Monday 17 November 2008

Implementing Six Sigma for Software

In our experience with implementing Six Sigma for software we found the following three principles most useful:
Principle No 1: Measure customer related metrics only
- Use Combinatory Metrics to cover all topics
Principle No 2: Adjust to moving targets
- Your goals may need change; accept change and manage it accordingly
Principle No 3: Enforce measurement
- Do not enforce meeting targets

The last principle is the most difficult one, because this is against the project manager’s carnet of duties.Indeed, this is what most often goes wrong in software projects: People want to enforce targets and consequently miss the goals. This is because setting targets that really lead to the goal is so difficult in software projects.
Just consider the ever-lurking dilemma: Should we make the milestones, or do it right the first time such that we can later use the knowledge gained to proceed faster? Writing or implementing software is not just an engineering discipline but in essence it is knowledge transfer.

Does Six Sigma work for software?

Nevertheless, there were only occasionally attempts to implement Six Sigma for software.Applying Six Sigma to software development makes product development and otherprojects transparent to both management and customers. However, transparency requires animportant cultural change.

We know from experience that bad communication is a major reason why projects fail, and software projects in particular. We expect from better transparency that meeting both deadlines and customer requirements becomes easier.

The major problem with early Six Sigma attempts was that there was no connection of
software metrics to economic success.Counting mistakes and defects is not a clear indication if the software project is going tobe successfulOther metrics like time-to-market and user friendliness are muchmore important in many application areas. Sometimes, reliability is of essence, but notalways.

There is no software metrics that serves all. It depends what kind of software we are
developing or installing.Finding good metrics for software development or deployment is a major task in itself.

Why do we need Six Sigma For Software?

Software today is responsible for most of the added value in products, and must be blamed for many of its failures. Even if the iron hook breaks, it may be the software embedded in the measurement instrument to blame for not having detected it in time. When in Germany the high speed intercity express train crashed into an overpass, it was software that didn’t detect
the broken wheel ring well before the accident.

Mobile networks are suffering from not being able to provide interconnection to the Internet and interoperability between their own services. It is the software that fails.In e-Commerce and for making Web Services to work, security, reliability and fault tolerance are of essence. Software and business processes are not cooperating, as they should to make it profitable.

Software is so ubiquitous that we must solve the software development problem to address a lot of other problems the society has.

The Six Sigma approach is:
Set the goal – Define
Define the metrics – Measure
Measure where you go – Analyse
Improve your processes while you go – Improve
Act immediately if going the wrong path – Control


We talk about “software development”, however we not only intend writing new software, but also software integration, deployment, and maintenance, as long as it has the character of a project. This means that there is a goal that can be reached or missed. Using Six Sigma, we want to measure how much we are going to miss that goal.

Thursday 6 November 2008

Six Sigma Tools

Variety of tools can be used to drive quality improvements within the DMAIC model. Many of these tools have been incorporated into Six Sigma software so that the computer carries out the underlying calculations.

Most can be classified into two categories:
a) Process optimization tools - which enable teams to design more efficient workflows,
b) Statistical analysis tools - which enable teams to analyze data more effectively.

Some of the most important tools:

1) Quality Function Deployment (QFD): The QFD is used to understand customer requirements. The "deployment" part comes from the fact that quality engineers used to be deployed to customer locations to fully understand a customer's needs. Today, a physical deployment might not take place, but the idea behind the tool is still valid. Basically, the QFD identifies customer requirements and rates them on a numerical scale, with higher numbers corresponding to pressing "must-haves" and lower numbers to "nice-to-haves." Then, various design options are listed and rated on their ability to address the customer's needs. Each design option earns a score, and those with high scores become the preferred solutions to pursue.

2) Fishbone Diagrams: In Six Sigma, all outcomes are the result of specific inputs. This cause-and-effect relationship can be clarified using either a fishbone diagram or a cause-and-effect matrix (see below). The fishbone diagram helps identify which input variables should be studied further. The finished diagram looks like a fish skeleton, which is how it earned its name. To create a fishbone diagram, you start with the problem of interest -- the head of the fish. Then you draw in the spine and, coming off the spine, six bones on which to list input variables that affect the problem. Each bone is reserved for a specific category of input variable, as shown below. After listing all input variables in their respective categories, a team of experts analyzes the diagram and identifies two or three input variables that are likely to be the source of the problem.


3) Cause-and-Effect (C&E) Matrix: The C&E matrix is an extension of the fishbone diagram. It helps Six Sigma teams identify, explore and graphically display all the possible causes related to a problem and search for the root cause. The C&E Matrix is typically used in the Measure phase of the DMAIC methodology.
­Failure Modes and Effects Analysis (FMEA): FMEA combats Murphy's Law by identifying ways a new product, process or service might fail. FMEA isn't worried just about issues with the Six Sigma project itself, but with other activities and processes that are related to the project. It's similar to the QFD in how it is set up. First, a list of possible failure scenarios is listed and rated by importance. Then a list of solutions is presented and ranked by how well they address the concerns. This generates scores that enable the team to prioritize things that could go wrong and develop preventative measures targeted at the failure scenarios.

