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A study by George Baker, Michael Gibbs, and Bengt Holmstrom confirms the link between promotions and wage growth.29 They obtained confidential personnel records from a large U.S. firm and found that employees received substantial increases in pay (5 to 7 percent, depending on level) when they were promoted. They also report that firms use promotion tournaments in conjunction with objective and subjective merit-based raises within job ranks. Other researchers have studied intrafirm wage differentials for evidence of tournament effects. Brian Main, Charles O’Reilly, and James Wade, for example, found that wage differentials increase with rank, as predicted by the theory.30 They also found that the difference in salary between CEOs and vice presidents is larger in firms that have more VPs, also as predicted by the theory. Tor Eriksson obtained similar findings using a broad sample of 2,600 executives at 210 Danish firms between 1992 and 1995.31

EFFICIENCY WAGES AND THE THREAT OF TERMINATION

Firms can also motivate workers by threatening to fire them. Like tournaments, firing is usually based on implicit criteria. Firms fire workers whose performance is “unsatisfactory,” where the meaning of this term is usually understood by both parties but not carefully defined. To study termination-based incentives, we sketch a simple model in which an employee must decide whether to work hard. Suppose that the cost to the employee of working hard is $50 but that if the employee works hard, the probability of being retained is 1. If the employee does not work hard, the firm will detect this lack of effort with probability p, where p , 1. If this happens, the firm will fire the worker.

The employee earns wage w from this job. The next best opportunity for a fired employee is a job that pays w**.33 In deciding whether to work hard, the employee compares the net payoff from working hard to the net payoff from shirking (that is, choosing not to work hard). Working hard guarantees a payoff of:

w 2 $50

Shirking leads to one of two possible outcomes. With probability 1 2 p, the employee keeps the job and earns w. With probability p, the employee is detected, fired, and earns w**. The expected payoff from shirking is thus:

pw** 1 (1 2 p)w

The employee will choose to work hard if

w 2 $50 . pw** 1 (1 2 p)w

or, equivalently, if

p(w 2 w**) . $50

This last inequality has a highly intuitive interpretation. The variable p is the probability of being fired if the employee shirks, and w 2 w** is the cost associated with being fired. Hence, p(w 2 w**) is the expected cost of shirking, whereas $50 is the cost of working hard. The inequality states that the employee will work hard if the expected cost of shirking is greater than the cost of working hard.

As one might expect, the firm can more easily motivate hard work if it detects shirking more often. That is, if p is higher, the expected cost of shirking is higher, and

Incentives in Teams • 427

this tips the employee’s cost/benefit trade-off in the direction of hard work. However, this model also identifies a second way for the firm to affect the employee’s actions. Firms can increase the expected cost of shirking by raising the employee’s wage, w. That is, by making the job more valuable, the firm can motivate an employee to take actions (such as working hard) to avoid losing the job.

Carl Shapiro and Joseph Stiglitz refer to a wage that is high enough to motivate effort as an efficiency wage.34 They use this idea to explain how having a pool of unemployed workers in a labor market serves to provide incentives for those who are employed. If, on the one hand, all firms offer a wage w and fired workers can easily find new employment at this wage, then being fired involves no loss to the worker and hence has no incentive effects. If, on the other hand, being fired means taking a less attractive job (or even worse, a long and costly spell of unemployment), the prospect of being caught shirking provides an incentive to work hard.

It is not difficult to find cases of firms paying what appear to be above-market wages. In one well-known example, on January 5, 1914, the Ford Motor Company announced an increase in workers’ wages from $2.30 per day to $5. The “Five-Dollar Day,” as it became known, was introduced in tandem with adoption of the eight-hour workday and an increase in the number of work shifts from two to three. Henry Ford told reporters that his plan was “neither charity nor wages, but profit sharing and efficiency engineering.”35 According to Ford’s later statements, the firm found that the change in wage policy improved both the discipline and efficiency of its workforce. Ford workers did not dare risk their jobs—there were no alternatives anywhere near as attractive. Efficiency wage theory may also explain why some firms offer attractive nonwage benefits. For example, firms that appear on lists such as Fortune magazine’s “Top 100 Companies to Work For” offer employee-friendly policies that encourage workers to do what they can to retain their jobs, lest they end up at one of the “Worst Companies to Work For.”

INCENTIVES IN TEAMS

Firms often find that the most effective means of production involves asking a group of employees to work together. Leading Indian car market Mahindra & Mahindra used teams to design its first global sports utility vehicle, the Scorpio. The firm split a 120-person development staff into 19 cross-functional teams combining marketing and engineering professionals. Each team tried to find ways of meeting marketing aims while keeping manufacturing costs low. Team leaders were made accountable for guaranteeing that targets were met. Mahindra & Mahindra credits this approach with keeping design costs under control; the firm claims that it spent just 6 billion rupees ($120 million) to design the Scorpio, compared to the 17 billion rupees rival Tata Engineering spent on the Indica passenger car. Examples such as this have become common throughout the world in recent years.

