Understanding Team Types

The Behavioral Assessment provides a deep look into an individual’s workplace behavior by understanding that person’s motivations and needs. However, most of the time work happens in teams, so it’s important to understand the overall behavioral styles of a team.  The larger the group, the more complex it can be to interpret what it all means in aggregate.  

Team Types provide a simple approach to understanding BA data at a team level.  By analyzing the aggregate Behavioral Assessment results of a team, PI is able to summarize the overall behavioral styles and emphasis of a team. We explore this concept here.

The Science of Teams

In 2019, PI scientists sought to find different possible behavioral make-up of teams based on Behavioral Assessment data. This research effort involved a large sample of 127k individuals across 22k teams. Each individual’s data was scored based on their most dominant behavioral factors, which were then considered across the team level.

This work resulted in the formation of 9 distinct Team Types based upon the dominant behaviors across the make-up of a team. Analyses demonstrated a balanced distribution of team types across the large sample.

Team Types

Explore the interactive below to learn about the strengths and blind spots of each Team Type.

This video will explain how those team types are determined based on the members that make up the team.

How a Team Type is Determined

Team Balancers

Team Types are calculated by everyone on the team, yet it is common to see teams with individuals who do not necessarily sit with the majority of the team in regards to placement within the work styles framework; rather they serve as balancers. The role of the balancer on a team is to provide a healthy contrast to a similar way of thinking and working across the team. Use the interactive below to learn more about the role that balancers play on various teams.

Distributions of Teams

The following chart shows the distributions of Team Configurations based on team data in PI software. The data below is from an analysis of 22,486 teams. 

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