It's All in the Numbers. Or Is It?
Ah,
the art of persuasion. It has many faces: wile, style, a simple smile.
But when it comes to a business proposal, persuasion, many believe,
takes its cue from numbers.
Quantitative
analysis is believed to enhance the persuasiveness of proposals by
managers, analysts, accountants and other corporate number
crunchers--and maximize the likelihood of a proposal's approval. As the
Schoolhouse Rock song for young TV viewers professes: "Numbers, you
see, are just my meat... 'Cause I'm a number cruncher, a mathematical
muncher."
But
as it turns out, a meaty proposal isn't necessarily the most satisfying
for its readers. In their paper, "The Persuasive Effects of
Quantification in Managerial Judgment," Kathryn Kadous and Kristy Towry
of Emory University and Lisa Koonce of the University of Texas test
exactly how quantification influences persuasion. Their accounting
expertise has made them all too familiar with the numbers game. "People
behave as though they believe they can 'snow' the decision-maker with
numbers," explains Towry, a professor of accounting at Emory's Goizueta Business School.
"I wondered if it really worked that way. Is it really that easy to
convince people by just throwing numbers at them? Are decision-makers
really that naive?"
Towry
and her co-authors determined that conventional wisdom about the
positive effects of quantification does hold true in that it increases
both the perceived competence of the preparer and the perceived
plausibility of a favorable outcome.
However, quantification also invites increased scrutiny of the proposal
details. Sometimes a closer look doesn't work to the proposer's
advantage. "It turns out that decision-makers are not that easily
convinced by numbers," notes Towry. "When a manager receives a
presentation with numbers, there's a positive effect, but it is
potentially offset by the negative effect of increased criticism."
Towry,
Kadous, a professor of finance at Goizueta, and Koonce reached their
conclusions through laboratory experiments involving MBA students who
had prior work experience. In two experiments, the co-authors look
closely at conditions that are more and less likely to result in
critical analysis of the details of the quantified proposal. "Each MBA
student gets a scenario about a company that is trying to make a
decision whether or not to postpone some costly maintenance," explains
Towry. "Each gets a packet describing the situation and we vary factors
such as the level of subjectivity involved or the incentives of the
person who prepared the proposal. For instance, some of the
participants see a scenario in which the preparer has short-term
incentives -- he's about to rotate out of the position and so he has an
incentive to postpone the maintenance in order to boost short-term
profits. We then ask the participants to answer a series of questions
and make a decision about the maintenance. We ask them to describe
their reasons, and that's how we assess the degree to which they have
scrutinized the numbers."
The
most important finding: blind trust of numbers is a myth. The authors'
model of the process by which quantification influences proposal
persuasiveness and their experimental results challenge the
conventional wisdom that numbers always improve the chances of a
proposal's approval. Yes, a quantified proposal can be more persuasive
than a non-quantified proposal, but only if the preparer is in step
with his firm's goals and his numbers are objective. The authors'
results suggest that if the preparer has incentives that diverge from
the firm's, then unless he can convince his superiors that a quantified
proposal is based on objective data, his efforts to quantify the
proposal are unlikely to increase its persuasive power.
"If
you include numbers that aren't based on good, hard facts, you might be
worse off than if you hadn't provided numbers at all," explains Towry.
"There's a positive effect of numbers, in that they make the preparer
look more competent. But if those numbers are based on a lot of
subjective guesses, you're going to invite more scrutiny. You need to
weigh those positive and negative effects. Similarly, decision-makers
are smart enough to look at the incentives facing the person who
prepared the proposal. If that person has an incentive to try to
mislead, it's going to make the decision-maker distrust the numbers
even more."
"The
Persuasive Effects of Quantification in Managerial Judgment" has
implications for managers and others who want to know how best to
present their proposals. If managers can't convince their superiors of
the appropriateness of their incentives or of data objectivity, the
authors write, the cost of quantifying a proposal will likely exceed
its benefits. This inherently has implications for superiors who read
proposals, as well. They too need to consider the context and the
quality of the numbers in the proposals they receive. The authors also
believe their study has strong implications for researchers, who can
learn from their original process model of how quantification
influences managerial decision-making.
Towry,
Kadous and Koonce are already tackling follow-up research involving
quantification. "We're trying to figure out what is it about numbers
that causes people to process them differently from other data," notes
Towry. "Is it the specificity? Is it the
precision? We're trying to take the research to a deeper level and
figure out what it is about numbers that causes these effects."
Considering the drive for quantitative analysis in making business
decisions, it would be good to know how and when to use the numbers to
make your case.
(December 2003)
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