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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!