Industrial and Organizational Psychology, 9(3), pp 641–689 September 2016. Copyright © 2016 Society for Industrial and Organizational Psychology. doi:10.1017/iop.2016.64 Commentary In Defense of Practical Theory Seymour Adler and Anthony S. Boyce Aon Hewitt Chamorro-Premuzic, Winsborough, Sherman, and Hogan (2016) end their focal article with a quote worth remembering from Immanuel Kant: “Theory without data is groundless, but data without theory is just uninterpretable.” We begin with a quote even better known to industrial–organizational (I-O) psychologists in part because it has served for over 65 years as a foundational principle of our feld: “There is nothing as practical as a good theory” (Lewin, 1951, p. 169). Fundamentally, we agree with the authors that, as a science, I-O psy- chology has developed over decades of theory development and empirical research a growing and more nuanced understanding of both the general and the specifc attributes that predict efective performance. Equally important, our feld has, through accumulated scientifc discovery, developed an under- standing of some of the boundary conditions and moderators impacting the degree to which our methods for assessing these attributes are efective as predictors of performance. Beyond summarizing these key and ongoing accomplishments in tal- ent assessment, the authors go on to describe what we consider to be a re- grettable return to the dustbowl empiricism that characterized our feld in the past. The vastness of data now available, and the increasing sophisti- cation of the tools available to mine those data, means we have the poten- tial to enhance predictive accuracy in the absence of having any organiz- ing taxonomy, nomological network, or theoretical model to explain those predictions. Moreover, as the authors point out, there are practitioners who seem wholly unconcerned with developing such insights when armed in- stead with the power of thousands, or even millions, of data points. We have also observed this trend and want to press beyond the authors’ assertion that “predicting behavior is clearly a key priority in talent identifcation, but understanding behavior is equally important” (Chamorro-Premuzic et al., Seymour Adler and Anthony S. Boyce, Aon Hewitt, New York, New York. Correspondence concerning this article should be addressed to Seymour Adler, Aon He- witt, 199 Water Street, New York, NY 10038. E-mail: seymour.adler@aonhewitt.com 641 https://www.cambridge.org/core/terms. https://doi.org/10.1017/iop.2016.64 Downloaded from https://www.cambridge.org/core. IP address: 54.163.42.124, on 09 Jun 2020 at 13:14:34, subject to the Cambridge Core terms of use, available at