Those pesky “Black Swans” – extremely low probability events with a large impact have been burned into the lexicon of just about every MBA.  With “Black Swan awareness” in mind, executives are counseled to be on the prowl for unlikely events that could potentially wipe out their headquarters, disrupt supply chains, bankrupt the company, or even lead to employee deaths. And while Black Swans are definitely reasons to seek safer ground, it’s inevitable the biggest risk is right under your nose!

Author Jared Diamond writes for the Weekend Financial Times about the importance of understanding everyday risks. In studies of New Guineans, he cites how jungle dwellers will refuse to camp out underneath a dead tree. That’s because even though the risk of such a tree falling on you is 1 in 1000; if one does enough camping under dead trees eventually it will lead to an untimely death. Diamond writes; “New Guineans have learnt from experience which are the real dangers in their lifestyle and they remain constantly alert to those dangers.”

Speaking of daily dangers, Diamond mentions for older adults, it’s more likely you’ll die slipping and falling in the shower, than in any horrific event your mind can conjure.

I blame the media for this over-estimation of extreme events. Simply open a newspaper and you’ll think the world is coming to an end. Fires, earthquakes, wars, pestilence and central bankers (yes, the inclusion of central bankers in “disasters” is intentional) are prominent.  With evidence of just your local paper or watching one hour of CNN, it’s easy to believe the world is filled with one extreme disaster after another.

And while Black Swans are definitely something to prepare for in terms of creating more robust or anti-fragile structures, it’s often daily events that are more likely to hurt us. Case in point, while dying in an airplane crash is a horrific way to check out (1:250,000 probability of death in a given year), it’s much more statistically likely that you’ll meet your maker traveling in a car to your local grocery store (1:5000).

So, yes, prepare as much as you can for extreme events.  Identify the “known knowns” for which you have probability theory to assist, the “known unknowns” where Bayes might help, and try to build robustness for the very infrequent Black Swan type “unknown unknowns”.  

But in all this, please pay attention to the risks closer to home, those dangers you might face every day. And watch out when taking a shower. That first step in, could be quite a doozy.