Spring 1999 (Vol. 21, Number 2, 19-21)

Goals are powerful motivators used by many managers, but getting the most mileage out of goals means managing risk and expectation and understanding how goals work. Professors RICHARD LARRICK, GEORGE WU, AND CHIP HEATH take goal setting to the next level.

MANAGERS HAVE LONG USED GOALS as a tool for motivating their employees and for good reason: A large literature in organizational behavior demonstrates that pursuing ambitious goals consistently leads to better work performance. The power of goals has been illustrated in hundreds of research studies involving work as diverse as clerical duties, assembly line operations, and investing. 

Yet while the effectiveness of goals is well documented, the reason they work has not been clearly identified. It is obvious why external incentives such as bonuses, promotions, or praise serve to improve performance. What is remarkable is the vast set of studies that shows the effectiveness of goals in the absence of external incentives. 

Research shows that a mere goal, such as a personal aspiration to complete thirty sales in one month, is sufficient to produce better performance.How can managers harness the power of goals as a source of motivation? To understand why goals work and how they work most effectively, it is first necessary to understand the psychology of how people evaluate performance.

Evaluating performance
Suppose Amy just joined a company as a sales representative. When Amy asks the previous sales representative for a goal, she says: “Do your best.” How might Amy judge different levels of performance in light of this advice? Being new at the job, Amy might regard ten sales as pretty good, twenty sales as even better, and thirty sales as better still. There is a sense, though, that the first ten sales are the most rewarding, the next ten sales are rewarding but less so, and, at some point, additional sales are a bonus. What we have described is the classic economic notion of diminishing marginal utility (figure 1): the marginal utility or value an individual gets from a sale decreases as the number of sales rises. 

 

Figure 2
Figure 1
Now consider a second new sales representative, Barbara, who is given a goal of thirty sales. How would this affect how Barbara values different levels of performance? We believe that goals alter the value of outcomes in predictable ways, described by what has been termed the prospect theory value function (figure 2) first suggested by two psychologists, Daniel Kahneman and Amos Tversky. The prospect theory value function has been used to explain behavior in many fields, including economics, medicine, consumer behavior, and political science. The major contribution of the value function is that it explains how comparisons affect the way people place values on outcomes. For our purposes, we believe it captures how people evaluate outcomes when they 
face a goal. Here are the key insights.

First, the value function suggests that goals divide the space of possible outcomes into gains or losses, success or failure. In our sales example, instead of every sale feeling like a gain as it did in figure 1, there is now a region of loss or failure for any performance that falls short of thirty sales. Second, creating the possibility of losing is significant because people think about losses and gains differently. The shorthand term for this is loss aversion: Losses are more painful than gains are attractive. The parallel effect in goal setting is that failure is a more intense experience than success. Since failure is more painful than success is satisfying, eliminating a sense of failure is actually more motivating than achieving a success. Loss aversion, or the greater pain of failure, is captured in figure 2 by the fact that the curve is steeper in the region below the goal than in the region above it. 

Finally, the value function suggests that people become less sensitive to incremental changes in performance when they are further from their goal. This distance effect is illustrated by the following problem. 

Charles and David are software manual writers who usually write twenty-five pages per week. One week Charles sets a goal of thirty pages. David sets a goal of forty pages. Friday afternoon, both Charles and David are quite tired after writing forty-two pages, and at most, have the energy to write one more. Who will work harder to write one additional page? Most people think that David will be more willing to work harder because of the distance effect. David experiences the improvement moving from two pages to three pages over his goal as bigger and hence more satisfying than does Charles when he moves from twelve to thirteen pages.

Suppose, however, Charles and David both got tired after having written only twenty-seven pages. Who would work harder to write one additional page? Recall that Charles has a goal of thirty and David has a goal of forty. In this case, people overwhelmingly believe that Charles will work harder. Moving from three pages to two pages short of the goal seems like a bigger gain than moving from thirteen to twelve pages short of the goal. Once again, the distance effect captures the idea that we experience more progress and more satisfaction the closer we are to a goal. This is captured in figure 2 by the fact that the curves flatten out when performance is well above or well short of the goal. 

