Category Archives: Quality

QSR Required Procedures

I have identified 40 procedures required by 21 CFR 820: the Quality System Regulation

  1. § 820.22 for quality audits…
  2. § 820.25(b) for identifying training needs…
  3. § 820.30(a)(1) to control the design of the device in order to ensure that specified design requirements are met
  4. § 820.30(c) to ensure that the design requirements relating to a device are appropriate and address the intended use of the device, including the needs of the user and patient
  5. § 820.30(d) for defining and documenting design output in terms that allow an adequate evaluation of conformance to design input requirements
  6. § 820.30(e) to ensure that formal documented reviews of the design results are planned and conducted at appropriate stages of the device’s design development
  7. § 820.30(f) for verifying the device design
  8. § 820.30(g) for validating the device design
  9. § 820.30(h) to ensure that the device design is correctly translated into production specifications
  10. § 820.30(i) for the identification, documentation, validation or where appropriate verification, review, and approval of design changes before their implementation
  11. § 820.40 to control all documents that are required by this part
  12. § 820.50 to ensure that all purchased or otherwise received product and services conform to specified requirements
  13. § 820.60 for identifying product during all stages of receipt, production, distribution, and installation to prevent mixups
  14. § 820.65 for identifying with a control number each unit, lot, or batch of finished devices and where appropriate components
  15. § 820.70(a) that describe any process controls necessary to ensure conformance to specifications
  16. § 820.70(b) for changes to a specification, method, process, or procedure
  17. § 820.70(c) to adequately control these environmental conditions
  18. § 820.70(e) to prevent contamination of equipment or product by substances that could reasonably be expected to have an adverse effect on product quality
  19. § 820.70(h) for the use and removal of such manufacturing material to ensure that it is removed or limited to an amount that does not adversely affect the device’s quality
  20. § 820.72(a) to ensure that equipment is routinely calibrated, inspected, checked, and maintained
  21. § 820.75(b) for monitoring and control of process parameters for validated processes to ensure that the specified requirements continue to be met
  22. § 820.80(a) for acceptance activities
  23. § 820.80(b) for acceptance of incoming product
  24. § 820.80(c) to ensure that specified requirements for in-process product are met
  25. § 820.80(d) for finished device acceptance to ensure that each production run, lot, or batch of finished devices meets acceptance criteria
  26. § 820.90(a) to control product that does not conform to specified requirements
  27. § 820.90(b)(1) that define the responsibility for review and the authority for the disposition of nonconforming product
  28. § 820.90(b)(2) for rework, to include retesting and reevaluation of the nonconforming product after rework, to ensure that the product meets its current approved specifications
  29. § 820.100(a) for implementing corrective and preventive action
  30. § 820.120 to control labeling activities
  31. § 820.140 to ensure that mixups, damage, deterioration, contamination, or other adverse effects to product do not occur during handling
  32. § 820.150(a) for the control of storage areas and stock rooms for product to prevent mixups, damage, deterioration, contamination, or other adverse effects pending use or distribution and to ensure that no obsolete, rejected, or deteriorated product is used or distributed
  33. § 820.150(b) that describe the methods for authorizing receipt from and dispatch to storage areas and stock rooms
  34. § 820.160(a) for control and distribution of finished devices to ensure that only those devices approved for release are distributed and that purchase orders are reviewed to ensure that ambiguities and errors are resolved before devices are released for distribution
  35. § 820.170(a) for ensuring proper installation so that the device will perform as intended after installation
  36. § 820.184 to ensure that DHR’s for each batch, lot, or unit are maintained to demonstrate that the device is manufactured in accordance with the DMR and the requirements of this part
  37. § 820.198(a) for receiving, reviewing, and evaluating complaints by a formally designated unit
  38. § 820.200(a) for performing and verifying that the servicing meets the specified requirements
  39. § 820.250(a) for identifying valid statistical techniques required for establishing, controlling, and verifying the acceptability of process capability and product characteristics
  40. § 820.250(b) to ensure that sampling methods are adequate for their intended use and to ensure that when changes occur the sampling plans are reviewed

Do It Well

While I have worked with hundreds of people, I can think of only a few who cared about what they did. The care they exercised showed in the superior quality of their work product. Most, however, don’t seem to show any care for the quality of what they produce. Tasks are treated as hot potatoes, to be shoved off to someone else as quickly as possible.

