When I studied Management Theory and Practice as a freshman undergraduate student in the late 1960s, the subject did not seem to have any connection with statistics. When I studied statistics in the early 1970s (undergraduate and graduate), it did not seem to have much direct relationship to management. Over the years, however, seeing statistics in action in modern business and industry, as well as nonprofit organizations, I have come to see many connections and parallels. These are, perhaps, highlighted in the work of W. Edwards Deming on Quality Improvement and in the more recent Six-Sigma and Design for Six Sigma (DFSS) quality programs. No one would argue with the fact that these “quality programs,” although quite different in methods and attitude, are based the important ideas of understanding and controlling variability, an important component of “statistical thinking.”
The definitive source that describes Deming’s “14 points” is Chapter 2 of his 1982 book Out of Crisis. More briefly, some background on Deming’s 14 points can be found, for example, at http://www.deming.org/theman/teachings02.html and http://www.hci.com.au/hcisite2/articles/deming.htm. As I read through these and other brief descriptions (Google on Deming points) I noticed somewhat different versions and interpretations.
Most information on Six Sigma on the WWW comes from the large number of consulting firms that provide training and support for implementation of Six Sigma programs (this has been a huge growth industry in the past five or six years). For background on Six Sigma, Google Six Sigma or see, for example, http://www.ge.com/sixsigma/, http://www.jmp.com/industries/sixsigma.shtml
An interesting case study comparing the two approaches would look carefully at the highly successful (according to some objective criteria) implementation of Six Sigma at GE and the extent to which that implementation agrees with the philosophy of Deming (I submit that there are lots of places where they would not agree).
W.Q. Meeker
7 September 2005