Loss aversion and the distance effect also explain why ambitious goals are more likely to lead to better performance than a simple desire to do well. Consider the goals of “do your best” (figure 1) and thirty sales (figure 2). Suppose that both Amy and Barbara have completed twenty sales. Additional sales might be quite costly in terms of time, energy, and aggravation. Who is more likely to strive for the next sale? The value function suggests that the answer is Barbara. The marginal benefit Barbara derives from an extra sale is higher than the marginal benefit Amy derives for three reasons. First, Barbara, posed with a goal, is eliminating a shortfall, while Amy, doing her best, is achieving a windfall. Second, the desire to eliminate losses is more motivating. And, third, Barbara (in figure 2) is closer to the comparison point than Amy (in figure 1), so the distance effect is not reducing the sense of satisfaction to the extent it is for Amy. 

What is most striking about the value function, however, is that it not only explains why goals are motivating but also it calls attention to some previously neglected consequences of setting ambitious goals. There are potential drawbacks to goals that managers need to recognize, monitor, and correct. We discuss three of these below.

The starting problem
Imagine sitting down to write up a fifty-page summary of a yearlong project. You sit down at your desk, flip on the computer, and open the word processing program. 

Staring at the blank screen, you think, “Only fifty pages to go.” Suddenly, cleaning your desk looks very appealing. The problem: There’s little satisfaction in getting that first page written when it hardly makes a dent in achieving your overall goal.

We call this the starting problem. One of the important implications of the distance effect is that when people face a very ambitious goal, the first few steps toward achieving it offer little sense of progress and therefore little satisfaction. Given the pain of starting any hard task, people may find other, easier tasks that are usually thought to be aversive–like cleaning their desk or returning phone calls–to be more appealing.

Stretch goals–a cornerstone of business practice in the 1990s–may lead to the starting problem because high goals make people feel that they are incapable of reaching such ambitious goals. However, this is not the case in our example of the fifty-page report: We all know we can and will get it written. Even when achieving the goal is not in doubt, the value function makes clear that ambitious goals can reduce motivation by squelching an initial sense of accomplishment. 

Many productive people have discovered a way around the starting problem: subgoals. Subgoals work because they make us more sensitive to progress. In terms of the value function, subgoals are a way of tricking ourselves into being on the steep part rather than the flat part of the loss curve. Consider the following problem.

Jill is a financial analyst preparing for a financial certification examination. She sets a goal of working through a set of six hundred practice questions over the next two months. The first night she works on twelve problems and feels exhausted the next night when she sits down with her practice questions. 

Tina is also a financial analyst preparing for the same financial certification examination. Tina also sets a goal of working through a set of six hundred practice questions over the next two months, but thinks of this as solving ten problems per night. The first night she works on twelve problems and feels exhausted the next night when she sits down with her practice questions.

Who is more likely to reach her overall goal? Most people think that Tina, with her subgoal of ten problems per night, is more likely to reach her overall goal. The value function suggests the reason: By separating a task into subgoals, people maximize their sensitivity to small movements toward their overall goal. When Jill finds herself tired after solving twelve problems the first night, she might find it hard to motivate herself to hit the books. After all, any number of problems she might be able to do that night seems to contribute so little to her distant goal of six hundred problems. In contrast, by dividing the overall goal into ten problems per day, Tina can see progress relative to her subgoal.

Risky business
A second implication of the value function is that goals change our willingness to take risks. To illustrate this point, we first consider some decisions that do not involve goals. There is a large body of research inspired by the value function showing that people think differently about winning money than they do about losing money. The distance effect predicts that people will be risk-averse when choosing between two gains. For example, most people opt for a sure $3,000 over an 80 percent chance of winning $4,000. Even though the sure thing has a lower expected value than the gamble, the sure $3,000 is more attractive because $4,000 doesn’t seem that much bigger than $3,000, and therefore isn’t worth the risk. Although the traditional literature in economics assumes that risk aversion is the norm, the distance effect predicts that preferences reverse when people think about losing money. 

Consider next a choice between a sure loss of $3,000 and an 80 percent chance of losing $4,000. In this case, most people would rather take the chance. Losing $4,000 doesn’t seem much worse than losing $3,000, so why not risk the larger loss and have a chance at no loss at all? 