4) T-Test: In Six­ Sigma, you need to be able to establish a confidence level about your measurements. Generally, a larger sample size is desirable when running any test, but sometimes it's not possible. The T-Test helps Six Sigma teams validate test results using sample sizes that range from two to 30 data points.
Control Charts: Statistical process control, or SPC, relies on statistical techniques to monitor and control the variation in processes. The control chart is the primary tool of SPC. Six Sigma teams use control charts to plot the performance of a process on one axis versus time on the other axis. The result is a visual representation of the process with three key components: a center line, an upper control limit and a lower control limit. Control charts are used to monitor variation in a process and determine if the variation falls within normal limits or is variation resulting from a problem or fundamental change in the process.

5) Design of Experiments: When a process is optimized, all inputs are set to deliver the best and most stable output. The trick, of course, is determining what those input settings should be. A design of experiments, or DOE, can help identify the optimum input settings. Performing a DOE can be time-consuming, but the payoffs can be significant. The biggest reward is the insight gained into the process.

WHAT WILL SIX SIGMA LOOK LIKE IN FUTURE

Six Sigma is a disciplined data-oriented approach to quality improvement that will survive and flourish. However, as it continues to evolve, some of its concepts—such as 3.4 defects per million opportunities—will be modified. Other characteristics of Six Sigma, such as its hierarchal organizational structure, will be adapted to changes in the environment. We will also continue to benefit from lessons learned1. Overall, Six Sigma will cast a continuingly broader net, but, will likely, be less in the headlines.

Key Concepts that Will Survive and Flourish

Six Sigma calls for a disciplined customer-focused approach to quality improvement, resting on the principle “In God we trust, all else bring data.” These basic concepts will be as important in the future as they are today. Here’s why.

Global competition and customer demands will continue to call for continuous quality improvement, coupled with cost reduction. Thus the pressures that lead to Six Sigma in the first place are unlikely to abate, and may even increase.

A disciplined and proactive approach to quality improvement that puts the customer first continues to make great sense and helps ensure that we move forward in an organized manner. The specific approach may vary from one situation to the next. DMAIC (define, measure, analyze, improve, control) was appropriate for the typical manufacturing applications for which Six Sigma was originally proposed. DMADOV (define, measure, analyze, design, optimize and verify) was subsequently proposed for Design for Six Sigma. Other approaches may be appropriate for other application areas. Necip Doganaksoy and I have, for example, recently proposed DEUPM (define, evaluate, understand, plan and monitor) as a disciplined approach for data acquisition2.

The need to base decisions on data, rather than on hunches, has always been there. What has changed in recent years—and has helped make Six Sigma a reality—is our ability to collect, harness and rapidly bring to bear such data in the decision-making process. We, no longer, need to rely on statisticians to do the work. Instead, Six Sigma practitioners are empowered to proceed on their own—calling on statisticians for guidance on the more complex issues. This trend is likely to accelerate. As technology continues to develop, so will our capabilities to use data to make the right decisions to improve quality. We can expect, for example, greater emphasis on the all-important task of getting the right data and more focus on meaningful and simple ways of presenting results graphically.

A Concept that May be Modified: The Goal of 3.4 Defects per Million Opportunities

Six Sigma has been presented as a drive to achieve “no more than 3.4 defects per million opportunities.” That, of course, is the basis for the terminology (with a little juggling to take into account the claimed mean shift of 1.5 sigma in moving from short-term to long-term variability). As quality practitioners become savvier, they recognize that this objective has its limitations.

As Deming pointed out repeatedly3, setting numerical goals can often lead to a search for ways to manipulate the measurement process, rather than improve the system. This is especially so when one is dealing with often vaguely defined terms, such as “defects” and “opportunities.” There is, indeed, frequently much subjectivity in deciding exactly what is a defect and, even more so, an opportunity.

All products, moreover, are not created equal. There are many more defect opportunities for a jet engine than for, say, a toaster. But, yet, the need for high reliability for a jet engine is generally greater. For a toaster, aiming for 3.4 defects per million opportunities might be overkill, or just too expensive. This level, on the other hand, may be fully appropriate for a jet engine.

Despite Deming’s warnings, we will continue to need numerical goals. But these will be tailored to the product at hand and closely tied to customer needs. For example, for a telephone-servicing center, a clear goal might be that of keeping the time that a customer has to wait for service to less than one minute 95% of the time and to less than three minutes 99% of the time.

