Personnel selection strives to contribute to the organisation's overall efficiency by maximising the economic value added to the organisation by selecting those employees best suited for vacant positions (Boudreau, 1991;Cook, 1998;Guion, 1991). Personnel selection essentially is a form of applied decisionmaking. The focus thus should be on the quality of the selection decisions and not only on the psychometric properties of the measuring instruments used to provide the information for the decision-making. Cronbach and Gleser (1965) acknowledge the usefulness of tests for accurate estimation of an underlying latent variable, but suggest that the value of a selection procedure depends on many other qualities in addition to the reliability and validity with which the critical attributes are being measured. This should, however, not be interpreted to mean that (classical) measurement and test theory should be regarded as obsolete and irrelevant. Although it would be wrong to equate quality of decision-making to the magnitude of the validity coefficient, the latter nonetheless still influences the former. If the other pertinent factors affecting selection decision quality are held constant, selection decision quality increases as the absolute value of the validity coefficient increases. Utility is a positive linear function of validity, and for zero cost, is proportional to validity (Brogden, 1946; Brogden, 1949).The validity coefficients typically encountered in validation studies are, however, disappointingly low. Validity coefficients typically fall below 0,50 and only very seldom reach values as high as 0,70 (Campbell, 1991;Guion, 1998). Typically selection instruments thus explain only 25% of the variance in the criterion (Campbell, 1991). The validity ceiling first identified by Hull (1928) seemingly still persists. Numerous possibilities have been considered on how to affect an increase in the magnitude of the validity coefficient (Campbell, 1991; Ghiseli, Campbell & Zedeck, 1981;Guion, 1991;Guion, 1998; Wiggens, 1973). Most of these attempts revolved around modifications and/or extensions to the regression strategy (Gatewood & Feild, 1994).A though-provoking alternative to the usual multipleregression based attempts may be found in the work of Ghiselli (1956Ghiselli ( , 1960aGhiselli ( , 1960b. Rather than elaborating on the basic mathematical model of multiple-regression, Ghiselli has chosen to attack the problem of improved prediction directly by the use of empirical procedures (Ghiselli, 1956(Ghiselli, , 1960a(Ghiselli, , 1960b. The essence of the proposed procedure revolves around the development of a composite predictability index that explains variance in the prediction errors or residuals resulting from an existing prediction model. It would, however appear as if the procedure has found very little if any practical acceptance. The actuarial nature of the procedure could probably to a large extent account for it not being utilized in the practical development of selection procedures. The lack of gener...