We suggest that the distance effect will also produce more risk taking when people are pursuing ambitious goals. To illustrate this, consider the following problem. You are the manager of a large manufacturing unit in a Fortune 100 company in the midst of a yearlong plan to cut costs in your unit. Your goal for this quarter is to do your best at saving money. At the present, you are considering two plans. Plan M will save $90,000. Plan N has an 80 percent chance of saving $50,000 and a 20 percent chance of saving $250,000. Both plans are one-time options and will not be available later in the year. You have time to complete only one of them during the current quarter. Which plan will you choose? 

Few people select Plan N, the risky plan. However, when they are given the goal of saving $250,000, many more people now are willing to choose Plan N. Two factors–loss aversion and the distance effect–produce greater risk seeking when the goal is to save $250,000. First, taking the risk provides the chance of completely eliminating the sense of failure. Second, both $50,000 and $90,000 are so far from the goal and so unsatisfying that people treat them as psychologically similar. Thus, they are willing to risk saving only $50,000 because it is not that much worse than saving only $90,000 in light of the $250,000 goal. 

When offered real money in experiments, University of Chicago Graduate School of Business students took more risks when they set an ambitious goal for themselves than when they were simply trying to do their best. In choosing among a large set of risky prospects that varied in probabilities and payoffs, students who were encouraged to set ambitious goals opted for risky gambles that had low expected values. In contrast, those who had no goals were more likely to choose the sure outcomes that had higher expected values. Similarly, in simulated work tasks, students encouraged to set high goals selected riskier strategies with higher payoffs but lower expected values than did students with no goals. This is particularly striking, as students sacrificed expected payoff in pursuit of ambitious goals, despite the lack of any tangible incentive for reaching the goal. 

Thus, goals change people’s willingness to take risks. Whether risk taking is prudent, however, depends on the situation. In many cases, it may actually be beneficial to encourage risk taking, assuming that risk and reward tend to be positively related. Thus, goals could be a useful managerial tool for encouraging risk taking. There are drawbacks, however. In recent years, the business world has seen some notable examples of stretch goals leading to unwise and even unethical risks. If employees are already taking prudent risks, high goals could force them to take imprudent risks. The main implication of our research is that managers need to recognize an unintended consequence of setting ambitious goals–taking big risks–and use it judiciously to encourage risk taking when appropriate. 

Emotion management
A final insight offered in this research is that using ambitious goals to motivate employees requires an awareness of the emotional consequences of goals. Because a goal sets up the possibility of failure, goal setting can be an anxiety-provoking affair. An interesting example of how goals shape emotional reactions is the recent experience of the Chicago Bulls when they became the first team to win seventy games in an NBA regular season. In December 1995, with three dozen victories and only a handful of losses, the Bulls realized that they could be the first team to break the previous record of sixty-nine wins in a season. For months they labored under the goal of reaching seventy victories, slowly recording one win, then another, then another. When they finally hit seventy, their emotions were surprising. Most people expected that such a great accomplishment would call for joy and excitement, but the players had a different reaction. Most of them indicated that their overriding emotion was relief. By reaching their goal, they eliminated a loss–the possibility of failing–rather than achieving a gain. 

Any time we set high goals, commit to them, and labor under them for an extended period of time, the possibility of failure starts to loom. Ironically, possible failure is very desirable, because it is precisely this possibility that motivates us. But it also creates a sense of anxiety during performance and disappointment at the end if we come up short, which we often will if we are pursuing truly ambitious goals. Even if we hit the goal, it deprives us of joy and gives us relief. Managers must be aware of the balancing act required in setting very ambitious goals. Extreme goals may lead to higher performance, but employees who come up short of a goal may be disappointed. As a result, a manager may find that the next ambitious goal set is less credible and hence less effective as a source of motivation. 

One way out of this dilemma is for managers to harness the power of goals by letting employees anticipate the pain of coming up short and helping them celebrate a goal if it is reached or relieving their disappointment if it is not. The way to do this is to help people frame their final performance in light of a comparison other than the goal. Fortunately, favorable comparisons abound, whether they be where we began, what we achieved in the past, or the performance of competitors. It is through this artful use of goals that managers can motivate employees to perform at higher and higher levels, while at the same time creating higher and higher levels of satisfaction. 

Larrick is associate professor of behavioral science and Wu is assistant professor of behavioral science. Heath, formerly with the GSB, is associate professor of management at Duke University's school of business.