In the daily work of our practice, I think a lot about risk. What it is, what tools are available to manage it, and what managing it thoughtfully even means. Throughout this process, I have often concluded that it's helpful for thinking through problems to simplify risk to two key parts:
- Probability: Properly assessing and aligning with the probability of different outcomes.
- Tolerance: Even when you align with high-probability outcomes, you won't always get the most likely outcome. In case you don't, you need to understand if you can truly tolerate the worst outcomes.
Why is this helpful? For one thing, anecdotally, I've noticed many people see very well through one of these prisms, though they vary on which one. Perhaps more people show up looking for the "correct" answer of what's most likely to happen, and a smaller percentage are fixated on outlier negative risks and are predisposed avoiding any such game entirely. But it seems most rare that people are able to combine the two views and their corresponding strategies together at once.
And of course, properly managing both sides gets closest to the heart of the matter.
The Probability Perspective
When many people think about risk, they tend to focus on likelihood. What's the chance of rain tomorrow? What's the probability this investment will outperform the market? What are the odds this business venture will succeed?
This probability-focused approach makes intuitive sense. We want to align our choices with what's most likely to happen. Statistical models, data analysis, and expert forecasts help us navigate toward decisions with favorable odds.
And there's value here. Understanding probabilities helps us make choices that will usually work out well. If something has a 90% chance of success, betting on it repeatedly will generally lead to good outcomes. Think of the problem-gambler and the casino (the "house"). The house knows the probabilities precisely, and they play the stronger side of the odds over and over again. They don't always win, but they know over many repetitions, they will overall. The problem-gambler, or the "sucker" no one wants to be, doesn't play to the odds. They make rash, outlandish, long-odds bets hoping for a big score.
Two key points here:
- I think this is why more people align with this "probability" perspective. We want to be the sharps, the house, the winner. We never want to feel like the sucker. There's comfort in trying to be on the right side of probability, and of course it helps that the math is on your side, over a large enough sample size.
- "Over a large enough sample size" or "over many repetitions" are critical to probability working out, and they are not to be glossed over. In decision-making, you have to ask yourself, "in this case, am I able to take advantage of averages and many samples, or am I really just making one bet, to receive one outcome?" There's no uniform answer to this – different decisions will yield different answers. But you have to determine which type of decision you're involved in.
The Missing Half: Loss Tolerance
But probability alone tells only part of the story. The critical question we often forget to ask is: "What if I'm wrong? Can I handle the consequences?"
This is tolerance: your capacity to absorb unexpected outcomes. And it's not just about the financial impact; it includes psychological, emotional, and practical considerations as well.
There's a concept called "Expected Value" (EV) which combines outcome probability with outcome severity by multiplying them.
- A bet with an 80% chance of making $100 (+$80 EV) and a 20% chance of losing $100 (-$20 EV) combine to make an expected value on the whole bet of +$60 (+$80 - $20).
- But if you make the bet once, you never actually can get $60. You can only get +$100 or -$100.
- The idea, though, is that if you do it enough times you'll converge toward the expected value, on average, over time.
- Your odds of winning in this made-up example are higher than your odds of losing, so it makes sense that if you keep doing it, you'll win more often than you lose, but sometimes you'll lose $100, and you'll average about +$60 average.
But consider two more skewed scenarios:
- A 99% chance of gaining $10,000, but a 1% chance of losing $100,000 (EV +$8,900)
- A 60% chance of gaining $1,000, but a 40% chance of losing $100 (EV +$560)
The first scenario has better odds of winning (99% instead of 60%), and, as it happens, a much higher expected value (+$8,900 vs +$560). But they aren't the same kind of bet. And the difference highlights the point above about how many chances you get. If you only get to bet once, the difference is stark. You're so much more likely to win the first bet, and if you do win, you'd win so much more.
