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The Five Fundamental Assumptions of Six Sigma

Some people are angry and upset about the effectiveness of Six Sigma as a problem-solving discipline. Individuals routinely call for the next new quality discipline or argue why Six Sigma will not work in this case or the other. Some of this is one-upping – this approach is better; some of this is sour grapes – this approach is simpler, easier or less intimidating. Most of these arguments, however, indicate a lack of understanding of just what Six Sigma is intended to do for an organization.

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To be fair, much of this dialogue is healthy. Six Sigma will never solve all problems and a smart leader knows he or she needs a complete set of quality approaches – not just one. Any continuous improvement processes must also be customized to the environment in which it is employed and must evolve as that environment changes. By far, however, the main reason for the clamor calling for new problem-solving methods is that Six Sigma has become more complex than necessary.

What follows in this article is a description of Six Sigma reduced to its fundamental assumptions, or theorems. If these simple concepts are understood, all the tools, all the tollgate deliverables, and all the statistics and jargon are put in their proper supporting roles. Rather than mastering all the tools and attempting to build the program from the bottom up, this approach depends on a top-down, theoretical foundation. Rather than a cookbook approach, Six Sigma should be seen as a mathematical proof.

Fundamental Assumption 1

Customers only pay for value.

It seems so simple. Of course the customer only pays for value, but most businesses define value incorrectly. The products and services being sold are not what confer value to the customer. Products and services are vehicles to deliver value. Value is only created when a specific need the customer has is fulfilled. If a customer need is not met, even if the product or service is perfect, no value is created. Quality is not a measure of perfection, but of effect.

Failing to understand customers and their needs is the biggest driver of cost in most businesses. Quality for many products is defined by whether engineering specifications are met rather than whether the product delivers to actual customer needs. Similarly, in many service environments, service quality is defined by what the customer wants or complains about rather than how the customer uses the service. This distinction is important because it is possible to deliver everything a customer asks for and do so perfectly while not satisfying his or her needs. When this happens, the costs to deliver go up but the revenue from delivering does not.

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First Theorem of Six Sigma: Changes in critical to quality (CTQ) parameters and only changes in CTQ parameters alter the fiscal relationship an organization has with its customers.

Those product or service qualities that alter the way a customer behaves with regard to purchase decisions are CTQs. Changes in CTQs, be they good or bad, drive customer loyalty. When CTQs are altered, a company’s ability to create customer value is altered. Improving the customer’s perception of value changes ultimately affects the fiscal relationship with that customer either in terms of price or cost to deliver.

The problem with managing to customer CTQs is not a question of intent. No business intentionally fails to deliver to CTQs. Companies fail to deliver to CTQs because of gaps in process knowledge. These gaps manifest themselves in process variation and poor process capabilities.

Fundamental Assumption 2

If a business has a profound and complete process knowledge, the products and services being delivered can be controlled so as to always create customer value. Gaps in process knowledge are the primary causes of failure and defect.

Process control focuses on ensuring that that the process is managed and executed in a consistent manner. If there are gaps in the understanding of how processes work or gaps in the understanding of how the customer ascribes value to the products and services being generated, process control is simply not possible. Six Sigma (and all continuous improvement processes) is fundamentally focused on closing these knowledge gaps.

Second Theorem of Six Sigma: Process outputs are caused by process, system and environmental inputs. 

 Y = ƒ (X1 . . . Xn)

The “holy grail” of Six Sigma is the process transfer function. Once this is properly defined, managers have all the tools they need to make the process perform in any manner desired. The transfer function is never really perfect, but were a company to ever have complete transfer functions for all their processes, optimizing costs, production and customer value would be a simple matter of arithmetic.

The big myth is that Six Sigma is about quality control and statistics. It is all that – but a helluva lot more! Six Sigma ultimately drives leadership to be better by providing the tools to think through tough issues. —Jack Welch

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Good leaders strive to make good decisions all of the time. If, however, there are gaps in understanding, incorrect assumptions or false assumptions, what looks like a good decision will result in bad outcomes. Six Sigma is about reducing the probability of these bad outcomes.