Doing something with care requires you to pay attention to the task and to be mindful of its context. That, in my experience, is rare. What I do know is that when the right actions are done right the outcome is most assuredly a quality product. There is a certain beauty and elegance about it.

Some pay great attention to getting the details of a task right while being oblivious to whether the task is appropriate for the context. Others may do the task appropriate for the context, but fail to pay attention to getting it right. Both of these failures generate poor quality outcomes that cause tremendous frustrations for people on the receiving end.

Caring about your work doesn’t mean you love what you do. It has more to do with the sense of pride you derive from producing something of high quality. Your workmanship is an expression of your skillfulness; your mastery of a process or craft. There is a sense of joy felt in exercising your skill.

People may be well-intentioned. I’ve seen many display such quotes as “Amateurs Practice Until They Get It Right; Professionals Practice Until They Can’t Get It Wrong”. Few, however, work to build mastery of a skill or develop a sense of awareness of their environment. To do that you must practice performing a task while being mindful of your context. That is hard.

Even if we don’t get to choose what we do, we can do what needs to be done with uncommon grace.

PDP — Design Verification

Design verification is the process by which we check whether what we designed (design output) matches what we asked for (design input). The concept is simple to state (Figure 1), but it can be incredibly challenging in practice, partly because of the sheer volume of checks that need to be made.

fc-Basic Verification Process

Figure 1. The basic concept of design verification: Did we get what we want?

In my experience, the design effort results in a drawing of the product which can then be used to make a physical prototype (Figure 2). So in verifying the design, we are checking whether the drawing or the prototype meet all the requirements we specified. The processes used for verifying the design range from simple visual inspection to elaborate tests.

FC--PDP

Figure 2. One possible product development process showing where design verification fits in.

Methods of Verification

Visual Inspection It is possible to confirm whether a design contains the required physical attributes through simple visual inspection. Physical attributes include:

  • Material
  • Size
    • Dimensions
      • Length
      • Radius
    • Aspect ratios
  • Shape
  • Color
  • Count of features
  • Surface finish
  • Surface coating

Table 1. The table shows one possible approach to design verification of physical characteristics. Design inputs are specified in the Engineering Requirements column. Design output in this example is the drawing titled B6-32.DWG. The evidence of the verification of a particular characteristic is given by the page number and grid location on the drawing.

t-design verification

Analysis Properties of the designed product may be calculated using physical laws (from Newtonian Mechanics)

  • Weight may be calculated using the design’s volume and material density
  • Deflection may be calculated using methods from Statics/Mechanics of Materials
  • Stress under given loads may be calculated using methods from Statics/Mechanics of Materials
    • Computational modeling such as finite element analysis (FEA) may be used, provided certain requirements are met (see the FDA’s guidance on Reporting of Computational Modeling Studies in Medical Device Submissions)
  • Tolerance Stack Analyses (TSA) may be performed for sub-assemblies and assemblies to determine whether the design conforms to the size requirements
  • TSA’s may similarly be used to determine whether the components of a sub-assembly or assembly fit together

Table 2. The table shows one possible approach to design verification of a property of the design. Design input is specified in the Engineering Requirements column. An engineering analysis report was created to show the calculation of the weight. The evidence of the verification is given by the page and section number of the report.

t-design verification 2

Testing Some aspects of the design will require testing. These include:

  • Biocompatibility
  • Package integrity

Table 3. The table shows a second possible approach to design verification of a property of the design. Design input is specified in the Engineering Requirements column. A prototype was built. The test was performed on it, and a test report was created to show the results. The evidence of the verification is given by the page and section number of the report.

t-design verification 3

Design Verification by Assembly Hierarchy

Now let’s take a step back and look at design verification from a different perspective: that of design hierarchy (Figure 3). Product design can be any combination of components, sub-assemblies, or assemblies. Verification should occur at each hierarchy of the design.

Figure 3. Overall product design can be any combination of components and sub-assemblies.

For example, in the case of an assembly made up of a bolt, a nut, and a washer, my approach to verification would be the following:

Component

Bolt

  • Perform a visual inspection of the bolt drawing to verify the bolt’s physical attributes e.g. size, material, color, etc.
  • Do the engineering calculations using the bolt’s design to demonstrate the bolt’s functional attributes e.g. torsional strength, bending strength, etc.

