Six Sigma

Six Sigma is a methodology to manage process variations that cause defects, defined as unacceptable deviation from the mean or target; and to systematically work towards managing variation to eliminate those defects^[1]. The objective of Six Sigma is to deliver high performance, reliability, and value to the end customer. It was pioneered by Bill Smith at Motorola in 1986^[2] and was originally defined^[3] as a metric for measuring defects and improving quality; and a methodology to reduce defect levels below 3.4 Defects Per (one) Million Opportunities (DPMO). Six Sigma has now grown beyond defect control.

Six Sigma is a registered service mark and trademark of Motorola, Inc^[4]. Motorola has reported over US$17 billion in savings^[5] from Six Sigma to date.

Application & Success

AlliedSignal and General Electric became early adopters of Six Sigma, with GE reporting benefits of more than US $300 million during its first year of application^[6]. Their CEOs, Larry Bossidy and Jack Welch played a vital role in popularizing Six Sigma. Other major organizations who claim to have benefited from Six Sigma implementation are Caterpillar Inc.^{[citation needed]}, Ford^{[citation needed]}, Cummins^{[citation needed]}, Microsoft^{[citation needed]}, Raytheon^{[citation needed]}, Quest Diagnostics^{[citation needed]}, Seagate Technology^{[citation needed]}, Siemens^{[citation needed]}, SKF^{[citation needed]}, Merrill Lynch^{[citation needed]}, Lear^{[citation needed]}, 3M^{[citation needed]} and many more.

Starting with manufacturing, today Six Sigma is being used across a wide range of industries like banking, telecommunications, insurance, marketing, construction, healthcare^[7], and software^[8]. Some non-manufacturing examples are given below:

Healthcare

North Carolina Baptist Hospital says^[9], "The Six Sigma process improvement deployment at North Carolina Baptist Hospital is starting to show the kind of results that convert skeptics to believers." and "A Six Sigma process improvement team charged with getting heart attack patients from the Emergency Department into the cardiac catheterization lab for treatment faster slashed 41 minutes off the hospital's mean time"

Banking

Bank of America has used Six Sigma for credit risk assessment reduction, fraud prevention, and customer satisfaction improvement, etc. Bank of America's Six Sigma initiative resulted in benefits of more than US$2 billion; and increased customer satisfaction by 25%^[10].

Insurance

Insurance companies have used Six Sigma for critical tasks like premium outstanding reduction and various cycle time reductions. For example, CIGNA Dental reports pending claim volume reduction by over 50% ^[11].

Construction

In engineering and construction of the Channel Tunnel Rail Link project in the UK, the Bechtel’s project team^[12] uncovered a way to save hundreds of job hours on one of the tunneling jobs.

The Institute of Quality Assurance has interesting success stories^[13] on Wipro, Citibank, and Motorola.

Military

The United States Navy has adopted Six Sigma as part of AIRSpeed[1], an overall set of practices designed to improve efficiency in aviation maintenance. The other components of AIRSpeed are Lean and Theory of Constraints^[14].

The United States Air Force process improvement program based on Lean and Six Sigma is named Air Force Smart Operations 21 (AFSO21)^[15].

Methodology

Six Sigma has two key methodologies^[16] – DMAIC and DMADV. DMAIC is used to improve an existing business process. DMADV is used to create new product designs or process designs in such a way that it results in a more predictable, mature and defect free performance. Sometimes a DMAIC project may turn into a DFSS project because the process in question requires complete redesign to bring about the desired degree of improvement.

DMAIC

Basic methodology consists of the following five phases:

• Define formally define the process improvement goals that are consistent with customer demands and enterprise strategy.
• Measure to define baseline measurements on current process for future comparison. Map and measure process in question and collect required process data.
• Analyze to verify relationship and causality of factors. What is the relationship? Are there other factors that have not been considered?
• Improve optimize the process based upon the analysis using techniques like Design of Experiments.
• Control setup pilot runs to establish process capability, transition to production and thereafter continuously measure the process and institute control mechanisms to ensure that variances are corrected before they result in defects.

DMADV

Basic methodology consists of the following five phases:

• Define formally define the goals of the design activity that are consistent with customer demands and enterprise strategy.
• Measure identify CTQs, product capabilities, production process capability, risk assessment, etc.
• Analyze develop and design alternatives, create high-level design and evaluate design capability to select the best design.
• Design develop detail design, optimize design, and plan for design verification. This phase may require simulations.
• Verify design, setup pilot runs, implement production process and handover to process owners.

Also see Design for Six Sigma quality.

Some people have used DMAICR (realize). Others contend that focusing on the financial gains realized through Six Sigma is counter-productive and that said financial gains are simply byproducts of a good process improvement.

Roles Required for Implementation

Six Sigma identifies five key roles^[17] for its successful implementation.

• Executive Leadership includes CEO and other key top management team members. 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 breakthrough improvements.
• Champions are responsible for the Six Sigma implementation across the organization in an integrated manner. The Executive Leadership draws them from the upper management. Champions also act as mentor to Black Belts. At GE this level of certification is now called "Quality Leader".
• Master Black Belts, identified by champions, act as in-house expert coach for the organization on Six Sigma. They devote 100% of their time to Six Sigma. They assist champions and guide Black Belts and Green Belts. Apart from the usual rigor of statistics, their time is spent on ensuring integrated deployment 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 are the employees who take up Six Sigma implementation along with their other job responsibilities. They operate under the guidance of Black Belts and support them in achieving the overall results.

Specific training programs are available to train people to take up these roles.

