Research on gender differences in the allocation and evaluation of three main components of academic work (i.e., research, teaching, and service) is very informative, and we argue that it may point to potential sources of the disparity in academic industrial and organizational (I-O) psychologists’ experiences. We also propose the addition of a few issues to the research agenda set forth by Gardner, Ryan, and Snoeyink (2018) with the belief that attention to these issues will help address the gender disparity.

In the focal article “Getting Rid of Performance Ratings: Genius or Folly? A Debate,” two groups of authors argued the merits of performance ratings (Adler et al., 2016). Despite varied views, both sides noted the importance of including multiple raters to obtain more accurate performance ratings. As the pro side noted, “if ratings can be pooled across many similarly situated raters, it should be possible to obtain quite reliable assessments” (Adler et al., p. 236). Even the con side noted, “In theory, it is possible to obtain ratings from multiple raters and pool them to eliminate some types of interrater agreement” (Adler et al., p. 225), although this side was certainly less optimistic about the merits of multiple raters. In the broader industrial–organizational psychology literature, authors have repeatedly heralded the benefits of adding additional raters for performance ratings, some even treating it as a panacea for inaccurate ratings. Although these authors extol the virtues of multiple raters, an important question is often omitted from relevant discussions of performance ratings: To what extent do additional raters actually improve performance ratings? Does adding an additional rater double the validity of performance ratings? Does an additional rater increase the validity of performance ratings by a constant value? Or is the answer something else altogether?

Adler et al. (2016) open with a summary of the business case driving our field to change and close by providing principles for accomplishing that change, where they conclude that “there is no right answer to the ratings question” (p. 244). Lying between the opening and closing sections is a series of arguments for and against today's performance rating status quo, arguments illustrating just what happens when too many years are spent seeking answers along too narrow a path. In this commentary, we provide additional support for the strategy- and outcome-driven approach to performance management advocated in the article. In addition, we offer ideas for what has contributed to getting us and keeping us where we are. Unless we understand what has driven performance ratings research and practice to be the object of an intense and lengthy debate, these same forces may well drive us to carry out years-long experiments of questionable value along similarly narrow paths. We want to offer our views on how to foster outcome-based practice more broadly.

Within the context of the 50th anniversary of the Civil Rights Act of 1964, and specifically as it pertains to the tenets of Title VII, Lindsey, King, Dunleavy, McCausland, and Jones (2013) state: “This focal article raises and addresses critical issues regarding a yet unanswered question: How can organizational researchers and practitioners contribute to the ultimate goal of eradicating employment discrimination” (p. 391). We argue that in the context of employment testing and selection, at least as per the disparate impact theory of discrimination, this question is the wrong one—certainly as framed by Lindsey et al. To the contrary, instead of holding up the "eradication of employment discrimination" as our ultimate goal, perhaps we should continue to focus on the development, implementation, and support of the best (i.e., most job-related and valid) employment practices possible.

Individual Psychological Assessment is widely practiced among I–O psychologists and supported as a core competency by a majority of the commentaries. Our response addresses some of the key points made in the commentaries, such as issues related to the definition, contextual and criterion variables, interpretation and integration methods, validity evidence, professional matters, and future research directions. We also respond to a few critics who want to entirely eliminate expert assessor judgment in IPAs. Models are presented for using assessor judgment and mechanical methods in IPAs and for distinguishing naïve and sophisticated IPA researchers and practitioners. We conclude that IPA is now widely accepted as a core part of I–O psychology.

Big data is becoming a buzzword in today's corporate language and lay discussions. From individually targeting advertising based on previous consumer behavior or Internet searches to debates by Congress concerning National Security Agency (NSA) access to phone metadata, the era of big data has arrived. Thus, the Guzzo, Fink, King, Tonidandel, and Landis (2015) discussion of the challenges (e.g., confidentiality, informed consent) that big data projects present to industrial and organizational (I-O) psychologists is timely. If the hype associated with these techniques is warranted, then our field has a clear imperative to debate the ethics and best practices surrounding use of these techniques. We believe that Guzzo et al. have done our field a service by starting this discussion.

The company I work for is one of the leading providers of performance management technology (Jones & Wang-Audia, 2013). This technology is used by more than 3,000 organizations worldwide, including several of the companies mentioned in Adler et al. (2016). The technology is highly configurable. It is currently being used to support performance management processes with no annual manager ratings, processes with traditional annual rating evaluations, processes that only evaluate competencies, processes that only evaluate goal accomplishment, processes that mix goals and competencies, processes that require forced-ranked comparisons between employees, processes that make no direct comparisons between employees, and much more. The capabilities of this and other human resources (HR) technology systems are allowing companies to radically rethink performance management because they enable companies to do things far differently from what was possible when they were constrained to more fixed electronic or paper forms (Hunt, 2011, 2015a). The result is an explosion in the diversity of approaches being taken toward performance management design.