It might sound silly when spoken out loud, but I found the following example quite enlightening about this phenomenon: imagine that you want to drive to the air

It might sound silly when spoken out loud, but I found the following example quite enlightening about this phenomenon: imagine that you want to drive to the airport, and you need to estimate how long it will take you to get there. You can simply measure how long it will take you to drive by dividing average speed by distance. If you actually drove there many times and measured your trip length, most of the time you would end up being later, sometimes horribly so. Why is that? The explanation is actually trivial: no matter how well things work, there is an absolute minimum time required to get to the airport. On the other hand, there are many things that might delay your trip: heavy traffic, closed roads, accidents... So, on the aggregate, there are very few things that can "go well", and they will reduce your trip time only a bit. On the other hand there are many things that can go wrong and make your trip last much, much longer. That's a sort of intuitive explanation of why things like software estimates are fat-tailed instead of normal.