Pay inequality remains a pervasive problem within the workforce. However, it can be challenging for even well-meaning and responsible organizations to effectively assess which jobs should be considered equivalent and paid the same based on both legal criteria (which have shifted over time and differ across specific statutes and jurisdictions) and scientific evidence (which continues to amass). This paper intends to initiate a solution-focused discussion on how organizations can proactively categorize jobs so that pay decisions that are made about men and women are both legally defensible and fair. We propose that integrating the job analysis/job classification literature and the pay discrimination literature (e.g., legal opinions given by courts) will inform this discussion. We first review federal and state legislation and court opinions that have set legal standards for identifying pay discrimination. We then review the relevance of job analysis/job classification for systematically defining and categorizing jobs, highlighting the legal issues that should be but (to the best of our knowledge) have not been considered when undertaking such processes. Our intention is for this article to spark dialogue among researchers and practitioners regarding the identification of methods with which organizations can strive to meet equal pay standards and goals, applying both legal and scientific perspectives.

Strah et al. (2021) claimed “pay inequality between men and women remains a salient societal issue” (p. 1). We agree that it is a societal issue, but we believe this issue has already been solved by existing job evaluation procedures. Job evaluation procedures have shown to be reliable and valid methods for assessing whether an organization can meet equal pay standards. The authors presented no scientific evidence that this was inaccurate. In fact, nearly 50 years ago there was considerable evidence that equal pay standards, both scientific and legal, were met by job evaluation.

Drawing on examples from published research, the authors offer a perspective on the side effects that are associated with organizational interventions. This perspective is framed in the context of the many hard-won positive influences that industrial and organizational (I-O) psychologists have had on individuals, groups, organizations, and social institutions over the last century. With a few exceptions, we argue that side effects tend to receive less attention from I-O psychology researchers and practitioners than they deserve. A systematic approach to studying, monitoring, and advertising side effects is needed to better understand their causes, consequences, and the contexts in which they are most likely to emerge. The purpose of this piece is to stimulate conversations within the field about the phenomenon of side effects as well as what might be done to improve our science and practice in this domain.

Organizations that are becoming more diverse and relying on teams to achieve performance outcomes often employ organizational interventions to deliver these outcomes. Although some negative or null side effects have been demonstrated related to these interventions, we argue that many positive side effects are often not captured or are disregarded and warrant further attention. Using examples from the training literature, we provide evidence for positive side effects of organizational interventions. We also identify lapses in the field’s approach to the measurement of the effects of organizational interventions and how this prevents our attempts to improve these interventions to create better and more holistic outcomes for employees and organizations. We suggest opportunities to improve interventions that can be applied in our diverse workplaces.

Despite the growing popularity and marketing of pulse surveys, there is little research concerning this practice. To this end, this practice forum reports the results of a four-wave pulse survey that was conducted in a health care organization. Pulse surveys provided reliable estimates of overall engagement, but scores remained stable across 8 months. Practically no differences in group scores or trends could be found despite high participation (≍ 50%). Item responses displayed little differences between groups, ICC(1) ranging from .03 to .18, and poor discriminant validity. Based on these results, pulse surveys may be adequate for estimating overall employee sentiment but not useful for detecting change over time or differences between groups. These limitations should be considered when designing or implementing pulse surveys.