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Having an effective model for the nature of data will inevitably identify two different paths to process improvement. One path seeks to operate a process up to its full potential while the other path seeks to operate to meet requirements. This article explains how these two paths differ and how they can be used together to successfully improve any process. Some of the figures (figures 1 through 10) referred to in this part of the series can be found in Part 1.
Assignable causes and common causes
If we use the Pareto principle to organize the uncontrolled factors of figure 10, we end up with figure 11. There, we see that the set of uncontrolled factors contains two dominant cause-and-effect relationships. Walter Shewhart called such dominant but uncontrolled causes, "assignable causes." W. Edwards Deming called the group of remaining, lesser uncontrolled factors, “common causes.” Thus, we have three types of cause-and-effect relationships: control factors, assignable causes, and common causes. Each of these three types of cause-and-effect relationships plays a different role in how the process behaves over time.
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Six Sigma
An article that gets back to basics, which should be simple enough for the myriads of Six Sigma addicts to understand. It should be noted that there are no dark mysterious forces causing predictable processes to drift, shift, or need to be "corrected" by a mystical 1.5 sigma. There is no point in management commanding processes and its workforce to produce a farcical 3.4 defects.
If more people read and understood articles like this, sanity might return to quality. Will managers ever come to realize the Six Sigma emperor has no clothes ?
Assignable causes
Don't understand a couple of things:
(1) If a dominant cause is always present in a process, then won't its effects stay within the control limits as part of the constant variation?
(2) If a cause is one-time or rare, but dominant when it shows up, won't it likely push the process variation beyond the control limits? This wouldn't be a dominant cause of variation in the process, since it almost always has no effect on the process (by definition), and so wouldn't be an assignable cause in the sense that seems to be used in this article. And hence isn't this a fourth type of cause?
Articles that might shed some light
Good Limits From Bad Data
When Can We Trust the Limits On a Process Behavior Chart?
Assignable cause identified - cue in unrealistic solution
During a meeting, it was noted by the external consultant that the metrics for the previous day was excellent - to the point of being an outlier. She then segued that whatever we were doing the previous day should be implemented and made part of the daily routine.
Then someone reminded the consultant that it was Valentine's day the previous day and the firm cannot realistically make all of the programs lined up the previous day to be part of the routine (dating game, live band, free food ...).
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