“Make hay while the sun shines!” If you’re considering buying a home, you might be…
In an Uncertain World, It Pays To Think Like a Gambler
What’s up is up, what’s down is down. What’s true is undoubtedly true and what’s false must always be false. The human mind tends to process the world in this way – absolute and deterministic, rigidly linear along a simple binary logic. And for good reason! We make choices constantly, most of them without conscious attention.
“That apple looks good, so it must taste good” <chomp>;
Simply put, if we tried to factor in every contingency and weigh the odds before taking a bite, we’d die of starvation. Instead, our minds use heuristics to simplify the world and our choices about it:
“That bear looks scary, scary things are dangerous, so it must be dangerous” <run away>
That person strikes me as friendly, I like friendly people, so I’ll like that person” <chat>
Sometimes, defaulting to these learned, linear responses saves us time and mental energy. But once we’ve been around the block a few times, we come to know that the world is full of uncertainty, anything but black and white. If we insist upon thinking about the world in a rigid, predetermined way, it can cost us dearly.
“That house is on a block with too much street noise, street noise is undesirable, so I won’t buy it. <missed opportunity>
“The last time I invested in a startup company, I lost money, that online bookstore company is also a startup, so I’m not going to invest in it.” <Amazon, anyone?>
The fact is, the world of business is trending away from rule-based predictability and towards ever-changing probability. Data is everywhere, the cloud is every growing! Like it or not, information technology means that we can analyze our decisions from every angle, and the more angles we see, the more possible outcomes there might be. The world is a gamble!
Any gambler worth his salt will tell you that, in a world of uncertainty, information is king. As we gather more and more data in a given scenario, the expected outcome becomes less random and more predictable. Let’s say someone’s playing poker and is dealt a weak hand. If they are a linear, deterministic thinker, they’ll default to their simple heuristic:
“I have a weak hand, weak lose to strong hands, so I’ll fold.”
But if they are a probabilistic thinker, they will embrace the uncertainty, consider all possible scenarios, consider the data available to them, and act accordingly:
“There are hundreds of hands that my opponent could be holding, but based on the way she’s bet so far, and on the way she’s holding her chips, she likely has a hand ranging from marginal to middling, and is unlikely to have a strong hand. If I bet, she will likely fold and I’ll win some money. And even if she calls me with a better hand, I’ll have more information about how she plays and I’ll better predict her actions next time.”
So, how can probabilistic thinking help us in the business world? Let’s take an HR manager for an example. A linear-thinking HR manager will develop a rigid set of rules for what sort of people make good hires, and will apply those to whomever they come across. Thinking probabilistically, that same manager will pour over the data to find the strongest candidates, but will also adjust their expectations as more and more data becomes available. While other companies rely on tried and true strategies, the probabilistic thinkers can find overlooked talent by considering all options.
A probabilistic sales professional has lots of advantages over a linear one: he or she won’t simply close a deal and move on. They’ll take every sale as a data point. Where did the buyer learn about our business? What were the buyers demographics? The more he or she gathers, the less the world of sales is a random guessing game, the more its a matter of well-informed prediction.
Or how about or risk managers? A linear one will assume that their well-worn models of risk assessment will accurately identify viable borrowers, but a probabilistic one will assume that their existing models are imperfect and seek to find more and more data sources. Are there credit-worthy segments of our client base that our models might have missed?
Let’s face facts: the world is changing constantly, and the second we think we know the lay of the land, it’s already changed. But when we assume that our understanding is never perfect and that our knowledge is always incomplete, then we will push ourselves to listen, to respond to new information, and to make well-informed choices in the face of uncertainty.