The advantages of Six Sigma do not exactly lie in huge cost benefits that can be realized by its implementation. The glaring examples of many corporations having saved billions of dollars are true benefits but the intangible results, such as having met the expectations of customers, and being able to improve employee relations are also paramount. Because some corporations have experienced its failure to meet stated goals, some critics often raise questions about the feasibility of implementing Six Sigma, while still others are dismissing it plainly.

Benefits of Six Sigma

Obviously, in almost all cases, the reasons for Six Sigma failure have been external factors such as wrong or misguided selection of the tools, lack of application and lack of support from upper management. It is important to keep in mind that the successful implementation of Six Sigma requires a top down approach and perseverance throughout. Also important to the process is proper and thorough Six Sigma training.

Six Sigma Is All About Eradicating Business Problems.

Problem solving involves rational thinking. Somehow, companies always found themselves compromising quality with problem solving, which is the main reason why companies decide to implement Six Sigma and support Six Sigma training.

The top-down approach of Six Sigma requires dedication and application at all levels of the organization and on a continuous basis. The statistical methodology of Six Sigma sheds light on existing flaws and their causes after thorough analysis. Emphasis is placed on experimentation following analysis and redefining the processes and their goals. This is unlike other quality assurance methodologies. The benefits of supporting Six Sigma training for company professionals are apparent.

Financial Benefits: Cash flow increases due to creation of additional revenue. Through this process although cost decreases and increased profitability can be seen. It is important that all professionals involved in Six Sigma implementation have proper Six Sigma training. Although Six Sigma training is relatively expensive, the financial benefits of supporting it greatly outweigh the upfront costs.

Operational Benefits Of Six Sigma Training: employee satisfaction due to improvement in work flow, reduction in process times and steps, better usage of work space, etc. result from implementation of Six Sigma. One major operational reason for choosing Six Sigma is its success in waste reduction and redundancy. Waste reduction is measured in terms of improving time, product movement and decreasing material consumption.

Conceptually, the benefits of implementation of Six Sigma emerge from breaking the mindset that product processes are invariable. Benefits also emerge as a result of interconnected activities. The result of this methodical approach to quality management is evidenced by reduced fluctuations in processes. Stability of this kind triggers a series of positive chain reactions within organizations.

Success stories of Six Sigma training are evident in all fields of business. Since Six Sigma methodology encompasses the entire process of doing business, it is likely to show a flaw here or there, such as companies that embraced Six Sigma have found out. Howsoever small in number the failures may be, they are all due to differing reasons. However, any negative results can probably be traced back to either improper implementation or incomplete Six Sigma training.



By: Tony Jacowski

About the Author:

Lean Six Sigma is a business improvement methodology which combines (as the name implies) tools from both Lean Enterprise (Manufacturing) and Six Sigma.  Lean eliminates the waste in your processes, while Six Sigma ensures quality through the elimination of variation in your processes and also provides a structured data driven structure to solve problems and implement sustainable change into your business. 

100% Effective Training believe therefore that the best approach for any business is to use Lean Six Sigma rather than one or the other.  The benefits from taking this approach are proven to out way taking only one approach at a time.   To understand Lean Six Sigma let us first explain the two methodologies. 

 Six Sigma is a set of practices originally developed by Motorola to systematically improve processes by eliminating defects.  A defect is defined as nonconformity of a product or service to its specifications.  In other words every time you do an activity you get exactly the same outcome (result), the same quality.  For example if I fill in a form or take an order or solve a customer issue or make a part no matter who does it the output is the same.

Top companies all over the world including Motorola have made Six Sigma a way of life for their business. This however requires commitment to the approach from top management down.  If this is achieve then implementation and acceptance is easier and leads to massive savings.  Motorola have made $17b savings up to 2006 using the approach.  It ensures that everyone focuses on reducing variation in every aspect of the business from filling in forms to making a part.  All activities in a business of any kind can be measured, analyzed, improved and controlled and thus using some simple tools can give a reduction in variation leading to improved quality and costs. 

Why do we want a reduction in the variation we obtain from any activity in our business?  When we have the same output from a process or activity we know what we are going to get which makes the next step in the process easier and quicker to complete.  It reduces the amount of time wasted completing a task and it means that the quality of a part or process step is higher reducing the need to rework or redo the activity.  The simplest analogy is to think of golf and putting into the hole.  If every time you took a putt you got the ball into the hole think how good that process would be, now think how good your putting is.  In business if every time a part was made it was identical in every way to how it was meant to be – shape, form, look, feel etc that would mean we would have no quality issues.  If we were completing a form and every time every field was correct, easy to read, all data correct, all numbers correct and it was the right form think how quickly things would be done.  Well that is what Six Sigma is all about reducing the variation in everything you do. 

The term “Six Sigma” refers to the ability of activities or processes to produce output within specification. In particular, processes that operate with six sigma quality produce at defect levels below 3.4 defects per (one) million opportunities (DMO).  Six Sigma’s implicit goal is to improve all processes to that level of quality or better.  That would mean that every time you did something one million times you would only make a mistake 3.4 times. 

To achieve these improvements in variation and therefore quality improvements and cost reduction Six Sigma uses an approach to solve problems (sources of variation) which is a standard methodology which everyone must use when solving problems regardless of size.   DMAIC which was inspired by Deming’s Plan-Do-Check-Act cycle is a sequence which if followed will ensure that not only will the root causes be identified but the best solution will be found then implemented into the organisation permanently rather than for a short period before it goes back to how it was.  If you are designing a new process or product then the methodology used would be DMADV.

DMAIC

Basic methodology consists of the following five steps:



Define the process improvement goal or problem to be solved this should be consistent with customer requirements and the business strategy.

easure the current process and collect relevant data for future comparison.

Analyze to verify relationship between factors and to identify the real root causes ensuring that all factors have been reviewed. 

Improve or optimize the process based upon various analysis tools to identify a number of solutions and then using data determine the most optimum for the problem.

Control to ensure that the solutions is implemented into the organisation and embedded so that it is does not return.  This uses a series of tools and techniques to continuously measure the process and institute control mechanisms.



 

 

DMADV

Basic methodology consists of the following five steps:



Define the goals of the design activity that are consistent with customer requirements and business strategy.

Measure and identify CTQs (critical to qualities), product capabilities, production process capability, and risk assessments.

Analyze to develop and design alternatives, create high-level design and evaluate design capability to select the best design.

Design details, optimize the design, and plan for design verification.

Verify the design, set up pilot runs, implement production process and handover to process owners. 





 

Many people get confused by Six Sigma and believe that it is simply a case of applying a number of tools.  This has lead to many failed implantations of the methodologies.  Other people are put off Six Sigma by the amount of data collection and analysis which is used.  Simply put Six Sigma is all about data, if you have not got data you are just another person with an opinion.  One of the reasons Six Sigma has been so successful in companies such as Motorola is that it is all data driven the methodology makes you use the data, analyse the data and then come up with solutions.  To do this you must use statistics and tools which use stats to investigate and solve problems.  As such typical tools used in Six Sigma include:-

They can seam daunting and put off many people but the simple truth is that you don’t have to know them all.  You don’t even need to use them all.  It is good ideas to have one or two people in your organisation who have detailed knowledge of them all you have to do is to know when they should be used then call in the experts. 

When used properly Six Sigma can dramatically reduce variation in your processes and lead to massive savings.  However when coupled with Lean it becomes even more powerful. 



Lean as the name suggest is the production of products or services using the least of everything – human effort, investment in inventory, machines, space, tools, time, development, transport / movement.  The term is called Lean, Lean Manufacturing and Lean Enterprise all meaning the same thing and deriving from the Toyota Production system and some other sources.  It is however very simply the reduction of waste from your processes it has enabled Toyota to become one of the biggest and most reliable car companies in the world.  

Lean is therefore the identification and steady elimination of waste through the implementation of perfect first time quality approaches to work, standardisation of processes, smoothing of flow, flexibility of work, long term relationships with customers and supplies and reduction in time leading to cost reduction and business improvement.  To achieve this, a number of tools have been developed which facilitate the removal of waste from processes and a number of methodologies to implement the principles.   

In organisations where the principles of Lean are fully understood the people use the tools and techniques with out thought as eliminating waste and improving flow become the norm.  Lean in its many guises has been around since the 1940’s and has developed and adapted over the years to become one of the key business improvement methodologies used in many of the worlds leading companies.  At its heart lean is effectively simple and easy to understand.  Lean implementation is therefore focused on getting the right things, to the right place, at the right time, in the right quantity to achieve perfect work flow while minimizing waste and inventor while being flexible and able to change if the customer requirements change. 

However, no matter how simple, at the heart of any lean implementation is the cultural and managerial aspects of Lean which are just as, and possibly more, important than the actual tools or methodologies of lean itself. There are many examples of Lean tool implementation without sustained benefit and these are often blamed on weak understanding of Lean in the organisation.

The first concept which must be understood is that waste is bad.  This has been the ethos for successful companies from Henry Ford onwards.  So what is waste?

Waste or non value added work is anything which doesn’t add value to your product or service.  When you examine your processes in real detail you discover that the vast majority of what we do is non value added.   To illustrate this Shigeo Shingo (a deep lean thinker) observed ‘that it’s only the last turn of a bolt that tightens it – the rest is just movement’.  If we review everything we do to this extent we see that most of our activities are waste.  To eliminate waste we must examine three aspects – the design and planning of our activities, the fluctuation at our operations such as quality and volume and thirdly the waste in our processes themselves in the movement of people and materials and the machines they use.  

