Abstract

In the context of software engineering, analyzing causality in the dynamics of development teams is essential for optimizing performance. Causality involves understanding how certain factors (organizational structures, individual interactions) directly influence the team's performance, allowing for the identification and implementation of effective improvements in development processes. Identifying and understanding the underlying causes of heterogeneous effects in team dynamics is essential for improving collaboration and productivity. The lack of specific methodologies to explore these causal relationships in complex organizational settings limits the ability of project leaders to implement effective changes. This article describes a method that uses causal inference in organizational mining to assess software development teams. Data are analyzed to identify interactions and causal factors affecting role dynamics, and causal inference techniques are employed to evaluate the effects of improvement actions. The effectiveness of this approach was confirmed with a pilot software development team at a Chilean payment processing company. By employing causal organizational analysis methods, managers were able to select more focused strategies, based on a deep and detailed understanding of the underlying causal dynamics. This work contributes to the field of software engineering by introducing a structured and causal approach to analyze team dynamics and providing project managers with tools to address the underlying factors that hinder team effectiveness.