### 1.5 sigma shift

The statistician Donald J. Wheeler has dismissed the 1.5 sigma shift as "goofy" because of its arbitrary nature.[48] Its universal applicability is seen as doubtful.

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 "six sigma process."[3][49] 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 over how Six Sigma measures are defined.[49] 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.[3]

## References

1. ^ "The Inventors of Six Sigma". Archived from the original on 2005-11-06. Retrieved 2006-01-29.
2. ^ Tennant, Geoff (2001). SIX SIGMA: SPC and TQM in Manufacturing and Services. Gower Publishing, Ltd. p. 6. ISBN 0-566-08374-4.
3. Tennant, Geoff (2001). SIX SIGMA: SPC and TQM in Manufacturing and Services. Gower Publishing, Ltd. p. 25. ISBN 0-566-08374-4.
4. ^ "Motorola University Six Sigma Dictionary". Archived from the original on 2006-01-28. Retrieved 2006-01-29.
5. ^ "About Motorola University". Archived from the original on 2005-12-22. Retrieved 2006-01-28.
6. ^ "Six Sigma: Where is it now?". Retrieved 2008-05-22.
7. 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.
8. ^ a b Walshe, Kieran; Harvey, Gill; Jas, Pauline (15 November 2010). Connecting Knowledge and Performance in Public Services: From Knowing to Doing. Cambridge University Press. p. 175. ISBN 978-0-521-19546-1. Retrieved 2011-08-22.
9. ^ "ISO 13053:2011". ISO.
10. ^ Webber, Larry; Wallace, Michael (15 December 2006). Quality Control for Dummies. For Dummies. pp. 42–43. ISBN 978-0-470-06909-7. Retrieved 2012-05-16.
11. ^ Harry, Mikel; Schroeder, Richard (2000). Six Sigma. Random House, Inc. ISBN 0-385-49437-8.
12. ^ "Six sigma support from upper management". 6sigma.us. Retrieved March 11, 2015.
13. ^ Bertels, Thomas (2003) Rath & Strong's Six Sigma Leadership Handbook. John Wiley and Sons. pp 57–83 ISBN 0-471-25124-0.
14. ^ Harry, Mikel J.; Mann, Prem S.; De Hodgins, Ofelia C.; Hulbert, Richard L.; Lacke, Christopher J. (20 September 2011). Practitioner's Guide to Statistics and Lean Six Sigma for Process Improvements. John Wiley and Sons. pp. 30–. ISBN 978-1-118-21021-5. Retrieved 2011-11-15.
15. ^ a b c Keller, Paul A.; Keller, Paul (16 December 2010). Six Sigma Demystified. McGraw-Hill Professional. p. 40. ISBN 978-0-07-174679-3. Retrieved 2011-09-20.
16. ^ Webber, Larry; Wallace, Michael (15 December 2006). Quality Control for Dummies. For Dummies. pp. 292–. ISBN 978-0-470-06909-7. Retrieved 2011-09-20.
17. ^ Coryea, R. Leroy; Cordy, Carl E.; Coryea, LeRoy R. (27 January 2006). Champion's Practical Six Sigma Summary. Xlibris Corporation. p. 65. ISBN 978-1-4134-9681-9. Retrieved 2011-09-20.[self-published source]
18. ^ "Certification – ASQ". Milwaukee, Wisconsin: American Society for Quality. Retrieved 2011-09-09.
19. ^ Harry, Mikel J. (1988). The Nature of six sigma quality. Rolling Meadows, Illinois: Motorola University Press. p. 25. ISBN 978-1-56946-009-2.
20. ^ 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.
21. ^ El-Haik, Basem; Suh, Nam P. (2005-04-15). Axiomatic Quality. John Wiley and Sons. p. 10. ISBN 978-0-471-68273-8.
22. ^ a b c d Dusharme, Dirk. "Six Sigma Survey: Breaking Through the Six Sigma Hype". Quality Digest.
23. ^ a b c d Kwak, Young Hoon; Anbari, Frank T. (2006). "Benefits, obstacles, and future of six sigma approach". Technovation. 26 (5–6): 708–715. doi:10.1016/j.technovation.2004.10.003.
