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Expert
Overconfidence
As we
saw in the Overconfidence game, even experts are overconfident in their ability
to predict. For experts there are additional difficulties
that fuel their overconfidence, such as motivational and
cognitive biases. Motivational bias affects the response
that the expert "wants" to give, usually motivated
a perception of reward or penalty. If I am a petroleum engineer,
I want to think that petroleum will continue to play an
influential role in the future economy.
Of various
cognitive biases, expert overconfidence is most noted in
the "confirmation" bias. Experts tend to look
for data that confirms or supports their preliminary findings
or beliefs. As an example, a marketing manager was researching
her company’s competitive position in acquiring "new
users" of her product to explain the recent decrease
in market share, since this is where she did all of her
marketing. It turned out that in actuality she was capturing
a high percentage of new users, while losing a high percentage
of current users, which she was not measuring. Thus, the
lesson learned is that experts should ask disconfirming
questions, such as "what data or causes would lead
us to change our minds?" If the data does not exist,
then the expert can be more confident in their opinion.
The
systematic, operational approach that systems thinking applies
to looking at complex systems provides the ground for asking
those disconfirming questions. Additionally, through the
use of the system dynamics simulator, experts are able to
test their hypotheses about how the system works, to see
if it really does work that way.
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