The case for behavioral strategy PART I
Left unchecked, subconscious biases will
undermine strategic decision making. Here’s how to counter them and improve
corporate performance.
Once heretical, behavioral
economics is now mainstream. Money managers employ its insights about the
limits of rationality in understanding investor behavior and exploiting
stock-pricing anomalies. Policy makers use behavioral principles to boost
participation in retirement-savings plans. Marketers now understand why some
promotions entice consumers and others don’t.
Yet very few corporate
strategists making important decisions consciously take into account the
cognitive biases—systematic tendencies to deviate from rational
calculations—revealed by behavioral economics. It’s easy to see why: unlike in
fields such as finance and marketing, where executives can use psychology to
make the most of the biases residing in others, in strategic
decision making leaders need to recognize their own biases. So
despite growing awareness of behavioral economics and numerous efforts by
management writers, including ourselves, to make the case for its application,
most executives have a justifiably difficult time knowing how to harness its
power.
This is not to say that
executives think their strategic decisions are perfect. In a recent McKinsey
Quarterly survey of 2,207 executives, only 28 percent said that the
quality of strategic decisions in their companies was generally good, 60
percent thought that bad decisions were about as frequent as good ones, and the
remaining 12 percent thought good decisions were altogether
infrequent. Our candid conversations with senior executives behind closed
doors reveal a similar unease with the quality of decision making and confirm
the significant body of research indicating that cognitive biases affect the
most important strategic decisions made by the smartest managers in the best
companies. Mergers routinely fail to deliver the expected synergies.3Strategic plans often ignore competitive responses. And
large investment projects are over budget and over time—over and over again.5
In this article, we
share the results of new research quantifying the financial benefits of
processes that “debias” strategic decisions. The size of this prize makes a
strong case for practicing behavioral strategy—a style of strategic decision
making that incorporates the lessons of psychology. It starts with the
recognition that even if we try, like Baron Münchhausen, to escape the swamp of
biases by pulling ourselves up by our own hair, we are unlikely to succeed.
Instead, we need new norms for activities such as managing meetings (for more
on running unbiased meetings, see “Taking the bias out of meetings”), gathering data, discussing analogies, and
stimulating debate that together can diminish the impact of cognitive biases on
critical decisions. To support those new norms, we also need a simple language
for recognizing and discussing biases, one that is grounded in the reality of
corporate life, as opposed to the sometimes-arcane language of academia. All
this represents a significant commitment and, in some organizations, a profound
cultural change.
The value of good decision processes
Think of a large
business decision your company made recently: a major acquisition, a large
capital expenditure, a key technological choice, or a new-product launch. Three
things went into it. The decision almost certainly involved some fact gathering
and analysis. It relied on the insights and judgment of a number of executives
(a number sometimes as small as one). And it was reached after a
process—sometimes very formal, sometimes completely informal—turned the data
and judgment into a decision.
Our research indicates
that, contrary to what one might assume, good analysis in the hands of managers
who have good judgment won’t naturally yield good decisions. The third
ingredient—the process—is also crucial. We discovered this by asking managers
to report on both the nature of an important decision and the process through
which it was reached. In all, we studied 1,048 major decisions made over the
past five years, including investments in new products, M&A decisions, and
large capital expenditures.
The research analyzed a variety of decisions.
We asked managers to
report on the extent to which they had applied 17 practices in making that
decision. Eight of these practices had to do with the quantity and detail of
the analysis: did you, for example, build a detailed financial model or run
sensitivity analyses? The others described the decision-making process: for
instance, did you explicitly explore and discuss major uncertainties or discuss
viewpoints that contradicted the senior leader’s? We chose these process characteristics
because in academic research and in our experience, they have proved effective
at overcoming biases.
After controlling for
factors like industry, geography, and company size, we used regression analysis
to calculate how much of the variance in decision outcomes7 was explained by the quality of the process and
how much by the quantity and detail of the analysis. The answer: process
mattered more than analysis—by a factor of six. This finding does not mean that
analysis is unimportant, as a closer look at the data reveals: almost no
decisions in our sample made through a very strong process were backed by very
poor analysis. Why? Because one of the things an unbiased decision-making
process will do is ferret out poor analysis. The reverse is not true; superb
analysis is useless unless the decision process gives it a fair hearing.
To get a sense of the
value at stake, we also assessed the return on investment (ROI) of decisions
characterized by a superior process. The analysis revealed that raising a
company’s game from the bottom to the top quartile on the decision-making
process improved its ROI by 6.9 percentage points. The ROI advantage for
top-quartile versus bottom-quartile analytics was 5.3 percentage points,
further underscoring the tight relationship between process and analysis. Good
process, in short, isn’t just good hygiene; it’s good business.
