Competitive strategy as a concept has been around for centuries.  A person selling an item similar to that sold by another can compete on price, by selling it for less money.  Perhaps the seller may try to compete by adding extras, gift-wrapping, for example.  Technical companies compete by being technology leaders and being on the cutting edge of new developments.  There are no end to methods to compete.  But some methods are more effective in the long run than others.

It is not a mistake that Deming’s first published book on the subject was entitled “On Quality, Productivity and Competitive Position”.  In the book, he sets forth the reasons why emphasis on quality leads to productivity improvement and how that is a very effective competitive strategy in the long run.  Phil Crosby in the early 80s in his book, “Quality is Free” pointed out that improving quality lowered cost.  But Deming had shown this to the Japanese  30 years earlier.  And, Deming pointed out the benefits of developing a competitive strategy based on quality.

One of the problems in talking about quality is that many people have pre-conceived notions of quality is.  For some it is meeting specifications.  Joseph Juran defines it as ‘meeting customer requirements’.  Zero Defects was Crosby’s nostrum, but is really just another way of saying quality is meeting specfications.

Deming’s ideas are much broader than that and are, perhaps, best captured with the phrase ‘continual improvement’.  This term connotes the ongoing nature of the strategy.  According to Deming, quality is not a state to be achieved in manufacturing, but is, rather, an ongoing company-wide effort at continual improvement.  What Bill Conway called “the process - the way everyone thinks, talks, works and acts every day.”

Whether or not this is a successful strategy is, in my opinion, not arguable.  One has only to look at the automobile industry for clear proof.  After all the nonsense is stripped away, the fact is that Japanese automakers (Toyota, Honda and Nissan) make better cars than American automakers (GM, Ford and Chrysler) and have done now for years.  Buyers are not idiots.  They understand value, and and realize that better quality at the same or lower cost is excellent value.  End of story.

But the implications of the story are not just confined to the auto industry.  Cameras, computers, appliances, power tools, earthmoving equipment, and more have fallen from America’s basic manufacturing industries to a legacy of plant closings, job losses and dwindling revenues and profits.

Deming’s re-write of his first book on competitiveness was called “Out of the Crisis”.  What crisis one may ask?

This one.

Each category could have several points made about it and, as time allows, I’ll go into some detail on each of them in the coming days and weeks.

• Quality as Competitive Strategy- The Chain Reaction

• Market Surveys - Living with the Customer

• Quality equals continuous improvement - Not just meeting requirements

• Statistical/Scientific Thinking - Vital to improvement

• Top Management Responsiblity - “Quality starts in the Board Room!”

• Knowledge as the basis

• Not ‘Instant Pudding

Deming’s System of Profound Knowledge

• Theory of Systems

• Theory of Variation

• Theory of Knowledge

• Theory of Psychology

AND

* The Interactions therefrom

Deming’s Psycho-Social Focus

• Joy in Work - There is a birthright to joy in work.

• Beat down the Societal Forces of Destruction

• Win/Win - Do away with win/lose competition

* Need any Country be Poor - Management and Poverty

AS I PASS through my incarnations in every age and race,
I make my proper prostrations to the Gods of the Market Place.
Peering through reverent fingers I watch them flourish and fall,
And the Gods of the Copybook Headings, I notice, outlast them all.

We were living in trees when they met us. They showed us each in turn
That Water would certainly wet us, as Fire would certainly burn:
But we found them lacking in Uplift, Vision and Breadth of Mind,
So we left them to teach the Gorillas while we followed the March of Mankind.

We moved as the Spirit listed. They never altered their pace,
Being neither cloud nor wind-borne like the Gods of the Market Place,
But they always caught up with our progress, and presently word would come
That a tribe had been wiped off its icefield, or the lights had gone out in Rome.

With the Hopes that our World is built on they were utterly out of touch,
They denied that the Moon was Stilton; they denied she was even Dutch;
They denied that Wishes were Horses; they denied that a Pig had Wings;
So we worshipped the Gods of the Market Who promised these beautiful things.

When the Cambrian measures were forming, They promised perpetual peace.
They swore, if we gave them our weapons, that the wars of the tribes would cease.
But when we disarmed They sold us and delivered us bound to our foe,
And the Gods of the Copybook Headings said: “Stick to the Devil you know.”

On the first Feminian Sandstones we were promised the Fuller Life
(Which started by loving our neighbour and ended by loving his wife)
Till our women had no more children and the men lost reason and faith,
And the Gods of the Copybook Headings said: “The Wages of Sin is Death.”

In the Carboniferous Epoch we were promised abundance for all,
By robbing selected Peter to pay for collective Paul;
But, though we had plenty of money, there was nothing our money could buy,
And the Gods of the Copybook Headings said: “If you don’t work you die.”

Then the Gods of the Market tumbled, and their smooth-tongued wizards withdrew
And the hearts of the meanest were humbled and began to believe it was true
That All is not Gold that Glitters, and Two and Two make Four
And the Gods of the Copybook Headings limped up to explain it once more.