When you examine your processes in this way you can be said to be ‘learning to see’ and can start to eliminate the waste and improve the processes.  To make things easier there are 7 ways to think about waste. 

The original seven wastes are:



Overproduction (production ahead of demand) – making things ahead of when the customer actually wants them.  We do this because our processes are not reliable, or we like to manufacture or do task in big batches (traditionally accountants tell us this is the most efficient way).

Transportation – moving parts, materials or work in progress around a factory or paper around an office.

Waiting – for parts or information so you can perform at task. 

Inventory (all materials, work-in-progress and finished product) – Items produced which can’t be used or sold straight away go into inventory tying up money, space and causing multiple management issues.

Motion -people or equipment moving or walking more than is required to perform the processing.

Over Processing – making more than is needed or doing more work than is needed because you can’t guarantee what the outcome will be ie I need 20 but I will make 25 just in case something goes wrong.

Defects / Rework – the effort involved in inspecting for and fixing defects, reworking items or having to scrap them.



 

There has now been identified an 8th Waste



Human talent – the waste of people’s talent – training, enthusiasms and brain power.



 

 

By identifying waste and non value added activities in our processes we can then start to use the lean tools to eliminate them.  Typical Lean tools include – 5S, visual management, TPM, SMED, Pokie Yokie, Standardised work, pull systems, takt time, single piece flow, Kanban, cellular manufacturing, design for manufacture, kaizen etc

Lean thinking and the tools associated with it have been used for decades all over the world by every type of business.  There is a standard approach to implementation of lean thinking.



Step 1: Specify Value

Define value from the perspective of the final customer. What does your customer actually want, what will they pay for and when do they want it.  

Step 2: Map

Identify the value stream, all the actions required to bring a specific product through the physical flow of the company.  This includes all the information flow and management flow steps to make things happen.  Create a map of how it is today and how you want it to look like. Identify and categorize waste in the Current State, and eliminate it! 

Step 3: Flow

Make the remaining steps in the value stream flow. Eliminate functional barriers and develop a product-focussed organization that dramatically improves lead-time. 

Step 4: Pull

Let the customer pull products as needed, eliminating the need for a sales forecast.

Step 5: Perfection

There is no end to the process of reducing effort, time, space, cost, and mistakes. Return to the first step and begin the next lean transformation, offering a product which is ever more nearly what the customer wants. 



 

 

If you have a top management team who understand the concepts and a workforce who embrace the culture then Lean will transform your business.

  So what is Lean Six Sigma?

As stated above Lean and Six Sigma when used together will provide a business improvement methodology which combines tools from both Lean Enterprise (Manufacturing) and Six Sigma.  Lean eliminates the waste in your processes, while Six Sigma ensures quality through the elimination of variation in your processes and also provides a structured data driven structure to solve problems and implement sustainable change into your business. 



Why is there even a debate about which one you should use?

For some reason two camps have emerged one supporting Lean and the other Six Sigma.  Lots of it is childish my way is better than yours and some of is lack of knowledge.  Either way what you find is that both approaches use each others tools any way.  So the whole thing is stupid.  As with any business improvement you should use the best tool for the job no matter what it is or where it has come from.  You should be constantly seeking out new tools, methods, applications and methodologies to satisfy your customer and business needs by eliminating waste and improving quality.  That is why we always train, consult and coach in Lean Six Sigma but bring in anything else we know.  That is why we don’t mind you calling your improvement initiate what ever you like and that is why we get results. 

www.100pceffectivetraining.com      0845 070 2987



By: John Wellwood

About the Author:

Consumer outlook has undergone considerable changes due to business globalization and revolutionary information exchange paradigms. Changing business conditions created by the flurry of increasing competition has led to diminishing margins for error. Exceeding the expectation levels of customers assumes the central position in the current and future era of business. It is for this reason that Six Sigma has assumed critical importance in the current business environment.

What is Six Sigma?

Six Sigma is a two-way quality management approach towards achieving zero errors by removing process defects for existing products and by designing verified process flow for new products. From a consumer’s point of view, Six Sigma is a highly disciplined process that enables product and service deliveries to a near perfect standard.

The term Six Sigma (also 6 sigma) signifies the statistical benchmark for quality assurance. Sigma is the standard deviation (allowable, standardized figure from the mean acceptance level), and when the measured number of deviations beyond the mean tolerance limit is six, you are barely producing quality products. Simply put, this means that if you found six defects in your products, you are very close to poor quality production.

Implementation Of Methodology

The choice of implementation of Six Sigma methodology depends on whether improvement is required on existing processes (DMAIC) or on new process/product design creation (DMADV).

DMAIC

In Six Sigma, DMAIC methodology involves defining improvement goals, measuring the existing standards at baseline for future reference and analyzing the relationship between defects and their causes. This Six Sigma methodology also entails improving processes to deliver consistent goal achievement in accordance with company strategy and consistent with customer demand. The analysis process of this Six Sigma methodology sets the stage for midway course correction, called improvement.

DMADV

This 6 sigma methodology applies to the creation of new processes for product development. This Six Sigma implementation differs from the DMAIC methodology at the final two stages. Defining and measuring the design and product goals and capabilities are the first two stages. The next stage is analyzing alternatives and evaluating to choose the best product design. The next stage consists of implementing the best design. The final stage entails verifying the design, pilot (or test) runs and testing implementation before the final presentation.

Several organizations such as Motorola, (which is a pioneer of Six Sigma), Microsoft, GE and the United States Navy have successfully implemented Six Sigma and reaped huge dividends. Six Sigma has benefited corporations with multiple products across various business sectors. Healthcare, banking and insurance, telecommunications, software, and construction are just some of the industries successfully implementing Six Sigma.

Six Sigma implementation requires organizations to play five key roles at various levels. At the top is executive leadership which includes the CEO, champions, master black belts, and black belts. Then there are the green belts, which dedicate 100% of their efforts towards the concerted implementation of the program until the end of the project. The difference between the green belts and the rest of the team is that the employees in the green belt level share the additional responsibility for Six Sigma implementation along with their normal work responsibilities.

Criticisms Of Six Sigma

Despite its scientific approach towards quality improvement, there are criticisms against Six Sigma. The most vocal one is the viewpoint that there is nothing new about Six Sigma as it imitates already existing and proven techniques. To a certain extent, this argument has some credibility. But proponents of Six Sigma believe that as long as 6 sigma achieves more predictable results with far lower effort, there is no harm in accepting and implementing it. Criticisms notwithstanding, what Six Sigma does is apply concerted efforts at utilizing existing techniques with new approaches.



By: Tony Jacowski

About the Author:

Any major change initiative requires a clearly defined supporting infrastructure to drive the program. Infrastructure is defined as the underlying foundation and basic framework of personnel and supporting systems needed to support Six Sigma deployment activities. Because every part of a company participates in Six Sigma activities, the infrastructure must be clear, consistent, and comprehensive.

An effective infrastructure facilitates the development of the core competency that will establish and link Six Sigma project teams to (1) projects, (2) financial targets, and (3) the strategic plan. These project teams will be multifunctional and will need multi-functional support to execute the projects.

If Six Sigma has any chance of being successful, the infrastructure will span from the CEO and his leadership team to business leaders and to people executing the projects. Remember we learned earlier that one of Kotter’s eight stages of leader change is “Create a Guiding Coalition.” Thus, there is the goal of the Six Sigma infrastructure.

The infrastructure creates a strong network among the Executive Team, the Six Sigma Champions, the Belts, and the functions and businesses. This makes sense because the CEO’s leadership team holds the accountability for executing the corporate strategic plan, and Six Sigma projects are instrumental in moving along the strategic plan.

One learning challenge of a Six Sigma deployment involves training the Six Sigma project teams. The human resources on these teams must learn how to work as a Six Sigma team. A new roadmap and a new set of tools, plus a more distinct focus on project accountability, add to the changes confronted by an organization when creating a Six Sigma environment.

Equally more important and complex is the learning challenge of the senior executives. Teaching the leadership team to learn how to lead a team-based organization is essential to strategic and long-term success. Because executing the strategy is a clear responsibility to which the senior executives are accountable, it follows that becoming a dynamic team leader within the Six Sigma deployment will support the strategic efforts.

Executing a good strategic plan entails the coordination of multifunctional internal activities. Senior executives must learn to deal with a multifunctional arena rather than the traditional functions. Hundreds of Six Sigma teams launched simultaneously is the outcome of an exemplary deployment of Six Sigma. Each of these teams need at minimum

1. Clear purpose for the Six Sigma team structure.

2. Clear Six Sigma program expectations.

3. Six Sigma project charters.

4. Six Sigma infrastructure tracking the number of teams.

5. Centralized repository for project results.

6. Six Sigma team goals.

7. Six Sigma team reporting mechanism.

8. Rewards and recognition alignment.

9. Six Sigma training and development plan.

10. Six Sigma team performance measures.

11. Deployment management of Six Sigma teams.

To accomplish all of the preceding requirements demands an extensive infrastructure with supporting systems. Preexisting resources are largely used to staff this infrastructure. Deploying a Six Sigma program, however, does not assume a requirement to add outside resources in a lot of new positions. The additional costs will usually have to do with the external consulting group you hire.

