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The Use of Performance Measures in Incentive ContractingAuthor(s): George BakerSource: The American Economic Review, Vol. 90, No. 2, Papers and Proceedings of the OneHundred Twelfth Annual Meeting of the American Economic Association (May, 2000), pp. 415-420Published by: American Economic AssociationStable URL: http://www.jstor.org/stable/117261 .

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The Use of Performance Measures in Incentive Contracting

BY GEORGE BAKER*

The strength of incentives used in an organization and the productivity of employees that results from these incentives depend to a large degree on the characteristics of the performance measures available to the organization. Some employees work under high-powered explicit incentive contracts, while others have no explicit incentive contracts at all. The ability of agency theory to predict the pattem of incentive provision in organizations has not been very impressive, and the divergence between the pre- scriptions of agency theory and the actual practice of firms has been widely noted.

This paper (along with both other papers in this session [Edward P. Lazear, 2000; Canice Prendergast, 2000]) attempts to fill some of the gap between theory and practice. I examine the characteristics of performance measures (those data on which explicit incentive contracts are based) to understand how firms use incentive contracting, and to predict the use of incentives in practice.

I. Risk and Distortion in Performance Measures

Agency theory before 1991 was chiefly concerned with the "much studied trade-off between incentives and insurance" (Robert Gibbons, 1998 p. 115). This literature stressed the problem of risk-bearing, and the fact that risk neutral firms would insure risk-averse employees against random variation in output by reducing the slope of their incentive contracts. Beginning with Bengt Holmstrom and Paul Milgrom (1991) and continuing with Baker (1992), Gerald Feltham and Jim Xie (1994), and many others, concern began to focus on another problem: the distortion of incentives that re- sulted when firms "rewarded for A while hoping

for B" (Steven Keff, 1975 p. 769). The use of distorted perfornance measures induces gaming, noncooperative behavior, sabotage of coworkers, and generally unintended and dysfunctional con- sequences of all sorts in organizations.

In a recent paper (Baker, 2000), I develop a simple two-parameter characterization of performance measures that captures both distortion and risk. The model in this paper allows the problems of distortion and risk to be examined simultaneously and reveals and explains many puzzles presented by the design of compensation systems. A key benefit of my model is its transformation of the "multi-tasking problem" from a complex multidimensional effort-choice problem into one that can be described in simple geometric terms, which greatly simplifies the characterization of the distortion in performance measures.

Baker (2000) shows that the slope of a linear incentive contract that uses a risky and distorted performance measure is

cos 0 (1) bP= U (l) ~ ~ ~ b + 2h 2?

In this expression, cos 0 captures the distortion in the performance measure, and a the risk in the performance measure (h is the employee's coefficient of absolute risk aversion).

There is a simple interpreltation for cos 0: it is the cosine of the angle between a pair of vectors. The first is the vector of marginal products of the employee's actions on the performance measure. The second is the vector of marginal products of the employee's actions on firm value. To the extent that the performance measure responds to employee actions differently from how firm value responds to these same actions, the angle between these vectors will increase, and the performance measure will distort incentives. As a result, the firm reduces the slope of the incentive contract.

Figure 1 shows lines of constant slope and constant surmlus in the risk-distortion nlane.

* Harvard Business School, Boston, MA 02163, and NBER. I thank Nancy Beaulieu, Brian Hall, Robert Gib- bons, Edward Lazear, Sherwin Rosen, and Lars Stole for helpful comments on this (and earlier versions of this) paper. This research was funded by the Harvard Business School Division of Research.

415



416 AEA PAPERS AND PROCEEDINGS MAY 2000

Firm Value

Lines of constant b,

10 Z ~~~~Iceaig Lines of

sncresn constant suplus and surplu weight on P u

cose9 cos9=O Distortion (1 - cos 0)

FIGURE 1. LINES OF CONSTANT SLOPE AND CONSTANT

SURPLUS IN THE RISK-DISTORTION PLANE

Consider choosing a performance measure from somewhere in this plane: performance measures to the southwest have optimally higher weight in an incentive contract and will deliver higher surplus.

11. Issues in the Use of Distorted and Risky Measures

Several issues and puzzles in the literature, and in the design of actual incentive contracts, are easily understood using this two-parameter characterization of performance measures. I be- gin by discussing examples of distortion that result in differences between the margins vectors described above, and which result in low values of cos 0.