The prediction that we will move away from the concept of 3.4 defects per million opportunities defies classical Six Sigma thinking and is, surely, controversial. I welcome other viewpoints.

Simplification of the Hierarchal Structure

Six Sigma came with a formal organizational structure of champions, master black belts, black belts, and green belts—each with designated responsibilities. As Six Sigma approaches its goal of becoming “the way we work,” this formal structure will be modified. Thus, as the value of Six Sigma is recognized universally, all managers will, ideally, be Six Sigma advocates, reducing the need for special champions. Master black belts will continue to serve as trainers, hands-on advocates and gurus—but their role may be merged with that of black belts. Also, master black belt status will increasingly be a stepping-stone to management. As Six Sigma training becomes commonplace both within companies and in universities, all professional employees will be green belts (even if not always identified as such). This, in fact, has been the situation in GE for some time. The Six Sigma organizational structure, like other parts of the organization, will, in addition, not be immune from cost-cutting pressures.

Casting a Continuingly Broader Net

Six Sigma will be enriched by the continued emergence of useful tools, such as simulation, that may not have been part of the original toolkit, but whose value has been demonstrated. It will also gain from integration with other approaches, such as lean thinking.

The areas of application for Six Sigma will continue to multiply. Early uses of Six Sigma tended to be mainly in product manufacturing. This provided relatively speedy and easy-to-quantify paybacks. It was soon recognized, however, that only so much can be achieved in manufacturing, and that product performance and reliability are principally determined at product design. This led to Design for Six Sigma and Design for Reliability. Next, Six Sigma was applied to business processes and customer service. As we move away from manufacturing applications, our ability to quantify the benefits of Six Sigma becomes more complicated. It is harder to measure the impact of avoiding a field failure or of having a delighted customer, than, say, that of a 90% reduction in scrap. This trend will continue as we seek new applications. We need to recognize and address the associated challenges.
Most of the applications of Six Sigma to date have been in large companies. In the future, Six Sigma will be adapted for use in small business with limited resources. Also, we are beginning to witness its application in areas other than manufacturing businesses, especially in the medical arena. Similar opportunities exist and will be leveraged in future years in such diverse fields as banking, schools, and government.
Key things done by MBB(Master Black Belt) in six sigma:

1. Provide a strategic vision for improvement and work towards its fulfillment.
2. Secure continuing commitment and resources from business leaders.
3. Develop and organize targeted training of the work force in Six Sigma, and participate in providing this training.
4. Help select and certify black belts to be Six Sigma project leaders.
5. Identify Six Sigma projects, establish the teams, help ensure their success and quantify their impact.
6. Serve as a technical and tactical resource to all in implementing Six Sigma.
7. Be untiring Six Sigma advocates and establish and maintain a Six Sigma environment.
8. Be role models for Six Sigma in all undertakings.

To meet these challenges, MBB’s must have some unique personal traits.

These include a quick and agile mind; unflinching drive, enthusiasm and commitment; a good understanding of the business and its goals; strong technical--and quick learning--abilities; a flexible, yet visionary, mindset; uncompromising integrity; and outstanding leadership, communications and diplomatic skills. Not a small order!

Issues faced by MBB's -

First, there is a need to achieve the right level of involvement. MBB’s are held responsible for the success of the Six Sigma effort, in general, and of specific Six Sigma projects, in particular. Their greatest impact is in selecting the “right projects” initially, and in establishing effective project teams. The right projects are ones that have high potential impact, and stand a reasonable chance of success. Selection of the project team starts with finding an effective black belt to lead the project. Then, in collaboration with the black belt, the MBB helps identify a project team that is up to the task, and has the authority to proceed. Once the project is underway, MBBs take a “behind the scenes” role, letting the team do its job. If everything goes right, there is little left to do other than provide encouragement and ensure that the team gets the recognition it deserves. However, things do not always go right. The MBB needs to be sufficiently savvy and on top of things to recognize problems early and help resolve them. Irrespective of how the project is going, MBBs use their experience and understanding to provide useful suggestions. All of this requires a delicate balance between giving the team the freedom to do its job and not micromanaging its activities, and being sufficiently involved to be a positive force, when needed.

In helping make things happen, MBBs need to be positioned to exert friendly clout. MBBs usually do not run any specific line operation, such as manufacturing or engineering. The leaders and members of the Six Sigma teams generally do not report to them directly. So, why should anybody listen to them? This issue must be addressed up front. MBBs need to ensure that there is close collaboration and feedback of information, including performance, to line management. The old adage “speak softly and carry a big stick” has relevance here, and the MBBs need to have, at least, a handle on the stick.

