Teams have long been the object of scientific enquiry given the central role they play in complex, safety critical, innovative and impactful work. Understanding how the most effective teams function is complex and multi-faceted. Whilst the science of teams has established a broad and deep knowledge base, there is an overreliance on theoretical models that do not account for the dynamic nature of teams (Ramos-Villagrasa et al., 2018). Moreover, there is a need for the science to evolve to understand teams in a new era; one characterised by the explosion of novel technologies likely to change the way teams interact, and the means by which these interactions can be measured (Benishek & Lazzara, 2019).
Many current methods of teamwork measurement are static (measuring only at a single point in time), thus are not reflective of the dynamic and changing nature of teams. Furthermore, the literature is reliant on subjective, self-report data, or the use of observer-raters who may disrupt natural team functioning. Therefore, this paper will present three promising methods of capturing meaningful data related to team behaviours utilising technological approaches: 1) real-time communication data, 2) social network analysis (SNA), and 3) wearables and sociometric badges.
Each of these are discussed in turn, identifying applied sciences related challenges such as usability, validity, and the analysis and interpretation of large amounts of data, before potential solutions to these challenges are offered. For each technology explored, reference is made to contemporary studies, commissioned by UK MOD (e.g., Roberts et al., 2019a; Pleva et al., 2021; Myers et al., 2021), to support the discussion. The paper is rounded off by drawing insights to inform further research opportunities.