Consider the use of accounting profits as a performance measure. To the extent that managers can "play games" with the accounting numbers by, for instance, changing accruals policies or altering when revenue is recognized, they can take actions that affect the performance measure but may have no effect on the true value of the firm. Thus, the marginal products on certain actions are positive for the performance measure, and zero for firm value. Simi- larly, actions such as investing in long-term R&D projects may increase the true value of the firm but have zero (or even a negative) effect on

accounting profits for the foreseeable future. Such examples of a divergence between the marginal products of actions on firm value and the performance measure lead the firm to optimally reduce the slope of an incentive contract based on such performance measures.

Consideration of distortion also helps to understand the difference between poorly designed and well-designed piece-rate systems. In a celebrated example, Sears offered piece-rate- style bonuses to its auto repair center personnel for performing repairs (Gregory Patterson, 1992). The plan paid service center advisors commissions for every dollar of parts and labor spent by customers on their cars. The results were predictable: mechanics took actions that increased the performance measure but did not increase (and in fact substantially reduced) the value of the organization.

Contrast the Sears incentive-plan design with that at Safelite glass (Edward Lazear, 1996). In that case, auto glass installers are paid a piece rate for each windshield that they install, with the proviso that if anything goes wrong with the windshield, the installer replaces the windshield on his or her own time. In the Safelite case, there is little that an installer can do that in- creases the bonus that does not also increase the value of the company. Thus, the margins vectors are aligned, and the optimal piece rate is high.

Traditional agency-theoretic treatments of the incentive problem tend to predict that low- risk performance measures will be used more extensively and more profitably. But as many observers have noted (particularly Prendergast [2000] in this issue) this prediction does not seem to be supported by either casual or formal empiricism. My model suggests that this simple prediction may not hold. Indeed, some low-risk performance measures (windshields installed) may get high weight in an incentive scheme, while others (repairs performed at an auto center) should receive low weight. The distinction between these two examples is simply whether employees can take actions that increase the performance measure without simultaneously increasing firm value. If not, then the performance measure has low distortion and can be profitably given high weight. If so, then using the performance measure will lead to significant dysfunctional behavior.



VOL. 90 NO. 2 UNRESOLVED ISSUES IN PERSONNEL ECONOMICS 417

III. The Trade-off Between Distortion and Risk

The argument thus far in this paper has been that, to understand the use of performance measures in incentive contracts, it is necessary to rec- ognize that both distortion and risk play crucial roles in determining the power of incentives. In this section, I go on to argue that the trade-off between distortion and risk is at the core of the problem of incentive design in many organizations. Organizations rarely have access to low- noise, low-distortion performance measures and so are often forced to trade one undesirable feature off against another. Understanding this trade-off reveals many of the difficulties faced by the de- signers of incentive contracts, and it explains many features of real incentive plans.

A. Timing of Measurement

Decisions about performance measurement often revolve around issues of timing: should employees be evaluated on short-run or long-run results? Two examples help to illustrate how this choice involves trading off distortion and risk.

1. Incentives for Bank Loan Officers.-The typical incentive plan for loan officers in a bank involves paying for "originations": the loan officer receives a bonus for lending money. The puzzle about this type of incentive is that it gives the loan officer no incentive to search for and write "good" loans, that is, high-interest-rate loans that are likely to be repaid. Instead, loan officers have incentives to make any loan, and banks typically have credit committees (made up of higher-level bank officers) whose job it is to determine the creditworthiness of the potential debtor and to approve or deny the loan.'

An alternative choice for banks would be to pay loan officers on the eventual profitability of the loan, rather than on its origination.2 Bonuses

based on loan profitability would have the ad- vantage of giving loan officers incentives to search out good credit risks and sell loans with higher expected value. In other words, such a performance measure would provide less- distorted incentives to the loan officers. How- ever, such a scheme would also give the loan officers greater risk, since mrany things can hap- pen to debtors that are unpredictable when a loan is written. In this case, it appears, the trade-off between risk and distortion is made in favor of lower risk and higher distortion.

2. Incentives for Project Managers.-The opposite choice is often made in the design of bonus plans for project managers in large con- struction projects. Project managers are often reassigned from one project to a second, some- times long before the first project is completed. Frequently, the project manager's bonus on the first project is based on the final profitability of the project when it is completed, even if this is long after he has left the project.

The problem with such a bonus plan is clear: the project manager's bonus for a particular project depends on many factors over which the project manager has no control. Yet the benefits are also clear: such a scheme gives the manager incentives to be concerned about the long-run profitability of his decisions. Trying to evaluate the project manager on the profitability of the project when he is reassigned would encourage him to hide problems that would not become clear until after he had left the project. In this case, the benefits of low incentive distortion outweigh the costs of high risk for the project manager.

