Effects of Team Facilitation

Many teams are confronted with having generated many more ideas during a brainstorming activity than they can meaningfully consider in detail. In order to achieve the task goal (e.g. solve a problem or make a decision), they need to focus their attention on a limited number of these ideas. This is accomplished during convergence in which teams concentrate on reducing and clarifying a list of generated ideas. However, teams often face challenges related to their collaboration process. They can make use of professional facilitators that provide knowledge on effective meeting management, handle group dynamics, and support the adequate use of technology. Past research showed that facilitation can have positive effects on team outcomes, such as satisfaction, team mental models, or quality of outcome. However, findings are inhomogeneous, which leaves the concept of facilitation and its components poorly understood. The consideration of team processes might help to better explain the effects of facilitation as facilitation neutrally contributes to a teams processes by enhancing communication and information processing. However, until now the mediating role of team processes in facilitated settings has yet not been sufficiently established. My research project addresses this gap in literature and focuses on facilitated, IT-supported teams performing problem-solving and decision-making tasks during face-to-face meetings. The aim of this research project is to theorize on the components of facilitation, i.e. attention guidance and discussion allowance, and their relations to team processes and team outcomes. To validate the components of facilitation that were identified in our previous work, I will collect data of facilitated business meetings in the field. Moreover, I will statistically test the mediating effects of team processes on outcomes on the basis of data collected in a laboratory experiment. I plan to conduct this research at the Center for Collaboration Science at the University of Nebraska at Omaha. Dr. Gert-Jan de Vreede is the managing director of the Center for Collaboration Science and a well-established researcher in the domains of facilitation, crowdsourcing, and collaboration engineering. This one-year research stay would enable us to advance in our theorizing on facilitation and allow me to acquire know-how from one of the top researchers in my research domain.

The goal of the project was to investigate the effects of feedback intervention during idea convergence. Idea convergence describes a demanding innovation process, in which a small team reduces and clarifies generated ideas. The research results show that teams with feedback intervention outperform teams without feedback intervention in terms of e.g., extent of idea development or depth of interaction. In this context, the effects on idea quality and shared understanding are dependent on the type of feedback that team leaders enact and that team leaders and team members perceive their interaction processes similarly good (or bad). Similar effects were identified in the crowd-context. It seems that idea convergence on crowd- sourced ideas is less successful than on self-generated ideas. The goal of idea convergence is to create a list of non-redundant, task-fit ideas that are clarified to useful levels of abstraction in order to aid proceeding phases of collaboration, e.g., idea evaluation. Idea convergence is challenging. Brainstorming sets consist oftentimes of hundreds of ideas many of those ideas are redundant or idea descriptions are vague. The information processing of humans is bounded because our cognitive resources as well as our attention is limited. Moreover, every person has his or her own mental model. The development of a shared mental model is therefore demanding, because the interpretation of an idea might differ from one team member to the other. In case the idea was generated by the crowd, the convergence team misses the background knowledge of an idea what makes the development of shared understanding even more demanding. Feedback intervention should overcome these challenges. However, we do not have enough knowledge to understand which mechanisms of intervention create which effects on processes and results during idea convergence. For the investigation of feedback intervention effects, I drew on data gathered in laboratory experiments with more than 400 students and an online innovation contest. Results of this research have implications for research, practice, and technology design. For research, the results suggest that the investigation on the level of feedback types is important because they affect outcomes differently. The tested moderation techniques and their effects are also interesting for practitioners that are interested to conduct effective idea convergence. Parts of the tested feedback interventions could also be relevant for the design of automated feedback, e.g., prompts to highlight potential redundancy of ideas.