Organizations are complex, multilevel, dynamic systems comprised of many interacting processes. The goal of organizational interventions is to generate an intentional positive influence on the way in which one or more organizational processes unfold. Watts, Gray, and Medeiros (2021) correctly point out that, through the act of intervening, unintended consequences may occur such that processes and outcomes not directly targeted by the intervention may be altered. Unfortunately, the complexity of organizations, combined with the typical way in which organizational scientists develop theory and conduct empirical research, limits our current ability to understand, predict, or detect unintended consequences of interventions. We propose that a promising avenue for improving this state of affairs is through the development of ‘process theories’ that provide a more precise description of the affective, cognitive, behavioral, and social actions which unfold in the organizational phenomena we study so that we can better understand the potential consequences, intended and unintended, of interventions. Importantly, these process theories should also be translated into computational models that enable specific predictions regarding when, where, why, and how the processes targeted by organizational interventions may be impacted. Doing so would enable researchers and practitioners to vet potential interventions prior to implementation as well as more efficiently and effectively guide future research.