For example, the only resource that Larry Bossidy added when he launched Six Sigma into AlliedSignal was a corporate program leader. Larry brought in Richard Schroeder from ABB to drive the program. All the other resources for AlliedSignal’s Six Sigma program already existed within the company. A small number of additional resources were added by the businesses as needed.

Because accountability represents the hallmark of successful Six Sigma deployments, defining the Six Sigma infrastructure and staffing and training the infrastructure players should happen very early in the Six Sigma deployment. Training is essential since, as Larry Bossidy has advised in his book, Confronting Reality, you must “Learn the guts of the initiative.” He also adds that key members of the leadership team should learn the guts of the initiative. Early leadership training becomes a natural part of Six Sigma deployments to allow the program leaders to learn the guts of Six Sigma before the program gets too far along.

Defining the Six Sigma infrastructure is a little tricky. There should be a small centralized unit to ensure consistency and cost effectiveness of Six Sigma activities across the businesses and functions. There should also be a decentralized process that allows each business and function to tailor the Six Sigma deployment to its special needs. There is a big difference in deploying Six Sigma into the Human Resources function when compared to deploying into product development and R&D. So, our recommended infrastructure has both centralized and decentralized elements in it.

 



By: Tom Smith

About the Author:

Since its introduction in the 1990′s, 6-Sigma has become the buzzword in both the manufacturing and service industries. The various methodologies used in 6-Sigma are based on a disciplined and data driven approach that help in eliminating defects and achieving near perfection by restricting the number of possible defects to less than 3.4 defects per million. The methodologies are effective in managing business processes of both the manufacturing and service industries. In manufacturing industries, the concepts and methodologies are used for reducing the number of defects whereas in service industries, they are used mainly for reducing transactional errors.

Although many companies have been successful in reducing the number of defects through Six Sigma projects, the arguments raised against the efficacy of 6-Sigma in all aspects of business processes still do not seem to die down. Some management experts think that Six Sigma is inherently flawed, as it does not take into account the flaws that might be present in the system itself. They are of the opinion that the analytical and statistical tools used in 6-Sigma only expose flaws in the execution and do not account for a process that itself is riddled with defects.

Supporters of Six Sigma offer a different viewpoint. According to them, quality management tools such as Total Quality Management (TQM) and 6-Sigma are conceptually quite similar except for their labels. Business organizations may use any of these for improving overall quality. However, they often give preference to 6-Sigma as they believe that Six Sigma is more than just a process improvement program and is based on concepts that focus on continuous quality improvements. They have the opinion that 6-Sigma concepts combine statistical measurement tools with contemporary management techniques for achieving extraordinary results.

The Limited Use Of Six Sigma

6-Sigma gained prominence as an effective quality improvement technique after it was successfully implemented in Motorola. Since then, many large organizations have implemented 6-Sigma programs and improved the quality of manufactured goods or services rendered. However, the full potential of 6-Sigma has not been realized so far because many competent small to medium level enterprises have still not implemented Six Sigma programs. These enterprises have all the resources to implement such programs, but are often wary of the final certification, as they believe that it is meant only for large organizations. These companies often do not realize that 6-Sigma delivers the same benefits to both large as well as small business enterprises. The only difference may be in the volume of goods manufactured or services rendered.

The Future Of Six Sigma

6-Sigma may appear similar to other quality management tools such as TQM or Kaizen Events, but in reality, it is quite different. Other quality management programs often reach a stage after which no further quality improvements can be made. 6-Sigma, on the other hand, is different as it focuses on taking quality improvement processes to the next level. This means that 6-Sigma has the potential to outlast other quality management programs in the future.

The scope of 6-Sigma is also much broader than other quality management programs as it can be applied to every business process of an organization. The future is bright for 6-Sigma programs with the growing awareness in small and medium enterprises about the potential benefits that can be derived from implementing such programs.



By: Tony Jacowski

About the Author:

The demand for people with Six Sigma expertise is constantly increasing. More and more organizations are discovering the many ways that the Six Sigma methodology can help them grow and improve. As Six Sigma spreads to many different industries beyond its genesis in manufacturing, you can now find many service and government organizations advertising for Six Sigma help. Plus, it is no longer the largest corporations looking for Six Sigma help. Smaller companies also are taking on Six Sigma projects and hiring people as consultants or permanent staff. The need for full-time Six Sigma professionals will only increase.

Types of Six Sigma Jobs

There are many Six Sigma jobs in many industries at junior and senior levels. The positions have descriptions and requirements unique to that organization and its requirements. It is true that many Six Sigma positions are filled internally as organizations train their own people already familiar with the organization’s culture in Six Sigma skills. However, organizations frequently reach outside to add personnel with Six Sigma expertise to lead Six Sigma projects or even the full-scale implementation of Six Sigma throughout the organization. These positions are usually dedicated full-time to Six Sigma projects.

Six Sigma jobs are advertised under many titles, not always as obvious as “Six Sigma Black Belt,” “Six Sigma Consultant,” or “Six Sigma Analyst.” Other possible titles include things like “Functional Project Lead” “Six Sigma Program Manager,” “Lead Analyst/Project Manager,” “Director of Operational Excellence,” “Business Process Manager,” or “Senior Projects Manager.” Whatever the exact title, the organization is looking for someone with the skills of a Six Sigma Black Belt. A Black Belt is an individual trained in the Six Sigma methodology and experienced leading cross-functional process improvement teams. They will lead individual Six Sigma projects.

Very senior Six Sigma positions are sometimes advertised. These are Master Black Belts, individuals trained in the Six Sigma methodology who acts as the organization-wide Six Sigma program manager. They will lead Six Sigma implementation at the organization and will oversee Black Belts and process improvement projects and provides guidance to Black Belts as required. Master Black Belt positions understandably demand the highest level of Six Sigma experience and qualifications.

Qualifying for Six Sigma Jobs

To be considered for a Six Sigma job, you need a combination of relevant academic and work experience. The first and foremost qualification is to be trained in Six Sigma, ideally as a certified Six Sigma Black Belt. This means formal training from qualified Six Sigma consultants who have extensive experience in training and implementation of Six Sigma. Specific training in Six Sigma DMAIC and/or DFSS methodology is often requested. The best teacher is, of course, experience and organizations will strongly prefer, if not insist, on people who have completed at least one Six Sigma project.

In addition to possessing Six Sigma training and project experience, organizations will ask that you have experience working in the industry of the organization’s business. So if the company is a manufacturer, they will usually want you to have direct experience in a manufacturing environment. Organizations will ask that you have a certain minimum period of experience (often five years) in that particular industry.

Management experience is a huge plus and will almost certainly be a requirement for a Six Sigma project team leader. Having on your resume proven project management success within a structured environment and being able to demonstrate good managerial skills will take you a long way. That’s because leading and facilitating Black Belts, Green Belts, and business teams through a Six Sigma project is often the role organizations are seeking to fill.

There are also essential personal skills. You need to be able to demonstrate a good understanding of processes and quality methodologies and a willingness to take an initiative and lead change. Another crucial skill is the ability to link strategy to execution. The aptitude to look beyond the surface and be creative to think conceptually about strategic business issues and develop creative but practical solutions is key.



By: Peter Peterka

About the Author:

 Introduction- Six Sigma Background and Issues

 Six Sigma is the practical application of a theoretical statistical measurement that equates to 3.4 defects per million opportunities -a position of practically zero defects for any process or service. Its attainment is one of the highest measures of quality and is based on the ideology that practically all errors are preventable (Behara et al, 1994). Initially originating in Motorola Inc. in 1985 as a response to drastic quality improvement pressures from the threat of Japanese competition (Harry & Schroeder, 2000), it quickly gained many followers particularly G.E., Allied Signal, Ford Motor Company etc. and more recently attentions have shifted to service environments.

Bob Galvin former CEO of Motorola stated that the lack of initial investment in the non manufacturing areas of the business over four years was a blunder that cost the business over 5 million dollars (Basu & Write, 2003, p43). However, organisations have implemented six sigma initiatives in transactional frameworks with success- testimonial for six sigma triumphs in services range from American Express and PriceWaterHouseCoopers to local NHS departments.

The nature of Six Sigma and it’s Quality Objectives

As outlined in Lagrosen & Lagrosen (2003) six core principles form the basis of quality management, constitute the common material measured by numerous recognised quality awards (e.g. Malcolm Baldridge Quality Award, Swedish Quality Award etc) and form the basis of  ideas presented by leading authors in this field (e.g. Dale, 1999, Bank, 2000 etc). These six core values are –

1.      Customer Orientation

2.      Leadership Commitment

3.      Participation of Everybody

4.      Continuous improvements

5.      Management by Facts

6.      Process Orientation

Six Sigma methodologies encompass all of these areas and thus in a sense is not revolutionary, rather it’s focus on directing resources and effort towards explicit goals with concrete objectives using a prescribed approach makes it unequivocal and robust to implement in organisations. Goal setting research indicates that there is a strong positive relationship between setting challenging, measurable, specific goals and performance (White & Locke, 1981). Linderman et al (2001) argues this is one of Six Sigma’s foundations of success. Thus Six Sigma may be succeeding in a manner TQM could not– TQM was often criticised for being weak – “It is very difficult to motivate and justify what seems to be a repeated circular path, where what in fact is required is a spiralling process that moves forward with each revolution” states Tennant (2001, p 35) in regards to the unclear targets of TQM.

This common goal in Six Sigma organisations is to reduce costs by eliminating defects (Greatbanks, Lecture- 18/11/03).

