The Newtonian-Cartesian dualism that informed the development of our socio-economic system also guides us to think in dichotomous or dualistic terms—win/lose, us/them, liberal/conservative, profit/loss, good/bad, favorable/unfavorable—and also to believe that if something is not quantifiable it isn’t important. Such thinking promotes judgment of experience not learning from experience. Because of this either/or habit of thought we don’t quite understand the depth of our experiences.
When presented with an outcome or event in the series of outcomes or events in experience what do most do? They seek to judge it asking, is it the lowest or highest we’ve had? Or people might compare the most recent with that of the immediately previous outcome asking is it higher or lower than the last?
Erroneously—and yes foolishly—many believe two points constitute a trend. But a straight line does not a trend make! Those a bit more arithmetically astute might compare the most recent outcome with the average of all outcomes only to ask is what we now have above or below average? Clearly, these scenarios represent dualistic thinking—which is superficial at best.
How much can people learn with this approach? Very little! In all of these, people are ignoring the pattern in the variation of the outcomes or events. They are failing to gain the knowledge inherent in the pattern of variation.
Reducing things to fit dualistic categories of thought removes the context and thus the opportunity to develop understanding of the process from the data. As Donald Wheeler asserts “no data have meaning apart from their context.” All we can do is label it or judge it good or bad, favorable or unfavorable, better or worse. We gain no knowledge, no insight about the process or system itself. All we are able to do is react to the label. Hence the prevalence of management-by-exception!
Why is this so common a practice? The answer (I believe) is that the vast majority of people haven’t learned how to understand variation and to think statistically; hence they reduce the variation presented to fit their pre-determined dichotomous categories of thought—everything is forced to fit the same limiting dualistic sense of order. Yes this approach is uncomplicated, easy to do and provides conclusions that are mostly true. However, what is gained is not true enough!
As illustration consider the headline U.S. Corporate Credit Risk Index Falls to Lowest in Five Months. What’s missing is the context within which the data was produced; what’s missing is meaning. Everything unfolds in time and is related in time, yet the connection to the dimension of time is ignored. The patterns of variation in a series means something, yet knowledge derived from understanding the pattern in the variation is nowhere to be found.
The decision whether to initiate action on the system or to react to the noted single event is dependent upon whether the pattern of variation shows evidence of a common or special/assignable cause situation. Neither judgment nor experience is adequate for this determination. Only an informed reading of the pattern—like a reading of an X-ray—can guide an appropriate determination.
The vast majority of managers make decisions using either/or thinking, which is both a limited and limiting way of thinking and managing. Decision-making is nothing more and nothing less than a process of prediction. What makes for better prediction than an advance in relevant knowledge and understanding? Yet because most are unable to understand variation, decisions are made absent of the requisite knowledge. Deming’s assertion that ‘there is no substitute for knowledge” communicates considerable depth of understanding in this regard.
How foolish it is not to properly educate those who rely on data to inform their decisions! Why is an understanding of variation and statistical thinking not taught in school? Do we really have to continue managing this way! The statement that if everyone is doing it, then it must be right is a logical fallacy. Where is it proven that whatever is the most popular is the most proper?
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