As it will be in the future, it was at the birth of Man
There are only four things certain since Social Progress began.
That the Dog returns to his Vomit and the Sow returns to her Mire,
And the burnt Fool’s bandaged finger goes wabbling back to the Fire;

And that after this is accomplished, and the brave new world begins
When all men are paid for existing and no man must pay for his sins,
As surely as Water will wet us, as surely as Fire will bum,
The Gods of the Copybook Headings with terror and slaughter return!

In a predictive model there are typically what statisticians call ‘main effects’. A good example in medicine is the effect of particular medications. But sometimes medications in combination potentiate (or neutralize) each other. In other words there is another effect caused by the combination of medicines that changes the outcome. That is the idea of an interaction. A catalyst in a chemical reaction might be another example.

One of the aspects of systems is that the parts of them interact. So it is with SOPK. Each of the pillars interacts with the others to produce effects that none produces alone. Marc Hersch’s continuing references to reductionist thinking is getting at this point. The “System of Profound Elephants” is a metaphor for the fact that one cannot understand an elephant to be a collection of components.

Consider a pile of sand. With a shovel you can divide it in two and have two smaller piles of sand. Cutting a cow in two does not produce two small cows.

Consider an example Deming loved to use; that of the symphony orchestra. An orchestra is not a collection of soloists. Two orchestras can play the same piece with the composition of the orchestra being the same and every note played being identically, but what a difference there can be. It’s how they play together that makes a difference. That is, it’s the sound of the individual and the interaction of the components that creates the sound.

On a more mundane level we can have team working on a task. A new member is added and suddenly the team’s progress accelerates markedly. A positive interaction at work. Or a different team after adding a person suddenly grinds to a halt. It’s how the team (a system) works together. The first instance we call “Good chemistry”.

Successful managers understand these interactions, how they work and they manage them as well as the main effects.

Using that model we can see that in a Normal Distribution approximately 31.73 of the values fall between plus and minus one standard deviation from the mean (average). So, for example, if the average height of a group of school boys is 155cm and the standard deviation is 5cm, we would expect a little over 68% of the boys to fall between 150cm and 160cm if height is normally distributed. We can go a bit further and say, if height is Normally distributed, the chances of beingOn the horizontal axis is the measure of interest (if we were studying height of kids it might be height in centimeters). In this depiction the average of the measurements is set to zero and the spread is measured as plus or minus one, two and three standard deviations. The vertical axis represents the frequency of occurrence of a particular point on the curve. The highest point, the average, is the one that occurs most often and as one moves away from the average, the frequency of occurrence decreases. Because this is a theoretical model, the tails (the extreme left or right points) are asymptotic; that is, they don’t touch. This is an important distinction between theoretical curves (such as the Gaussian or Normal Distribution) and the real world.Each statistic used to test hypotheses has a probability distribution associated with it.

It is from that distribution that probability distribution that we make our decision as to the sufficiency of evidence of an experimental effect.Recall that we originally formed two hypotheses, the research hypothesis (what we think the effect will be of our action) and the null hypothesis which states that there is no effect at all. We likened the hypothesis testing logic to that of the court room where the burden of proof rests with the person (organization) making the assertion of an effect That is, enough evidence of an effect (guilt) must be presented to cause us to reject the “no effect” starting assumption.The hypothesis is tested in a study or experiment and a numerical estimate of an effect is produced. For example if two suppliers are to be compared as to the relative quality of their products, a sample from each supplier might be obtained. The samples are measured and an average value calculated for the sample from each supplier. The null hypothesis might be that there is no difference between the two suppliers. The means are compared and a difference is calculated and a test statistic (in this case “t”) is generated.

There is, as we said, a sampling distribution for the statistic t. A probability distribution has been created showing the frequency of occurrence for different values of ‘t’ that would be obtained when repeated samples have been drawn from the same population. That is, when the null hypothesis is true. This is important. Our value for t is compared with values for t obtained when the samples are drawn from the same pool. That is, we know they are not from different samples; the null hypothesis is true by definition.There are as we said, two mistakes that can be made. We can say that the two suppliers are different when they really aren’t or we can fail to say they are different when they are.

We can set the probability of making the first type of mistake as the cut off point at which we will decide there is sufficient evidence to assume there is some experimental effect.Thus if we have a t value that has less than a 1% of occurring when the null hypothesis is true, we will say that this occurrence is unlikely and we’ll reject the hypothesis as being very unlikely. How unlikely? We’d expect a difference this large (or larger) less than 1 time in 100 occurrences.

Does that mean that the alternative hypothesis is correct? Not at all. It means that according to the criteria we set for evidence we have rejected the idea that the difference between the two means is due to chance. We could be wrong…in fact if we do enough of these types of comparisons, we will be wrong.Are we wrong in this case? If we had enough information to answer that question, we wouldn’t need to do the test.