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Before the
discovery of Australia,
people in the old world believed that all swans were white; a belief that was
based on enormous historical empirical evidence. But then black swans were seen
in Australia
and people realized that rare, unpredictable events, can occur. Since then a
“Black Swan Event” has come to mean more than a rare event.
Taleb
defines a Black Swan event as having 3 characteristics:
- It is an
outlier, beyond prior expectations or experience. It represents a qualitative
change to society or marketplace.
It has a huge impact. Black Swan effects drive
all society from culture to religion to historical events to economics to
elements of personal lives. In contrast,
ordinary events, those we read about in the newspaper, are mostly inconsequential.
- After the
Black Swan event occurs people find ways to make the event seem explainable and
even predictable. In retrospect, a Black Swan event is not so surprising but a
logical outcome of the emerging innovations and societal forces.
The concept
has helped explain the stock market collapses and the changes caused by
innovations such as the telegraph, the battlefield tank, and the airplane.
Think of the auto industry’s Black Swan events – the invention of the
automobile itself, the enclosed car, the automatic transmission, the Beetle,
the minivan, the SUV, rental cars, the hybrid and dozens of others. The
marketplace dynamics in-between these events are largely insignificant.
There are
several implications to the Black Swan concept.
First, we
largely study by examining the past, by making judgments about what works and
by projecting the past into the future. The assumption is that major
disruptions of the past or extreme outliers will not occur and, in any event,
are impossible to model, an assumption that should be more frequently
challenged. That was true of the Maginot Line that was supposed to protect France from Germany in WWII and in fact ended
up failing to even slow down the German Army who did not obey the logic of
history and simply went around it in a classic Black Swan event.
Second, we
should spend more time thinking about qualitative changes that might occur and
their first order and second order implications. We should think more about
what we don’t know as opposed to what we do know. Scenario analysis tools are
relevant to this task.
Third, we
should spend more resources on creating and/or managing responses to Black Swan
perturbations to the marketplace and less time in optimizing the current status
quo.
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