Predictive validity: Conclusion
Self-ratings of higher-order factors of personality modestly relate to supervisor and objective ratings of overall job performance. The magnitude of the correlations (or corrected operational validities) typically ranges from 0.0 to 0.3 and this is true whether personality factors are examined in univariate (single-factor correlations) or multivariate (as a group of five factors) fashion. With the exception of conscientiousness, many broad personality factors appear to be generally unrelated to ratings of overall job performance. However, broad personality factors do offer much greater levels of prediction of other crucial elements of workplace performance, such as counterproductive behaviours, leadership and teamwork.
At this point, some might conclude that personality is generally not fit for purpose in the selection context (e.g., Morgeson et al., 2007a). However, that personality measures as a stand-alone do not offer particularly grand levels of predictive validity does not mean that they are useless. Rather, personality measures offer significant and cost-effective (in terms of time and money) incremental predictive validity over other selection methods. Notably, the combination of cognitive ability and personality is among the most powerful combinations of selection methods. Thus, we can endorse the use of personality as a component of a rigorous selection programme (Schmidt & Hunter, 1998; Schmidt et al., 2008).
Further, when we step away from meta-analytic correlations of the Big Five the picture is much more interesting. Narrow, lower-order facets offer much greater predictive validity (with the exception of conscientiousness, between 2 and 6 times more) than do their broad composite factors. While facet-level analyses are clearly superior to broad factor analyses, it is also likely that our current estimates of this superiority represent underestimates. Currently, the data we have lack nuance as they pertain to job performance en masse across numerous industries, organizations and roles. However, as we suggest, personality is not a universal predictor: different roles require the utilization of different levels and combinations of behaviours. In addition, no single facet list from popular measures of personality is exhaustive, and thus omits potentially important personality traits (e.g., the dark triad) and further underestimating the predictive validity of personality.
In spite of the current limitations on our estimates, it is clear that matching a few narrow traits on the basis of existing empirical evidence and theory leads to increased predictive validity (Judge et al., 2013; Paunonen & Ashton, 2001). Personality-oriented job analysis offers an avenue to identify the narrow facets of relevance and, if utilized appropriately, can further increase the predictive validity of self-ratings of personality. We know of no studies that have examined the incremental predictive validity of facet-level personality ratings, based on job analysis, over and above cognitive ability. We suggest that such a study is of great importance in furthering this debate.
One of the likely limiting factors in the validity of personality measures is their susceptibility to response distortions (e.g. low self-awareness, faking). The evidence reviewed here suggests that replacing self-ratings with other ratings might mitigate self-report response distortions and offer substantially increased predictive validity. An intriguing question remains just how much predictive validity increases by the simultaneous use of job analysis to identify relevant narrow facets, which are rated by others and used in a multivariate manner to predict nuanced measures of job performance. The evidence reviewed in this chapter suggests that this approach could yield substantial gains in predictive validity and ultimately improve our selection practices.
Equally, recent research suggests that partially ipsative personality measures have improved predictive validities compared to traditional, Likert-type measures. The utility of partially ipsative measures is even more pronounced when the moderating effects of job role are taken into account, with univariate relationships with performance within specific roles ranging from 0.3 to 0.7. In addition, recent advances in the scoring and modelling of ipsative items (Brown & Maydeu-Olivares, 2013, in press) make the measures more appealing and practically useful.
In sum, we believe that the predictive validity evidence suggests that personality traits are valuable during selection. Even a simple measure of conscientiousness offers incremental predictive validity in most selection scenarios. However, more nuanced use of personality measures leads to even greater levels of predictive validity which, in our view, make personality an important component of the selection toolbox.