Nut

  • Perform a visual inspection of the nut drawing to verify the nut’s physical attributes e.g. size, material, color, etc.
  • Do the engineering calculations using the nut’s design to demonstrate the nut’s functional attributes

Washer

  • Perform a visual inspection of the washer drawing to verify the washer’s physical functional attributes
  • Do the engineering calculations using the washer’s design to demonstrate the washer’s performance attributes

Assembly

Nut-Washer-Bolt

  • Perform a visual inspection of the assembly drawing to verify the assembly’s physical attributes:
    • Are the correct bolt, nut, and washers specified?
    • Does the drawing specify the number of each component to be used in a single assembly?
    • Does it show how these components are to be assembled?
  • Perform a tolerance stack analysis of the components to show components will fit together, or build prototypes of each component and perform a test of assembly.

Different aspects of the design are verified at each level of the assembly hierarchy.

The Value of Experience

Experience by itself teaches nothing… Without theory, experience has no meaning. Without theory, one has no questions to ask. Hence, without theory, there is no learning.

― W. Edwards Deming, The New Economics for Industry, Government, Education

fAnd yet I routinely hear people declare “I’ve been doing this for 30 years!” Experience is particular; shaped by chance causes; unique to an individual. It by itself cannot be generalized. To do that you need theory.

Theory links “what” (experience) to “how” (process). It can be tested in diverse circumstances. If it produces expected outcomes, it is useful. It can be shared and used with confidence. Theory builds understanding. Shared understanding, not shared experience, leads to individual empowerment, personal responsibility and accountability, and cooperation.

Declarations like that above are nothing more than chest-thumping meant to discourage inquiry and end debate. Instead of building faith they further mistrust. They ask obedience not understanding. They are an exercise of power and authority. Territorial. Protectionist.

It shouldn’t come as a surprise that people who appeal to experience alone have no credibility with me. I view them as ignorant and hold them in the lowest possible regard.

Discovering Quality – A Personal Journey

I have been asked many times, where do you see yourself in five or ten years? Usually it has been in the context of a job interview or a performance appraisal. Early on when my career was getting started I had no idea, so I answered in vague tentative terms. “I see myself doing what the company needs me to do.” “I see myself in a more responsible role,” whatever that meant. Truth be told, I did not give the future much thought. I was more concerned about the present. I need to start earning a living. Would I get this job? Would they sponsor me for a work visa? Don’t mess up.

One word sums up my early career: naive. For my first job, I was hired as an applications engineer by a semiconductor equipment manufacturer. The company made machines that chip makers used. It had nothing to do with my background in mechanical engineering. I did not know anything about the semiconductor industry, its technology or the company’s products. I did not know how the company was organized. I did not know what my role was about. How did I fit in? What was my function? Who was I supporting? In hindsight, I did not know what it is I even ought to know so I did not know what questions to ask or that I should ask any at all.

The way I dealt with my naiveté and feeling lost was to put my trust in management. Do what I was told. They, of course, had experience that informed their judgment, and good motives, too, didn’t they? On one occasion, I remember clearly, the general manager of my unit saying to me “This isn’t college where someone has mapped a curriculum for you to follow. Figure it out.” I did my best with right intentions, but best efforts and right intentions are not enough when you do not know what to do. For my efforts to be meaningful, for me to be productive, I needed to understand my context. I needed help, and I got lucky.

I was introduced to quality at the midpoint in my career by Samsung. When the company hired me as a quality assurance engineer I had no clue what it was about. But they sent me to their main facility to get training—a huge and impressive campus near Seoul, South Korea. The trip was for five full weeks; every day was spent on training. Part of each day was spent in the classroom being taught quality concepts like viewing work as a process where the next step is the customer, and performing root cause analysis by repeatedly asking “Why?” The rest of the day was spent learning how these concepts were used in practice with basic quality tools like process flow charts, checklists and Pareto charts. I was asked to “walk” and map various processes to understand what was happening and to compare what I found with what was supposed to happen. While I cannot recall my first impressions anymore, I do remember feeling engaged and curious.

Many different teachers were pulled in. These were men and women who had been performing the related functions for a long time. Training with them was intense. Not only was I asked to practice the lessons I was taught, but they would quiz me about what I learned. Sometimes they would know the answers and ask leading questions. Other times they would work with me to find the answers. I returned from my trip with a solid foundation and a context for my work. This was unlike anything in my previous jobs where I did stuff assigned to me without understanding. I had found purpose for my work—why I was doing what I was doing—and with it the joy of doing it.