MBBs need to have excellent rapport with business leaders and the Six Sigma Champion, if there is one. They need to help leaders keep focused on Six Sigma and maintain momentum and interest, even when Six Sigma is no longer “front page news.” They must keep leaders informed of significant progress and challenges. They need to provide a vision for the future, and lobby for the resources required to make things happen. And they should make it especially easy for leaders to communicate to the staff and to their own management by providing information in a format that can be readily passed on to others. Thus, MBBs help leaders set the tone for moving forward in making Six Sigma “the way we work.”

On a more technical note, MBBs need to ensure the thorough consideration of all key CTQs. Six Sigma projects have often addressed one or a small number of well-defined CTQs, such as reducing end of line scrap and rework. It is, therefore, possible to overlook the implications on other important CTQs—that is, fail to consider the full impact of proposed “improvements” on the entire system. Changes to reduce end of line rejects, for example, often also impact product performance and reliability. The result is often positive. But this is not necessarily the case—and depends on the specific nature of the changes. MBBs need to help define projects sufficiently broadly so that all key CTQs are considered both in the project itself and in assessing its impact.

MBBs also need to balance short-term payoffs and long-term business goals, and be customer focused. It is important to gain some big successes early, and to show clear and rapidly identifiable payoffs, perhaps in manufacturing settings. However, these may be only the tip of the proverbial iceberg of what Six Sigma can do. As Six Sigma receives increased acceptance, we need to move upstream and ensure that products are designed to be maximally robust to whatever environment they may encounter, and to provide value through the entire life cycle. This requires the business to excel on all fronts, including the processes that it engenders. And it raises some special challenges in quantifying the impact of improvements. How, for example, can we quantify the financial impact of on-time delivery, or that of averting an early failure? MBBs need to provide leadership in ensuring that proper emphasis is given to projects that are critical to the business, but whose consequences are difficult, or take a long time, to measure. The transient nature of the MBB position as a path to higher management might make some MBBs reluctant to take on the riskier and less definitive tasks that long-term business needs demand—but they must.

Finally, MBBs need to evolve second-generation training programs. Training to get green belts and black belts on board initially is now well understood. But the initial training needs to be supplemented with timely “booster shots.” These have a number of goals. The first is to ensure that the basic concepts are retained and reinforced. The second is to build on “lessons learned,” based on experiences within one’s own business. The third is to make available new technology--highlighting approaches that have been found most valuable in applications, but have not been emphasized sufficiently in the original training. Two examples are essential systems to get the needed data up front and simulation tools for everything from evaluating sample size requirements to modeling a process. As areas of application shift, so need the arsenal of available tools. Some of these second-generation tools may be provided in an off-line format, and the details accessed as needed.

The role of the Master Black Belt continues to develop, and the challenges and opportunities for leadership are still evolving. The MBB position is now being combined in some organizations with other management responsibilities. How to achieve a proper balance, and to ensure that the MBB role gets sufficient attention, raises new questions. Special issues enter in introducing Six Sigma to organizations other than those that manufacture a product, such as schools, banks, hospitals and government. And so does the recent trend to work with customers directly in implementing Six Sigma. Clearly, the fun for MBBs has just begun!
Six Sigma :LESSONS LEARNED

1. The time is right.
2. The enthusiastic commitment of top management is essential.
3. Develop an infrastructure.
4. Commit top people.
5. Invest in relevant hands-on training.
6.Select initial projects to build credibility rapidly.
7. Make it all pervasive, and involve everybody.
8. Emphasize Design for Six Sigma (DFSS).
9. Don’t forget design for reliability.
10.Focus on the entire system.
11.Emphasize customer critical to quality characteristics (CTQs).
12. Include commercial quality improvement.
13.Recognize all savings.
14. Customize to meet business needs.
15. Consider the variability as well as the mean.
16. Plan to get the right data.
17. Beware of dogmatism.
18.Avoid nonessential bureaucracy.
19.Keep the toolbox vital.
20. Expect it Six Sigma to become a more silent partner.

When Jack Welch brought Six Sigma to General Electric (GE) in 1995, he proudly said he would build on the successful experiences of other organizations such as Motorola and Allied Signal.

Since then, nimble companies have introduced or improved Six Sigma by adapting best practices from GE and elsewhere. In the same vein, those who today want to make Six Sigma happen can learn from the accumulated experiences of their predecessors.

1. The Time Is Right
Six Sigma makes sense. Most Six Sigma Forum Magazine readers take this statement as self-evident. Nevertheless, it warrants repeating.

A key difference between Six Sigma and other approaches is the integration of a highly disciplined process (such as DMAIC for Define, Measure, Analyze, Improve, Control or DMADOV for Define, Measure, Analyze, Design, Optimize, Verify) with one that is very quantitative and data oriented. This is a winning combination—as evidenced by the results of the companies that have used it.

