Measurement and individual differences. This example highlights the important role of measurement in selection research. Numbers assigned to predictors and criteria enable us to make the necessary fine distinctions among individuals. Subsequent analyses of these numbers help us meet one of our goals: devveloping a system for predicting job performance successfully. Without measurement, we would probably be left with our intuition and personal best guesses. Perhaps, for a very small number of us, these judgments will work. For the most - deciding by the seat of our pants will not work.
Measurement is to identify those who should be hired for the job. Predictors and criteria help identify those who should be hired. e.g. making baskets - very few people will make really high quantity or low quantity (most will make somewhere in the middle - bell curve). If we can assume quantity of production is a suitable criterion , our objective is to obtain a predictor that will detect the individual difference or variance in productivity. I If our predictor is useful, individuals' scores on the predictor will be associated with their productivity scores.