A Computational Approach to Foster Diverse Teams

AI technology for automating team formation helping to select optimal teams with specific competencies, personality, and preferences to match specific tasks, jobs, or projects. The resulting teams are balanced, which means that no team is over-competent nor under-competent.

Market need: Collaborative work is an indisputable reality where the efficiency of the teams is a determining factor for the success of the company or the task. The composition of balanced and inclusive groups that are as effective as possible is an optimization problem that becomes more complex while the number of people or required groups increases.

Proposed solution: The team formation algorithms automate the creation of teams among a large sample of people, betting on diverse and complementary teams that allow an optimal result taking into account multiple variables, such as competencies, personality and preferences. The are two implementations that enact the technology: EduTeams (eduteams.iiia.csic.es), which allows group formation in the classroom, and Edu2com that adapts the technology to human resources or recruiting needs.

Competitive advantages

Applicable to different sectors: education, human resources, recruitment, etc.
Allows selecting either the best team or the most balanced team for a project
Supports in finding the best candidate for the position or for joining a team.
Assures competitiveness for a wide range of emerging collaborative applications.