|THE SURPRISE FACTOR
The unexpected "driver" in technology innovation
Surprise is the main characteristic of innovation. Professor
Jeffrey Funk studied 19 electronic industries and found
that in 12 of them, the types of customers who actually
purchased the new products were unexpected. Also the
new technology trajectories generated also new unexpected
new industries. His findings can be found in his article
"Creating and Succeeding in New Industries: lessons
from the electronics industry", available on the web.
Jorge Nascimento Rodrigues interviews Jeffrey L. Funk, professor at Hitotsubashi
University, Institute of Innovation Research, Japan,
Professor Funk is in Japan since 1996. First as an associate
professor at the Graduate School of Business Administration
at Kobe University, and since 2003 as professor at the
Institute of Innovation Research at Hitotsubashi University,
at Kunitachi Campus, near Tokyo. It took its Ph.D. at
Carnegie Mellon University at US in 1984, and was visiting
scholar at Michigan University until 1995.
One of the major findings of your study is the conclusion
that the growth and mature of new industries are based
in unexpected customers, people that the entrepreneurs
and marketers of emergent sectors do not even imagine
as clients in their original business or mental plans.
What is the main result of this empirical finding for
strategic management in new industries?
Firms design products and services based on assumptions
about customer needs. When firms aim the new products
and services at the wrong customers, they end up developing
products that are not appropriate for the actual customers.
Firms need to put more resources into identifying the
The Entrepreneurs' sin
Do you think that one of the reasons for high rate
death of start ups comes from this difficulty to rapidly
change strategies in order to capture those unexpected
Yes. Studies have found that start ups fail for more
often for market than technical reasons and the large
number of unexpected customers in new industries contributes
to these problems.
Another major finding of your paper regards the
empirical conclusion that new technologies trajectories
"generated" unexpected applications or business
models in adjacent or not adjacent sectors. What is
the implication of this finding?
There are implications for firms and governments. An
interesting example for both is the current debate about
new energies for automobiles. While the focus is largely
on electric or hydrogen vehicles where the trajectories
are not very steep, the electronic trajectories (both
wireless and semiconductors) are very steep and can
be used to create completely new traffic systems. Governments
should be using forecasts of the state of the electronics
industry in 2020 to think about redesigning traffic
systems using for example inexpensive wireless sensors,
microprocessors, and wireless LANs.
Do you think that these unexpected applications
and the "convergence" and interaction between
multiple tech trajectories are one of the big opportunities
for growth strategies based on adjacent diversification?
How can a manager or entrepreneur "identify"
Yes I do. Firms can use the examples from the past
to better understand the future. By understanding how
firms have made mistakes about the initial customers
and applications, they can better understand the currently
unmet needs in society. Firms can then use their estimates
of technological trajectories to better understand the
ways in which new industries can be created in the future
and when it is likely that they can be created.
The Mobile Business - a live case
Another interesting point of your paper is the clear
distinction between the Web platform of the 90's and
the mobility emergent sector of 21st century. Can you
explain the reasons for a different approach regarding
Many people have mistakenly assumed that the mobile
Internet is merely the PC Internet on your phone. Instead,
a new set of users and applications have driven the
initial growth in the mobile Internet. Thus, firms need
to understand how these users and applications are different
and how technological trajectories like improved microprocessors
for phones are expanding these applications. For more
information, see my recent book entitled "Mobile
Disruption: The Technologies and Applications Driving
the Mobile Internet.". My conclusion: Mobile Internet
has a different set of initial customers and business
models that requires a rather different kind of approach
than the one used with the Web.
Japanese service providers were
the first ones to find the unexpected initial customers
- young people, largely through the use of entertainment
contents and an expected business model, the micro payment
Can you refer the implications of your findings
for regional or local cluster formation policy?
The importance of information about a new industry
including both customer needs and how the new industry
satisfies those needs is the major reason for clustering.
Unexpected customers and business models contribute
to this clustering since most regions will not focus
on the appropriate customers or introduce the appropriate
business models. This problem is magnified by barriers
to information flows that might include different languages
or different cultures. For example, this is a major
reason why the U.S. and Europe continues to underestimate
the importance of the mobile Internet, which is most
successful in Japan and Korea.
In fact, Asia was the "driver" of mobility
innovation with NTT DoCoMo,as you mention in your recent
Japanese service providers were the first ones to find
the unexpected initial customers - young people, largely
through the use of entertainment contents and an expected
business model, the micro payment system.
What can we expect from tech trajectories in the
The emergence of standard application processes, 3D
rendering techniques, GPS applications, infrared techniques
or intranet applications will also impact on the overall
architecture for the mobile Internet.
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