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Belbin Team Roles—Hard Science for “Soft Skills”

The Research Behind Belbin’s Proven Corporate Team Development System

Have you ever wondered why certain teams run smoothly and others just limp along? Three decades years ago, British social scientist R. Meredith Belbin wondered precisely the same thing.

Belbin’s Insight into the Structure of Successful Teams

After nine years of research with management teams at Henley College, UK, Belbin realized that selecting teams according to commonly assessed traits—intelligence, for example, or personality type—was no guarantee of a team’s success.

In fact, he discovered that teams made up of similar people tended to do worse than teams that were picked according to other criteria.

Eventually, he developed a list of nine skill sets that, when combined, made the difference between teams that achieved consistent success—and teams that struggled to meet expectations. These became known as Team Roles.

Validation of Belbin’s Model

Of course, Belbin’s ideas didn’t just stay ideas. He tested his Team Roles theories in two series of trials—simulated management exercises in which several teams competed against one another.

The graph below shows the results of one management simulation, in which Belbin didn’t pick the teams, but predicted their success.

Graph showing predictability of Belbin Team Roles
Here’s how to interpret the graph

The red x’s on the graph represent the different teams that participated in the management simulation.

  • Shapes on the diagonal line represent where Belbin’s predictions and the team’s performance matched exactly.
  • Shapes that are closer to the diagonal line represent where Belbin’s predictions were within a few ranks of the team’s actual performance.
  • Any shapes that were far away from the diagonal line would show where Belbin’s predictions did not reflect the team’s performance.

As you can see, Belbin’s predictions were either exactly accurate or within one rank of the final result.

Using Team Role Theory over further tests, Belbin was able to predict the success of a team with an accuracy rate of 86%—even when he hadn’t picked the team members.

Now you can do the same—building and developing teams whose performance isn’t simply a matter of chance, but a matter of science.

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