Do you like horror films? How you answer that question, compared to how your prospective teammates answer that question, may be a strong indicator of how efficiently you will work together.

Everybody knows that teams that get on well, work well. Now Alistair Shepherd thinks he’s found an algorithm that will predict how well a group of people will get along – and he discovered that algorithm by studying online dating.

©Pat Brans

Shepherd and colleagues sifted through mounds of data from online dating questionnaires and determined which factors correlated most with a couple’s success. It turns out that one of the key questions to determine compatibility is whether or not people have similar tastes, or distastes, for horror films. From this study of romantic compatibility, Shepherd’s team came up with a more general model for compatibility.

They then tested their theories in a business setting by polling members of teams in business planning competitions. Shepherd says that time after time, not only could they predict contest winners, they could also predict the two runners up.

To capitalise on their findings, Shepherd and a friend founded Saberr, a company that provides tools to help managers build high-performing teams, and for HR departments to predict how well new hires will fit in. To get their company going, the pair sought help through the London startup ecosystem. They got support from Startup Weekend and Google Campus, and landed initial funding from Seedcamp.

Shepherd says, “Starting a business can be really painful while you are still in the phase of trying to figure it all out. It’s good to be around other entrepreneurs to share ideas and experiences - and sometimes it’s just good to have somebody around who understands your sense of frustration.”

So far it seems to be working for Saberr. In just two short years, the company has landed contracts with the likes of Thompson Reuters and Deloitte.

Does the compatibility model really work? We don’t know, but we feel safe in the knowledge that none of us like horror films.

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