HBR Special Issue
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social types of learning are
more likely to result in the
formation of new habits and
practical behaviors. Most of
the problems we encounter
during our everyday working
lives are ill-defi ned rather than
well-structured, so they do
not have an objectively correct
solution, requiring adaptive
rather than technical learning.
However, this requires seeking
the right feedback and being
receptive to others’ sugges-
tions, including criticism.
Most of us are so busy trying
to demonstrate competence
that we forget to learn, and we
believe asking for suggestions
is a sign of weakness. If you
have limited opportunities to
learn from others, though, you
can always learn something
about yourself: How do others
perceive you, including your
talents and performance? An-
swering these questions will
help you identify gaps, as well
as future learning areas.
Learning should never
stop. Regardless of your past
achievements and present
level of expertise, your future
depends on your ability to
keep learning.
Originally published on HBR.org
July 20, 2018
HBR Reprint H04G6O
Tomas Chamorro-Premuzic
is the chief talent scientist at
ManpowerGroup, a professor of
business psychology at Univer-
sity College London and Colum-
bia University, and an associate
at Harvard’s Entrepreneurial
Finance Lab. He is the author of
Why Do So Many Incompetent
Men Become Leaders? (And
How to Fix It) (Harvard Business
Review Press, 2019). Follow him
on Twitter: @drtcp.
OUR VIEW OF the world is
powered by personal algo-
rithms: observing how all
the component pieces (and
people) that make up our
personal social system inter-
act and looking for patterns
to predict what will happen
next. When systems behave
linearly and react immedi-
ately, we tend to be fairly
accurate with our forecasts.
This is why toddlers love
discovering light switches:
Cause and eff ect are immedi-
ate. The child fl ips the switch,
- Throw
Your Life
a Curve
→ by WHITNEY
JOHNSON
and on goes the light. But our
predictive power plummets
when there is a time delay or
nonlinearity, as in the case of
a CEO who delivers better-
than-expected earnings only
to be surprised by a drop in
the stock price.
Enter my coauthor,
MIT-trained strategist
and engineer Juan Carlos
Méndez- García, who consults
with both start-ups and For-
tune 500 companies. Accord-
ing to Méndez-García, one of
the best models for making
sense of a nonlinear world
is the S-curve, the model
we have used to understand
the diff usion of disruptive
innovations and which he
and I speculate can be used to
understand personal disrup-
tion—the necessary pivots in
our own career paths.
In complex systems like a
business (or a brain), cause
and eff ect may not always be
as clear as the relationship
between a light switch and a
light bulb. There are time-
delayed and time-dependent
relationships in which huge
eff ort may yield little in the
near term or in which high
output today may be the
result of actions taken a long
time ago. The S-curve de-
codes these systems by pro-
viding signposts along a path
that, while frequently trod, is
not always evident. Our hy-
pothesis is that those who can
successfully navigate, or even
harness, the successive cycles
of learning and maxing out
that resemble the S-curve will
thrive in this era of personal
disruption.
Let’s do a quick review.
According to the theory
of the diff usion of innova-
tions—an attempt to under-
stand how, why, and at what
rate ideas and technology
spread throughout cultures—
diff usion or adoption is rela-
tively slow at the outset until
a tipping point is reached.
Then you enter hypergrowth,
which typically happens
somewhere between 10% and
15% of market penetration.
Saturation is reached at 90%
or more.
For example, assuming an
estimated market opportu-
nity of one billion, Facebook
took roughly four years to
reach 10% penetration. Once
it reached a critical mass of
100 million users, hyper-
growth kicked in due to the
network eff ect (for example,
friends and family were now
on Facebook), as well as
virality (email updates, photo
albums for friends of friends,
and so forth). Although we
could quibble, depending
on our inputs, over when
Facebook will reach satura-
tion, there is no question the
rate of growth has begun to
slow and is now limited, if for
no other reason than by the
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