The trip to South Korea was just the beginning of my education in quality. My manager, a veteran of the Samsung way, insisted on careful observation and deep thinking in my work. For example, in dealing with nonconforming product I was asked to check whether it was a process issue or a measurement issue, whether it was a recurrence of an issue, whether other attributes were also affected, and so on. I was asked to step through the consequences of my observations to determine how such an issue would manifest itself in the final product. My colleagues, short-term expatriates from South Korea, provided daily examples of how to do this through their own practice. It was one of them, as he was studying to take ASQ’s Certified Quality Engineer (CQE) exam, who introduced me to ASQ. In my time with the company, I went through further training that included an eight week course for Six Sigma Green Belt, and a week long course for lead auditor in ISO 16949. The people at Samsung made a heavy investment in my development for which I will forever be grateful.

There is no doubt luck played a crucial part in how I came to discover my context. And that discovery had to be enabled by an outside factor. But much of what has come about since has been through hard work and religious practice. Since my time with Samsung I went on to earn my CQE and CQA through self-study. In studying for those exams I discovered the breadth of scope of quality. It caused me to reframe my context, enlarging it beyond an individual company and traditional boundaries. I learned to view production as a system in Dr. Deming’s Out of the Crisis [1]. This systems view was developed further by Dr. Ackoff’s Redesigning the Future [2], and Peter Senge’s The Fifth Discipline [3]. Dr. Shewhart’s book, Economic Control of Quality of Manufactured Product [4], and Dr. Wheeler’s Understanding Statistical Process Control [5] taught me the ubiquity and nature of variation and how to differentiate between the two fundamental types: common cause variation and special cause variation. I developed a functional understanding of the psychology of human motivation through Daniel Kahneman’s Thinking, Fast and Slow [6], and the Buddha’s “Dhammapada.” And Karl Popper in his The Logic of Scientific Discovery [7] and Thomas Kuhn in his The Structure of Scientific Revolutions [8] showed me how knowledge grows.

I continue to read on the history of the field, the fashions and fads that came and went, its development, its successes and failures, and its challenges. My studying has been non-stop. So has practicing what I have learned. It is now second nature for me to plot the data when I am confronted with a problem; to understand it in its context, and whether it represents a potential signal or just noise. I use checklists as memory supplements everywhere—as daily to-do lists, as lists to define and meet the requirements of an operation or process, and as data collection lists to track frequency. I doodle process maps to understand what is happening or being described.

Quality has had a profound impact on me. It touches every aspect of my life. The ideas that make up the field of quality have helped me develop my observation skills, taught me how to reflect on the observations and understand them, and to then respond to them appropriately. While I am still subject to the vagaries of life, conscious practice of these learned skills has reduced the chaos I introduce to life through my actions. This in turn has improved the outcomes of those actions. And that, I hope, has made some small difference in the lives of those I touch. A trivial example of this is my daily commute to work. I observed that it made no meaningful difference in the time it took whether I actively changed lanes or stayed in the same lane. But the repeated lane changes significantly increased the risk of getting into or causing an accident. It increased everyone’s degree of frustration. It increased my driving effort, and reduced my fuel economy. So I no longer change lanes unless absolutely necessary. I get to work in just the same time, safe and sound, and hopefully so do others.

It will be ten years in 2016 since my fortunate introduction to quality. I could not have seen this is where I would be all those years ago. In the zigzag path my career has taken I have had a chance to work with many different companies in several different industries. I have taken advantage of each opportunity to observe how a company operated, particularly as it related to its employees. When I have come across coworkers, new or experienced, who reminded me of my naive self, I have tried to help them to understand their context and how they fit within it—something my management never did for me. I believe it has helped them to orient themselves, discover their purpose, and labor in a way that bore fruit instead of frustration. That has been most satisfying.

References and Notes

1. Deming, W. Edwards. Out of the Crisis. Cambridge, MA: MIT CAES. 1991. Print. ISBN 0-911379-01-0

2. Ackoff, Russell L. Redesigning the Future: a Systems Approach to Societal Problems. New York: Wiley, 1974. Print. ISBN 0-471002-96-8

3. Senge, Peter M. The Fifth Discipline: The Art and Practice of the Learning Organization. New York: Doubleday/Currency, 1990. Print. ISBN 0-385260-94-6

4. Shewhart, Walter A. Economic Control of Quality of Manufactured Product. New York: D. Van Nostrand Company, Inc, 1931. Print.

