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Recently, the leadership team
of an American supermarket chain
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decided that their business
needed to get a lot more efficient,
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so they embraced their digital
transformation with zeal.
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Out went the teams
supervising meat, veg, bakery,
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and in came an algorithmic task allocator.
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Now, instead of people working together,
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each employee went, clocked in,
got assigned a task, did it,
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came back for more.
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This was scientific
management on steroids,
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standardizing and allocating work.
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It was super-efficient.
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Well, not quite,
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because the task allocator
didn't know when a customer
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was going to drop a box of eggs,
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couldn't predict when some crazy kid
was going to knock over a display,
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or when the local high school decided
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that everybody needed
to bring in coconuts the next day.
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Efficiency works really well
when you can predict
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exactly what you're going to need,
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but when the anomalous
or unexpected comes along --
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kids, customers, coconuts --
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well then efficiency
is no longer your friend.
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This has become a really crucial issue,
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its ability to deal with the unexpected,
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because the unexpected
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is becoming the norm.
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It's why experts and forecasters
are reluctant to predict anything
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more than 400 days out.
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Why?
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Because over the last 20 or 30 years,
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much of the world has gone
from being complicated
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to being complex,
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which means that yes there are patterns,
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but they don't repeat
themselves regularly.
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It means that very small changes
can make a disproportionate impact.
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And it means that expertise
won't always suffice,
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because the system
just keeps changing too fast.