412
n
The success trap (and some ideas how to get out of it)
found that older rms came up with more innovations but that
these were usually less inuential and concerned mere variations
on already well-known themes.
The problem for top managers is that a lack of innovation is not
solved by money alone. Top managers can decide many things;
as discussed in Chapter 1, they can decide to acquire company
X, throw in money and a team of bankers and see it done. They
can decide to enter country Y, tell business development to
make it so, and it will happen. They can choose to change an
incentive system from individual to group rewards, and HR will
do it. However, you can’t just decide to have more innovation.
You can say it, order it, shout it really loudly, but that doesn’t
mean products will magically materialize. Innovation is a subtle
process that involves many aspects of the organization, some of
them tangible but many of them much more tacit and informal.
And once those start to ossify, there’s no pill that will cure that.
Framing something as a threat or an opportunity
dramatically alters what we choose
So far, I have discussed how the mental models of our business
and its environment are shaped by prior success and how they
signicantly inuence people’s decisions in terms of what course
of action to pursue. Recall the research by Professors Allen
Amason and Ann Mooney, discussed earlier in this chapter,
which showed that CEOs from high-performance rms were
inclined to interpret changes in their business environment as a
threat, where CEOs of poorly performing companies tended to
interpret changes as a positive thing? It reminded me of a famous
experiment by Nobel Prize-winner Daniel Kahneman and Amos
Tversky, which went as follows:
Imagine that the US is preparing for an outbreak of an unusual Asian disease,
which is expected to kill 600 people. Two alternative programs to combat the
disease have been proposed.
Assume that the exact scientic estimates of the consequences of the programs
are as follows:
Business Exposed42
If program A is adopted, 200 will be saved.
If program B is adopted, there is a one-third probability that 600 people will be
saved and a two-thirds probability that no people will be saved.
Which one of the two programs would you prefer?
Kahneman and Tversky found that a substantial majority of people would
choose program A.
Then they gave another group of people the assignment but with the
following description of the (same) options:
If program A is adopted, 400 people will die.
If program B is adopted, there is a one-third probability that nobody will die and
a two-thirds probability that 600 people will die.
They found that, in this case, a clear majority of respondents favored
program B! But the programs are exactly the same in both cases . . . !? How
come people’s preferences ip although they are confronted with the
same set of choices (albeit described slightly differently)?
It is due to what we call “framing effects”, and they greatly affect
people’s preferences and decisions. For instance, in the rst case,
program A is described in terms of the certainty of surviving
(which people like), but in the second case it is described in
terms of the certainty of dying (which people don’t like at all!).
Therefore, people choose A when confronted with the rst
program description, while in the second case they favor B,
although the programs are the same in both situations.
We also see this inuence in strategic decision-making, for
instance in terms of whether particular environmental develop-
ments are “framed” as opportunities (which we like) or threats
(which we don’t like). A few years back, Clark Gilbert – at the
time a professor at the Harvard Business School – analyzed
American newspapers’ responses to the rise of online media in
the mid-1990s.
He found that those newspapers that, in their internal commu-
nications and deliberations, described online media as an
opportunity (e.g., “a new avenue for attracting advertising
revenue”) coped quite well. In contrast, those newspapers that
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