5. Wheeler, Donald J, and David S. Chambers. Understanding Statistical Process Control. Knoxville, Tenn: SPC Press, 1992. Print. ISBN 0-945320-13-2

6. Kahneman, Daniel. Thinking, Fast and Slow. New York : Farrar, Straus and Giroux , 2011. Print. ISBN 978-0-374275-63-1

7. Popper, Karl R. The Logic of Scientific Discovery. New York : Basic Books, Inc., 1959. Print.

8. Kuhn, Thomas S. The Structure of Scientific Revolutions. Chicago: University of Chicago Press, 1970. Print. ISBN 0-226458-04-0

The Weekly Meeting

Monday afternoons at two-thirty. That was the time for our weekly staff meeting. When I joined the company everyone was required to attend it: engineers, technicians and operators. The head of our department, the Director of Quality, led it.

It was a rare week when the meeting started on time. Mondays were also when we had our one-on-one meetings with the Director and he had one of those exchanges going on right before our staff meeting. It always went over. So several of us would gather and wait outside of the meeting room until we were noticed and motioned to come in.

Even with this routine delay I don’t remember a single week when everyone was present before the meeting started. There was frequently at least one person who creeped in late. It wasn’t always the same person either. Some late comers might put on an apologetic face at times, but a few were shamelessly indifferent of their indiscretion.

Just as the meeting never started on time, it didn’t end on time either. I recall a few occasions when I wondered whether the meeting actually ended.

The Director got our meeting going by sharing a subset of the highlights and lowlights of the previous week that he gets in an email from the corporate overlords. We cheered the highlights and bemoaned the lowlights even though none of us could draw a connection to any them with the specific work we did. They did not prompt any actions for our department. They were also divorced from similar points shared in the previous week; presented as stand-alone bits of information. On those occasions when someone did make a tentative connection, it unleashed pent up frustrations with people feeding off of each other to blame some nonpresent “they.” So what purpose did this update serve? I couldn’t tell you.

Following the update, the Director shared his schedule for the current week. It always showed back-to-back meetings, sometimes overlapping, from the start of the workday to its end, for the whole week. So when did he have time to think and plan, to draw up an agenda for his meetings, to follow-up on assignments, to analyze, understand, and guide the performance of the system he was charged to direct? At first I had felt sympathy. What sort of monstrous organization drives its people like this? But it didn’t last long. I recognized much of it was self imposed and not a demand of the organization. It was his way of showing others how busy and engaged he was, how hard he was working, how committed he was to the company. It was all light and no heat. Perhaps I’m being harsh, but I don’t think so.

After he finished his update he would ask each staff member if they had anything to share. Most did not. Some, though, shared information on what they were doing in excruciating detail. Usually it was about “unexpected” hurdles, blocks, or breakdowns. They were the same from week to week. This was another opportunity to vent about those others who didn’t follow procedures, the unreasonable surge in demand for our services, or how the system is broken and needs fixing. Who is going to fix it? How should it be fixed? What resources are needed for the fix? That requires a plan. But when is there time and space for that?

Once a month the Director would remind everyone to calculate and report metrics they were responsible for. It shouldn’t come as a surprise that at least one was delayed. Not always the same one, but it came with all the usual excuses.

That was the ritual.

Hiring the Best and Brightest

Companies have been proudly proclaiming that they hire only the best and brightest. Ignoring the fact that this is a bogus claim – personal experience at a dozen different companies has demonstrated otherwise – a firm would find it all but impossible to function with the best and brightest.

Back in 1994 Dr Russell Ackoff shared an example that elegantly explains why.

I read in the New York Times recently that 457 different automobiles are available in the United States. Let’s buy one of each and bring them into a large garage.

Let’s then hire 200 of the best automotive engineers in the world and ask them to determine which car has the best engine. Suppose they come back and say Rolls Royce has the best engine. Make a note of it.

“Which one has the best transmission?”, we ask them and they go run tests and come back and say the Mercedes does.

“Which one has the best battery?” [They] come back and say the Buick does.

And one by one, for every part required for an automobile, they tell us which is the best one available.

Now we take that list and give it back to them and say “Remove those parts from those cars. Put them together into the best possible automobile,” because now we’ll have an automobile consisting of all the best parts.

What do we get? You don’t even get an automobile, for the obvious reason that the parts don’t fit!

The performance of the system depends on how the parts fit, not how they act taken separately.