Costs of Defects

It is argued that Six Sigma should be implemented through the processes that affect customer satisfaction and organisational effectiveness to reduce costs (Eckes, 2003, p3). The following costs are associated in services:

·        Verifyable Failure costs- service defect is detected by customer and brought to the attention of the server for rectification, e.g. a hair is found in the soup at a restaurant, the soup must be replaced.

·        Nonverifyable Failure costs- difficult to measure ‘hidden’ costs that are not reported back, e.g. people rarely complain and ask for a refund if they attend a bad theatre production.

-Issues include declining image and goodwill due to negative word of mouth and the costs associated with regaining a lost customer (3-5 times more expensive than attracting a new one) Without a loyal customer base a service organisation would be financially very unstable.                                  

·        Internal Failure Costs- costs of correcting defects uncovered by the producer before they reach the customer e.g.  Slightly overbooking for an excursion means the service provider needs to book 2 minibuses instead of one.

-Often internal failures result in higher staff turnover and lower morale which in turn leads to recruitment and training costs above the overt costs of rectifying the problem.

 (Heskett et al, 1990, p76)

 The Costs of Poor Quality (COPQ) corresponds with sigma levels, for instance if Six Sigma has been attained, the COPQ is less that 1% of cost of sales, while operating at a three sigma level, which many companies do, equates to a COPQ level of approximately 25-30% of cost of sales (Basu & Wright, 2002, p39). This demonstrates what a powerful tool Six Sigma can be in reducing costs. 

Six Sigma is very relevant for services as it has been found that the costs of quality in service organisations are greater relative to manufacturing (Asher, 1987)

The Nature of Services

Services are notorious for their wastage, inefficiencies and variability (George, 2003, p3), and as the basis of service is human delivery, one may assume that clear goals and a prescribed system of change could motivate transformations in the workforce. However there are more issues that have their roots in the nature of services that effect how Six Sigma can be implemented in such a context.

Six Sigma was initially designed within the framework of the manufacturing company. It is important to note that services differ in nature to physical products in the following regards: 

Inseparability – The customer is involved in the actual production process- the service is delivered and consumed at the same time.

Perishability – Being intangible, the service cannot be stored.

Heterogeneity – difficulties in standardising services every time for every customer.

(Ghobadian et al, 1994)

Service Quality

Quality is an important issue in services due to the features of inseparability, intangibility and perishability. That which can not be stored and is intangible cannot be checked for defects before ‘delivery’ to customers.  In addition each individual involved in the exchange process brings with them varying levels of expectations and levels of satisfaction in addition to the unpredictable nature of human beings. It is this dominant role of human interaction in services that shape customers expectations and create difficulties in understanding and implementing quality initiatives (Behara & Gundersen (2001)).

The most commonly used definition of quality is the extent to which goods or services meet or exceed customer expectations (Zeithaml, 1981). Customer satisfaction should lead to repeat utilisation of the service; so if ‘zero defects’ are the goals of manufacturing then ‘zero defection’ should be the sign of quality coming to services (Reichheld & Sasser, 1990). Thus for the Define stage of the Six Sigma methodology the areas linked to optimising customer satisfaction should be concentrated upon. Yet it is important to stress that this in itself can be a muddled and complicated feat.

Six Sigma strives for Total Customer Satisfaction in services (Erwin, 2000).

 As illustrated by Behara et al (1994, p12) customer satisfaction is a multistage process where levels of satisfaction are multiplied as different facets of the service are exposed to the customer. These facets cover a broad range from ethical practices of the business to timely response to knowledgably staff etc. So for instance no matter how fresh and tasty a McDonald’s burger is, for a customer who has moral issues with the low wages of their employees, fulfilment will never be attained.  The key notion is that different customers have different patterns of expectations for the components involved and so, is it possible to have zero customer defection? Not everyone likes the same things and thinks in the same way and thus the service provider must focus on the elements that will please the majority only.

Also as services are intangible, there are greater problems in the measurement of quality, as discussed, what constitutes quality may be different for different individuals based on their perceptions and past experiences and thus what defines defect in services? Often this will be an obvious matter of simply delivering what is promised, yet in most cases reliance on customer feedback, complaints and measurement (as demonstrated in the case study) will have to be used for enlightenment of issues. Six Sigma advocated the measurement of such variables as the only way to gain insight into service defects.                

Implications for Services

The use of quality programs in relatively high in the service environment, for example Robinson (2003) found that 90% of the sport and leisure facilities managed by local authorities implement some quality scheme, however it follows that the type of quality schemes in services are considerably less ‘technical’ based (e.g. Statistical Process Control, Design of Experiments, Quality Circles and Failure Mode and Effects Analysis- FMEA) than those found in manufacturing and more in tune with ‘softer’ cultural issues and creating an proficient and efficient climate through employees, not processes (Lagrosen & Lagrosen, 2003). But as Tennant (2001, p36) puts so eloquently this is not the purpose of Six Sigma- “Six Sigma has the tools and the power to cut ice where hot air has contributed little in the past”.

The Six Sigma methodology relies heavily on statistical analysis; traditionally services have minimal data and examination of their techniques, thus this may poise an initial hurdle. Over and above many individuals have a fear of metrics and don’t connect their use to services. Breyfogle (cited from Smith, www.qualitydigest.com) explains “They (services) don’t appreciate the importance of creating meaningful metrics that give insight into how their business processes perform over time. This can lead to fire fighting common cause variability as though they were special cause”. He argues that only the use of statistical control charts will enable services to focus on prevention rather than reacting to problems. Monitoring processes is the only way to progress from subjective hypothesising of reasons of error to concrete data and this one of the main principles of Six Sigma. 

Is this fear of metrics justified? Many academics have confronted the problem of applying statistical techniques to non-manufacturing environments, for example Deming (1987, Ch7) gives a long listing of measurements in service industries where SPC or similar can be applied.  It is noted by Oakland (1989, p226) that “Data is Data…whether numbers represent defects or invoice errors, the information relates to machine settings, process variables, prices, quantities, discounts, customers, or supply points is irrelevant, the techniques can always be used”. The inference is that statistics can be transferred to services; it is rare though, that problems and issues are documented in the literature (merely success stories) this does not mean however by implication these problems do not exist (Wood, 1994). It will often involve creativity and flair to apply statistical techniques to services in a fashion that causes true understanding of what the reality is through numerical representation.

Healthcare Case Study

 (Kooy et al, 2002)

The following example is simplified and divided into the common methodology of DMAIC to illustrate how Six Sigma is implemented in services.

Background

In June 2001 VirtuaHealth,  an organisation of 4 Hospitals in New Jersey USA, put together a team of internal employees including frontline staff members and a six sigma project leader (black belt trained by GE Medical Systems), the aim being to –Ensure safe and effective acute anticoagulation capability.

            The project would focus on the drug Heparin (an anticoagulant) which was used for the treatment and prevention of thromboembolic diseases (blockages in the veins). Patients administered Heparin within 24 hrs of detection of problems saw a significant reduction in future problems, but there were side affects involved also with the Heparin therapy, including serious bleeding (thromboctopenia) and life or limb threatening thromboses.  As a result, a weight based protocol was used to administer correct dosage of the drug.

DEFINE

Team identifies customer (i.e. patient) requirements and process deliverables as preventing or addressing anaemia and thromboctopenia during therapy.

These 2 attributes are defined as follows-

Anaemia- drop in haemoglobin at rate of at least 1g/dL per day (and final value less that 12g/dL)

Thrombocytopenia- 50% drop in platelet count (enables blood clot) or a count less than 100,000.

 

-         Occurrence of these attributes was considered out of the ‘Therapeutic Range’.

Acceptable practice was defined as the recognition of the reduction at monitoring stage and actions being taken by the physician- discontinue heparin therapy or other such appropriate measures.

MEASURE

Team used pharmacy and laboratory databases and manual data to measure current performance. From the 815 patients who had received therapeutic doses over the last 6 months, 18% were sub-therapeutic and 35% were supra-therapeutic.

The Team constructed a high level process map to better understand the flow of activities involved in administering and monitoring Heparin (this is the service component).

The mean time from administering the drug to monitoring the outcomes was 8.5hrs, which was considered late but acceptable, yet it was the amount of variation in mean times that was causing problems. Samples being drawn early could lead to drug adjustments based on non-steady state results, whilst those drawn too late could result in an unacceptable diffusion rate of the drug being administered.  

 ANALYSE

This phase entails the identification of the factors that drive the process results. Barriers towards successful completion of each process step was identified and a more detailed process map was drawn (including the laboratory and pharmacy sub cycles), a total of 92 steps were identified for reaching completion of first dose adjustment.

            Many problems were identified. Step completion was often down to staff remembering to act, often hours after triggering the event. It was concluded that the complexity of the system was impeding performance and there were few system elements in place to help prevent problems. In particular, the initial step using the weight based protocol was rarely followed meticulously due to time constraints- only 48% of patients were being weighed at all (critical for accurate measurement of drugs) and out of the remaining patients where the weight was estimated, 20% of estimates were more that 10% off.  Finally the progression from each step was disjointed and there was often uncertainty as to who had responsibility for the various stages.  

            In summary, adverse outcomes were not due to minor process variation; rather, they were connected with major break-downs in the delivery of procedure. The team concluded that by simplifying the acute anticoagulation method and error- proofing each stage this would act as the greatest prospect for ensuing safety.

