Algorithmic Management in Traditional Organizations

Abstract Traditional organizations increasingly utilize algorithmic management (AM) to manage their permanent workers. While existing research has extensively explored AM within platform organizations, there is a need to understand its application in traditional work environments, given workers’ close connection to the organization and the existing work relationships. Moreover, current AM research primarily focuses on possible negative effects for workers, with limited recognition of its beneficial impact within organizations. The paper addresses these aspects by investigating the impact of AM on traditional organizations, examining the role of socio-technical characteristics in enhancing workers’ efficiency. Conducting mixed-methods research within an international automotive supplier, an archival dataset comprising 12,743 manufacturing errors is analyzed, complemented by 15 semi-structured interviews with affected workers and managers. The results give objective evidence that AM significantly improves efficiency within traditional organizations. In addition, the interviews reveal that human managers maintain a supportive role in this hybrid organizational setting, while established work relationships among co-workers are heavily influenced by AM. This research offers valuable practical contributions for the successful implementation of AM in traditional organizations, emphasizing the need for a tailored approach that considers the distinct dynamics of the traditional work context.