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I have just finished rereading Walter A. Shewhart's 1939 book Statistical Method from the Viewpoint of Quality Control (Dover Publications, 1986). Mine is the 1986 edition, which has a foreword by W. Edwards Deming. Shewhart, a Bell Labs man, pioneered quality control and was a major inspiration to Deming (who met him at Bell Labs). Deming is well known in his own right for his contributions to such issues as manufacturing quality in post-war Japan and for laying the foundations of Six Sigma. While these and other accomplishments have made Deming justly famous, he was never shy about recognizing the contribution of Shewhart to science and industry, and the influence of Shewhart on his own career. Indeed, Deming may to some extent have communicated some of Shewhart's ideas in ways that could be more easily understood and applied than Shewhart himself was able to.
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Shewhart, Deming and Knowledge
Malcolm:
Nice article. I would mention that Shewhart's 1931 "Economic Control of Manufactured Product" was as revealing.
The notion that we seem to fight with data is that we have too much of it and most of it is junk. Technology folks seem to equate information with knowledge . . . it is not. Dr. Deming encouraged us to "get knowledge" in the systems in which we operate. This is a far cry from today where the decision-making has been separated from the work command and control style and decisions are instead made from IT reports. This is not getting knowledge, we lost too much context and poor decision making follows.
In the information age we lack this context to the point we would be better rolling dice and flipping a coin than reliance on such things as business analytics or intelligence. Most of these IT solutions add to costs and do little in the pursuit of knowledge or profound knowledge in Deming's terms.
If we are to use IT, we are best using it when we understand the work. For our biggest opportunity for change lies there.
Tripp Babbitt
www.newsystemsthinking.com
Data Affected by Measurement
I enjoyed the article. I wanted to add a comment about considering the quality of the data. In my university days we were taught in a class on design of experiments, that any measurement affects what you are measuring to some extent. For example, if you want to measure the temperature of a small part, you can do so by attaching a thermocouple, but the mass of the thermocouple will affect the rate of a temperature change, and the contact area changes the heat loss in that area. Similarly, making measurements of any sort of data may impact the data. Classic cases are (1) the measurer rounds the measurements or reports them on Mondays even though they occurred on the weekend, (2) the workers pay more attention to the process being measured, thereby modifying the error rate. Consideration of these aspects may affect the way we collect data or interpret the data collected.
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