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In the sixth chapter of their book Six Sigma:  The Breakthrough Strategy Revolutionizing the World’s Top Corporations, by Ikel Harry, Ph.D., and Richard Schroeder, called “Unmasking the Hidden Factory,” the authors discuss the metric called “yield”.  The basic concept of yield is that it takes the number of units that leave an inspection point after passing inspection, called the “output”, and divides it by the number of units that enter that particular inspection point, known as the “input”.   So if 100% of the units pass, the yield is 100%, but if only 50% of them pass, the yield is 50%.   This is sometimes referred to as “first-time yield” if the yield is measured at the first point of inspection.   The “final yield” would be, in contrast, the yield measured after the final point of inspection.

What is the problem with this metric?   Well, the problem with is that not all yields are created alike.   From a quality perspective, the total defects per unit is a better measure of the quality of a unit.   If 50% of the units of product A and product B are found to have at least one defect, then the yields would be considered the same.    But a better metric comparing product A and product B would be the total number of defects per unit (TDPU).   So if product A has 2 defects per unit and product B only has on average 1 defect per unit, then product B has higher quality.

First-time yield therefore does not give an indication of quality as reliable as the TDPU.   Another way that it is not a reliable indicator is the factor that, if an inspection shows that 5 out of 10 units contain defects, and the inspector throws out the 5 defect-containing units, then someone down the line may think, “wow, all of the units coming out of the last inspection point are defect-free; we must be doing high quality work!”   Unfortunately, this is only if the cost of the 5 scrapped units are not taken into consideration.

So that is why it is important to have a good metric of “yield”, because not all yields are created alike.

The next post goes into more detail about the difference between first-time yield, the total number of units with one or more defects, and throughput yield, the total number of defects per defect opportunity.

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In the sixth chapter of their book Six Sigma:  The Breakthrough Management Strategy Revolutionizing the World’s Top Corporations, the authors Ikel Harry, Ph.D. and Richard Schroeder bring up a fascinating concept of the “Hidden Factory.”

What is a factory?  It is a place where things are made.   Theoretically, the materials and staff in the factory should all be engaging in processes which either directly involve manufacturing or indirectly support those efforts.    However, the problem with a company that is producing products and services at quality levels of four Sigma or lower is that a lot of its time and attention are focused on detection and correction of defects.   The correction may involve reworking those products that contain defects, or it may involve scrapping those products if they are beyond repair.   Those processes in a factory that detect and correct mistakes made during the originally conceived manufacturing process are termed “the hidden factory.”   They are called “hidden” since these processes for correcting mistakes are not part of the original plan for the factory.

Whether planned for or not, the costs associated with these processes, whether they cover the extra material and labor costs involved, end up hurting the bottom line of the company.   Those companies that base their financial strategy on the profitability of the factory will find that those strategic targets may end up not being met because of the unanticipated costs created by the hidden factory.

So it should be the goal of every company that runs a factory where the processes are the level of four Sigma or lower to unmask the hidden factory.   Unmasking it is the first stage in dismantling it, and how to unmask it is the subject of the next post.

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In their book Six Sigma:  The Breakthrough Management Strategy Revolutionizing the World’s Top Corporations, Ikel Harry, Ph.D., and Richard Schroeder discuss the topic “Changing What Companies Measure” in chapter six.

In the last post, I discussed the importance of CTQ or Critical-to-Quality characteristics and how they need to be linked first and foremost to customer satisfaction, and then to the processes which a company needs to focus on improving in order to increase quality.   Again, it is important to remind the readers that the common sense of the meaning “quality”, that is, the absence of defects, is a necessary but not sufficient condition for quality.   Meaning that yes, the product has to be defect-free, but it also has to be what the customer wanted.   Necessary but not sufficient means that if the product is defect-free, but is not what the customer wanted, then the customer won’t buy it.   So “quality” in the world of manufacturing has to mean “a product the customer wants which is free of defects.”

The purpose of this post is to delve a little more deeply into what “customer satisfaction” means.  There are three areas:

1. Products that are high-quality (no defects and in line with customer requirements)
2. Products that are delivered on time
3. Products that are at the lowest possible cost (while being consistent with 1 and 2)

Why is this important for companies to focus on?   Many companies focus on quantities like “production time”, or how fast the products are being put through the manufacturing line, which do not correlate with 1, 2 or 3 above.   One of the famous scenes in the I Love Lucy series is the one where Lucy and Ethel decide to get a job in a chocolate factory.   They do okay during the first line test, so the supervisor yells “SPEED IT UP!” and it goes so impossibly fast that the hapless pair end up cramming the chocolates into mouths, pockets, and anywhere they can in order to make sure none of the chocolates end up going unwrapped through the conveyor belt to the next station.    The chances that some chocolate may have defects in them (like Lucy and Ethel’s teeth marks) has been increased by the unreasoning “need for speed” on the part of the supervisor.

