How games, social media are changing the way people get hired

Attention self-starters, creative thinkers and change agents the interview and resume game is yesterday's bagels, say entrepreneurs who suggest the mighty algorithm is poised to overturn the way companies hire people.

"Someone is going to say 'we're looking for team players.' Well, what does that mean?" asks Guy Halfteck, founder and CEO of Knack, a Silicon Valley-based company that matches potential employees with companies using online games and predictive analytics.

"Seriously, not to be cynical about it but it's almost meaningless. It just makes the person who wrote it feel good."

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Instead, Halfteck suggests a more scientific approach that relies less on a recruiter's instinct and more on a candidate's potential to succeed, as shown literally by how someone plays the game.

Halfteck developed the idea for Knack after he was rejected for a management job.

The process was prolonged relying on the usual resume, cover letter, personality questionnaires and interviews. Ultimately, it proved fruitless for Halfteck and he set out to create a system that would enable people to get to know each other using science and technology.

Specifically, he wanted to use game theory as a means of revealing someone's true self.

"As you play, you're basically sending and revealing those honest signals about who you are," Halfteck said of the online games such as Meta Maze or Wasabi Waiter that Knack employs.

'Wasabi Waiter'

In a game such as Wasabi Waiter, the player must act as a server in a sushi restaurant and respond to the needs and moods of the hungry customers.

Technology enables us to understand a person and predict whether that person is going to be successful.- Guy Halfteck, CEO Knack

Thousands of bits of data are collected while playing these games, data that can measure traits such as resilience, self-restraint and empathy.

With clients including the Royal Bank of Canada, American Express and IBM, Knack develops a formula for each job based on the traits possessed by successful people already doing the work.

If an applicant's gaming score is a match against the behavioural science formula, then it's projected that individual will do well in this role. A potential match has been made.

"Technology enables us to understand a person and predict whether that person is going to be successful," said Halfteck. "There's going to be enormous rebalancing between credentials and potential."

New match-ups for people with autism, ADHD

New York-based Pymetrics also uses games to evaluate potential candidates, particularly for the financial sector. In this case, neuroscience games.

"We're able to actually gather tens of thousands of data points per person through these games, whereas questionnaires, you have one question, you have one data point," says Pymetric's head of marketing Alena Chiang.

"The traditional way of doing HR is not great. It's actually unintentionallydiscriminatory, and what we really want to do is democratize that and take out any subjectivity or bias that exists right now."

Begun by Frida Polli and Julie Yoo, a Canadian who studied at Waterloo University, Pymetrics is building analytical models and tests to help find jobs for people with autism, ADHD and dyslexia, in particular.

These are applicants who have often been short-changed by traditional hiring procedures.

Using data, the company hopes to quantify the value of a person's incredible attention to detail or meticulous focus and match them up to jobs where they are likely to thrive, Chiang says.

Skilled people have to be found

The potential for these systems is great, says Michael Daniels a professor of organizational behaviour and human resources at University of British Columbia's Sauder School of Business.

But, he cautions, recruiters haven't revealed the data that drive their algorithms, so it can be difficult to gauge that the correlations are reliable.

As he sees it, how well a person performed in a previous job is probably still the best indicator.

"Assessing someone's success on their previous job over the course of, say, five years, gives an indication of their 'typical performance' and incorporates additional factors like their day-to-day motivation, ability to work well in teams and their perseverance to finish long-term projects."

In this new data world, though, California-based Entelo has developed a software platform that uses algorithms to create data banks of even potential job seekers, before they've dropped that first resume in the email.

Entelo, which names Facebook, GE and Uber as its clients, does a deep scan of social media, including Twitter, Linkedin and professional community sites such as Stack Overflow and Dribble, and sometimes even Pinterest or Instagram.

"If you're an engineer or a more experienced salesperson or a marketer, the reality is there's way more demand than supply," says Entelo CEO and founder Jon Bischke.

"Historically job boards would work for engineering roles, you could post to your corporate website, people would apply," he says.

"But for the highly skilled workforce today, they're frankly not applying for jobs, they have to be found."

Predictive analytics

Using social media data, Entelo has created more than 100 million profiles of potential candidates that recruiters can access using a search engine.

These candidates have not signed up for this service or asked to be included in the database. But for many that doesn't matter.

Bischke recounts a story about an individual who Entelo suspected was ready to make a job move based on small changes he had made to his Twitter profile.

Entelo checked the profile against the algorithm it had developed to identify restless staff and were able to successfully recommend this person to recruiters.

This man was happily surprised to find his job search had already begun unbeknownst to him. Though others, Bischke acknowledges, have asked to be removed from the database when they found out about it.

The use of data by recruiters has been a common practice for years. But the hurdle, Daniels says, has been the ability of corporate management to understand the complexity of what the data and algorithms represent.

Indeed, according to a 2014 report by the international consulting group Deloitte found that companies have been slow to embrace talent analytics.

Its survey of more than 2,500 business and HR leaders around the world found that only four per cent of organizations felt they had predictive talent analytics capabilities, though 60 per cent said they wanted to create a plan to start using the method.

"It is notoriously tricky to get leaders to believe the power of data and predictive analytics over their own intuition about people," Daniels says, "even though the former is almost always superior to the latter."