The concepts underlying Six Sigma have always made sense. What makes Six Sigma especially timely today is the combination of the following:

Intense competitive pressures, including those resulting from globalization.
Greater consumer demand for high quality products and management recognition of the cost of poor quality.
The accessibility of large databases and our ability to digest and analyze data.

The last point is especially important. I have witnessed other initiatives with some similarity to Six Sigma. Although generally moderately successful, they have floundered for two reasons. One was the inability to harness data speedily. This has changed radically with the computer revolution, in general, and the increased accessibility of user oriented software, in particular.

2: The Enthusiastic Commitment of Top Management Is Essential
This gets to the second reason many initiatives have floundered in the past. Many quality improvement efforts have been promoted by lower or middle management and took a bottom up, rather than a top down, approach.

It is unlikely Six Sigma would have succeeded at GE without CEO Jack Welch’s (and now Jeff Immelt’s) unflinching leadership. Tacit approval is not enough. What is needed is both an up-front investment in funding and a system that actively rewards successful implementation and implementers.

Welch required employees to be “lunatic” about quality and made Six Sigma a major criterion for incentive compensation and promotion. Enthusiasm spread from management to the entire workforce.

Local business leaders, called Six Sigma Champions, play an important role in making Six Sigma happen in large companies. They establish the mechanism, select the local Master Black Belts (MBBs), provide the needed resources, ensure everybody in the workforce pays attention and take overall responsibility for successful implementation and continued commitment.

3: Develop an Infrastructure
Six Sigma cannot be an informal extracurricular activity. A formal supporting infrastructure is required. Management’s commitment includes establishing and supporting such an infrastructure.

This commitment includes setting up the formal organization, defining key objectives and responsibilities, developing a budgeting process and specifying a solid process for measuring results. This process needs to be closely integrated with the existing system and must be an important element of it.

4: Commit Top People
There is a natural inclination to assign to Six Sigma people that happen to be available, rather than those that would be best suited for the job. Instead, Six Sigma merits the assignment of the most capable people to be MBBs and Black Belts (BBs). They should not only excel technically but also be imaginative and persuasive leaders.

At GE, for example, MBBs are likely candidates for subsequent high management positions. Also, But they need to be relieved of existing responsibilities so they can, at least initially, give Six Sigma their full commitment.

5: Invest in Relevant Hands-on Training
Once the structure for implementing Six Sigma is in place, the hard work follows. It begins with providing the workforce the training needed for successful implementation. The following are some key learningsSome key points about training include the following:6, 7


Ensure trainers are knowledgeable and outstanding communicators.
Customize the training, especially the examples, to the needs of the specific business. This often requires deviations from and extensions to previously developed canned materials; , as advised insee lesson 14.
Ensure the common vocabulary of Six Sigma is retained—an essential for expediting communications.
Incorporate hands-on involvement. The classical Six Sigma curriculum has four three-day sessions (approximately corresponding to DMAIC) offered four weeks apart. Six Sigma projects are conducted by the class participants during the intervening time. Green belt (GB) and BB certification requires successful completion of two Six Sigma projects, as judged by a MBB.
Engage Consider engaging external gurus to expedite Six Sigma introduction. GE followed this formula did this in introducing both DMAIC and the DMADOV processes for DFSS. Within a few years, these efforts were, however, fully transitioned to people within the company.

6: Select Initial Projects To Build Credibility Rapidly
Total management commitment, appropriate infrastructure, involvement of top people and the right training set the stage for success and result in high expectations. These expectations need to be met—and met rapidly—to maintain momentum. All Six Sigma projects need be selected judiciously. This is particularly critical for start-up projects. They need to meet the following criteria:

Their importance is evident or can be readily demonstrated.
They are viable and doable in a short time (preferably less than three months).
Their success can be readily quantified.

This often translates into addressing the proverbial low-hanging fruit. Initial Six Sigma applications have frequently been in manufacturing, for which the DMAIC process is especially suitable. Key metrics of success, such as the reduction of end of line rejects as measured by scrap and rework, can generally be rapidly impacted in manufacturing and are usually well-publicized and well recorded.

A successful start, built on accepted and highly demonstrable successes, will expedite the path forward.

7: Make It All Pervasive, and Involve Everybody

Once credibility for Six Sigma is established, you need to leverage the momentum. The goal should be to make Six Sigma all pervasive within the organization and beyond.8 The initial distinction between Six Sigma projects and other projects should disappear as Six Sigma becomes “the way we work.”

Short-term successes in manufacturing generally represent just the tip of the iceberg. Six Sigma also must include vendors (product can be only as good as its raw materials) and customers (more on that starting in lesson nine).

The all pervasiveness of Six Sigma is reflected in many of the subsequent lessons learned.