In both of these examples, the choice of performance measures involves trading off risk and distortion. Figure 2 shows this trade-off graph- ically. In both cases, the choice is between a higher-risk, lower-distortion performance measure (loan performance, final profitability) and a lower-risk, higher-distortion measure (loan origination, current profitability). Which measure is chosen depends on the relative costs of distortion and risk.

B. Level of Aggregation

Compensation design problems frequently involve choosing the level of aggregation at

1 This separation of decision rights into "initiation" and "ratification" rights is labeled a "decision hierarchy" by Eugene Fama and Michael Jensen (1983) and is more col- loquially called bureaucracy or "red tape." It may foster specialization, in that the loan officer need not be expert in determining creditworthiness.

2 For long-term loans (say, 15-20 years), this might be problematic (because of turnover, retirement, etc.). But for many shorter-term loans, these problems would not seem to be overwhelming.




Firm Value

Lines of constant surplus

Loan

Officer

oa Performance

0i Loan Origination

cosO=l ~~~Cos90=0 co CS 0 I O

4 5 Firm Value

Lines of constant Project surplus Manager

0 Final Profitability

Current Profitability

cosO=l cosO=O

Distortion (1 - cos 0)

FIGURE 2. TRADING OFF RISK AND DISTORTION

which to measure performance. I examine two examples, one involving the choice of the group size over which to measure performance, and the other involving responsibility accounting.

1. Group Size.-A key decision in determining an employee's incentive package is the weight to place on individual versus group performance. Consider the design of an incentive plan for a worker who is a member of a work group. Each worker in the group engages in tasks that affect his own measured performance and also engages in cooperative activities that improve the performance of the entire group. Rewarding the worker only for individual per-

CEO

Division Division Division Manager Manager Manager

Plant Plant Sales Manager Manager Manager

FIGURE 3. ORGANIZATION OF A MULTI-DIVISIONAL FIRM

formance may reduce teamwork and destroy cooperation. On the other hand, rewarding individuals on the basis of group performance makes their rewards depend on the performance of the entire group, including all of the uncontrollable events (and actions of others in the group) that affect group output. In recognition of the riskiness of rewarding individuals for group performance, organizations generally reduce the slope of incentive contracts based on group performance, which causes the so-called "free-rider" problem in group incentive plans? Thus, group rewards subject group members to uncontrollable events, while individual rewards distort incentives to cooperate. How this trade- off gets resolved depends mainly on the value of cooperation (and thus the distortion induced by an individual reward scheme) and the riskiness of group (relative to individual) output.

2. Responsibility Accounting.-In large multi- unit firms, the question of what to hold managers accountable for involves a similar trade-off. Con- sider the design of an incentive contract for a divisional plant manager in a multi-divisional firm. The plant manager works for a division manager, who works for the CEO of the company. The division has multiple plants, and there is a divisional sales organization that reports to the division manager (see Fig. 3).

3Iolmstrom (1982) showed that the usual characterization of the free-rider problem (each group member in a group of size m receives only /rm of his or her marginal contribution) was an artifact of the constraint not to promise to pay out more than the total output of the group. Such a constraint can be relaxed with the introduction of a "budget- breaker." The fact that schemes that pay group members more than /rm of group output are rarely (if ever) seen in practice suggests that some other reasons (risk and/or distortion) lead to low slopes and free-riding in group pay plans.



VOL. 90 NO. 2 UNRESOLVED ISSUES IN PERSONNEL ECONOMICS 419

TABLE 1-POSSIBLE PERFORMANCE MEASURES AND ASSOCIATED INCENTIVE SYSTEMS

Performance measure Incentive system

Firm value Employee stock-ownership Firm-wide accounting profits Firm-wide profit-sharing Divisional profits Divisional profit-sharing Plant-level profits Plant profit center Plant-level costs Plant cost center

Costs and revenues are measured at the plant, division, and company levels. Consider the five possible performance measures and associated incentive systems shown in Table 1. Each of these performance measures (or a combination of them) represents a possible basis for the plant manager's incentive contract. Moving down this table represents a reduction in the amount of risk that would be borne, but an increase in the distortion associated with the performance measure. Consider a switch from divisional profits to plant-level profits. Clearly, holding the plant manager accountable for divisional profits subjects him to risks (from events affect- ing the other plant) that he would not bear if he were only accountable for his own plant's profits. However, if he can take actions that might affect (positively or negatively) the profitability of other plants, holding him accountable only for his own plant's performance eliminates any incentive to consider the effects of such actions.

