Context. Large-scale software development projects are those consisting of a large number of teams, maybe even spread across multiple locations, and working on large and complex software tasks. That means that neither a team member individually nor an entire team holds all the knowledge about the software being developed and teams have to communicate and coordinate their knowledge. Therefore, teams and team members in large-scale software development projects must acquire and manage expertise as one of the critical resources for high-quality work.

Objectives. We aim at understanding whether software teams in different contexts develop transactive memory systems (TMS) and whether well-developed TMS leads to performance benefits as suggested by research conducted in other knowledge-intensive disciplines. Because multiple factors may influence the development of TMS, based on related TMS literature we also suggest to focus on task allocation strategies, task characteristics and management decisions regarding the project structure, team structure and team composition.

Methods. We use the data from two large-scale distributed development companies and 9 teams, including quantitative data collected through a survey and qualitative data from interviews to measure transactive memory systems and their role in determining team performance. We measure teams’ TMS with a latent variable model. Finally, we use focus group interviews to analyze different organizational practices with respect to team management, as a set of decisions based on two aspects: team structure and composition, and task allocation.

Results. Data from two companies and 9 teams are analyzed and the positive influence of well-developed TMS on team performance is found. We found that in large-scale software development, teams need not only well-developed team’s internal TMS, but also have well- developed and effective team’s external TMS. Furthermore, we identified practices that help of hinder development of TMS in large-scale projects.

Conclusions. Our findings suggest that teams working in large-scale software development can achieve performance benefits if transactive memory practices within the team are supported with networking practices in the organization.