Measurement is, or should be, a concept that is at the center most peoples’ practice.  It comes in many forms: “No Child Left Behind” in education, “evidence-based practice” in medicine and psychology, six sigma in manufacturing, balanced scorecard in management, or performance improvement in human-resources.  All of these programs have measurement at the process core and the results of these processes begin with the quality of the measure and the ability to target measures to illuminate the intended purpose.  But, much of the efforts that are made to impliment these programs focus much more on the methodology that surround the measures, than on the measures themselves.

Achieving quality measures and quality data is not that easy.  Understanding this begins  with the idea of the measurement construct. 

“In philosophy of science, a ‘construct‘ is an ideal object (i.e., one whose existence depends on a subject’s mind), as opposed to “real objects” (i.e., those whose existence is non dependent on a subject’s mind)”

 “Measurement is the process of assigning a number to an attribute (or phenomenon) according to a rule or set of rules” (Wikipedia.com).

Measurement assigns numbers to constructs; attributes that are idea objects.  Measures do not create real objects.  Some of these objects are more problematic in definition (like personality) than others (like temperature),  but they can all be defined as constructs or idea objects.

This leads to the importance of the concept of validity in measurement that will be the next topic.