If you aren’t prepared for what life can throw at you, you may be in for a great fall.
As I’m sure everyone understands all too well by now, life has a way of throwing monkeywrenches into the system. If there’s anything that’s been consistent about 2020, it’s that every month seemingly has a new surprise to spring upon humanity.
Instead of traveling over smooth ground, we are on precipitous terrain. Any kind of long term forecast is currently impossible.
When chaos is the order of the day, you must be able to make and act on snap judgements without overcommitting on your previous decision. How do you do that?
As I was folding my laundry tonight, I was thinking about everything that’s happened over the past few days, at the national level, but more importantly what was going around me in my local city. And some things aren’t adding up.
(As I’m writing this, President Trump has just declared a national emergency over the spread of COVID-19, aka the Coronavirus. It’s been only a few days since major sporting events were suspended and cancelled, most notably the NBA and March Madness. So I don’t know right now how things are going to play out over the next few weeks or months.)
Over a decade and a half ago, I used to be a manufacturing engineer in the automotive industry. One of my regular duties was to conduct something called an FMEA, Failure Modes Effects and Analysis. It was a risk assessment over what could possibly go wrong in a car (or a component of it), which guided what type of preventive measures and quality checks had to happen.
The Big Three automakers had a pretty standard system: there were three measures, rated on a scale from 1 to 10. You multiply the three numbers to get anything between 1 and 1 thousand. The bigger the number, the bigger the risk. If it was something under a hundred, you almost didn’t think about. However, if it was close to a thousand, it was all hands-on-deck, the-company-could-go-out-of-business bad.
These were the three measures: severity (what’s the worst case), occurrence (how often does it happen), and detection (how quickly can it be spotted).
I’m going to add in a fourth factor to the calculation: contagion. The automotive FMEA doesn’t account for this, because when a tire blows out on one Ford Explorer, it doesn’t cause three or four other Explorers to crash. So now our scale goes from one to ten thousand.
In thinking about the virus, I decided to apply my FMEA math. So let’s go:
(Disclaimer, I’m going to throw out some numbers, but all of these are second-hand with no references. This is a thought experiment, not a policy paper.)
