Enhancing distributed collaboration using sociometric feedback

Abstract

Distributed collaboration is often more challenging than co-located collaboration as many of the social signals become lost in computer-mediated communication. I propose a system that improves the performance of distributed groups using sociometric feedback. Sociometric feedback is a real-time visualization of the quantitative measurement of social interactions. Sociometric feedback helps distributed group members have a better understanding of the members that are not co-present. Moreover, a persuasively-designed sociometric feedback can control the direction of change in the communication pattern of groups, so that the change can lead to a performance increase. Laboratory studies verify the strong relationship between communication patterns and group performance in two types of tasks. Based on these relationships, sociometric feedback is introduced to enhance both the communication pattern and the performance of distributed groups. Results show that sociometric feedback influences the communication patterns of distributed groups to be more like that of co-located groups, which results in an increase in performance. Additionally, sociometric feedback helps groups to have a more consistent pattern of communication even when they face a change in member distribution; this effect also results in an increase in performance. Data from two pilot studies of real-world teams suggests that sociometric feedback may be applicable to real-world organizations to benefit their performance.