Business Exposed164
returns, industry dynamism, municence, etc. And they found
the following: nothing. Absolutely zilch.
Analyzing 114,191 observations from a variety of industries,
starting from the late 1970s, they found that some lines of
business may be turbulent, but no more turbulent than before.
Or, as they say, “Our results suggest that managers today face
markets no more dynamic and opportunities to gain and
sustain competitive advantage no more challenging than in
the past.”
So please stop telling me that “the world of business is increas-
ingly changing fast”. It ain’t. It is the same as it ever was.
Is innovation over-rated?
Let me now grumble at some other business press favorite:
innovation. And the accompanying proclamations such as
“innovation in today’s business is key”. Innovation is grand;
innovation is what we should all strive for; innovators are
always the heroes of the story. They saw the opportunity
when no-one else could see it; they persisted stubbornly when
everyone said they were a fool; they suffered hardship but
eventually deed the odds to make it big, and so on and so
forth.
And, granted, innovation is great. But we hear very little about
the (undoubtedly many) poor sods who thought they were
seeing something, but it really was just their imagination, who
persisted stubbornly and foolhardily with something that was
never ever going to work, who continued to suffer hardship till
they vanished.
Do innovating rms perform better? Evidence from academic
research on the topic is certainly equivocal: it is very hard to
nd solid evidence that rms which innovate (e.g., obtain more
patents) perform better.
It so happened that I had a database of about 1,300 rms active
in the Chinese pharmaceutical industry, and all their innova-
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Making far-reaching decisions
tions. Note, innovations did not all have to be real blockbusters
but could just be new types of products or applications. These
new types could concern truly new drugs but more often they
concerned a new dosage of some existing drug, a new intake form
(e.g., pills versus injections), a new application of the same drug
(i.e., a different disease for which a particular existing drug might
also work), etc. Thus, not all of them were very radical innova-
tions, but they were all new enough for them to have required
clinical trials before their launch.
Using these data, I rst tested, through some fancy statistical
methodology, whether such innovations contributed to the
growth of the rms over the subsequent years. The answer was a
clear “no”; in fact, innovators grew more slowly.
Then I thought, “Perhaps they are innovating because they’re
running out of growth”, so I applied a different (and even
fancier) statistical technique to correct for that. Still, the answer
was a resounding “no”: innovators subsequently really had
more trouble growing and this was a direct consequence of their
innovations.
So then I thought, “Perhaps I am looking at the wrong thing; and
I should not be looking at growth but at rm survival.” Therefore,
I changed my (already fancy) statistical methodology to test the
impact of innovations on rm survival. But no, innovators died
(i.e., went bankrupt) more often than non-innovators.
Then I thought, “Ah, it must be because innovation is risky;
innovators may be the big failures of the industry but they are
probably also the biggest success stories (I should really have
thought of this earlier . . . better not tell anyone . . .).” So I used
an even fancier statistical methodology to model not only the
average survival probability of the innovators (vis-à-vis the
non-innovators) but also their “variance”. But no . . . innovators
really did fail more often than non-innovators, and with very
little “risk”! In layman’s terms: they died pretty quickly and
you could be pretty sure of it. No risk–return trade-off here: the
message is, do not innovate and you’ll get a higher return for
less risk!
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