The quality function is an information-gathering service: from the mass of data which
is available in every production process and every service activity in the complex world of
commerce, quality extracts that which is most meaningful from that which is less so, and
by analysis of such process data sets out to control the future behaviour of the process
towards even greater customer satisfaction – towards better and better quality. Because all
modern business systems generate such colossal amounts of data, quality makes use of the
mathematics of big numbers – statistical methods – to distill useful meaning from the
daunting mega-heaps of data. So the belief has arisen that quality is little more than applied
statistics; this is on a par with averring that Chippendale furniture-making is little more
than the applying of chisels to wood. Quality makes use of statistical thinking purely as a
tool of convenience, because there is no other tool as appropriate to the task as that
provided by mathematical statistics. This tends to put people off: memories of the blank
incomprehension occasioned by the algebra of schooldays shroud the subject in veils of
mystery. It all seems too complicated, and best left to the specialist practitioners who have
mastered its mysteries. Often these ‘experts’ themselves foster this mystification by speaking
in their own esoteric tongue which is unintelligible to the rest of us. This leads us to ask
what has all this fancy mathematics to do with quality in the workaday world, to which the
answer is ‘not much’. Maybe this is one of the reasons why quality used to be a despised
discipline done by despised people, whereas nowadays, thanks in large measure to Japan on
the one hand and the Ford Motor Company’s quality training initiative on the other, quality
is a highly respected discipline. Done by despised people.