ABSTRACT
Organizational researchers are motivated by the idea that the data that we collect on workplace phenomena (e.g., data on employees, on teams, on the work environment) are ultimately supposed to provide better information and guidance than human intuition provides on its own. A considerable amount of empirical research has demonstrated experts are critically important for identifying variables and measures on which to collect data. Research has also shown that once experts identify variables and measures, a statistical combination of quantitative data (e.g., a simple sum or linear regression) is consistently superior to the judgments of a single expert. Remarkably, this conclusion is reached across a very diverse range of phenomena relevant to organizations, such as employee performance, training effectiveness, managerial success, achievement in school, and physical and psychological health (Dawes, Faust, & Meehl, 1989; Grove, Zald, Lebow, Snitz, & Nelson, 2000; Ostroff, 1991). The false belief that expert judgments trump algorithms is a stubborn one, for example in personnel selection practice (Highhouse, 2008). This is perhaps because the experts stand to gain financially from this belief by self-promoting it.
