Saturday, August 10, 2024

theory of variation (W. Edwards Deming)

 
 
 
 
[[ read this, specially as related to the understanding of variation (theory of variation) ]]
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 carburetor makers, quartz movement watch

carburetor makers

https://en.wikipedia.org/wiki/Carburetor
 
https://en.wikipedia.org/wiki/Fuel_injection

quartz movement watch

What happened to the carburetor makers? The paradigm shifted. A paradigm is a working model of beliefs or assumptions used to define and limit parameters of a given approach to a system or process. The carburetor makers’ paradigm was limited to the carburetor being the only way to mix the fuel and air. Past success is no guarantee of future success when the paradigm shifts. Innovation is usually what causes the paradigm to shift. In Switzerland, the Swiss watchmakers failed to realize the impact of the quartz movement watch, even though it was invented by the Swiss. The result of this paradigm shift was the Swiss watchmaker work force dropped from 65,000 to 10,000 in ten years. Past troubles at IBM can be traced, in part, to the failure to respond to the personal computer paradigm shift. Defining your basic business is one key to setting the aim of the system. It is important to remember that people work in the system; management works on the system.

In a steel mill, one department is supposed to clean the scale on tubes. The operators must know why it is important to remove the scale to be able to do their job. Why is it important to have clean tubes for the next operation or for the final customer? The why makes a difference on the operational definition of “clean.”

Harvard Business School professor Michael Porter told the people gathered at then President-elect Bill Clinton’s economic summit in December 1992 that, on the average, a share of stock in corporate America is held for only two years. “Our investors are too concerned with guessing what stock is going to appreciate in the next six months or a year rather than in understanding the fundamental health of the company.”

1. Define the boundaries of the system. As a starting point, the boundary will probably be the company, its customers, its suppliers, and the community where the company is located. In the future, the boundaries may change to include competitors. Work with suppliers who understand the system of profound knowledge. You may have to educate your suppliers and your customers.

Boundaries of a System

Two things are critical in applying this part of the system of profound knowledge. First is defining the boundaries of the system. For example, if you are a motor freight company, does the system include only your suppliers, your customers, and your company or does the system include all motor freight carriers, suppliers, and customers? This distinction is important because, if it includes your competition, then you must work together with your competitors to improve the system.

Dr. Deming actually supports companies working with their competitors to optimize the system for long-term survival.

 In the world according to Dr. Deming, companies would be just one component of the system with the aim being to “stay in business for the long term, and to provide maximum benefit to themselves, to their customers and suppliers, and to society.” In this world, companies would not set prices that would hurt the system in the long term.


source:
       https://www.spcforexcel.com/knowledge/dr-w-edwards-deming/profound-knowledge-part-1/
 
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By John Hunter

The data provided by the Red Bead Experiment is often much more convincing than the data we get from our organizations. One lesson I think is underplayed is the lesson that data that seems very clear, is not providing the evidence we think it is. I think because we can easily see this data can’t be providing value we discount it. But I think in many organization if they looked at data like this they would have easier decision than the data they actually have. The Red Bead data seems to be showing clearer difference than the data we normally view. This isn’t the case if you have knowledge about variation, but without that knowledge the data can be deceiving.


source:  
       https://deming.org/lessons-from-the-red-bead-experiment-with-dr-deming/
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run chart vs control chart

[[ the following URL result came from google.com ]]
https://www.england.nhs.uk/improvement-hub/wp-content/uploads/sites/44/2017/11/A-guide-to-creating-and-interpreting-run-and-control-charts.pdf


[[ the following URL result came from bing.com ]]
https://thisvsthat.io/control-chart-vs-run-chart

https://pmstudycircle.com/control-chart-versus-run-chart/
 
 
 
Limitations of Run Charts
https://pmstudycircle.com/control-chart-versus-run-chart/
To understand a run chart, you must know the context around the data.

Without further information, you may think a trend is normal when it is a variation. Sometimes, you may think a trend is abnormal when it is not. 
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