A similar argument holds for the switch from plant-level profits to plant-level costs. To the extent the manager has any influence over the quality of the product produced by the plant, holding him accountable for plant costs rather than plant profits will tend to distort his incentives with respect to a cost-quality trade-off. On the other hand, holding him accountable for plant profits will make him bear the risk of sales variation over which he may have little control.

The choice of which performance measures to use (and the weights to place on them) depends on how the amount of distortion and the amount of risk change as one moves from one performance measure to another. In the case of a diversified conglomerate trying to decide whether to use firm-wide profits or divisional profits in an incentive plan for division managers, the amount of interdivisional cooperation or synergy will be critical. If there is no scope for such cooperation, then the trade-off between

distortion and risk will be simple: little will be lost by holding the division manager accountable only for divisional profits, since the amount of distortion in incentives will be small. On the other hand, when the scope for cooperative activities across units is large, the trade-off will tend to favor a riskier but less distorted performance measure.

IV. Conclusions

The foregoing discussion suggests at least two ways of thinking about the choice of performance measures. The first, and the perspective that I have used in this paper, is to suppose the existence of a set of performance measures that the firm could use in an incentive contract and ask which measure (or combination of measures) yields the strongest incentives and/or the highest surplus. A second way of looking at the question is to ask how much the firm should pay to develop better performance measures. To make real progress on the second perspective is beyond the scope of this paper, since it requires some model of how firms produce information and create performance measures. Nonetheless, certain conclusions can be drawn about the cost of performance measurement, and the optimal use of incentive contracts, from casual empiricism.

The fact that most real-world incentive contracts pay people on the basis of risky and distorted performance measures is powerful ev- idence that developing riskless and undistorted performance measures is a costly activity. In- deed, many of the examples given in Section III suggest the existence of a "performance mea- surenment possibility frontier," running from the northwest region of Figure 1 to the southeast region. The location of this frontier depends on the technology of performnance measurement for a particular type of work; where firms choose to be on the frontier depends on the relative costs of risk and distortion for a particular employee. For some types of work (sales, for instance) the set o:f possible performance measures may lie close to the origin. For these employees, high- powered explicit incentives are optimal. For other types of work, however, there may be no good performance measures available at any reasonable cost. For employees doing these types of work, high-powered explicit incentive contracts are not optimal.




Of course, firms do not provide zero incentives to employees for whom no good performance measures are available. Rather, they rely on alternatives to explicit incentive contracts. Career concerns, promotions and bonuses based on subjective performance evaluation, and employee selection (perhaps favoring those with high intrinsic motivation) are all alternative sources of incentives and motivation in circum- stances where explicit incentive contracts are weak. It is the simultaneous choice of each of these techniques that determines the observed pattern of incentive provision in organizations.

REFERENCES

Baker, George. "Incentive Contracts and Perfor- mance Measurement." Journal of Political Economy, June 1992, 100(3), pp. 598-614.

e "Distortion and Risk in Optimal Incen- tive Contracts." Working paper, Harvard Business School, 11 January 2000.

Fama, Eugene and Jensen, Michael. "Separation of Ownership and Control." Journal of Law and Economics, June 1983, 26(2), pp. 301- 25.

Feltham, Gerald and Xie, Jim. "Performance Measure Congruity and Diversity in Multi- Task Principal/Agent Relations." Accounting Review. July 1994, 69(3), pp. 429-53.

Gibbons, Robert. "Incentives in Organizations." Journal of Economic Perspectives, Fall 1998, 12(4), pp. 115-32.

Holmstrom, Bengt. "Moral Hazard in Teams." Bell Journal of Economics, Autumn 1982, 13(2), pp. 324-40.

Holmstrom, Bengt and Milgrom, Paul. "Multitask Principal-Agent Analyses: Incentive Con- tracts, Asset Ownership, and Job Design." Journal of Law, Economics, and Organiza- tion, Special Issue 1991, 7, pp. 24-52.

Kerr, Steven. "On the Folly of Rewarding for A while Hoping for B." Academy of Manage- ment Journal, December 1975, 18(4), pp. 769-83.

Lazear, Edward. "Performance Pay and Produc- tivity." National Bureau of Economic Re- search (Cambridge, MA) Working Paper No. 5672, July 1996.

_-____"The Power of Incentives." American Economic Review, May 2000 (Papers and Proceedings), 90(2), pp. 410-14.

Patterson, Gregory. "Distressed Shoppers, Dis- affected Workers Prompt Stores To Alter Sales Commissions." Wall Street Journal, 1 July 1992, p. B1.

Prendergast, Canice. "What Trade-off of Risk and Incentives?" American Economic Re- view, May 2000 (Papers and Proceedings), 90(2), pp. 421-25.



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