The above listed roles conform to the old Mikel Harry/Richard Schroeder model, which is far from being universally accepted. In many successful programs, both Green Belts and Black Belts lead projects, and work on problems in their existing area of responsibility.

Examples of Some Key Tools Used

• Failure Modes Effects Analysis
• Cost Benefit Analysis
• CTQ Tree
• Customer Output Process Input Supplier Maps
• Customer survey
• Process Maps
• Run Charts
• Histograms
• Stratification
• ANOVA Gage R&R
• Cause & Effects Diagram (a.k.a. Fishbone or Ishikawa Diagram)
• Homogeneity of Variance
• ANOVA
• Chi-Square Test of Independence and Fits
• General Linear Model
• Regression
• Correlation
• Design of Experiments
• Taguchi
• Control Charts
• 5 Whys
• Axiomatic design

Criticisms of Six Sigma

Origin

Robert Galvin did not really "invent" Six Sigma in the 1980s, but would more correctly be said to have applied methodologies that had been available since the 1920s and were developed by luminaries like Shewhart, Deming, Juran, Ishikawa, Ohno, Shingo, Taguchi and Shainin. The goal of Six Sigma, then, is to use the old tools in concert, for a greater effect than a sum-of-parts approach.

The use of "Black Belts" as itinerant change agents is controversial as it has created a cottage industry of training and certification which arguably relieves management of accountability for change; pre-Six Sigma implementations, exemplified by the Toyota Production System and Japan's industrial ascension, simply used the technical talent at hand — Design, Manufacturing and Quality Engineers, Toolmakers, Maintenance and Production workers — to optimize the processes.

Meanwhile, for companies not solely devoted to manufacturing (including GE, which holds NBC Universal as a subsidiary), the spillover effects of Six Sigma have been troubling, especially as executives trained in the Six Sigma methodology for change and growth, clash with the creative minds behind less industrial business functions.

The Term Six Sigma

Sigma (the lower-case Greek letter "s") is used to represent standard deviation (a measure of variation) of a population (whereas lower-case 's', represents the estimate of the population standard deviation, based on a sample). The term "six sigma" comes from the notion that if you have six standard deviations between the mean result of a process and the nearest specification limit, you will make practically no items that exceed the specifications. This is the basis for the Process Capability Study, often used by quality professionals, and the term "Six Sigma" has its roots in this tool. Criticism of the tool itself, and the way that the term was derived from the tool, often sparks criticism of Six Sigma.

It is often said that a Six Sigma process produces 3.4 defective parts per million. A process that is normally distributed will have 3.4 parts per million beyond a point that is 4.5 standard deviations above the mean. A Capability Study on normally distributed data, mean 0, standard deviation 1, with an upper specification limit of 4.5 will confirm this. Some six sigma practitioners call this 4.5 sigma process a 6 sigma process by invoking the 1.5 sigma shift. Selection of 1.5 as the correct magnitude is completely arbitrary. And adding whatever arbitrary value is selected, rather than subtracting it, assumes that processes tend to automatically self-improve with time. The 1.5 sigma shift is a notion that has existed since before Motorola’s program, and which gets little acceptance from professional statisticians. Donald J. Wheeler, one of the most respected workers in statistics, dismisses it as "goofy".

As sample size increases, the error in the estimate of standard deviation converges much more slowly than the estimate of the mean (see confidence interval). Even with a few dozen samples, the estimate of standard deviation often drags an alarming amount of uncertainty into the Capability Study calculations. It follows that estimates of defect rates can be very greatly influenced by uncertainty in the estimate of standard deviation.

Estimates for the number of defective parts per million produced depend on knowing something about the shape of the distribution from which the samples are drawn. Unfortunately, we have no means for proving that data belong to any particular distribution. We only assume normality, based on finding no evidence to the contrary. Estimating defective parts per million down into the 100’s or 10’s of units based on such an assumption is wishful thinking, since actual defects are often deviations from normality, which have been assumed not to exist.

In summary, the term “Six Sigma” has its roots in a quality tool that can easily be misapplied by a naïve user and to the controversial 1.5 sigma shift.

Statistics and robustness

Six Sigma is controversial with the statistics profession. Some teachers of statistics are critical of the standard of statistical teaching found in Six Sigma materials. Others object to the idea that a single universal standard can be appropriate across all domains of application. They argue that quality standards should be set on a case-by-case basis using decision theory or cost-benefit analysis. Additionally, Six Sigma has been broadly criticized for clinging to the concepts of "attribute" and "variable" data, rather than the much more widely accepted "nominal", "ordinal", "interval", and "ratio" model.

The 1.5-sigma shift theory is often disputed by statisticans because the sample size is too small to make mathematically justified predictions. Also, the Six Sigma calculations might not be robust enough to handle non-normal statistics, where the measurement is not in a normal distribution (bell curve). In particular, the widely used Capability Study drags an alarmingly high level of uncertainty into its calculations, and is often assigned a greater statistical importance than it deserves.

Methods vs. Methodology

Others suggest that Six Sigma, rather than being a true methodology, is more often implemented to start an unending cycle of improvement and use of better tools on the industry day-to-day practices, rather than to use advanced statistical theories that cannot be daily applied. Six Sigma can be considered just a collection of tools and methods, rather than a methodology, itself. A full methodology, such as the Deming System (of W. Edwards Deming), would still be beneficial to address the human factors as to why some people might misrepresent measurements, including how to avoid slanted test results, how to survey customers, how to evaluate employee performance, and how to improve cooperation throughout the organization. Six Sigma has been described as a collection of superficial changes that ignore many of the major factors affecting quality and productivity.