8: Emphasize DFSS
The quality of a product is fundamentally determined by its design. What can be done in manufacturing is generally reactive and limited., and the In contrast, the impact of high quality in design goes well beyond improving end of line yield. It can also heavily influence the quality experienced by the customer. Thus, DFSS has become an integral element of Six Sigma, with long-term payoffs that may well exceed those in manufacturing.9, 10

The importance of DFSS is being recognized in the The training of those who can impact design is recognizing this importance of DFSS. Thus, the basic implementation process is DMADOV, with its emphasis on design, in place of the closely related DMAIC, which emphasizes improvement. Implementation has rapidly followed.

For example, according to GE’s 2000 annual report, its medical systems business alone introduced 22 DFSS products that year. Most significant among these were the Senographe and Innova proprietary digital x-ray systems, claimed to revolutionize breast cancer detection and interventional cardiac imaging.

An important element of DFSS is robustness of design—ensuring the product performs well under diverse operational environments (from the tropics to the Artic), varied customer use (and misuse) scenarios and subtle changes in production conditions (such as variability in raw materials).

9: Don’t Forget Design for Reliability
Design quality has both short- and long-term elements. Short-term quality is reflected by customer delight in on-time delivery and initial experience with the product, but most major products (for example, automobiles, washing machines, locomotives and aircraft engines) are purchased for the long haul.

For such products, quality is reflected by high reliability (problem free operation) over many years. Such long-term performance of a product is most vivid in the minds of customers at the time of product replacement.

Thus, a key goal in an all pervasive Six Sigma program is to design products for long life and high reliability. Methods for reliability improvement need to be an integral part of the Six Sigma toolset for design and product engineers.

10: Focus on the Entire System
An important part of making Six Sigma all pervasive is to focus on the entire system. Initial Six Sigma projects traditionally address individual critical to quality characteristics (CTQs), such as the elimination or drastic reduction in the occurrence rate of a specific defect.

In an uncompromising attack on the CTQ at hand, little attention might be given to other CTQ’s. In many cases, such as ones dealing with the removal of defects, projects that improve one CTQ will also improve others, but this is not necessarily so.

As an extreme example, Oone way to decrease the rejection rate is might be to broaden product specifications. This could have a deleterious impact on other CTQs—such as the reliability of the product in the field. Moreover, while the positive impact of yield improvement is usually evident, the possible negative effect on reliability is often delayed, and, therefore, may not be recognized readily..


You need to recognize that Because CTQs are frequently closely related, so you must evaluate the impact and associated cost of any action on all important CTQs. The focus needs to be More generally, you need to focus projects on overall system improvement rather than on the improvement of any individual CTQ.

11: Emphasize Customer CTQ’s
The initial successes at GE and elsewhere were due principally to involved internal improvements that even though they had a significant impact on the bottom line. However, Ccustomers felt left out. They were quoted by Welch and in the GE 1998 annual report, as asking “When do I get to see the benefits of Six Sigma?”

This question led to the introduction of the outside in thinking concept, with the goal of focusing on customer directed CTQs, such as time to delivery, waiting time to respond to customer enquiries and general customer satisfaction.

These concepts were recently extended by GE through its ACFC (at the customer, for the customer) initiative. Its purpose is to train customers in Six Sigma and help them in the start-up process, including guiding them on specific projects.

Interestingly, GE’s annual reports from 1996 to 1999 quantified the mostly internal savings from Six Sigma (for example, $2 billion for a $550 millionin 1999). In contrast, the GE 2000 annual report emphasized savings to the customer.


In contrast, the GE 2000 annual report emphasized savings to the customer. For example, GE helped airlines undertake more than 1,2000 customer Six Sigma projects, realizing more than $300 million in savings. The company also generated more than $100 million in benefits for medical systems customers, serving as a catalyst for 1,000 Six Sigma projects aimed at improving patient throughput and reducing variability in healthcare delivery.

12: Include Commercial Quality Improvement
The broadening of Six Sigma to encompass commercial and transactional quality almost coincided with GE’s drive to address customer CTQs. Successful applications includeddealt with portfolio acquisition and management, pricing, marketing strategy and collections. Again the basic design of such processes (DFSS for commercial quality), as well as the improvement of existing processes, was emphasized.

It soon became evident evident that these concepts provided payoffs to backroom operations as well as to customers, matching that could match those from product design and improvement.11

13: Recognize All Savings
A significant element of Six Sigma is the quantifying of hard number savings. The relatively easy and speedy quantification of dollar savings is, as already suggested, why many companies focus initial Six Sigma projects on manufacturing.

But here’s the rub: How can you make Six Sigma all pervasive, systems oriented and customer responsive if you cannot readily achieve financial recognition of the resulting gains? In particular, how can you quantify the added sales resulting from customer goodwill and word of mouth recommendations created by DFSS or improved commercial quality?

