Multidisciplinary teams (MDTs) are increasingly being used in a range of assurance engagements. In particular, standard setters have recognised the need for the diverse expertise possessed by members of such teams in the conduct of nonfinancial assurance engagements including greenhouse gas (GHG) assurance. Ironically, the performance of MDTs is often impeded by their diversity. We employ a between-subjects experiment utilizing a complex multi-stage analytical procedures task for a GHG assurance engagement to investigate the effectiveness of two training interventions drawn from the educational and cognitive psychology literature - analogical encoding (AE) and collaborative learning (CL) - in enhancing MDT performance. We find that combining AE and CL techniques leads to the highest task performance outcomes. Our results suggest that when these techniques are combined, the potential problems of each individual technique are outweighed by their inherent benefits, enabling the team member familiarity and sharing of workload generally associated with CL to enhance the improved understanding and task ability generally associated with AE to facilitate greater improvement in performance.