And just because the chocolates are shooting out of the conveyor belt at lightning speed doesn’t mean they’ll get to the customer on time, because that will depend on delivery trucks, etc.    And the fact that there may need to be some “rework” on the assembly line will increase the cost of the product, not decrease it.

So this is an example of how the company is focusing on something that impressed the supervisor and may even impress someone in the board room but does not correlate to customer satisfaction in any way, shape or form.   Although this is a ridiculous example taken from a classic comedy show, the authors assure us that there are examples such as ridiculous out there in the world of manufacturing, with one difference:   the stories told by those companies more often as not end up not being comedies, but tragedies.

In the last post on this chapter, the authors talk about the difference between product technology and process technology, which is why many inventions created in America, from the transistor back in the 1950s to the fax machine in the1960s, were only made profitable by the Japanese.   This culture difference is the subject of the next post.

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In their book Six Sigma:  The Breakthrough Management Strategy Revolutionizing the World’s Top Corporations, the authors Ikel Harry, Ph.D., and Richard Schroeder discuss in chapter six the issue of changing what it is that companies measure.   One of the ways that companies can “measure” customer satisfaction is with a set of characteristics called “CTQ” or Critical-To-Quality.

Archimedes, the Greek mathematician and engineer, once said “Give me a lever long enough and a fulcrum on which to place it, and I shall move the world.”   In the world of manufacturing, you want to be able to move customer satisfaction, because that is what will get the customers buying your product and making your company profitable.

In the world of quality, the lever with which you move customer satisfaction is “CTQ” or “Critical-To-Quality” characteristics.   These are the characteristics which correlate with customer satisfaction.   And where is the fulcrum, the place you position the lever?   That is determined through Six Sigma–you have process metrics which reflect how well your processes are creating products and services which meet the CTQ characteristics and thus have a positive impact on customer satisfaction.

The problem is “satisfaction” is a quality internal to the customer, and so you must interpret what features in the external world correlate to that inner sense of satisfaction.   This is where skillfully written surveys, or even better yet, focus groups come into play.   Sometimes the customer cannot articulate what it is about a product that moves him or her to buy it, because the features may trigger some unconscious reaction that the customer, by definition, is not consciously aware of.

Note that creating a defect-free product, which is what people normally think of as “quality”, is a necessary condition for a product to create customer satisfaction, but it is not a sufficient condition.   In other words, if a product has no defects but is not what the customer ordered, well then the customer isn’t going to buy it no matter how defect-free it is.

So the key here is make the following links:

customer satisfaction ↔ critical-to-quality characteristics ↔ manufacturing and/or business processes

Companies who either don’t find out the CTQ characteristics that correlate to customer satisfaction, or who don’t correlate their process improvement with those same CTQ characteristics are going to find that their “quality wheels are spinning without any traction.”

To go into this matter further, let’s discuss the “customer satisfaction” part of the equation in more detail, which I will do in the following post.

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In the last post, I mentioned that the authors Ikel Harry, Ph.D., and Richard Schroeder of the book Six Sigma:  The Breakthrough Management Strategy Revolutionizing the World’s Top Corporation were extolling the value of metrics to be able to reveal the hidden cause “X” of the outcome “Y”.

I wanted to expand this basic concept of Six Sigma by mentioning that the outcome “Y” is what can be observed in the product, so that when you are inspecting a product, you are looking at outcome “Y”.   Obviously, if outcome “Y” contains defects, you want to get rid of them.   But you don’t focus on Six Sigma on changing “Y”.  What you do is you focus on the process “X” which is somehow causing “Y”.

Sometimes you have to go through a process of elimination, where you end up formulating hypothesis and hypothesis that posits a series of processes as the hidden culprit, only to find that changing them doesn’t make the defects in “Y” go away.  In that way, it’s like if you were in a sculpture class, and the instructor gave you a block of marble and said “carve a copy of this statue of an elephant.”   If you say “I don’t know how to carve an elephant,” he may say, “well, then take the block of marble and chip away everything that isn’t an elephant.”

In a sculpting class, that may not be practical advice, but in the Six Sigma world, proving hypotheses to be false (chipping away those parts that are not the problem) may end up revealing or hinting at those hypotheses that end up being true.

But you will only get to that correct hypothesis by focusing on the various processes that produce the product.   And that is why Six Sigma is said to test the process.    Since you cannot test a process directly, you have to test it indirectly by studying what effect changing it has on the visible product “Y”.

So it is an excellent tool for detection–but only if you first know where to look and what you are looking for!

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Why are metrics important in Six Sigma?   According to the authors of the book Six Sigma:  The Breakthrough Management Strategy Revolutionizing the World’s Top Corporations, Ikel Harry, Ph.D., and Richard Schroder, metrics establish the difference between perception, intuition, and reality.

Let’s say there is some problem that is causing defects, a problem that is detected by an inspection process.   That outcome is referred to as “Y”.   Now let’s say that engineers get together and brainstorm to find out what the potential cause is of that visible problem, and let’s call that potential cause “X”.   In order to change the outcome “Y”, you have to change the potential cause “X”.