Even more complex, how can you ensure proper recognition of the savings from averting problems resulting from DFSS, such as a design change that significantly reduces the probability of a product failing during its first five years of operation?


Best practices for answering these questions are needed. One approach might be to establish CTQs that, in their own right, recognize such factors as premature failure. Clearly, for Six Sigma to be all encompassing youwe need to develop ways of recognizing all savings and loss avoidances, including long-term ones—even if those savings cannot be immediately or even ever quantified precisely by the finance department.

14: Customize To Meet Business Needs
The basic concepts of Six Sigma, such as a highly disciplined data oriented approach to quality improvement, are directly applicable to all operations, but the relative importance of specific tools varies from one operation and one business to another.

This variance needs to be recognized in keeping training fully relevant as Six Sigma moves from the manufacturing floor to other functions. For example, the proper planning of investigations is universally relevant. For most product development and manufacturing situations, therefore, design of experiments (DOE) merits close attention. In addition, for chemical processing businesses, mixture experiments (evaluating the impact of product ingredients that need to add up to 100%) also warrant consideration.

In contrast, in marketing or servicing operations you might provide only minimal training in formal DOE and instead focus on the planning and conduct of customer surveys.

It is also important to adjust the tools to the sophistication of those involved and remain cognizant of practitioners’ ability to learn these while pushing forward new and improved approaches.

15: Consider the Variability as Well as the Mean
As Six Sigma has matured, there has been increased recognition of the importance of improving the mean and reducing variability, in addition to the traditional goal of improving the mean. “Variability is evil” has become a a Six Sigma slogan. A typical application is the reduction of variability in the time from the placement of an order for a product or service to its delivery.

A typical application is the reduction of variability in the time from the placement of an order for a product or service to delivery.

Some even claim variability, not the mean, is what principally impacts customers. I think this is an overstatement.

For example, Ccustomers seek a consistently long life for a product. A consistently short life would generally not do. Neither would a long life for some units, and early failure for others. In this and many other applications, both the mean and variability are important and need to be addressed. Their relative importance varies from one application to the next.

There are some situations for which variability is inherent and can only be partially eliminated. In teaching the workforce to perform specified tasks, for example, you can reduce, but not completely remove, variability by judicious hiring practices and targeted training. The

Some variability due to inherent differences between workers will likely remain. The challenge then becomes that of helping ensure the process is maximally robust to such remaining variability.

16: Plan To Get the Right Data

A Six Sigma slogan goes, “In God we trust, all else others bring data.” Unfortunately, the data that are readily available, even though sometimes voluminous, are often insufficient for the task at hand. Frequently, this is because the data were obtained for reasons other than analysis, such as to meet accounting requirements. In fact, the most relevant information might not even be recorded, or the data that are available may be inconsistent or ambiguous.

Say, for example, you wish to learn about the root causes of field failures that have not been eliminated by DFSS. Data may be available only on units that failed under warranty, and nothing may be known about the others those that failed out of warranty. In addition, there may be little information on unfailed units. Even for

Even for units with failure data, knowledge may be limited to the date of failure, the cost to the manufacturer and perhaps a general description of the failure.

Detailed failure descriptions may be at the discretion of repairpersons and thus can be highly inconsistent. Important information about such factors such as production date and shift, time or number of cycles in service, operating environment, degradation of the unit= and the specific cause of failure are often missing.

Thus, it is often necessary to obtain added information, even though When added information is required, this costs money and takes time.

The data that are available may be useful in helping decide what added information would be most useful. Data Data on every unit is not always needed. Instead, a carefully selected sample often suffices. This is because it is the quality rather than the quantity of the data that counts.

In obtaining a better understanding of refrigerator failures, for example, good information on a statistically selected sample of 10,000 units is generally more useful than incomplete and inconsistent data on a million units.

Because there is generally a significant delay between planning the data acquisition system and getting the data, it is important to establish a good data procurement system proactively, rather than wait until it is required by a problem. In some situations, a well-designed experiment can also provide needed information.

17: Beware of Dogmatism

Six Sigma concepts and tools are sound and have proven their worth. You can apply them with confidence, but you often need to adapt them they often need to be adapted to be maximally responsive to the issue at hand. For example, the concept of 3.4 defects per opportunity can sometimes be vague. And how do you define an “opportunity?” Does a shift of exactly 1.5 sigma in the mean from the short-term to the long-term really always apply?

Instead of debating these questions, it may be better to directly use the percentage of defect in the final product or in the process as your criterion. Also, you should not insist on the use of any specific tool from the Six Sigma toolkit.

The goal is to gain significant quality improvement—not to use DOE, gage repeatability and reproducibility (R&R) or whatever just for the sake of using it. These tools are very powerful and have much applicability, but they are not equally relevant for all situations and to need to be used judiciously.