A significant portion of organizational excellence depends on how employees interact with one another i.e. how they fit together, not how they act individually.

Dr. Ackoff’s entire talk titled “Beyond Continual Improvement” is worth listening to.

Targets Deconstructed

“Eliminate numerical goals, posters, and slogans for the work force, asking for new levels of productivity without providing methods.”

— Point No. 10 in Dr. W. E. Deming’s 14 points for management as written in “Quality, Productivity, and Competitive Position.”

A few weeks ago I had an excellent exchange on Twitter with UK Police Inspector Simon Guilfoyle on the topic of setting numerical targets. He asked “How do you set a numerical target without it being arbitrary? By what method?” Unfortunately, Twitter’s 140 character limit isn’t sufficient for adequately answering his question. I promised him I would write a post that explained my thinking.

When I was working for Samsung Austin Semiconductor (SAS) as a quality assurance engineer, one of my assigned responsibilities was to manage the factory’s overall nonconforming material rate. Over the course of my second year, the factory averaged a four percent* nonconforming material rate. The run chart for the monthly nonconforming material rate showed a stable system of variation.

As the year drew to a close, I began thinking about my goals for the following year. I knew I would continue to be responsible for managing the factory’s overall nonconforming material rate. What should I set as my target for it? Not knowing any better, I set it to be the rate we achieved for the current year: four percent. If nothing else, it was based on data. But my manager at the time, a Korean professional on assignment to the factory, mockingly asked me if I wasn’t motivated to do better. He set my target at two percent*; a fifty percent reduction.

What was the two percent number based on? How did he come about it? I had no insight and he didn’t bother to explain it either. From my perspective, it was an arbitrary numerical target; plucked out of thin air. I remember how incredibly nervous I felt about it. How was I going to achieve it? I had no clue nor guidance. I also remember how anxiety filled and frustrating the following year turned out for me. I watched the rate with a hawk eye. I hounded process engineers to do something whenever their process created a nonconforming lot. It was not a pleasant time for anyone.

Since then I’ve worked at several other companies in different industries. Nevertheless, my experience at SAS seems to be the norm when it comes to setting targets. This is regardless of the role, the industry or the culture. And, as far as I’ve been able to figure out, this approach to setting targets is driven more by tradition and arrogance than any objective thoughtful method. “Improve performance by 50% over last year!”, so the mantra goes. Worse still, no method is provided for achieving such arbitrary improvement targets. I’ve been told “You’re smart. You’ll figure out how to do it.”

So it’s not a surprise for me that folks like the good Inspector have become convinced all numerical targets are inherently arbitrary; that there is no objective and justifiable way to set them. Having been on the receiving end of such targets many times, I used to think the same, too. But just because people don’t know of a different way to set a target, one that is objective and can be justified, doesn’t mean there isn’t one. I believe numerical targets can be set in an objective fashion. It, however, requires thoughtfulness, great effort and understanding on the part of the person setting the target.

One way to set a target is to use the performance of a reference for comparison. In my case, the SAS factory I worked at had a sister facility in Korea. It would have been reasonable, albeit crude, to set my target for the nonconforming material rate to that achieved by the sister facility (if it was better.**) An argument could have been made that the target was achieved elsewhere, so it can be reached.

As part of our Twitter exchange, the Inspector made the point that regardless of whether these factories were defined to be sisters, there would still be differences between them. Therefore, they will generate a nonconforming material rate that is a function of their present system architecture. He is absolutely right! Setting a target for my factory based on the performance achieved by its sister facility alone will do nothing to improve the performance of my factory. It’s already doing the best it can.

But that’s not the point of setting the target: to operate the same system and expect an improved performance. The point of setting the target is to trigger a change in the system, a redesign in such a way as to achieve a level of performance that, in this case, has been achieved elsewhere. The sister system can be treated as a reference and studied. Differences between systems may be identified and eliminated. Along the way we may find out that some differences cannot be eliminated. Nevertheless, by eliminating the differences where possible the two systems are made more similar to one another and we will have improved the performance.

In the absence of a reference, simulations may be used to objectively define a target. The factory’s overall nonconforming material rate is the combined result of the nonconforming material rates of its individual processes. Investigating the performance of these inputs can help identify opportunities for improvement for each: stabilizing unstable processes, running stable processes on target, reducing the variability of stable on-target processes. All of this can be simulated to determine what is ideally possible. A justifiable target for the nonconforming material rate can then be set with the results. Best of all, the method by which it can be achieved gets defined as part of the exercise.

