How to increase team performance?

Abstract

During the last decades, researchers in the area of personal economics have developed a bundle of possibilities to increase team performance. This paper wants to give an overview of the latest incentive schemes as well as concepts of peer pressure, norms and mutual monitoring. The findings of this paper are that a well-balanced integrated team incentive plan, which includes elements of rewards and of pressure is expected to be the most promising. The ideas in this paper are applied to a basic economic model that allows a deeper understanding of the concepts.

1 Introduction

During the last 20 years, teamwork has become prevalent in many firms. While 1987, 27% of the firms supported self-managed teams, 1999 this number rose to 72% (Lazear and Shaw (2007)). Together with the increment of usage, the research of teams as a part of personal economics has increased. Many advantages of teams have been identified as reasons for the augmented use of teams. But also the negative effects, organization, coordination and free-riding have been further analyzed. Special attention was given to the possibilities of increasing the team performance and mitigating the negative effects. During the last decades, researchers and practitioners have developed a huge array of incentive schemes and bonus plans. These incentives can be monetary, non-monetary, they can be based on outcomes of the team and team members or on acquainted team skills. In addition to the incentive schemes, concepts of peer-pressure, mutual monitoring and punishments were further analyzed and improved. Today, an integrated, well-balanced usage of the methods promises a considerable improvement of team performance.

This paper begins with an analysis of the benefits of teams, namely specialization and knowledge transfer. The third section explains the problem that is related with the usage of teams, the free-riding effect. Section 4 and 5 offer possibilities to increase the team performance and to mitigate the free-rider effect. While Section 4 concentrates on incentives and bonuses, section 5 refers to the effects of monitoring, pressure and punishment. In this context, a model including peer pressure and mutual monitoring is developed. Section 6 provides a numerical example for this model to clarify the concepts introduced section 5. Section 7 analyzes the concepts with regard to the team size before the following conclusion reflects and summarizes the findings.

2 The benefits of teams

Why the usage of teams has become so popular during the last couple of decades? Actually, teams have many disadvantages. As Lazear and Shaw (2007) point out, the organization, selection and coordination of teams can be time consuming. Furthermore, an omnipresent, potential problem in teams is the free-rider problem, in which team members will free-ride on the effort of the others.

Nevertheless, in certain circumstances, teams can have crucial advantages over indi- viduals working alone. Generally, the benefits from teamwork are the greatest if large complementarities between the tasks of two employees exist (Lazear (1998) p. 307).

The easiest example would be a physical labour that cannot be done by a worker alone. In this case, only a team can generate an output.

But teams have more direct benefits to offer: specialization and knowledge transfer.

Specialization

Specialists can often work together more efficiently in a team. If each worker has access to the skills of the other workers, they can help each other with their specific knowledge and accomplish the task faster, as shown by Lazear and Shaw (2007). Therefore, gains from team interaction are greater when individuals have different skills or information (Lazear (1999)). On the other hand, if the skill sets of the workers are completely overlapping, the individuals in the team do not have any benefits from the specialization.

Knowledge Transfer

The second direct benefit in teams, knowledge transfer among team members, is closely related to specialization. Without specialization of the team members, knowledge trans- fer cannot occur since all workers have the same knowledge. Actually, the workers must have distinct but relevant information sets as argued by Lazear (1998). Relevance means that the knowledge of one team member is helpful for the completion of another team member’s task. For example, while the knowledge of an accountant and an economist might be relevant and therefore knowledge transfer might occur, the same is unlikely to be true for an engineer and a lawyer.

However, putting workers with a very similar background in the same team will not result in knowledge transfer neither, since their information sets are nearly identical (Lazear (1998)). The two factors, specialization and relevance, should help to choose the right members for a team.

An important factor for the knowledge transfer is communication, as pointed out by Lazear (1999). Only if the team members are able to communicate with each other, they can discover their information sets and start to learn from each other in order to perform the tasks more efficiently.

The ideas of specialization and knowledge transfer are visualized in figure 2.1. The information sets of two specialized workers are displayed. The right rectangle denotes the information set of worker 1, the left that of worker 2. The smaller rectangle in the middle is where both information sets are overlapping. Since large parts of the infor- mation sets are not overlapping, there is a big potential gain from teamwork through

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Figure 2.1: Information sets and tasks of workers in a team environment, Source: Authors depiction on basis of Lazear (1998) knowledge transfer. However, the question if teamwork is valuable or not depends on the tasks that each worker has to do.

