Let’s say Bob is jetting from Heathrow to JFK on a Virgin Airways A330. Chance of crashing? One in 5.4 million. That means that he could apparently expect to fly on the route for 14,716 years before plummeting into the Atlantic, writes The Economist (Jan.29, 2015). The 14,716 years figure might cause your students a bit of confusion. It’s the average length of time people will fly before crashing, if lots and lots of them do it every day. An alternative way of expressing it would be to say that if you were to arrange to fly this route every day for the next 10,210 years, your chance of dying would be 50%. And if you wanted to book enough flights to be almost certain of crashing, you reach a 99% probability at 67,833 years of daily flights.
Safety statistics collated by IATA, the airline association, show that in 2013 more than 3 billion people flew on commercial aircraft. During that time, there were 81 accidents and 210 fatalities. What is more, this figure has been falling for years. By way of comparison, the World Health Organisation says there were over 1.2 million road traffic deaths around the world in 2010. It is the leading cause of death among 15-29 year olds. Oxford University calculates that in 2006, a British resident had odds of 1 in 36,512 of dying in a motor accident and 1 in 3.5 million dying in a plane crash.
The deadliest plane crash in history occurred in 1977 in Tenerife when 583 people were killed after two jumbos collided on the runway. Yet, that many people die from heart disease in the U.S. every 8 hours. As the book How Risky Is it, Really explains, air crashes are considered catastrophes while heart attacks are not, because they fulfill 3 criteria: “A catastrophe has to be big, it has to happen all at once, and something about it has to be calamitous—disastrous—really bad. A plane crash kills a lot of people all at once, in one place, and in a really horrific way. But heart disease meets only one of those criteria.”
Classroom discussion questions:
1. How does this concept impact supply chain disruptions that we discuss in Supplement 11?
2. Why are probabilities such as these important in operations management?
