One of the most useful things I learned when I worked at McKinsey’s Financial Institutions Group was understanding risk.

It was a concept that I did not fully grasp before working in risk-based industries like consumer lending.

However, once it was explained to me, it made total sense.

A decision with unknown variables has risk. Risk is the same as uncertainty.

You know with high confidence that 2 + 2 = 4.

Making this calculation has zero risk because all variables are known.

But let’s consider the following equation:

2 + X > 7

In this equation, X isn’t just an unknown (in the algebraic sense) but is also not yet knowable (in the real-world sense that some data just isn’t available).

When people think about decision-making under uncertainty, the tendency is to look at the outcome of a decision to determine whether the decision was a good one.

From a risk-mathematics (a.k.a. statistical) standpoint, this thinking is flawed.

Let’s say you’re offered the opportunity to earn \$1.

To earn this \$1, you have to walk across a busy freeway at a specific time of day specified by someone else while blindfolded and at a consistent speed, without stopping.

If you take this deal and make it across without injury or death, it’s tempting to conclude that you made a good decision because you made \$1.

Intuitively, I hope you can see the problem with this kind of thinking.

In the world of risk management, we differentiate between downside risk exposure versus downside risk realization.

This is a very important distinction.

Just because the downside event didn’t happen doesn’t mean you made a good decision on a risk-adjusted basis.

Walking across a busy freeway blindfolded exposes you to a lot of risk regardless of whether the adverse outcome occurs or not.

Sometimes, you can expose yourself to enormous risk and have a positive outcome. This doesn’t mean you were special or talented. It simply means you got “lucky.”

If your goal is to make \$1 million, you’re offered the opportunity to walk across the freeway blindfolded for \$1, and you’re allowed to do it one million times, I hope you can intuitively sense that this is a bad idea.

If you’re inclined to do this because you did it one time and nothing bad happened, you’re confusing risk (of a downside event) realized with risk exposure.

Much of the work I do with clients is focused on risk management.

I try to find ways to increase the payoff of a decision with uncertainty while minimizing the likelihood and magnitude of an adverse event.

To extend our earlier analogy, I’d try to renegotiate that deal of walking across the freeway blindfolded so that the compensation for safely crossing the road isn’t \$1, it’s \$1 million.

Then, I’d try to find a way to restructure the game so that I could choose the day of week and time of day when there’s daylight (so drivers can see me) but there aren’t a lot of cars on the road (like noon on a holiday when people tend to stay at home).

I’d also ask if I’d be allowed to wear high-visibility clothing or a helmet with a flashing red light (similar to a fire truck siren). I’d also want to carry and use an air horn (so I could warn others).

What I’ve described above is the practice of risk management.

Risk management involves increasing the likelihood and magnitude of the upside of a decision with uncertainty while simultaneously reducing the likelihood and severity of an adverse/downside event.

The ability to make decisions in the face of uncertainty is enormously useful.

You can use this type of thinking to decide whether to take a particular job offer.

You can use this approach to decide what time to leave for the airport when catching a flight to an important family event.

You can use this framework when deciding whether or not to get a COVID-19 vaccine.

Many aspects of life can be considered through the lens of risk management. It isn’t the only way to think through a decision, but it is one useful framework (of many) to consider when making a decision.