Page 311 - The Handbook for Quality Management a Complete Guide to Operational Excellence

298 C o n t i n u o u s I m p r o v e m e n t M e a s u r e S t a g e 299

experience. Obtaining credible customer feedback is an important part of
this definition. Customer surveys, focus groups, interviews, and bench-
marking are all used, generally in conjunction with one another, to better
understand customer needs, desires, and those items known in the Kano
model as exciters. These topics were discussed in Part 2.

Measurement Systems Analysis

An argument can be made for asserting that quality begins with measure-
ment. Only when quality is quantified can meaningful discussion about
improvement begin. Conceptually, measurement is quite simple: measure-
ment is the assignment of numbers to observed phenomena according to
cer tain rules. Measurement is a sine qua non of any science, including man-
agement science.

Levels of Measurement
A measurement is simply a numerical assignment to something, usually a
non-numerical element. Measurements convey certain information about
the relationship between the element and other elements. Measurement
involves a theoretical domain, an area of substantive concern represented
as an empir ical relational system, and a domain represented by a particular
selected nu merical relational system. There is a mapping function that car-
ries us from the empirical system into the numerical system. The numerical
system is manip ulated and the results of the manipulation are studied to
help the manager better understand the empirical system.
In reality, measurement is problematic: the manager can never know
the “true” value of the element being measured. The numbers provide
informa tion on a certain scale, and they represent measurements of some
unobservable variable of interest. Some measurements are richer than oth-
ers; that is, some measurements provide more information than other mea-
surements. The information content of a number is dependent on the scale
of measurement used. This scale determines the types of statistical analy-
ses that can be prop erly employed in studying the numbers. Until one has
determined the scale of measurement, one cannot know if a given method
of analysis is valid.
The four measurement scales are: nominal, ordinal, interval, and ratio.
Harrington (1992) summarizes the properties of each scale in Table 14.1.
Numbers on a nominal scale aren’t measurements at all, they are merely
cat egory labels in numerical form. Nominal measurements might indicate
mem bership in a group (1 = male, 2 = female) or simply represent a desig-
nation ( John Doe is #43 on the team). Nominal scales represent the sim-
plest and weakest form of measurement. Nominal variables are perhaps
best viewed as a form of classification rather than as a measurement scale.
Ideally, categories on the nominal scale are constructed in such a way that

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