18: Avoid Nonessential Bureaucracy

One of GE’s key initiatives prior to Six Sigma was “work out.” Its goal was to do away with bureaucracy and all else that impeded progress. Welch surprised many employees in introducing Six Sigma when he urged proceeding even if it might sometimes result in adding a small amount of bureaucracy.

This addition, indeed, is a price one pays for a highly disciplined process (such as DMAIC, tollgates and establishment of an infrastructure). It has, however, resulted in some criticism, especially from those in the trenches who perhaps experience some frustration in the added work or possible delay that might result from Six Sigma.

Bureaucracy, moreover, can build on itself. You need to be vigilant to ensure only the most essential bureaucratic elements are added and to carefully scrutinize these to keep them to an absolute minimum. As Six Sigma develops into the way you work, you should even be able to chip away at the bureaucracy that remains. some Elementsese.

19: Keep the Toolbox Vital
Statistical and other tools form the backbone of Six Sigma. These often involve technical concepts—such as emphasis on the measurement system (gage R&R), DOE, quality function deployment—that are important in practice but are unlikely to be encountered in standard college training.

What has helped make Six Sigma powerful is the tools being imbedded into a process and immediately put to practical use. Six Sigma is therefore much more than a toolbox. With experience, some tools have been found to be more important than others, and some not included originally have been found to warrant addition.12, 13

Statistical topics not included in the original training that have proven their value include:
Handling of nonnormal data.
DOE as a step-by-step process.
Simulation analysis (especially for determining sample size).
Quantifying individual sources of variability.
Expressing uncertainty by statistical intervals in place of hypothesis (or significance) testing.
Analyzing product life data using special methods.
Tools for analyzing large data sets, such as CART (classification and regression trees) and MARS (multivariate adaptive regression splines).
Graphical methods for supplementing formal statistical analyses.

20: Expect Six Sigma It To Become a More Silent Partner
The introduction of Six Sigma is often accompanied by much fanfare. This needs to be rapidly followed by solid evidence of successful applications resulting in important quality improvements. The concepts are then extended to broader, longer-term, more systems focused and customer oriented improvement challenges.

As Six Sigma becomes engrained within an organization and applied to vendors and customers, it may no longer be front-page news. This should not come as a surprise and certainly should not imply it is any less relevant.

The momentum can be retained by continued successful and broader applications. Best practices need to be sought and implemented as Six Sigma truly becomes the way we you work.

Where Six Sigma Is Headed
Six Sigma got started and has been applied, with much success, in large corporations—perhaps because these have the greatest resources. But it is clearly adaptable to the needs of medium-sized and small businesses.

Its relevance, moreover, is not limited to the corporate world. It has, for example been applied recently to farming. and is even being used on a farm.14 Six Sigma can also be valuable to the public sector, including government, hospitals, nonprofit organizations and schools.
Six Sigma’s deployment in these new arenas represents its new frontier and presents some important opportunities and exciting challenges. I hope the pointers I’ve presented provided will help expedite successful jump-starts in many new and diverse applications.
Six Sigma - What is Six Sigma?

Six Sigma at many organizations simply means a measure of quality that strives for near perfection. Six Sigma is a disciplined, data-driven approach and methodology for eliminating defects (driving towards six standard deviations between the mean and the nearest specification limit) in any process -- from manufacturing to transactional and from product to service.

The
statistical representation of Six Sigma describes quantitatively how a process is performing. To achieve Six Sigma, a process must not produce more than 3.4 defects per million opportunities.

A Six Sigma defect is defined as anything outside of customer specifications. A Six Sigma opportunity is then the total quantity of chances for a defect.

The fundamental objective of the Six Sigma methodology is the implementation of a measurement-based strategy that focuses on process improvement and variation reduction through the application of Six Sigma improvement projects. This is accomplished through the use of two Six Sigma sub-methodologies: DMAIC and DMADV.

The Six Sigma DMAIC process (define, measure, analyze, improve, control) is an improvement system for existing processes falling below specification and looking for incremental improvement.

The Six Sigma DMADV process (define, measure, analyze, design, verify) is an improvement system used to develop new processes or products at Six Sigma quality levels. It can also be employed if a current process requires more than just incremental improvement. Both Six Sigma processes are executed by Six Sigma Green Belts and Six Sigma Black Belts, and are overseen by Six Sigma Master Black Belts.

According to the Six Sigma Academy, Black Belts save companies approximately $230,000 per project and can complete four to 6 projects per year. General Electric, one of the most successful companies implementing Six Sigma, has estimated benefits on the order of $10 billion during the first five years of implementation. GE first began Six Sigma in 1995 after Motorola and Allied Signal blazed the Six Sigma trail. Since then,
thousands of companies around the world have discovered the far reaching benefits of Six Sigma.