Risky Business
In the 1983 movie by the same name, Joel Goodsen (Tom Cruise) nearly makes a career out of misunderstanding the risks associated with several decisions he makes while his parents are out of town. Unfortunately, this is not just the purview of coming-of-age comedy films. We often fail to understand and accurately assess the risks we face every day.
This was brought home for me this weekend as I stood under the stands with 55,000 other people while we waited out a storm delay at Boone Pickens Stadium. The reason we were instructed to go under the stands was the potential danger of lightning. An average of 25 people die each year in the United States due to lightning. The NCAA only put severe weather guidelines in place, including lightning, about 14 years ago. Prior to that I could find no account of a lightning strike at an American football stadium. Does this mean the danger isn’t real? No, it’s just very unlikely (the probability). However, the result (the severity) of being struck by lightning can be catastrophic. So, when lightning strikes, we scurry for cover.
What I find ironic is the same leaders who clear the stadium when a flash of lightning is seen, also sell beer at the stadium with little or no effort to limit over-drinking. According to the National Highway Traffic Safety Administration, 37,133 people died in traffic crashes in 2017 in the United States (latest figures available), including an estimated 10,874 people who were killed in drunk driving crashes involving a driver with an illegal BAC (.08 or greater). So, to be clear, the probability of being killed by a drunk driver (including you as the drunk) is 434 times greater than the probability of being struck by lightning. Yet we drink and we get in our cars and drive home surrounded by people who drink.
It turns out that people are notoriously bad at evaluating the probability that something will occur, and also terrible at accurately estimating the severity of a bad outcome or the benefit of a good one.
People are really bad at probability. The classic example is the coin-flip. If a tossed coin comes up tails 10 times in a row, most people will expect it to come up heads on the next flip. The reality, as we know if we think it through, is that the chance of either heads or tails is the same 50/50. People just don’t naturally think in terms of computational probability.
A simple heuristic for helping to better analyze the probabilities we face every day is to separate events into some broad categories based on how frequently they seem to occur. The sun always rises, rain falls frequently but not always, being attacked by a lion rarely occurs, and people sprouting wings and flying never happens. By using historic data, we can group things into areas that help us determine how and when to respond.
People are also highly prone to misestimating the result of an event (good or bad.) For this problem we need to address three common errors our brains make.
First, reward often obscures risk. We tend to overestimate the upside and dismiss the downside when the trend has been positive or when we want what is offered if we take the risk. To mitigate this thinking error, we need to get better at asking ourselves what our winning (or potential winning) is keeping us from seeing. Sometimes we need to ask other people who are not invested in the choice to point out the blind spots.
Second, sunk cost tends to keep us committed to a path even when the probability is poor for a good outcome. The “accountant” in our brain tends to not speak up because of what we already have invested in the path we are on. This skews the analysis and we continue to underestimate to problem. To resolve this, we need to be honest about our failures, and also learn that facing losses is better than avoiding them. Again, another set of eyes can be helpful.
Finally, paralysis in the face of the unknown often causes us to simply not analyze the future impact. We tend to use present data rather than trying to assess and test the unknown. There are many strategies for creating a learning loop that helps mitigate the downsides. The Plan-Do-Check-Act Cycle is just one.
The need for accurate risk assessment including both the probability and the severity of potential risks is critical for an organization. Making sure that we understand how likely something is and what the most realistic result will be if it happens allows us to properly apply our resources. Combining probability and severity into a single measurement reflects the importance of an event.
If there is high probability but no real downside (like the sun rising) we know it will happen, but it doesn’t need a response.
If there is some probability and only inconvenience as a result (like rain falling) we should look for clear signs that it could happen and prepare when we see those signs.
If there is low probability but high cost (like being attacked by lions) we should be vigilant and, if we see ANY sign it might be happening or could happen, take appropriate action.
If there is no chance it will happen, no matter how severe the result is, we probably don’t need to worry about a response (no one has asteroid falling insurance.)
This weekend, 55,000 people spent considerable effort protecting themselves from something that was highly unlikely (though it would have been fairly severe if it had happened) and very little effort protecting themselves from something that was fairly likely to happen (and also could be very severe.)
We just participated in a risk assessment exercise with Lockton, our insurance broker, to help us quantify the importance of the various risks we face as a company. The result is a graphic representation of the importance of each risk which enables us to focus our energy and resources on things that have large potential impact and fulfill our core value to be good stewards of the resources God has given us.
Business is risky. Life is risky. We can and should understand and mitigate those risks when and where we can and then trust that God is in control. That is the least risky way to live and it is The Kimray Way.