My recommendation for improving
your skills at navigation in these exponentially changing environments has
three parts. First, learn the vocabulary
used in these discussions; the accompanying table summarizes.
Second, learn to use the S-curve
model, which you can fit to your data
to estimate where the inflection and
saturation points are likely to be. This
model is your sextant.
Third, learn key skills of navigation:
• Becoming aware of the histories
of communities, enabling you to
see the concerns, breakdowns, and
anomalies that are opportunities for
• Discerning possibilities that are
in social space, spotting openings enabled by emerging technologies and
avoiding cul-de-sacs of obsolescent
• Sensing the moods of user communities, regions, and the world, enabling you to detect what people are
• Learning which groups, organizations, or networks have social power,
enabling you to follow the movements
Are the historical forces in the seas of
change so strong that we are adrift and
navigation makes no discernable difference? I think not. We are not rudderless.
Navigation helps us steer the rudder. We
join fellow navigators who, throughout
the ages, have crossed the seas.
1. Bass, F., Krishnan, T., and Jain, D. Why the Bass model
fits without decision variables. Marketing Science 13
(Summer 1994), 203–223.
2. Friedman, T. Thank You for Being Late. Farrar, Straus,
3. Gladwell, M. The Tipping Point. Back Bay Books, 2002.
4. Grove, A. Only the Paranoid Survive. Crown
5. Kelley, K. The Inevitable. Penguin, 2016.
6. Kurzweil, R. The Singularity Is Near. Penguin, 2006.
7. Seba, T. Rethinking Transportation 2020–2030.
8. Seely Brown, J. and DuGuid, P. The Social Life of
Information (2nd ed). Harvard Business, 2017.
Peter J. Denning ( firstname.lastname@example.org) is Distinguished
Professor of Computer Science and Director of the
Cebrowski Institute for information innovation at the
Naval Postgraduate School in Monterey, CA, USA, is Editor
of ACM Ubiquity, and is a past president of ACM. The
author’s views expressed here are not necessarily those of
his employer or the U.S. federal government.
I thank Nicholas Dew, Fernando Flores, Ron Kaufman,
Ted Lewis, and Peter Yaholkovsky for enlightening
conversations on these topics.
Copyright held by author.
These approaches are based on the
claim that an inflection or jump point
signals an impending disruption. Because the models are only approximate, the exact timing of an inflection
or jump point can vary considerably.
Most of the technology forecasters
who work with these models therefore hedge by giving a five-year to 20-
year window in which the disruption
is likely to happen, if it happens at all.
Even if the modeling error could be
removed, the prediction of a disruption depends on many other factors
that are not captured by the S-curve
model. The most notable is that the
adoptions counted by the adoption
function all reflect human choices.
Whether a given individual decides
to adopt depends on a host of fac-
tors such as the opinions of friends,
the assessment that the new technol-
ogy is more valuable than the old, the
economic condition of the adopter,
the perceived cost of the transition,
the mood of the times (for example,
bull or bear markets), and an individ-
ual’s own receptivity toward change.
Professionals have to assess all these
factors about their clients and mar-
kets before acting on the claim of a
is not a reliable
at some point the
resources to support
the growth run out.
Terminology for exponentially changing environments.
The rate of change of adoption function n(t) is increasing
exponentially over time. Moore’s Law is the exponential
growth of the number of transistors on a chip.
Tipping point A somewhat subjective point on an exponential curve where
the extent of adoption n(t) has become noticeable and its
Adoption People commit to using a new technology.
Diffusion Technology adoption over time, spreading throughout a
community of use.
S-curve The n(t) function rises exponentially to an inflection point,
Inflection point The point at which an S-curve switches from increasing rate
to decreasing rate (zero second derivative).
Technology jumping Vendors whose technology S-curve has reached its inflection
point switch to a new technology whose S-curve is still in
its exponential growth stage, thereby maintaining overall
10x jump point A rule of thumb: An inflection point exists when an emerging
technology can do a job of the existing technology 10 times
faster or cheaper.
Contingencies Future events that are possible but not guaranteed. There is
no way to predict when or if they will occur. If they do occur
the environment changes and people change their practices
Black swan An improbable, unforeseen contingency.
Deep historical forces Influences that persist over a long time and bring about
change without any apparent cause.
Disruption A rapid change of practice in a community.
Avalanches Sweeping and profound economic and social changes that
accompany multiple disruptions. They change professions,
identities, practices, and commonsense assumptions.
Navigating A skill of finding a way to a goal in the unpredictable swirls
of the world that accompany historical forces, contingencies,
black swans, disruptions, and avalanches.