Tom Viggers, director, pymetrics EMEA, discusses why recruiters could learn a thing or two from the World of Poker
If you haven’t heard of Daniel Negreanu, I recommend looking him up on YouTube. Daniel is a Canadian poker champion and, as one of his opponents describes him, a “sick human.” They mean this as a compliment; Daniel has an uncanny knack for knowing exactly what cards his opponents have while revealing nothing about his own hand.
And if you are on YouTube and follow the rabbit hole, eventually you will find a video series where Daniel teaches his craft and explains the process behind the magic. I always assumed that reading and concealing body language was the key to poker – hence the hats and sunglasses – but I was missing something.
It turns out, the key to poker is probability.
In the series, Daniel talks through his thinking process. Based on careful calculations, he doesn’t play the cards in front of him but the whole range of cards – both those that his opponent might have and those that any opponent might reasonably think he has. He constantly adjusts his behaviour throughout the game to reflect an unfolding range of measured probabilities that he sees more clearly than his opponents.
Listening to the language he uses in his videos, it’s clear that when he sits at the poker table, Daniel sees the world in another dimension. He doesn’t just see one hand and one table of opponents in front of him but hundreds of variations of the whole game simultaneously. He then judges whether checking, calling, folding or raising would be the right thing to do in the majority of cases.
Exploiting probability patterns
Daniel thrives in poker’s uncertain world because he recognises that uncertainty is not the same as chaos. There are patterns of probability that, when you can define and plan for them, can be exploited for huge gain.
That, of course, is not what most people do when faced with an uncertain world – which is why Daniel is a poker champion and the rest of us are not. For the most part, human beings rely on cognitive short-cuts, or biases, to make decisions. That means that often our decisions are poorly informed and, when they cause us to fail, we use biases to justify them so we don’t even learn from our mistakes. For example, we over-estimate the importance of information based on how available it is to us (availability bias) or show favour towards evidence that confirms what we already believe (confirmation bias). See Wikipedia for a long list of these, it’s terrifying.
Perhaps nowhere are these biases more prevalent or more impactful than in the world of recruitment and HR where mental shortcuts routinely have a bearing on other people’s careers and livelihoods. For example, we know at a conscious level that a person’s job history and the opportunities they’ve been given to date are almost entirely unpredictive of their success in a role. And yet a six-second CV/resume screen is commonly the first filter at the top of the recruitment funnel.
What are also common, of course, are skills gaps, first-year attrition rates as high as 50% and women and minority groups being adversely impacted in a multitude of different ways. This is a lose/lose situation.
But things are changing. We now have technological tools (in particular big data and machine learning) to take advantage of the patterns in the uncertainty, just like Daniel does. Companies like our client, Unilever, are using these tools to their significant advantage. And while it’s still relatively early in the game, I’d bet on them becoming more and more dominant over the next few years.