24. ^ Dasgupta, Tirthankar (2003-05-01). "Using the six-sigma metric to measure and improve the performance of a supply chain". Total Quality Management & Business Excellence. 14 (3): 355–366. doi:10.1080/1478336032000046652. ISSN 1478-3363.
25. ^ Cascini, Egidio. Sei Sigma per Docenti in 14 Capitoli (PDF). RCE Multimedia.
26. ^ Celegato, Alessandro (2017). "IN MEMORY OF EGIDIO CASCINI" (PDF). Statistica Applicata - Italian Journal of Applied Statistics Vol. 29: 107–110.
27. ^ Paton, Scott M. (August 2002). "Juran: A Lifetime of Quality". Quality Digest. 22 (8): 19–23. Retrieved 2009-04-01.
28. ^ Crosby, Philip B. (1999). Quality and Me: Lessons from an Evolving Life. San Francisco: Jossey-Bass. p. 159. OCLC 40444566. Quality is measured by the price of nonconformance, not by indexes.
29. ^ Crosby, Philip B. (1996). Quality Is Still Free: Making Quality Certain in Uncertain Times. New York: McGraw-Hill. p. xiv. OCLC 32820340. The nonconformance situation semiconductor suppliers found recently emerged from embracing the standard of "Six Sigma." This permits 3.4 defects per million components. Why anyone would want to do that is beyond me. But they are now paying the price. When even ordinary chips contain a million or more components, such a standard means that they are all defective.
30. ^ Lean Six Sigma: Cost Reduction Strategies, Ade Asefeso MCIPS MBA (2012)
31. ^ Morris, Betsy (11 July 2006). "Tearing up the Jack Welch playbook". Fortune. Retrieved 2006-11-26.
32. ^ Richardson, Karen (7 January 2007). "The 'Six Sigma' Factor for Home Depot". Wall Street Journal Online. Retrieved 2007-10-15.
33. ^ Ficalora, Joe; Costello, Joe. "Wall Street Journal SBTI Rebuttal" (PDF). Sigma Breakthrough Technologies, Inc. Archived from the original (PDF) on 2007-10-25. Retrieved 2007-10-15.
34. ^ a b "Six Sigma Friend or Foe" (PDF). Retrieved 2012-02-10.
35. ^
36. ^
37. ^ "y-FX". Archived from the original on 2013-06-20.
38. ^ Harlow, Lisa Lavoie; Stanley A. Mulaik; James H. Steiger, eds. (1997). What If There Were No Significance Tests?. Lawrence Erlbaum Associates. ISBN 978-0-8058-2634-0.
39. ^ Morrison, Denton; Henkel, Ramon, eds. (2006) [1970]. The Significance Test Controversy. AldineTransaction. ISBN 0-202-30879-0.
40. ^ McCloskey, Deirdre N.; Ziliak, Stephen T. (2008). The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives. University of Michigan Press. ISBN 978-0-472-05007-9.
41. ^ Chow, Siu L. (1997). Statistical Significance: Rationale, Validity and Utility. ISBN 0-7619-5205-5.
42. ^ Paparone, Dr. Christopher R. "Army Logistician (A Values-Based Critique of Lean and Six Sigma as a Management Ideology)". Almc.army.mil. Retrieved 2012-02-10.
43. ^ The fourth quadrant: a map of the limits of statistics [9.15.08] Nassim Nicholas Taleb, An Edge Original Essay
44. ^ "Special Workshop on Risk Acceptance and Risk Communication" (PDF). Stanford University. 26–27 March 2007.
45. ^ Dodge, John (10 December 2007). "3M Shelves Six Sigma in R&D". Design News. Retrieved 2013-04-02.
46. ^ Hindo, Brian (6 June 2007). "At 3M, a struggle between efficiency and creativity". Business Week. Retrieved 2007-06-06.
47. ^ 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 978-0-8144-1057-8.
48. ^ Wheeler, Donald J. (2004). The Six Sigma Practitioner's Guide to Data Analysis. SPC Press. p. 307. ISBN 978-0-945320-62-3.
49. ^ 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 0-07-135806-4. key bones of contention amongst the statistical experts about how Six Sigma measures are defined.