Combating quality resistance
Q: I was recently introduced to quality management (QM) and ISO 9001:2015. My organization’s culture has not embraced QM and frequently makes it the subject of outright antagonism. How can I arm myself with greater knowledge or qualifications to help change the organization’s attitude toward QM at all levels? How should I focus my efforts to overcome these growing pains? I’m overwhelmed because there are so many channels of information, certifications and conferences.
A: Because QM is often the subject of antagonism in your organization, it is clear that QM has not added any value to what your organization produces or the services it provides. The main reason QM is seen as an adversary is that those in QM think they have final say in what is acceptable and what is not acceptable. However, that is not the reality.
The reality is that what is and isn’t acceptable, or what is and isn’t shipped, is a business decision. These decisions are made by departments such as production, sales or marketing. QM’s role is simply to:
- Collect information in terms of testing, inspection or design of experiments.
- Decide whether products or services meet requirements, and report the results in terms of pass or fail to the concerned parties. Let them decide what products or services failed to meet the requirements.
Never go in and hassle anyone about what should be shipped. That is not QM’s role. Never lose sight that QM is a support function and not a "bread and butter" function. Unfortunately, I have come across few organizations in which QM clearly understands its role.
Quality certifications and conferences have value only if an organization has embraced QM; otherwise, it really does not matter which certifications you have—or how many—or what you have learned at conferences.
The best thing to arm yourself with in this situation is common sense. Because common sense is not common, those who have it have a competitive advantage. Let me elaborate on what I mean by common sense.
Management pays attention when it comes to money, and the easiest way to communicate to management is through the language of money. You should, therefore, find out with reasonable accuracy where you can save your organization money using QM principles and practices.
There are several areas that may offer such an opportunity. For example, review customer complaints and look at the reasons for those complaints. How well and fast are they resolved and how much is it costing the organization? Investigate the scrap and rework being produced. You also should review quality failures, either in testing or inspection. Look for not only the material costs, but also how much administrative time is wasted on addressing those issues.
The opportunities are limitless. You just need to have a fresh viewpoint and positive attitude. Ask management for time to briefly show what you have found and what you can do to add value to the organization in terms of money.
If you do this well, management will give you a chance, and you can begin to turn things around. After management sees that QM can add value to the organization, there will be no going back: You will always have management’s support and commitment.
Here is a real-life example: The director of quality assurance (QA) at an apparel manufacturer known for excellent quality was not getting the resources he wanted. In one of his organization’s six plants, the QA director found that the quality of the final product was excellent, but there was too much rework and time and money wasted in inspections.
He collected information about this situation, put a dollar value to what the organization was wasting and calculated how much would be saved if it addressed this situation. He asked management for 15 minutes to present his findings.
That 15-minute presentation lasted an hour. From that point, the QA director got any resources he needed. In addition, the monthly operations meeting—which was chaired by the executive vice president and six plant managers—started with a QA presentation for that month, covering each of the six plants.
The QA director and six plant managers got along well because the director simply provided information and plant managers decided what happened with the final product. That QA director never got involved in what was and wasn’t shipped.
Pradip V. Mehta
Mehta Consulting LLC
Breaking down sigma levels
Q: Help me understand the statement "… adding a 1.5 sigma shift in the mean results." I’m familiar with the bell curve and +/- three sigma. How does the extra +/- 1.5 sigma fit in, and what is meant by a shift in the mean?
A: I’ll use a normal probability distribution plot to begin my explanation (see Figure 1). This plot shows the fraction of the normal curve outside of various sigma levels—with the sigma level defined as the number of standard deviations from the mean. Each sigma level shown can be explained as follows:
1.5 sigma—This sigma level is shown for illustration purposes. That area represents the fraction of the normal curve beyond 1.5 sigma from the mean on both sides.
This fraction represents 13.36% (2 x 6.68%) of the area under the curve. The remaining 86.64%, therefore, represents the area under the curve that is within +/- 1.5 sigma of the mean.
Incidentally, "fraction of the area" can be understood in practical terms as meaning a fraction of data, product characteristic or process parameter that is being measured—as long as the data follow the normal distribution. The 13.36% can be considered the defect rate for the situation in which specification limits are set at 1.5 sigma.
Three sigma—About 0.135% of the data are greater than +/- 3 sigma from the mean, or 0.27% total. This is the origin of the commonly quoted number of 99.73% (that is, 100% - 0.27%) of the data being within +/- 3 sigma of the mean.
4.5 sigma—This enters Six Sigma-jargon territory. On each side of the normal curve, 3.4 parts per million (PPM) of the data are outside +/- 4.5 sigma. Note this is 6.8 PPM total, so clearly, the two-sided 4.5 sigma level is not the source of the well-known Six Sigma process capability that’s indicative of a 3.4 PPM defect rate.
Six Sigma—On each side of the normal curve, about one part per billion of the data is outside +/- 6 sigma. This number is so small that it would be difficult to measure due to the large sample sizes required.
The 1.5 sigma shift is an estimate of the difference between short and long-term variation—with long-term variation being defined as the variation that takes into account all sources over an extended time. The idea is that if a process is capable of Six Sigma performance in a controlled and limited environment, it will be somewhat less capable after additional operators, manufacturing lots, seasonal and environmental effects, and even special causes are taken into account.
That capability difference has historically been defined as 1.5 sigma, which is basically an adjustment that considers all factors that cause variation in real life. So, Six Sigma capability is not truly Six Sigma: It is of the order of 4.5 sigma, but as I explained, it is not strictly equal to 4.5 sigma.
To explain the origins of Six Sigma’s frequently referenced "3.4 PPM" capability, assume that a process has been demonstrated to achieve short-term Six Sigma capability versus a two-sided specification. Assume that over an extended time, the mean shifts 1.5 sigma while the standard deviation—or width—of the normal curve remains the same.
The effect of the shift is that the data distribution moves to within 4.5 (6 - 1.5) sigma of one specification while moving to 7.5 (6 + 1.5) sigma away from the other specification. The PPM outside the specification is, therefore, 3.4 PPM on the 4.5 sigma side. On the other side—at 7.5 sigma—there only would be about three in 100 trillion items outside the specification, which is negligible compared to the 3.4 PPM and can be ignored. So, 3.4 PPM plus a negligible number is a total of 3.4 PPM.
Senior manager, quality engineering and risk management