But many people simply couldn't afford to lose Bet #1. Bet #2? They could plug away regardless of the outcome. It's a worse bet - again, less likely to win and winning less at that. But any outcome is survivable. A math wonk, risk-taker, or trader may scoff at the intuitive feeling many would have about Bet #1 - that it's not worth it, because it could go wrong. But that's really not incorrect! That's the whole issue with failing to successfully merge probability and tolerance.
The probabilities matter a lot more if you get to take a lot of bets, but if you only get to go once, maybe you just can't tolerate the negative outcome. That's a good reason to avoid it. Risk of ruin really does matter. When you're ruined, you don't get to keep playing.
Maybe, when you look at the above, you see something different. Maybe you are just the sort of person who wouldn't hesitate to take Bet #1. But that's not really the point. What does it mean to be that sort of risk taker? Maybe you understand the math and feel like it's worth it - it's a more than fair bet, statistically. Maybe it just means you're less likely to see yourself as the kind of person who'd be that unlucky - you get that technically 1% happens sometimes, but you just don't think it would happen to you.
Those are really just ways of saying you are using the probability lens and not merging it with the tolerance lens. Avoidance and denial aren't strategies, but they might allow you to move forward with decisions you'd prefer to make.
When Good Odds Aren't Good Enough
On the other hand, maybe you could afford to lose $100,000, and you're not really sure what the big deal is. It's popular to use money to illustrate these points, because numbers help to make comparisons and outcomes obvious. Try not to let that get in the way. If you can imagine something you would never want to happen to you, your loved ones, your family or friends, then you, too, have risk and loss tolerance concerns that are worth considering and addressing. Some things just aren't worth even a low probability chance of occurring, if you can possibly avoid it.
It's important to acknowledge and accept this - it means you have something(s) of value in your life, and that you have something to lose.
Once you know that, you can harness that clarity to make even better decisions.
Sometimes, even a small chance of failure is unacceptable:
- A safety engineer designing an airplane can't just aim for 99.9% reliability.
- A retirement strategy can't just be "probably enough" if running out of money means homelessness or starvation.
- A critical medical decision can't ignore rare but devastating side effects.
In these cases, the tail risk - what happens in those unlikely scenarios - matters more than the probable outcome or "expected value."
Blending Both Perspectives - It's Not Binary
True risk management requires balancing and blending both probability and tolerance. This means:
- Assessing what's most likely to happen (probability)
- Evaluating what the real worst-case scenario is (loss/tail risk)
- Evaluating what you can handle if things do go wrong (tolerance)
- Adjusting your approach when the potential downside exceeds your capacity
This balanced perspective often leads to counterintuitive decisions. You might pass on opportunities with excellent odds because you can't absorb the potential downside. Conversely, you might accept less favorable odds when the consequences of failure are minimal. The point is that all of this is OK, and in my opinion, it's preferred.
Key Point: Strategic Adjustment
So far, we've mostly focused on when you may or may not want to take a given risk, as though it's binary. In real life, it often isn't. At its best, good decision making looks like:
- Determining what's expected to happen
- Being honest and thoughtful about what would go wrong if it didn't go as expected, and whether that would be tolerable
- Protecting against or preparing a backup plan for the worst, least tolerable outcomes
- Continuing to move forward in alignment with the most probable expected outcomes!
Sometimes, all it takes to turn potentially reckless risk-taking into a good plan is just explicitly neutralizing the risk. That's the importance of using both lenses in tandem. And that's advanced decision making - understanding the whole picture and knowing how to work within it.
The Path Forward
To improve your risk management:
- Separate your analysis of probability from your assessment of tolerance and be thoughtful about the potential for loss.
- Be honest about what outcomes you genuinely cannot afford or would never want to see happen.
- Look for ways to maintain upside while limiting catastrophic downside.
- Remember that your tolerance for certain outcomes may differ from others, and that your choices should differ accordingly.
Successful decision-makers understand that it's not enough to bet on what's likely - you must also ensure you can handle what's unlikely.
By confronting both faces of risk, you'll make decisions that not only have good odds of success but also protect you from the outcomes you truly cannot afford.
2025-8120985.1 Exp 07/2027