Leadership Jul 7, 2014
Are Bean Counters More Selfish?
Emphasizing a “calculative mindset” encourages people to act more selfishly and less ethically when making decisions.
People are often naturally suspicious of leaders who display an overreliance on number crunching: they are considered bean counters who lack people skills; their decisions are seen as penny-wise and pound-foolish. To describe someone as “calculating” is almost never a compliment. So why do business schools emphasize an almost purely quantitative approach to leadership and decision making? Moreover, is there empirical evidence to support the intuition that a calculating person is more likely to act selfishly or unethically?
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J. Keith Murnighan, a professor of management and organizations at the Kellogg School, recently investigated these questions with his collaborators Long Wang of the City University of Hong Kong and Chen-Bo Zhong of the University of Toronto. “We were interested in what drives people’s unethical choices, and we also wanted to examine the fact that business schools emphasize [the] quantitative analysis of problems,” Murnighan says. “We put the two questions together, because one of our goals is to train and grow effective leaders.”
Murnighan’s own training in social psychology provides a perspective on decision making that traditional economics often overlooks.
“There’s very little discussion of greed in economics,” he says. “Self-interest is important; it’s a cornerstone of capitalistic economies and efficient markets. But economic theory provides no stopping point for self-interest. Where should it end? Almost no decision that any organizational leader makes has solely individual consequences, and when someone acts selfishly or unethically, it’s hard to create and maintain systems that are consistently fair, efficient, and sustainable.”
The researchers’ interest in the impact of quantitative thinking on ethical behavior grew out of previous research that established a connection between rational analysis and self-interested decision making. The researchers designed a series of experiments that used two classic exercises from game theory—the “ultimatum game” and the “dictator game”—to measure how unethical or selfish participants’ behavior became after they were primed with a quantitative task. In one experiment, a group was told to read a tutorial on net present value, “a backbone of business-school analysis,” says Murnighan; the control group read a historical overview of the industrial revolution, “which concerned commerce and capitalism, but had no numbers in it.”
Says Murnighan, “we were surprised at how strong the results were.” In both the ultimatum and dictator games, participants start with a monetary “endowment.” In the dictator game, they can keep all of it; in the ultimatum game, they must offer part of their endowment to another, anonymous person, and they only keep their remaining part of the endowment if the other person accepts their offer. The twist is, in the ultimatum game only the offerer knows the original endowment and can lie to the responder about the total size of the pie. How much the participants kept and how much they offered were up to them. Participants who reviewed the quantitative tutorial before playing the game offered significantly less money to the receiver compared with those who read the historical article. They were also more likely to lie to the receiver about the size of their endowment.
Numbers Are Not the Only Answer
Murnighan does not believe that all quantitative analysis leads people to act selfishly or unethically. “If you’re analyzing how much of your income to donate to charity, these effects might not happen,” he says. “But the everyday activities of a business analyst are relentlessly quantitative. And if you’re a CEO of a company where everyone approaches every decision with only this kind of analysis, our research suggests that the likelihood of someone acting unethically increases.”
The danger, says Murnighan, comes not from the calculative mindset itself, but from using it as the only way to solve problems. Quantifying everything inhibits individuals’ normal desires “to appear moral to themselves and to others,” he continues. In other words, it is not that numerical thinking brings out the worst in people, but rather that it blocks their other social intuitions about avoiding greed and dishonesty.
“We should not be encouraging people to maximize profits; instead we should encourage them to maximize value.” — J. Keith Murnighan
Ethical awareness can come from at least two sources, according to Murnighan: anticipatory guilt, i.e., “when you think about doing something unethical and imagine how bad you’ll feel about it afterwards;” and social consequences, “when you realize that your bad behavior reduces another person’s tangible outcomes.” The researchers wondered if reactivating a person’s ethical awareness would help blunt the temptation to act selfishly. In a final experiment, they added a social element to the quantitative and historical tasks: before playing the dictator game, participants reviewed a set of four family photographs.
“When we show those photos, social consciousness pops back into their heads,” Murnighan says. “Some people still lied and some people still acted selfishly. But the likelihood of that kind of behavior went way down compared to the experimental conditions that didn’t include the family photos.”
A Bigger Pie, Not Just a Bigger Slice
Murnighan hopes that these findings will encourage a change in how business and management skills are taught. “We should not be encouraging people to maximize profits; instead we should encourage them to maximize value,” he asserts. “Maximizing value is still self-interested, but it takes into account the fact that other people and their organizations are also relevant. In addition to fighting for the biggest slice of the pie, a value-maximizing approach expands the pie so that there’s more to go around for yourself and for others.”
Looking beyond a calculative mindset encourages longer-term thinking about sustainable, rather than simply profitable, outcomes. “Most people’s negotiations are not one-offs—they’re repeated,” Murnighan explains. “Imagine a negotiation where you get every spare crumb off the table, but you have to negotiate again with that same person next month. How are they feeling about you then?”
Rigorous thinking is too often assumed to be synonymous with numerical thinking, according to Murnighan. A more effective approach would incorporate rigor in the consideration of quantitative and qualitative factors. “We know from many years of research that effective leaders pay attention to the task and to the people,” Murnigan says. “Our research suggests that it is dangerous to pay too much attention to the task and to do strictly quantitative analysis that ignores social consequences.”
“I have great respect for quantitative analysis, but we would like it to be combined with social awareness,” Murnighan says. “That makes problem solving long-term rather than short-, and it’s more sustainable because it generates repeat business. That’s where real success happens.”
John Pavlus is a writer and filmmaker focusing on science, technology, and design topics. He lives in Portland, Oregon.
Wang, Long, Chen-Bo Zhong, and J. Keith Murnighan. Forthcoming. “The Social and Ethical Consequences of a Calculative Mindset.” Organizational Behavior and Human Decision Processes.
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