A New York Times article on how Uber is using insights from behavioral economics to push, or nudge, its drivers to pick up more fares — sometimes with little benefit to them — has generated quite a bit of criticism of Uber. It raises a question that executives often ask about how their own organizations might apply behavioral economics: “Isn’t there a danger it will be used with ill intent?” Behavioral economics takes the view that people have fallible judgment and malleable preferences and behaviors, can make mistakes calculating risks, can be impulsive or myopic, and are driven by social desires. Organizations that embrace behavioral economics design processes to use these tendencies to nudge people to do something. The determining factor between when nudges should be deemed good and when they should be deemed bad is: Are they being used to benefit both parties involved in the interaction or do they create benefits for one side and costs for the other?
A recent New York Times article on how Uber is using various insights from behavioral economics to push, or nudge, its drivers to pick up more fares — sometimes with little benefit to them — has generated quite a bit of criticism of Uber. It’s just one of several stories of late that have cast the company in a poor light.
When I read the piece, it reminded me of a question executives often ask me when I talk to them about the benefits of behavioral economics or give them examples of how they could use it in their own organizations: “Aren’t you afraid it will be used with ill intent?”
I always respond that, like many tools, it can be used in good and bad ways. Before I delve into the differences between the two, I should first make sure you are familiar with the somewhat new field of behavioral economics.
According to the traditional view in economics, we are rational agents, well informed with stable preferences, self-controlled, self-interested, and optimizing. The behavioral perspective takes issue with this view and suggests that we are characterized by fallible judgment and malleable preferences and behaviors, can make mistakes calculating risks, can be impulsive or myopic, and are driven by social desires (e.g., looking good in the eyes of others). In other words, we are simply human.
Behavioral economics starts with this latter assumption. It is a discipline that combines insights from the fields of psychology, economics, judgment, and decision making, and neuroscience to understand, predict, and ultimately change human behavior in ways that are more powerful than any one of those fields could provide on its own. Over the last few years, organizations in both the private and public sectors have applied some of the insights from behavioral economics to address a wide range of problems — from reducing cheating on taxes, work stress, and turnover to encouraging healthy habits, increasing savings for retirement as well as turning up to vote (as I wrote previously).
Uber has been using similar insights to influence drivers’ behavior. As Noam Scheiber writes in the Times article, “Employing hundreds of social scientists and data scientists, Uber has experimented with video game techniques, graphics and noncash rewards of little value that can prod drivers into working longer and harder — and sometimes at hours and locations that are less lucrative for them.”
One such approach, according to Scheiber, compels drivers toward collecting more fares based on the insight from behavioral sciences that people are highly influenced by goals. According to the article, Uber alerts drivers that they are very close to hitting a precious target when they try to log off. And it also sends drivers their next fare opportunity before their current ride is over.
Now let’s return to the question of when are nudges good and when are they bad. In discussing this topic with executives, I first provide a couple of examples. One of my favorites is the use of checklists in surgery to reduce patient complications. Checklists describe several standard critical processes of care that many operating rooms typically implement from memory. In a paper published in 2009, Alex Haynes and colleagues examined the use and effectiveness of checklists in eight hospitals in eight cities in the Unites States. They found the rate of death for patients undergoing surgery fell from 1.6% to 0.8% following the introduction of checklists. Inpatient complications also fell from 11% to 7%.
In a related paper published in 2013, Alexander Arriaga and colleagues had 17 operating-room teams participate in 106 simulated surgical-crisis scenarios. Each team was randomly assigned to work with or without a checklist and instructed to implement the critical processes of care.
The results were striking: Checklists reduced missed steps in the processes of care from 23% to 6%. Every team performed better when checklists were available. Remarkably, 97% of those who participated in the study reported that if one of these crises occurred while they were undergoing an operation, they would want the checklist used.
Another example I often give concerns the use of fuel- and carbon-efficient flight practices in the airline industry. In a recent paper, using data from more than 40,000 unique flights, John List and colleagues found significant savings in carbon emissions and monetary costs when airline captains received tailored monthly information on fuel efficiency, along with targets and individualized feedback. In the field study, captains were randomly assigned to one of four groups, including one “business as usual” control group and three intervention groups, and were provided with monthly letters from February 2014 through September 2014. The letters included one or more of the following: personalized feedback on the previous month’s fuel-efficiency practices; targets and feedback on fuel efficiency in the upcoming month; and a £10 donation to a charity of the captain’s choosing for each of three behavior targets met.
The result? All four groups increased their implementation of fuel-efficient behaviors. Thus, informing captains of their involvement in a study significantly changed their actions. (It’s a well-documented social-science finding called the Hawthorne effect.) Tailored information with targets and feedback was the most cost-effective intervention, improving fueling precision, in-flight efficiency measures, and efficient taxiing practices by 9% to 20%. The intervention, it appears, encourages a new habit, as fuel efficiency measures remained in use after the study ended. The implication? An estimated cost savings of $5.37 million in fuel costs for the airline and reduced emissions of more than 21,500 metric tons of CO2 over the eight-month period of the study.
Both in the case of surgeons using checklists or captains receiving feedback about fuel efficiency, one of the main goals of the intervention was to motivate the participants to act in a certain way. So, in a sense, the researchers were trying to encourage a change in behavior the same way managers at Uber were trying to bring about a change in their drivers’ behavior.
But there is an important difference across these three examples. Are the nudges used to benefit both parties involved in the interaction or do they create benefits for one side and costs for the other? If the former, then (as Richard Thaler and Cass Sunstein argue in their influential book Nudge) we are “nudging for good.” Thaler and Sunstein identify three guiding principles that should be on top of mind when designing nudges: Nudges should be transparent and never misleading, easily opted out of, and driven by the strong belief that the behavior being encouraged will improve the welfare of those being nudged.
That’s where the line between encouraging certain behaviors and manipulating people lies. And that’s also where I see little difference between applying behavioral economics or any other strategies or frameworks for leadership, talent management, and negotiations that I teach in my classes. We always have the opportunity to use them for either good or bad.
If the interests of a company and its employees differ, the organization can exploit its own members as Uber appears to have done. But there are plenty of situations where the interests are, in fact, aligned — the company certainly benefits from higher levels of performance and motivation, but the workers do, too, because they feel more satisfied with their work.
And that is where I see great potential in applying behavioral economics in organizations: to create real win-wins.