The building blocks of behavioral strategy
Any seasoned executive
will of course recognize some biases and take them into account. That is what
we do when we apply a discount factor to a plan from a direct report
(correcting for that person’s overoptimism). That is also what we do when we
fear that one person’s recommendation may be colored by self-interest and ask a
neutral third party for an independent opinion.
However, academic
research and empirical observation suggest that these corrections are too
inexact and limited to be helpful. The prevalence of biases in corporate
decisions is partly a function of habit, training, executive selection, and corporate
culture. But most fundamentally, biases are pervasive because they are a
product of human nature—hardwired and highly resistant to feedback, however
brutal. For example, drivers laid up in hospitals for traffic accidents they
themselves caused overestimate their driving abilities just as much as the rest
of us do.9
Improving strategic
decision making therefore requires not only trying to limit our own (and
others’) biases but also orchestrating a decision-making process that will
confront different biases and limit their impact. To use a judicial analogy, we
cannot trust the judges or the jurors to be infallible; they are, after all,
human. But as citizens, we can expect verdicts to be rendered by juries and
trials to follow the rules of due process. It is through teamwork, and the
process that organizes it, that we seek a high-quality outcome.
Building such a process
for strategic decision making requires an understanding of the biases the
process needs to address. In the discussion that follows, we focus on the
subset of biases we have found to be most relevant for executives and classify
those biases into five simple, business-oriented groupings. (You can download a PDF of the groupings
of biases that occur most frequently in business.) A familiarity with this
classification is useful in itself because, as the psychologist and Nobel
laureate in economics Daniel Kahneman has pointed out, the odds of defeating
biases in a group setting rise when discussion of them is widespread. But
familiarity alone isn’t enough to ensure unbiased decision making, so as we
discuss each family of bias, we also provide some general principles and
specific examples of practices that can help counteract it.
Counter pattern-recognition biases by
changing the angle of vision
The ability to identify
patterns helps set humans apart but also carries with it a risk of
misinterpreting conceptual relationships. Common pattern-recognition biases
include saliency biases (which lead us to overweight recent or highly memorable
events) and the confirmation bias (the tendency, once a hypothesis has been
formed, to ignore evidence that would disprove it). Particularly imperiled are
senior executives, whose deep experience boosts the odds that they will rely on
analogies, from their own experience, that may turn out to be
misleading.Whenever analogies, comparisons, or salient examples are used to
justify a decision, and whenever convincing champions use their powers of
persuasion to tell a compelling story, pattern-recognition biases may be at
work.
Pattern recognition is
second nature to all of us—and often quite valuable—so fighting biases
associated with it is challenging. The best we can do is to change the angle of
vision by encouraging participants to see facts in a different light and to
test alternative hypotheses to explain those facts. This practice starts with
things as simple as field and customer visits. It continues with
meeting-management techniques such as reframing or role reversal, which
encourage participants to formulate alternative explanations for the evidence
with which they are presented. It can also leverage tools, such as competitive
war games, that promote out-of-the-box thinking.
Sometimes, simply
coaxing managers to articulate the experiences influencing them is valuable.
According to Kleiner Perkins partner Randy Komisar, for example, a contentious
discussion over manufacturing strategy at the start-up WebTV suddenly
became much more manageable once it was clear that the preferences of
executives about which strategy to pursue stemmed from their previous career
experience. When that realization came, he told us, there was immediately a
“sense of exhaling in the room.” Managers with software experience were
frightened about building hardware; managers with hardware experience were
afraid of ceding control to contract manufacturers.
Getting these
experiences into the open helped WebTV’s management team become aware of the
pattern recognition they triggered and see more clearly the pros and cons of
both options. Ultimately, WebTV’s executives decided both to outsource hardware
production to large electronics makers and, heeding the worries of executives
with hardware experience, to establish a manufacturing line in Mexico as a backup,
in case the contractors did not deliver in time for the Christmas season. That
in fact happened, and the backup plan, which would not have existed without a
decision process that changed the angle of vision, “saved the company.”
Another useful means of
changing the angle of vision is to make it wider by creating a reasonably
large—in our experience at least six—set of similar endeavors for comparative
analysis. For example, in an effort to improve US military effectiveness in
Iraq in 2004, Colonel Kalev Sepp—by himself, in 36 hours—developed a reference
class of 53 similar counterinsurgency conflicts, complete with strategies and
outcomes. This effort informed subsequent policy changes.
CONTINUES IN PART II
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