The Six Sigma process focuses on the potential cause “X”.   Let’s say the engineers mentioned in the paragraph above change the process so as to change the potential cause “X”, and then they see if the outcome “Y” occurs.   If “Y” still occurs, then despite their intuition that “X” caused “Y” to occur, they have found through the Six Sigma process that “X” did not indeed cause “Y” as they believed.   It separates the intuition they had about where the problem was and the reality of where it wasn’t.   That’s obviously not the end of the story, because now the engineers have to go back to the proverbial blackboard and figure out a different culprit for the hidden cause of the visible outcome “Y”.

This means that, once the hidden cause “X” is found, changed and then proved via statistics that it also changes the outcome “Y”, then this means that engineers have found a correlation between the two.   Wow, that means they are done, right?

Not necessarily!   It is possible that “X” and “Y” are BOTH caused by some other hidden variable, which we shall call “Z”.  Let me tell you a story to illustrate.   I remember in an Introduction to Psychology course back in college that the teacher was trying to explain the principle that “correlation is not causation”.   He showed a graph which was taken by a census of a lot of French rural towns where the X-axis had the number of storks cited in a given year in the town, and the Y-axis had the number of babies born in that same town during that given year.   The graph showed an almost perfect correlation between the two:   as the number of storks cited in the town increased, so did the number of babies reported being born!

Someone might look at these two variables and to speculate that somehow the storks are causing the birth of the babies, as told in folk legend and the Warner Brothers Looney Tunes cartoon “The Apes of Wrath”, where a drunken stork mistakenly delivers Bugs Bunny to an expectant couple of gorillas (with hilarious consequences).

Well, I puzzled over the problem for a few seconds and them remembered a factoid I learned in French class, that in rural France, storks often make their nest in the chimneys of houses.   And so if there are more houses, there are more storks.  And also if there are more houses, there are more families, and therefore more babies.   So the “stork” variable and the “baby” variable were both independent of each other, but dependent on the variable of “houses”, and that’s why they seemed to go up together.   Not because one was causing the other, but that both were being caused by something else in the same way.

I mentioned my hypothesis to the teacher, and he said that not only was I right, but I was the only was in all of his three classes to get the answer right.   But it was only because I understood the concept he was trying to get at, AND I had a piece of information that the students didn’t possess, mainly the correlation between the storks (a variable mentioned in the problem) and the houses (which was not mentioned in the problem).   Knowing this made me solve the problem and uncover the secret “cause” of the higher number of babies:   not their conveyance via stork, but their parents’ accommodation with additional houses.

This shows that metrics, if properly understood and used, can reveal secrets that may remain hidden otherwise.   And that is only one reason for their adoption by companies as tools for measurement and change.

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According to the authors Ikel Harry, Ph.D., and Richard Schroeder in the fifth chapter of their book SIx Sigma:  The Breakthrough Management Strategy Revolutionizing the World’s Top Corporations, Six Sigma is a tool for changing the processes that companies use to create their products or services in order to improve their quality.

However, there is two caveats to this statement.    In order to change a process, you have to be able to measure it.   Also, improving quality does not mean getting rid of defects.   A defect-free product which a customer does not want is not going to be sold.    So what companies need to do is measure their customer’s opinions, and then to link those measurements of the customer’s requirements to a company’s processes.

How do companies fail at this central task?    Some don’t measure quality accurately in the sense of quantitatively capturing their customer’s opinions.   Some take these measurements of quality but don’t follow them up to make sure that the customer’s requirements are linked to a company’s processes.    Some fail to describe their processes in terms of numbers, rather than words.

The author’s basic credo (listed in italics in the first paragraph) has a negative corollary:  if you don’t understand your processes quantitatively, you can’t control them.   These processes have to be correlated with a customer’s opinions, as mentioned above, but they also have to be correlated with the company’s fundamental economics.   This is the only way to make sure that a company’s business case for producing the product is solid.

How are processes described quantitatively?   By the use of metrics, which are discussed in the next post.

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In the fourth chapter of their book Six Sigma:  The Breakthrough Management Strategy Revolutionizing the World’s Top Corporations, Ikel Harry, Ph.D. and Richard Schroeder discuss the issue of benchmarking:   what it is, why companies should benchmark, what categories of benchmarking exist, and how Six Sigma methods can assist in benchmarking.   All of these topics are discussed in previous posts.

The final topic of the chapter is:  having discussed the various types of benchmarking and their methods, what specifically do the authors recommend that a company should benchmark?   Here are their suggestions of topics to consider:

1.   Customer satisfaction

2.   Internal areas of competition (between divisions)

3.  External areas of competition

4.  Major cost drivers

5.  Easily improved processes

6.  Product characteristics (to differentiate yours from those of competitors)

7.  Critical-to-quality characteristics (CTQs)

No matter what you choose to benchmark, the authors agree on one thing:   it has to be something that the company does on a continuous basis.   Why?   The purpose of benchmarking is to improve your company and its processes.  But just remember, other companies are improving their processes at the same time.   Your competitors are (or should be) moving targets!

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