Relational Mechanisms to Explain Collective Performance Data Use

Abstract

Performance management theory has been largely organizational with a focus on the decision maker, operating within the public-sector hierarchy. But such an understanding misses most contexts that are more horizontal and fall somewhere between intra-organizational team structures and inter-organizational collaborations. To address this gap, this article puts forward the concept of collective performance data use; a group-level construct defined through the lateral, voluntary, and reciprocal negotiations among partners. Drawing on related literatures, it develops a theoretical framework to explain collective data use based on three relational mechanisms (system sensemaking, deliberation routines, and dissent-conflict balancing) and a set of mechanism-activating antecedents, out of which four are featured in greater detail: connectedness, power imbalance, expertise configurations, and distributed leadership. The article argues we need to update extant performance management theory using a relational perspective if we want to better understand the social side of performance practices and related behaviors.