Most processes have subject matter experts and institutional knowledge. In most cases, these subject matter experts and institutional knowledge allow businesses to create transfer functions that are 90 percent to 95 percent correct, which gives the illusion of expert knowledge. It is the illusion of expert knowledge that makes it difficult. Since most of the rules for how to run processes are known and since the knowledge gaps are subtle, it is believed that the issues are execution-related, not understanding-related. This is a dangerous situation as these small process knowledge gaps, compounded over a multistep process, can result in significant losses even when people attempt to execute the process to the best of their abilities.

Fundamental Assumption 3

All variation is caused.

Often the only clue to gaps in process knowledge is the degree of variability in the process. Processes always have variation (remember – entropy increases!) but it does not spontaneously occur. It must be caused. Variation is just another output of systems. Transfer functions can be written to describe it; the more complete those functions are the better variation can be controlled. There is no myth or magic. When a system does not perform in exactly the same manner for a static set of process inputs, that simply means there are additional factors that are not yet understood that influence those processes.

Third Theorem of Six Sigma: Variation in process outputs are caused by process, system and environmental inputs.

∂Y / ∂X = ƒ′ (X1 . . . Xn)

If Taguchi’s loss hypothesis (the cost of a system increases as it diverges from the performance expectations of its customer) is accepted, then process variation is the leading cause of customer dissatisfaction and operating costs. The factors that drive the process output and the process variation can be defined and controlled. Processes can then perform at the optimum balance between delivery and stability, thus driving the lowest possible cost and the highest possible customer satisfaction. In other words, if enough “profound knowledge” is added to the system, maximum value can be produced. The goal of Six Sigma, therefore, is always to increase process understanding. The goal is to populate transfer functions to the degree needed, and warranted, in order to best serve customers.

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Fundamental Assumption 4

Given the right process knowledge and the ability to deliver products and services that satisfy the customers’ CTQs, management will always make the decision that most benefits the customer and achieves the highest possible return on investment.

The number one assumption when doing any type of continuous improvement is that if leadership is provided with the know-how, if knowledge gaps are filled in, leadership will make (or allow others to make) decisions that are best for the long-term well-being of the business. Some people are afraid to test this assumption; it is a trust issue. If power is held because of the ability to solve a recurring problem, if teams are rewarded for firefighting rather than preventing problems, then this process collapses. While it is tempting to let experience and tradition supersede structured problem solving, in the long term when overall systems understanding is improved, and leadership employs that learning for the advantage of all parties in the supply chain, the business prospers.

Fundamental Assumption 5

Given a choice between long-term sustainable growth and short-term profit, long-term growth will always outperform the short-term gain.

This is the final and most critical assumption. It is cornerstone to total quality management, the Toyota Production System (Lean) and Six Sigma. If people are helped with controlling their own destinies, and if they are provided with the wherewithal to achieve self-determination, they will naturally do what profits them the most. When educated about the long-term benefits of creating sustainable customer relationships, most people will choose to create value and maximize their payback on the relationship. This is a question of ethics.

Conclusion

There are three foundational theorems and a simple set of postulates or assumptions that these theorems are based upon. All the tools and processes of Six Sigma – both DMAIC (Define, Measure, Analyze, Improve, Control) and DFSS (Design for Six Sigma) – are grounded in these simple foundations. Get the assumptions correct and all else is commentary.

Comments 4

  1. Patrick R Dillon

    Something that I have wondered about but sometimes have gotten puzzled looks when I bring up; here’s a recent example: Our packaging machine applies an adhesive to laminate two sheets of plastic film together; we have been doing this for a few years, the strength that the two sheets are held together by the glue after being laminated is very important, we evaluated a new adhesive and the strength was very low, we tried many things before deciding to implement a DOE team; at the first meeting I explained that I think that we should start with the manufacturers and vendors recommended specifications for the machine settings, e.g., heat, pressure, speed, etc., plus apply the adhesive at the vendors recommended thickness, before beginning experiments. My analogy was a race car, if I wanted to investigate why my race car isn’t very fast, first I would use the specified fuel, tire air pressure, motor oil, etc.; but this idea was voted down. Am I thinking incorrectly about how to approach this? Thank-you,

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  2. Chris Seider

    An interesting article for water cooler talk. Thanks for the time.

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  3. Michael Carver

    Yours is certainly a valid approach but there may be other equally valid ways to attack this problem. Given the current resistance, you might just start comparing your current process as the baseline to key factors. I do think the DOE approach is best but you don’t need to go all the way back to original specifications for your baseline.

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