Figure 2.1 illustrates two cases. In the first case, the workers have to do the tasks in the solid ellipses. Worker 1 alone does not have all the necessary knowledge to complete this task but together with worker 2 in the team, he is able to fulfil it. Similarly, worker 2 cannot fulfil his task alone but with the knowledge of worker 1 it is possible. Teamwork in this case has a clear benefit.

The second case is illustrated by the dotted ellipses. Again, worker 1 does not have sufficient knowledge to fulfil this task but this time the knowledge of worker 2 would not be of any help for him, since part of the ellipse is outside the information set of both workers. The same is valid for the task of worker 2. In this case, the nonoverlapping parts of the information sets are irrelevant and teamwork will not have any benefits.

To sum up, teams should be used generally when the explained benefits of specialization and knowledge transfer overcome the costs associated with teams Empirical studies could confirm the above stated theoretical frameworks. Hamilton et al. (2003) were able to confirm the positive effect of heterogenic, specialized workers within teams. Boning et al. (2007) made an inquiry in US steel mills and were able to show that in this environment of complicated problems, team systems have the greatest gains.

3 The free-riding effect in teams

The free-riding problem in team production is one of the most investigated issues in literature of economics. It is based on the classical work of Alchian and Demsetz (1972), distinguishing partnerships and firms. They argue that the weakening of incentives in large firms will aggravate the free-riding effect. Holmström (1982) concludes that it is possible to overcome the free-riding problem with the enforcement of a bonus system that is able to implement efficient effort.

The main problem in teams is that the individual member bears the full personal costs of his efforts but shares the gains from those efforts with all team members (Baron and Kreps (1999)). Selfish behavior and a trade off between the own effort and the benefits lead to purposely underperformance of the worker. Instead, he will rely on the efforts of his co-workers in order to receive his share of profits. Unfortunately, if all workers think and act in that way, an efficient outcome will not be achieved.

The free-riding problem can be easily explained, using basic algebra. The following model is taken from Kandel and Lazear (1992). Each worker i can choose his individual effort e i. The output of the team can be calculated as a function of all workers efforts f (e). We assume that the output is equally shared among the N workers so that each worker gets.However,sinceeffortmeansacostforaworker,acostfunction C (e i) has to be deducted from his utility. For an increasing effort, the cost function increases with greater proportion C ′ > 0, C ′′ > 0. Each worker wants to maximize so the first order condition is.

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It can be shown that the equilibrium effort of the workers in this situation is lower then the optimal solution in which the total surplus is maximized

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with the first-order conditions

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Since C ′′ > 0), the solution of e ′ in (3.4) must exceed the solution of e in (3.2). Hence, the chosen level of effort in a team is lower then the efficient level.

4 Team performance through incentives

One attempt to lower the negative effects of teamwork and especially the free-riding ef- fect is to introduce team incentives. Hoffman and Rogelberg (1998) distinguish between seven systems of team incentives which we will summarize to four incentive systems depending on the factor that is evaluated. Each system has advantages and disadvan- tages is suited to special situations, which have to be considered before introducing a new team incentive scheme. In addition, incentives have to be separated in explicit and implicit rewards.

System I: Team gain sharing/profit sharing

This system evaluates the outcome of the organization as a whole. A profit sharing plan distributes some share of the company profits to the team members. In contrast, gain sharing usually refers to non-financial organizational successes like quality, productivity and consumer satisfaction (Miller and Schuster (1993)). Typically, the incentive does not only depend on the current year’s profit but also on the difference between this year’s profit and the past profits.

A problem of profit or gain sharing is the distance between the team’s performance and the basis for the incentives. Following Sisco (1992), a team will only improve its performance if it sees an impact of its effort on the incentive measure. If the effect on the company’s profit or on the other gain sharing goals is minimal, departmental goals should be more efficient than global goals (Nickel and O’Neill (1991)).

Another important factor is the distribution of the profit and gain sharing. Recardo and Pricone (1996) argued that in organizations where cooperation among teams is important, the incentives should be shared evenly among the different teams. In this way, the share of common goals can improve the cooperation of the teams. However, if cooperation is not an important factor within the organization, teams may also receive different shares in dependence of their performance to increase the competition among the teams and with it team performance (Johnson et al. (1981)).

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