IMPROVE

At this juncture, the implementation and measurement of changes to the process toward desired performance is considered. The weighing problem was overcome by investing in beds that had integrated scales, which the hospital used in other departments with much success for routine weighing. This problem had been “flying under the radar” for several years and had only been made explicit through the Six Sigma intervention. This is coupled with an administration record for the weight based Heparin protocol that notes the responsibility (given by doctor taking on case to shift nurse) of re measurement in the agreed time of 6 hours. In addition, new infusion machines that restricted the range of infusion based on the weight calculation were implemented to reduce the possibility of overdose due to lapse of nurse attention.

CONTROL

Visible metric or ‘dashboards’ (control charts, run charts, reports etc.) are used by the project owner to ensure performance is sustained at optimal levels. The performance will also be tracked on a monthly basis by a local quality analyst in the hospitals quality assurance department. Deviations are to be reported to and reviewed in detail by the quality director and pharmacy and therapeutics committee.

Commentary

A public sector example was used to display how six sigma methodologies can be extended to cater for goals that are not primarily cost reduction. Reduction in defect and cost reduction are not mutual concepts in the short term.  Customer has been substituted for patient, and reduced cost for successful therapy. Although not explicit, the case study did suggest that in the long term costs would be abridged through a reduced amount of administration time and investigation into faults/ compensation. Thus all Six Sigma projects have long term cost reduction consequences, however this is not always (but mostly) the motivation for implementation (as with the treatment of life threatening diseases).

The case study demonstrates the importance of the measurement of all major inputs into performance in order analyse how a process can be improved. Six Sigma stresses this measurement opposed to theoretical conjecture; it is “management by facts, not emotion” (Randall, R. cited in Erwin, 2001, p38)

Conclusion

Application to Services-  Six Sigma Influence

 

Six Sigma is undeniably more complicated to apply in some service situation than those in manufacturing. Even where a process and goal exists some may argue that the setting of the specification limits can be somewhat a subjective issue and sometimes organisations spend time and money adding a specification value where one is not appropriate (Breyfogle et al, 2001, p196). This may be overcome by implementing a measurement systems analysis (MSA), however it must be noted that due to such issues, in services primary tasks may take longer than anticipated due to determining the appropriate measurement systems. (Breyfogle et al, 2001, p196).

This does not however mean that Six Sigma is not useful or is too difficult to implement- the extent of use and thus difficulty is dependent on company objectives. The methodology can be used to bring quick financial savings early on by tacking what Breyfogle coins the obvious ‘low hanging fruit’ problems in an organisation. By contrast it can also serve as a model for organisational culture “whereby everyone at all levels has a passion for continuous improvement with the ultimate aim of achieving virtual perfection” (cited from Basu & Wright, 2003, p3)

Reduced Quality? 

Some writers also maintain that various types of service industry are unsuitable for such rigid methodology as it will hinder the very facets that create customer satisfaction. There is often a trade off between customer satisfaction and running a business efficiently. For example a hairdressers may lose clients if it merely tried to fit as many haircuts in as possible (assuming no decline in haircutting quality), the customer in such circumstances like to be pampered, for the hairdresser to take their time and a relaxed atmosphere be upheld. Powell (1995) found that success derived more from HR intangibles, such as an open organisational culture, employee empowerment and executive commitment than on improved measurement, process improvement and benchmarking

This also links into the concept of reducing variability to decrease defect and increase efficiency. Although primarily founded on manufacturing quality, some services take this route- e.g. the mechanised “have a nice day” script in fast food chains etc. It is important to note that this will not lead to customer satisfaction in such sectors.

Process or Goal?

Behara et al (1995) state that in the early 1990s companies in the US (summary of all industries) were operating at around a three /four sigma quality level. The question is do companies need to reach Six Sigma level and is it in their best interests to do so? Initially one may believe that zero defects or total customer satisfaction is the ultimate goal that all companies should strive for (even if just for motivational purposes) as conveyed by the principles of Crosby. However understanding the traditional view of the trade-off between costs and prevention of service failures adds a different perspective. This concept is based on the premise that error prevention costs increase as the level of quality increases; in fact the relationship is exponential increases in prevention costs for mere incremental quality gains. Thus the target quality level managers should endeavour for may be under 100% and variable for different services dependent on their nature. (Heskett et al, 1990).

 Six Sigma does not necessarily need to be achieved (Hammer & Goding, 2001), merely its methodology followed and an understanding of the optimal levels for overall cost reduction should be understood and set as the goal.

Fashion?

Among the literature, some authors have debated that Six Sigma is the latest fad, and that consists of a ‘repackaging’ of what has already come previously (Dusharme www.qualitydigest.com).

The challenge of Six Sigma is to overcome the ‘Innovative Fatigue’ (cited in Basu & Wright, 2003) which can cause loss of interest in an initiative. It has been shown by Turner (1993) that any quality initiative must be reinvented at regular intervals in order to sustain motivational levels of employees and that the maintenance and implementation of a quality program is approximately 2.5 years.

Improvement initiatives often forgo their initial success and do not gather the momentum necessary for true permanent organisational change for various hidden reasons. “Six Sigma is a quality approach that takes a whole system approach to improvement of quality and customer service so as to improve the bottom line” (Basu and Wright, 2003, p2)  The main concept at this juncture is the ‘bottom line’ or return on assets as the key measure of success. This is a historical measurement that inherently can only inform of the result after it is too late to influence it. In many cases this may be too late and formal periodic assessments must be made in order to enable the flexibility to respond to various pressures. The ‘Control’ variable in the DMAIC methodology should ensure longevity and suppleness, and the DMADV (Define, Measure, Analyse, Design, Verify) methodology will serve to update and sustain processes also. Thus the question of whether Six Sigma is fashion or here to stay will only be answered through time.

Alternatives and improvements

It is also worth mentioning how Six Sigma has expanded and developed to illustrate its evolution is business and particularly services. Lean Six Sigma focuses on the maximisation of process velocity and provides tools for analysing the delay times and process flow for activities (George, 2003). It aims to reduce work in process and waste in procedures. Fit sigma (Basu & Wright, 2003) adds the element of sustainability and focuses not on the perfect goal of 3.4 defects per million but whatever the right ‘fit’ is for the organisation.

Finally Human Sigma does not focus so much on eliminating error, rather in reducing variance in key employee and customer outcomes, on the assumption that high variance equates to inefficient management. (Coffman, 2003). It seems that so many adaptations and variations of quality initiatives are being introduced due to the fact that organisations, particularly services are different in structure, ethics, goals etc. There does not seem to be one ‘best fit’ model and thus it is the predicament of the company to pick the one that suits it best.

As discussed in this essay there are many issues that must be considered when assessing whether to implement six sigma in services. These range from how one defines quality, identifies the costs of poor quality, implements statistical techniques to measure the situation, decides the level of sigma which will be optimal for the particular service industry they operate in etc. Despite these considerations one believes that Six Sigma is a useful tool in services, perhaps a reason why it has been criticised is that people have taken too literal an interpretation

It provides companies with a common metric that can be used across and organisation from production to customer satisfaction. It also presents one with the opportunities to compare results year on year, benchmark against rival firms and set goals for business evolution. Generally speaking, a higher sigma represents fewer errors and higher customer satisfaction (Behara et al, 1994).

The facts are that in the business world it is results that count and in this respect Six Sigma has been very successful (Hammer & Goding, 2001)

REFERENCES

Asher, J.M., (1987), “Cost of Quality in Service Industries”, International Journal of Quality and Reliability Management, 5:5, pp38-46.

Bank, J., (2000), The Essence of Total Quality Management, FT/Prentice Hall, Harlow.

Basu, R. & Wright, J.N., (2003), Quality beyond Six Sigma, Butterworth-Heinemann, Oxford.

Behara, R.S., Gundersen, D.E., (2001), Analysis of Quality Management Practices in Services, International Journal of Quality and Reliability Management. 18:6, pp584-603.

Behara, R.S., Fontenot, G.F., Greysham, A., (1994), “Customer Satisfaction and analysis using six sigma”, International Journal of Quality and Reliability Management, 12:3, pp9-18.

Dale, B. G., (1999), Managing Quality, Blackwell Publishers, Oxford.

Deming, W.E., (1986), Out of the Crisis, Cambridge University Press, Cambridge.

Eckes, G., (2003) Six Sigma for Everyone, John Wiley & Sons, New Jersey.

George, M.L., (2003), Lean Six Sigma for Services, McGraw Hill, USA.

Ghobadian, A., Speller, S., Jones, M., “Service Quality- Concepts and Models”, International Journal of Quality and Reliability Management, 11:9, pp43-66.

Hammer, M., Goding, J., (2001), “Putting Six Sigma in Perspective”, Quality, 40:10, pp58.

Harry, M.J., Schroeder, R., (2000), Six Sigma: The Breakthrough Management Strategy Revolutionising the World’s Top Corporations, Doubleday, NY.

Heskett, J. l., Earlsasser, W., Hart, C.W.L., (1990), Service Breakthroughs: Changing the Rules of the Game, Macmillon Inc. USA.

Kooy, M.V., Edell, L, Melchiorre-Scheckner, H., (2002), “Use of Six Sigma to improve the Saftely and Efficacy of Acute Anticoagulation with Heparin”, Journal of Clinical Outcomes Management, 9:8, pp445-453.

Lagrasen, S., Lagrosen, Y., (2003) “Management of service quality- differences in values, practices and outcomes”, Managing Service Quality, 13:5, pp370-381.

