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6 December 2014

Can maths help us make better choices about people?

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by Amanda Fone.

Big data has stirred up a revolution in many industry sectors already. But why not in recruitment? Why can we use maths to predict complex systems like weather or finance but not the suitability of a person for a team or company? Well, the ability to do so is finally here and we’ve been talking to Alistair Shepherd whose company, Saberr, is at the beginning of a big data revolution that could transform our industry.

We all know that personality and ‘fit’ make more difference to a happy and successful professional life than skills or experience. Getting the fit right when you move jobs or hire someone for your team is all important. To date, that fit has been very hard to achieve other than through personal insight and hunch. But now there is enough academic research, enough computational ability and enough access to big data to assess personality fit as well as skills.

Saberr’s work starts with the notion that we do not operate exclusively but that we are influenced by the people around us more than we realise or would like to acknowledge. This is why team dynamics and fit are so important to our success. From a series of questionnaires followed by some unfathomable mathematical modelling Saberr produces results that let you see which people work best together based on their personalities not their skills. We’ve done it here at f1 and it is spookily accurate.

While Saberr’s current focus is on helping companies to build high-performing teams among existing employees, there is an obvious application to recruiting, too. “We really want to help.” Alistair says. “It’s readily acknowledged that the best recruiters take the time to get to know their candidates and clients. We’re giving the recruitment industry a new set of tools to get the job done faster and to increase the volume of people in the system. Recruiters will be able to pass on more and more accurate information to the client and the candidate.”

A challenge we have at f1, for example, is in explaining the nuances of different agency environments when the language they all use to describe themselves is identical – they are all creative, all fun, all innovative, etc. A tool like Saberr’s could enable candidates to see the nuances in the data so that they can judge a characteristic against their own personal benchmark.

Another challenge we face is ‘LinkedIn Fatigue’. Last time we asked candidates about it, some of them told us they are contacted by in house recruiters more than ten times a week and are fed up with it. We also have anecdotal evidence that hiring through LinkedIn incurs a much higher drop-out rate than hiring candidates found through a search firm that meets them face to face and matches values and behaviours as well as skills. LinkedIn is seen as the Holy Grail when it comes to sourcing and recruiting talent and its recent launch of a service that tries to make a personality fit is no surprise. It’s something Alistair Shepherd says he’s seen coming for a long time. But the challenge is that the information we share via LinkedIn is relatively limited, particularly when it comes to personality and behaviour. I am sure that if there is a “big bang” moment for recruitment in the near future it will come not from the power of LinkedIn but from analytics and the science of matching an individual’s values and behaviours to those of an organisation.

Saberr wants big data to help people make better decisions. People in recruitment expressly define their role as being anti-data, about interpreting the human, soft, fuzzy stuff. But they will soon face the possibility that tools are available to confirm or even improve their intuition. When we ask clients and clients why they come to f1 we get answers such as, “you listen actively” or “you are interested in me”. It implies that at f1 we have wired our brains to think in a similar way to the Saberr tool about matching people with organisations. But now Saberr has the science to enhance this human hard-wiring.

As the revolution takes hold in recruitment as it has done in other sectors we should be prepared to see radical changes in the make-up of our industry. Saberr itself employs an aeronautical engineer and an astrophysicist, for example. We’ll need hard-core data scientists mixed with people that can interpret, explain and act on the results.

Imagine the day when you can search online for the perfect career opportunity knowing that the role is going to develop you and be financially rewarding, and be for a company that matches your own beliefs and values. This is a long way off but it is coming. Saberr has already done some show-stopping experiments, such as correctly predicting which team would win a Coca Cola innovation competition without knowing anything about the people or their ideas, and correctly predicting which entrepreneurs would leave a group of start-up companies first. If data can help humans process and interpret character qualities at scale then recruitment could look very different in a very short space of time.