Finally, targets may be set by the state of the greater environment within which a system operates. All systems operate in a greater environment (e.g. national or global economy); one that is continuously changing in unpredictable ways. City populations grow or shrink. Markets grow or shrink. Polities combine or fragment. What we once produced to meet a demand will in a new environment prove to be too little or too much. A change in state of the external environment should trigger a change in the target of the system. A change in the target of the system should trigger a redesign of the system to achieve it. In Systems lingo, this is a tracking problem.

Targets are essential. They help guide the design or redesign of the system. They can be defined objectively in several different ways. I’ve outlined three above. They do not have to be set in the arbitrary way they currently are. But setting targets isn’t enough. Methods by which to achieve them must be defined. Targets, even objective ones, are meaningless and destructive without the means of achieving them. Failure to achieve targets should trigger an analysis into why the system failed. They should not be used to judge and blame workers within the system.

Sadly, people are like water, finding and using the path of least resistance. Setting arbitrary improvement targets is easier than doing all the work required to set objective ones. They have been successfully justified on the grounds of mindless ambition. No one questions the approach out of fear or ignorance. Positional authority is often used to mock or belittle the worker for not being motivated enough when the truth is something else: managerial ignorance and laziness to do their job.


* I’ve changed the numbers for obvious reasons. However, the message remains the same.

** As it turned out, the nonconforming material rate achieved at my factory was the best ever in all of Samsung!

 

Quality Is The Problem

Last month I asked “How are you, as a Quality professional, perceived?” in several LinkedIn discussion groups. I hoped to understand what we thought others thought of us. I wanted a qualitative measure of our awareness.

I parsed 108 comments from 55 people. Of them, 30 felt they were perceived poorly, 17 were ambivalent, and 8 felt that others viewed them favorably. The comments fell into one of the following categories:

(+) Consultant/Improvers
(-) Fear/Loathe
(-) Cops/Surveillance
(-) Barriers/Bottlenecks
(-) Necessary Evil/Imposed Cost
(-) Hard to Understand

It appears we, Quality professionals, are very aware. We are sensitive to what others think of us. That is the good news. The bad news, however, and it is really bad news, is that we seem to think others consider us a serious drag on business.

I wondered if such harsh self-criticism was just an issue of poor self-esteem, but I don’t think it is. Based on my observations and experience, I find it to be a fair assessment of how others view us. Even we hold such views of other fellow Quality professionals.

But hold on second. That is not what our profession is about. We are not supposed to be drags on business. We are supposed to be the people that help the makers make things better, faster, stronger.

So where are we going wrong?

If the definition of quality has to do with meeting or exceeding the expectations of the consumer, first we need to understand who is the consumer of the services that Quality professionals offer. Isn’t it our employer? The end user isn’t paying for what we do. Next we need to understand what are the consumer’s expectations. How many of us really understand our employer’s wants? (Try not to substitute in what you think the employer should want with what the employer actually wants. Also, let’s get real, most companies’ Quality Policy is just a set of platitudes.) Finally, we need to evaluate our efforts in the context of what our employer wants.

In this light, do the results our actions as Quality professionals conform to the requirements of our employer? If not, aren’t we imposing a loss on our employer, to use Taguchi’s term? And, from the looks of the categories above, it is not an insignificant loss. Contrary to our purpose, we are generating suffering through our actions!

It is not the role of the Quality professional to set the objectives for the company. It is our role in the service of our employer to provide options on how best to meet those objectives. It is not the role of the Quality professional to choose the ‘best’ option. It is our role to help execute our employer’s choice in the most effective way. I think it would serve us well to get off of our high horses and stop thinking of ourselves as saviors. The sooner we start cooperating with others – being of service to them instead of demanding actions from them – the better we will all be.

References

How We Look For A New Law

In general we look for a new law by the following process. First we guess it. Then we…Now don’t laugh. That’s really true.

Then we compute the consequences of the guess to see what…if this is right…if this law that we guessed is right we see what it would imply.

And then we compare those computation results to Nature. Or we say compare to experiment or experience; compared directly with observation to see if it works.

If it disagrees with experiment, it’s wrong. In that simple statement is the key to Science. It doesn’t make a difference how beautiful your guess is; it doesn’t make a difference how smart you are who made the guess, or what his name is. If it disagrees with experiment, it’s wrong. That’s all there is to it.

— Richard Feynman