Linderman, K., Schroeder, R. G., Zaheer, S., Choo, A.S., (2001), “Six Sigma: A Goal Theoretic Perspective”, Journal of Operations Management, 21:2, pp193-203.

McAdam, R., Canning, N. (2001), “ISO in the service sector: perceptions of small professional firms”, Managing Service Quality, 11:2, pp80-92.

Oakland, J.S. (1989), Total Quality Management, Heinemann Professional, Oxford.

Powell, T.C. (1995), “Total Quality Management as competitive advantage: a review and empirical study”, Strategic Management Journal, 16:1, pp15-37.

Reichheld, F., Sasser, W., (1990), “Zero Defections: Quality comes to services”. Harvard Business Review, Sept-Oct, pp105-11.

Robinson, L., (2003), “Committed to Quality: the use of quality schemes in UK public leisure services”, Managing Service Quality, 12:3, pp247-55.

Turner, J.R., (!999), The handbook of Project Based Management: Improving the process for achieving strategic objectives. 2nd Ed. McGraw Hill, London.

White, F.M., Locke, E. A., (1981), “Perceived Determinants of high and low productivity in three occupational groups: a critical incident study” Journal of Management Studies, 18, pp375-387.

Wood, M., (1994), “Statistical Methods for Monitoring Service Processes”, International Journal of Service Industry Management, 5:4, pp53-69.

Zeithaml, V.A., (1981),. “How Consumer evaluation processes differ between goods and Services” in Donnelly, J. and George, W. (Eds) Marketing of Services. American Marketing Association, Chicago, pp186-190.

 WEB PAGES

 Coffman, C. (2003), HumanSigma, Managing the human Difference. Gallup Management Journal.

Dusharme, D., “Survey: Six Sigma Packs a Punch”.

Erwin, J. (2001), “Flawless”, Quality World, Jan ed.

Erwin, J. (2000), “Achieving Total Customer Satisfaction through Six Sigma”, Quality Digest.

 Smith, K., “Six Sigma for the service sector”



By: steve jones

About the Author:

ffinity Diagram – A technique for organizing individual pieces of information into groups or broader categories.

ANOVA – Analysis of Variance – A statistical test for identifying significant differences between process or system treatments or conditions. It is done by comparing the variances around the means of the conditions being compared.

Attribute Data – Data which on one of a set of discrete values such as pass or fail, yes or no.

Average – Also called the mean, it is the arithmetic average of all of the sample values. It is calculated by adding all of the sample values together and dividing by the number of elements (n) in the sample.

Bar Chart – A graphical method which depicts how data fall into different categories.

Black Belt – An individual who receives approximately four weeks training in DMAIC, analytical problem solving, and change management methods. A Black Belt is a full time six sigma team leader solving problems under the direction of a Champion.

Breakthrough Improvement – A rate of improvement at or near 70% over baseline performance of the as-is process characteristic.

Capability - A comparison of the required operation width of a process or system to its actual performance width. Expressed as a percentage (yield), a defect rate (dpm, dpmo,), an index (Cp, Cpk, Pp, Ppk), or as a sigma score (Z).

Cause and Effect Diagram – Fishbone Diagram – A pictorial diagram in the shape of a fishbone showing all possible variables that could affect a given process output measure.

Central Tendency - A measure of the point about which a group of values is clustered; two measures of central tendency are the mean, and the median.

Champion -A Champion recognizes, defines, assigns and supports the successful completion of six sigma projects; they are accountable for the results of the project and the business roadmap to achieve six sigma within their span of control.

Characteristic – A process input or output which can be measured and monitored.

Common Causes of Variation – Those sources of variability in a process which are truly random, i.e., inherent in the process itself.

Complexity -The level of difficulty to build, solve or understand something based on the number of inputs, interactions and uncertainty involved.

Control Chart – The most powerful tool of statistical process control. It consists of a run chart, together with statistically determined upper and lower control limits and a centerline.

Control Limits – Upper and lower bounds in a control chart that are determined by the process itself. They can be used to detect special or common causes of variation. They are usually set at ±3 standard deviations from the central tendency.





Correlation Coefficient - A measure of the linear relationship between two variables.





Cost of Poor Quality (COPQ) – The costs associated with any activity that is not doing the right thing right the first time. It is the financial qualification any waste that is not integral to the product or service.

CP – A capability measure defined as the ratio of the specification width to short-term process performance width.

CPk. - An adjusted short-term capability index that reduces the capability score in proportion to the offset of the process center from the specification target.

Critical to Quality (CTQ) – Any characteristic that is critical to the perceived quality of the product, process or system. See Significant Y.

Critical X – An input to a process or system that exerts a significant influence on any one or all of the key outputs of a process.

Customer – Anyone who uses or consumes a product or service, whether internal or external to the providing organization or provider.





Cycle Time – The total amount of elapsed time expended from the time a task, product or service is started until it is completed.

Defect - An output of a process that does not meet a defined specification, requirement or desire such as time, length, color, finish, quantity, temperature etc.

Defective – A unit of product or service that contains at least one defect.

Deployment (Six Sigma) – The planning, launch, training and implementation management of a six sigma initiative within a company.

Design of Experiments (DOE) – Generally, it is the discipline of using an efficient, structured, and proven approach to interrogating a process or system for the purpose of maximizing the gain in process or system knowledge.





Design for Six Sigma (DFSS) – The use of six sigma thinking, tools and methods applied to the design of products and services to improve the initial release performance, ongoing reliability, and life-cycle cost.

DMAIC - The acronym for core phases of the six sigma methodology used to solve process and business problems through data and analytical methods. See define, measure, analyze, improve and control.

DPMO – Defects per million opportunities – The total number of defects observed divided by the total number of opportunities, expressed in parts per million. Sometimes called Defects per Million (DPM).

DPU – Defects per unit – The total number of defects detected in some number of units divided by the total number of those units.

Entitlement - The best demonstrated performance for an existing configuration of a process or system. It is an empirical demonstration of what level of improvement can potentially be reached.

Epsilon S – Greek symbol used to represent residual error.

Experimental Design – See Design of Experiments.

Failure Mode and Effects Analysis (FMEA) – A procedure used to identify, assess, and mitigate risks associated with potential product, system, or process failure modes.

Finance Representative – An individual who provides an independent evaluation of a six sigma project in terms of hard and/or soft savings. They are a project support resource to both Champions and Project Leaders.

Fishbone Diagram – See cause and effect diagram.

Flowchart - A graphic model of the flow of activities, material, and/or information that occurs during a process.

Gage R&R - Quantitative assessment of how much variation (repeatability and reproducibility) is in a measurement system compared to the total variation of the process or system.

Green Belt – An individual who receives approximately two weeks of training in DMAIC, analytical problem solving, and change management methods. A Green Belt is a part time six sigma position that applies six sigma to their local area, doing smaller-scoped projects and providing support to Black Belt projects.





Hidden Factory or Operation – Corrective and non-value-added work required to produce a unit of output that is generally not recognized as an unnecessary generator of waste in form of resources, materials and cost.

Histogram - A bar chart that depicts the frequencies (by the height of the plotted bars) of numerical or measurement categories.

Implementation Team – A cross-functional executive team representing various areas of the company . Its charter is to drive the implementation of six sigma by defining and documenting practices, methods and operating policies.

Input - A resource consumed, utilized, or added to a process or system. Synonymous with X, characteristic, and input variable.

Input-Process-Output (IPO) Diagram – A visual representation of a process or system where inputs are represented by input arrows to a box (representing the process or system) and outputs are shown using arrows emanating out of the box.

lshikawa Diagram – See cause and effect diagram and fishbone diagram.

Least Squares – A method of curve-fitting that defines the best fit as the one that minimizes the sum of the squared deviations of the data points from the fitted curve.

Long-term Variation – The observed variation of an input or output characteristic which has had the opportunity to experience the majority of the variation effects that influence it.

Lower Control Limit (LCL) -  for control charts: the limit above which the subgroup statistics must remain for the process to be in control. Typically, 3 standard deviations below the central tendency.





Lower Specification Limit (LSL) – The lowest value of a characteristic which is acceptable.





Master Black Belt – An individual who has received training beyond a Black Belt. The technical, go-to expert regarding technical and project issues in six sigma. Master Black Belts teach and mentor other six sigma Belts, their projects and support Champions.

Mean – See average.





Measurement – The act of obtaining knowledge about an event or characteristic through measured quantification or assignment to categories.





Measurement Accuracy – For a repeated measurement, it is a comparison of the average of the measurements compare to some known standard.

Measurement Precision – For a repeated measurement, it is the amount of variation that exists in the measured values.

Measurement Systems Analysis (MSA) – An assessment of the accuracy and precision of a method of obtaining measurements. See also Gage R&R.

Median – The middle value of a data set when the values are arranged in either ascending or descending order.





Metric – A  measure that is considered to be a key indicator of performance. It should be linked to goals or objectives and carefully monitored.

Natural Tolerances of a Process – See Control Limits.

Nominal Group Technique – A structured method that a team can use to generate and rank a list of ideas or items.





Non-Value Added (NVA) – Any activity performed in producing a product or delivering a service that does not add value, where value is defined as changing the form, fit or function of the product or service and is something for which the customer is willing to pay.

Normal Distribution – The distribution characterized by the smooth, bell- shaped curve. Synonymous with Gaussian Distribution.





