It’s All in the Numbers. Or Is It?Published: January 14, 2004 in Knowledge@Emory
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 naïve?”
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 accounting 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.