Achieving the full benefits of team production requires rewarding individuals for the performance of the team. Mahindra & Mahindra could have attempted to separately identify each team member’s contribution toward the final Scorpio design, rewarding engineers for design improvements and marketing executives for improving the Scorpio’s market appeal. This approach might have caused individuals to work at cross purposes. A marketing executive might have proposed a product feature that

428 • Chapter 12 • Performance Measurement and Incentives

increased manufacturing costs. The design engineers, whose pay depended on holding down costs, would have balked and might even have exaggerated the impact on costs in order to block the proposal. An engineer might have found a way to cut costs but make the car seem more generic. The marketers would have objected and might have exaggerated the marketing impact. When performance is measured at the individual level, there is little incentive for the employees to combine their knowledge to make the decision that is best overall. Measuring performance by the overall profits generated by the new product eliminates this problem and motivates all parties to work together.

In order to realize this important benefit, firms must develop ways to combat the costs of team-based performance measures. To illustrate these costs, consider a design engineer working as part of a six-person team to design part of a new automobile. Suppose that all team members are evaluated on whether their design meets marketing objectives and cost targets. The team will split a bonus of $10,000 if the targets are met, but it will receive no additional compensation if targets are not met.

Suppose that the engineer believes that redesigning a vehicle part will reduce manufacturing costs substantially and therefore will increase the likelihood of meeting design targets from 40 to 70 percent. Although the idea seems promising, it will take considerable time and effort for the engineer to work out all the details. Will the engineer be willing to incur the cost, in terms of time and effort, necessary to fully develop this idea? If the engineer develops the idea, the likelihood of the team’s success in meeting targets goes up by 30 percentage points, which means that the expected bonus paid to the team increases by $3,000. From the team’s perspective, the idea should be pursued as long as the cost is less than $3,000. (From the firm’s perspective, the idea should be pursued as long as the cost is less than $10,000.) But the engineer will split the team’s bonus and only stands to gain $500. So the engineer will work on the idea as long as the expected cost is less than $500. The engineer’s incentives and the team’s incentives are not the same.

We can think about this problem more generally. Consider any actions with the following two properties:

1.Total benefit to team from action . total cost of action

2.Total cost of action . (1/n) 3 total benefit to team from action

Actions with property (1) are value-creating actions in that the total benefit is greater than the total cost. However, since the individual undertaking the action compares this cost to the personal benefit, actions with property (2) may not be undertaken. The mismatch between the total benefit to the team and the personal benefit to the individual team member means that the individuals may not take actions that maximize overall welfare.

This effect is known as the free-rider problem, although this name may be something of a misnomer. The phrase suggests that one team member may elect not to work and instead try to get a “free ride” on the efforts of teammates. The problem is even worse than the phrase suggests, however, since it affects not just one but every team member, because everyone has an incentive to free ride on the group.

While our example makes use of a bonus based on a verifiable performance measure, free-rider problems are present even if team performance is an input into a subjective performance evaluation system. Suppose that a marketing executive’s

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compensation depends on a supervisor’s subjective assessment of the quality of the marketer’s joint work with the design engineer. The design engineer’s efforts will affect the performance evaluations of both employees. In making an effort choice, however, the design engineer may fail to account for the impact on the marketer’s compensation.

The free-rider problem can be exacerbated by multitasking. Suppose, for example, that a design engineer pursues two tasks. The first is a solo project in which the engineer works to design parts for a new vehicle without input from marketing. The second is the team-based project described earlier. The design engineer receives the full benefit if the solo project succeeds but shares the benefit associated with the second task with team members. The engineer will naturally devote more effort to the solo project.

There is considerable evidence of free-riding in professional partnerships. Partnership arrangements are common in law, accounting, medicine, and consulting. Such firms typically pool the profits generated by each partner’s activities and divide this pool according to some predetermined sharing rule. Some firms divide the pool equally (so that each partner receives share 1/n of the total), while others award larger shares to partners who are more productive or more senior. Regardless of the particular sharing rule, some fraction of the profit generated by an individual is captured by the other partners. This means that the personal benefit from effort is always lower than the total benefit, raising the possibility that partners will provide too little effort. Martin Gaynor and Mark Pauly demonstrated this effect in their study of medical practices. They found that increases in the size of partnerships led to reductions in individual productivity.36 Similarly, a study of law firms by Arleen Leibowitz and Robert Tollison revealed that larger firms were less able to contain costs than smaller ones.37

Firms can mitigate the free-rider problem in a number of ways. First, they can keep teams small. Second, firms can allow employees to work together for long periods. Repeated interaction allows team members to make their current actions depend on what other members have done in the past. Thus, if one member fails to contribute to the team’s goals today, others can punish the miscreant in the future, through peer pressure, social isolation, or simply a refusal to help that individual. This is analogous to the “tit-for-tat” solution to harmful competition discussed in Chapter 7.

The firm will reap the benefits of repeated interactions if team members can identify the free riders and do something about it. Mark Knez and Duncan Simester illustrated this point in their study of team-based incentives at Continental Airlines.38 In 1995, the airline offered each hourly worker a $65 bonus for every month in which it ranked among the top five in the industry in on-time arrivals. Although this scheme would appear to suffer from severe free-rider problems, Knez and Simester found that Continental’s on-time arrival rates increased at airports where the system was implemented. They argued that an important aspect of Continental’s success was the division of the firm’s employees into autonomous work groups at each airport location. Members of these groups could easily observe one another’s actions. Sources of delay were quickly discovered, and employees were motivated to offer help in clearing the bottlenecks. Workers publicly challenged underperforming team members and sometimes reported them to management. These benefits could not have been achieved had employees been unable to observe one another’s actions.