Objective Statement – A succinct statement of the goals, timing and expectations of a six sigma improvement project.

Opportunities – The number of characteristics, parameters or features of a product or service that can be classified as acceptable or unacceptable.

Out of Control – A process is said to be out of control if it exhibits variations larger than its control limits or shows a pattern of variation.

Output – A resource or item or characteristic that is the product of a process or system. See also Y, CTQ.





Pareto Chart – A bar chart for attribute (or categorical) data categories are presented in descending order of frequency.





Pareto Principle – The general principle originally proposed by Vilfredo Pareto (1848-1923) that the majority of influence on an outcome is exerted by a minority of input factors.

Poka-Yoke - A translation of a Japanese term meaning to mistake-proof.

Probability – The likelihood of an event or circumstance occurring.

Problem Statement – A succinct statement of a business situation which is used to bound and describe the problem the six sigma project is attempting to solve.





Process - A set of activities and material and/or information flow which transforms a set of inputs into outputs for the purpose of producing a product, providing a service or performing a task.





Process Characterization – The act of thoroughly understanding a process, including the specific relationship(s) between its outputs and the inputs, and its performance and capability.





Process Certification – Establishing documented evidence that a process will consistently produce required outcome or meet required specifications.

Process Flow Diagram – See flowchart.

Process Member – A individual who performs activities within a process to deliver a process output, a product or a service to a customer.

Process Owner – Process Owners have responsibility for process performance and resources. They provide support, resources and functional expertise to six sigma projects. They are accountable for implementing developed six sigma solutions into their process.

Quality Function Deployment (QFD) – A systematic process used to integrate customer requirements into every aspect of the design and delivery of products and services.





Range - A measure of the variability in a data set. It is the difference between the largest and smallest values in a data set.





Regression Analysis - A statistical technique for determining the mathematical relation between a measured quantity and the variables it depends on. Includes Simple and Multiple Linear Regression.

Repeatability (of a Measurement) – The extent to which repeated measurements of a particular object with a particular instrument produce the same value. See also Gage R&R.





Reproducibility (of a Measurement) – The extent to which repeated measurements of a particular object with a particular individual produce the same value. See also Gage R&R.

Rework - Activity required to correct defects produced by a process.

Risk Priority Number (RPN) – In Failure Mode Effects Analysis — the aggregate score of a failure mode including its severity, frequency of occurrence, and ability to be detected.

Rolled Throughput Yield (RTY) – The probability of a unit going through all process steps or system characteristics with zero defects.

 

R.U.M.B.A. - An acronym used to describe a method to determine the validity of customer requirements. It stands for Reasonable, Understandable, Measurable, Believable, and Achievable.

Run Chart – A basic graphical tool that charts a characteristic’s performance over time.

Scatter Plot – A chart in which one variable is plotted against another to determine the relationship, if any, between the two.

Screening Experiment - A type of experiment to identify the subset of significant factors from among a large group of potential factors.





Short Term Variation – The amount of variation observed in a characteristic which has not had the opportunity to experience all the sources of variation from the inputs acting on it.

Sigma Score (Z) – A commonly used measure of process capability that represents the number of short-term standard deviations between the center of a process and the closest specification limit. Sometimes referred to as sigma level, or simply Sigma.

Significant Y – An output of a process that exerts a significant influence on the success of the process or the customer.

Six Sigma Leader – An individual that leads the implementation of Six Sigma, coordinating all of the necessary activities, assures optimal results are obtained and keeps everyone informed of progress made.

Six Sigma Project - A well defined effort that states a business problem in quantifiable terms and with known improvement expectations.

Six Sigma (System) – A proven set of analytical tools, project management techniques, reporting methods and management techniques combined to form a powerful problem solving and business improvement methodology.

Special Cause Variation – Those non-random causes of variation that can be detected by the use of control charts and good process documentation.

Specification Limits – The bounds of acceptable performance for a characteristic.





Stability (of a Process) – A process is said to be stable if it shows no recognizable pattern of change and no special causes of variation are present.





Standard Deviation – One of the most common measures of variability in a data set or in a population. It is the square root of the variance.





Statistical Problem – A problem that is addressed with facts and data analysis methods.

Statistical Process Control (SPC) – The use of basic graphical and statistical methods for measuring, analyzing, and controlling the variation of a process for the purpose of continuously improving the process. A process is said to be in a state of statistical control when it exhibits only random variation.

Statistical Solution – A data driven solution with known confidence/risk levels,  as opposed to a qualitative, “I think” solution.

Supplier – An individual or entity responsible for providing an input to a process in the form of resources or information.

Trend - A gradual, systematic change over time or some other variable.

TSSW – Thinking the six sigma way – A mental model for improvement which perceives outcomes through a cause and effect relationship combined with six sigma concepts to solve everyday and business problems.

Two-Level Design – An experiment where all factors are set at one of two levels, denoted as low and high (-1 and + 1).





Upper Control Limit (UCL) for Control Charts – The upper limit below which a process statistic must remain to be in control. Typically this value is 3 standard deviations above the central tendency.





Upper Specification Limit (USL) – The highest value of a characteristic which is acceptable.





Variability – A generic term that refers to the property of a characteristic, process or system to take on different values when it is repeated.





Variables – Quantities which are subject to change or variability.





Variable Data – Data which is continuous, which can be meaningfully subdivided, i.e. can have decimal subdivisions.

Variance – A specifically defined mathematical measure of variability in a data set or population. It is the square of the standard deviation.

Variation – See variability.

VOB – Voice of the business – Represents the needs of the business and the key stakeholders of the business. It is usually items such as profitability, revenue, growth, market share, etc.

VOC – Voice of the customer – Represents the expressed and non-expressed needs, wants and desires of the recipient of a process output, a product or a service. Its is usually expressed as specifications, requirements or expectations.

VOP – Voice of the process – Represents the performance and capability of a process to achieve both business and customer needs. It is usually expressed in some form of an efficiency and/or effectiveness metric.

Waste – Waste represents material, effort and time that does not add value in the eyes of key stakeholders (Customers, Employees, Investors).

X – An input characteristic to a process or system. In six sigma it is usually used in the expression of Y=f(X), where the output (Y) is a function of the inputs (X).

Y – An output characteristic of a process. In six sigma it is usually used in the expression of Y=f(X), where the output (Y) is a function of the inputs (X).





Yellow Belt - An individual who receives approximately one week of training in problem solving and process optimization methods. Yellow Belts participate in Process Management activates, participate on Green and Black Belt projects and apply concepts to their work area and their job.

Z Score – See Sigma Score.

 



By: Rizalito Garcia

About the Author:

Six Sigma is a program that deals with quality management and is designed to achieve an outstanding level of quality for products. Motorola was the first company to pioneer this process in the mid-eighties and since then it has been adopted by many other companies and manufacturers. Service companies, in order to enhance customer service and relations also utilize these strategies. 6 Sigma has evolved from a normal distribution curve where failures in quality and customer satisfaction arise after the sixth sigma of likelihood. Hence, the main idea is to reduce or lessen the defects per product or customer service.

Companies that make use of Six Sigma have proved the critics wrong by achieving the 6 levels of quality that were believed to be an impossible achievement. Going beyond Six Sigma is not been unheard of and has been achieved by many companies like GE Aircraft Engines that function at nine sigma levels of quality. It is highly convenient, as it reduces the amount of failures or errors in product quality and customer service. Not only does this help in increasing customer satisfaction and revenue but it also leads to an increase in the number of returning customers and the acquirement of new customers. Companies that employ this process successfully have higher quality standards and produce superior products and services.

Importance Of 6 Sigma

A fairly unknown fact about Six Sigma is that it relates to 3.4 defects per million. Most people do not know how quality is improved considerably by having 6 levels of sigma. Previously, most companies utilized less sigma, approximately three or four, but Motorola was the first company to use six levels of sigma. Four-sigma relates to only about 2.6 defects per thousand whereas 6 Sigma relates to 3.4 defects per million making it a perfect number. However, deviation proves to be a major problem. With Six Sigma, the defective rates are more sensible than with four-sigma.

Large and very profitable companies have also been using 6 Sigma as a tool to help their businesses run better. Since it’s commencement, it has helped many companies save millions of dollars. Six Sigma can help any type of business and the concepts can be applied to any department of that business. Marketing, sales, production, design, administration and service are all the various departments in which 6 Sigma has been successfully used. Six Sigma uses business, statistic and engineering principles to help eliminate company defects. A 6 Sigma consultant or master can be hired to help the company adjust to the changes. Not only does Six Sigma improve quality, it also improves performance and delivery.

Conclusion

In a business, quality is valued above all other things by customers. Businesses that produce high quality goods and services will always attract more customers and will ensure that these customers return for more. 6 Sigma helps ensure that the quality of these products and services is nothing but the best. Six Sigma is very effective, when implemented correctly and this is the main reason why most companies utilize 6 Sigma. This process that was discovered more than 20 years ago has withstood all criticism and has proven it’s lasting qualities in the business world. Companies should consider using Six Sigma as a means of gaining and retaining customers by producing superior quality products.



By: Tony Jacowski

About the Author:

What is Six Sigma?

The concepts surrounding the drive to Six Sigma quality are essentially those of statistics and probability. In simple language, these concepts boil down to, “How confident can I be that what I planned to happen actually will happen?” Basically, the concept of Six Sigma deals with measuring and improving how close we come to delivering on what we planned to do.

