Six years ago, one of the first posts in this blog — Is SPC Obsolete? — started a spirited discussion with 122 comments. Reflecting on it, however, I find that the participants, including myself, missed the mark in many ways:

1. My own post and comments were too long on what is wrong with SPC, as taught to this day, and too short on alternatives. Here, I am attempting to remedy this by presenting two techniques, induction trees and naive Bayes, that I think should be taught as part of anything reasonably called statistical process control. I conclude with what I think are the cultural reasons why they are ignored.
2. The discussions were too narrowly focused on control charts. While the Wikipedia article on SPC is only about control charts, other authors, like Douglas Montgomery or Jack B. Revelle, see it as including other tools, such as scatterplots, Pareto charts, and histograms, topics that none of the discussion participants said anything about. Even among control charts, there was undue emphasis on just one kind, the XmR chart, that Don Wheeler thinks is all you need to understand variation.
3. Many of the contributors resorted to the argument of authority, saying that an approach must be right because of who said so, as opposed to what it says. With all due respect to Shewhart, Deming, and Juran, we are not going to solve today’s quality problems by parsing their words. If they were still around, perhaps they would chime in and exhort quality professionals to apply their own judgment instead.