Anything we do varies, even if only slightly, from the plan. Since no result can exactly match our intention, we usually think in terms of ranges of acceptability for whatever we plan to do. Those ranges of acceptability (or tolerance limits) respond to the intended use of the product of our labors–the needs and expectations of the customer.

Here’s an example. Consider how your tolerance limits might be structured to respond to customer expectations in these two instructions:

“Cut two medium potatoes into quarter-inch cubes.” and “Drill and tap two quarter-inch holes in carbon steel brackets.”

What would be your range of acceptability–or tolerances–for the value quarter-inch? (Hint: a 5/16” potato cube probably would be acceptable; a 5/16”threaded hole probably would not.)Another consideration in your manufacture of potato cubes and holes would be the inherent capability of the way you produce the quarter inch dimension–the capability of the process. Are you hand-slicing potatoes with a knife or are you using a special slicer with preset blades?

Are you drilling holes with a portable drill or are you using a drill press? If we measured enough completed potato cubes and holes, the capabilities of the various processes would speak to us. Their language would be distribution curves.

Distribution curves tell us not only how well our processes have done; they also tell us the probability of what our process will do next. Statisticians group those probabilities in segments of the distribution curve called standard deviations from the mean. The symbol they use for standard deviation is the lower-case Greek letter sigma.

For any process with a standard distribution (something that looks like a bell-shaped curve), the probability is 68.26% that the next value will be within one standard deviation from the mean. The probability is 95.44% that the same next value will fall within two standard deviations. The probability is 99.73% that it will be within three sigma; and 99.994% that it will be within four sigma.

If the range of acceptability, or tolerance limit, for your product is at or outside the four sigma point on the distribution curve for your process, you are virtually assured of producing acceptable material every time–provided, of course, that your process is centered and stays centered on your target value.

Unfortunately, even if you can center your process once, it will tend to drift. Experimental data show that most processes that are in control still drift about 1.5 sigma on either side of their center point over time.

This means that the real probability of a process with tolerance limits at four sigma, producing acceptable material is actually more like 98.76%, not 99.994%.

To reach near-perfect process output, the process capability curve must fit inside the tolerances such that the tolerances are at or beyond six standard deviations, or Six Sigma, on the distribution curve. That is why we call our goal Six Sigma quality.

Quality makes us strong

In the past, conventional wisdom said that high levels of quality cost more in the long run than poorer quality, raising the price you had to ask for your product and making you less competitive. Balancing quality with cost was thought to be the key to economic survival. The surprising discovery of companies which initially developed Six Sigma, or world-class, quality is that the best quality does not cost more. It actually costs less. The reason for this is something called cost-of-quality. Cost-of-quality is actually the cost of deviating from quality–paying for things like rework, scrap and warranty claims. Making things right the first time–even if it takes more effort to get to that level of performance–actually costs much less than creating then finding and fixing defects.

Shooting for Six Sigma:

An illustrative fable

The underlying logic of Six Sigma quality involves some understanding of the role of statistical variation. Here’s a story about that. Robin Hood is out in the meadow practicing for the archery contest to be held next week at the castle. After Robin’s first 100 shots, Friar Tuck, Robin’s Master Black Belt in archery, adds up the number of hits in the bull’s eye of each target. He finds that Robin hit within the bull’s eye 68% of the time.

Friar Tuck plots the results of Robin’s target practice on a chart called a histogram. The results look something like this. “Note that the bars in the chart form a curve that looks something like a bell,” says the friar. “This is a standard distribution curve. Every process that varies uniformly around a center point will form a plot that looks like a smooth bell curve, if you make a large enough number of trials or, in this case, shoot enough arrows.”

Robin scratches his head. Friar Tuck explains that Robin’s process involves selecting straight arrows (raw material); holding the bow steady and smoothly releasing the bowstring (the human factor); the wood of the bow and the strength of the string (machinery); and the technique of aiming to center the process on the bull’s eye (calibration and statistical process control).

The product of Robin’s process is an arrow in a target. More specifically, products that satisfy the customer are arrows that score. Arrows outside the third circle on these targets don’t count, so they are defects. Robin’s process appears to be 100% within specification. In other words, every product produced is acceptable in the eyes of the customer.

“You appear to be a three- to four-sigma archer,” the friar continues. “We’d have to measure a lot more holes to know for sure, but let’s assume that 99.99% of your shots score, that you’re a four sigma shooter.” Robin strides off to tell his merry men.

The next day, the wind is constantly changing directions; there is a light mist. Robin thinks he feels a cold coming on. Whatever the reason, his process doesn’t stay centered on the mean the way it did before. In fact, it drifts unpredictably as much as 1.5 sigma either side of the mean. Now, instead of producing no defects, after a hundred shots, Robin has produced a defect, a hole outside the third circle. In fact, instead of 99.99% of his shot scoring only 99.38% do.

While this may not seem as if much has changed, imagine that, instead of shooting at targets, Robin was laser-drilling holes in turbine blades. Let’s say there were 100 holes in each blade. The probability of producing even one defect-free blade would not be good. (Because the creation of defects would be random, his process would produce some good blades as well as some blades with multiple defects.)

Without inspecting everything many times over (not to mention spending an enormous amount for rework and rejected material), Robin, the laser driller, would find it virtually impossible to ever deliver even one set of turbine blades with properly drilled holes.

Not only would the four-sigma producer have to spend much time and money finding and fixing defects before products could be shipped, but since inspection cannot find all the defects, she would also have to fix problems after they got to

the customer. The Six Sigma producer, on the other hand, would be able to concentrate on only a handful of defects to further improve the process.

How can the tools of Six Sigma quality help? If Robin the archer were to use those tools to become a Six Sigma sharpshooter instead of a four-sigma marksman, when he went out into the wind and rain, he would still make every

shot score. Some arrows might now be in the second circle, but they would all still be acceptable to the customer, guaranteeing first prize at the contest. Robin the laser driller would also succeed; he would be making virtually defect free turbine blades.

The steps on the path to Six Sigma quality:

1. Measurement

Six Sigma quality means attaining a businesswide standard of making fewer than 3.4 mistakes per million opportunities to make a mistake.

This quality standard includes design, manufacturing, marketing, administration, service, support–all facets of the business. Everyone has the same quality goal and essentially the same method to reach it. While the application to engine design and manufacturing is obvious, the goal of Six Sigma performance–and most of the same tools–also apply to the softer, more administrative processes as well.

After the improvement project has been clearly defined and bounded, the first element in the process of quality improvement is the measurement of performance. Effective measurement demands taking a statistical view of all processes and all problems. This reliance on data and logic is crucial to the pursuit of Six Sigma quality.

The next step is, knowing what to measure. The determination of sigma level is essentially based on counting defects, so we must measure the frequency of defects. Mistakes or defects in a manufacturing process tend to be relatively easy to define–simply a failure to meet a specification. To broaden the application to other processes and to further improve manufacturing, a new definition is helpful: a defect is any failure to meet a customer satisfaction requirement, and the customer is always the next person in the process.

In this beginning phase, you would select the critical-to-quality characteristics you plan to improve. These would be based on an analysis of your customer’s requirements–(usually using a tool like Quality Function Deployment.) After you clearly define your performance standards and validate your measurement system (with gage reliability and repeatability studies), you would then be able to determine short-term and long-term process capability and actual process performance (Cp and Cpk).

2. Analysis

The second step is to define performance objectives and identify the sources of process variation. As a business, we have set Six Sigma performance of all processes within five years as our objective. This must be translated into specific objectives in each operation and process. To identify sources of variation, after counting the defects we must determine when, where and how they occur. Many tools can be used to identify the causes of the variation that creates defects.

These include tools that many people have seen before (process mapping, Pareto charts, fishbone diagrams, histograms, scatter diagrams, run charts) and some that may be new (affinity diagrams, box-and-whisker diagrams, multivariate analysis, hypothesis testing).

3. Improvement

This phase involves screening for potential causes of variation and discovering interrelationships between them. (The tool commonly used in this phase is Design of Experiment or DOE.) Understanding these complex interrelationships, then allows the setting of individual process tolerances that interact to produce the desired result.

4. Control

In the Control Phase, the process of validating the measurement system and evaluating capability is repeated to insure that improvement occurred. Steps are then taken to control the improved processes. (Some examples of tools used in this phase are statistical process control, mistake proofing and internal quality audits.)

Words of Wisdom about Quality

If you believe it is natural to have defects, and that quality consists of finding defects and fixing them before they get to the customer, you are just waiting to go out of business. To improve speed and quality, you must first measure it–and you must use a common measure.

The common business-wide measures that drive our quality improvement are defects per unit of work and cycle time per unit of work. These measures apply equally to design, production, marketing, service, support and administration.

Everyone is responsible for producing quality; therefore, everyone must be measured and accountable for quality. Measuring quality within an organization and pursuing an aggressive rate of improvement is the responsibility of operational management.

Customers want on-time delivery, a product that works immediately, no early life failures and a product that is reliable over its lifetime. If the process makes defects, the customer cannot easily be saved from them by inspection and testing.

A robust design (one that is well within the capabilities of existing processes to produce it) is the key to increasing customer satisfaction and reducing cost. The way to a robust design is through concurrent engineering and integrated design processes.

Because higher quality ultimately reduces costs, the highest quality producer is most able to be the lowest cost producer and, therefore, the most effective competitor in the marketplace.



By: Steven Bonacorsi

About the Author: