Incentives: Components of Incentive Mechanisms

An incentive mechanism is used to influence behavior. This is accomplished by putting rules and processes in place to detect desirable and undesirable behaviors, and respectively, reward and sanction them. Detecting behaviors in practice involves monitoring actions and understanding which behaviors are likely to yield desired outcomes and which will not. 

This text is part of the series on the design of decision governance. Decision Governance refers to values, principles, practices designed to improve the quality of decisions. Find all texts on decision governance here, including “What is Decision Governance?” here.

Research in economics has extensively explored incentive mechanisms, emphasizing their role in addressing principal-agent problems (e.g., Jensen & Meckling, 1976; Holmstrom, 1979) and aligning individual motivations with organizational goals. Key publications in this field include works by Lazear (2000), which discusses the effectiveness of performance-based pay, and Holmstrom and Milgrom (1991), which provides a theoretical framework for understanding incentive contracts in multi-task environments. These studies have significantly contributed to the understanding of how incentives can address moral hazard and adverse selection while promoting optimal behavior within organizations.

Moral hazard occurs when individuals or entities are more likely to take risks because they do not bear the full consequences of their actions. This typically arises when one party is protected from risk while another bears the cost. For example, employees might exert less effort if they know their compensation is guaranteed regardless of performance.

Adverse selection refers to a situation where asymmetrical information leads to the selection of participants whose actions or characteristics may be detrimental to an organization. For instance, in hiring, a lack of insight into applicants’ true abilities may result in choosing less qualified candidates.

Both concepts are central to understanding incentive mechanisms because they illustrate challenges in aligning individual behavior with organizational goals. Incentive mechanisms aim to mitigate these problems by structuring rewards and penalties that encourage desirable actions and discourage harmful ones. Studies highlight how well-designed incentives can mitigate issues like moral hazard and adverse selection by ensuring participants act in ways that lead to collective benefit. For example, performance-based pay structures or reputation-based incentives have been shown to improve productivity and compliance in various settings (Lazear, 2000; Holmstrom & Milgrom, 1991).

Infrastructure for Incentive Mechanisms

To establish and operate an incentive mechanism, the following components, referred to here as “infrastructure,” are necessary:

1. Rules: A clear specification of how the incentive mechanism functions. This includes defining roles, rights, responsibilities, processes, and metrics.
2. Education: Individuals subject to the mechanism must be informed about it. They need to understand what behaviors are rewarded or sanctioned, why, and how they are involved. Additionally, they should know how to opt out of situations where the mechanism is active.
3. Monitoring: Tools and processes must be in place to observe behavior effectively. Monitoring systems should distinguish between individuals’ actions and differentiate between desirable and undesirable actions or their outcomes.
4. Incentive Delivery: A system to deliver rewards or sanctions based on observed behaviors. This process should be consistent and transparent.
5. Improvement: Mechanisms to gather information on the failures of the incentive system. This data should be analyzed to facilitate continuous improvement.
6. Performance Measurement: Metrics and methods must exist to assess whether the incentive mechanism is steering behavior in the desired direction.

Each of these components is interdependent. For example, education cannot proceed without rules, and incentive delivery is impossible without effective monitoring. It is unlikely that a functional incentive mechanism could omit any of these components.

Example of an Incentive Mechanism

Consider a sales team within an organization where a performance-based pay structure is implemented as an incentive mechanism. This system rewards employees with bonuses based on the total sales they generate each quarter. Below, each component of the incentive mechanism is discussed using this example:

1. Rules: The organization establishes clear guidelines, specifying the percentage of sales revenue that will translate into bonuses. Roles are defined, such as who qualifies for the bonuses, how sales are tracked, and the thresholds for different bonus levels. Metrics such as individual and team sales are outlined.
   
2. Education: Sales team members are trained to understand the mechanism, including how their performance translates to rewards, the timelines for payouts, and how disputes or errors in sales tracking will be addressed. They are also educated on how to achieve higher sales ethically and effectively.
   
3. Monitoring: The organization implements a system to track individual and team sales accurately. This might involve CRM software that records sales transactions in real-time and distinguishes between verified and unverified sales.
   
4. Incentive Delivery: Bonuses are calculated and distributed transparently at the end of each quarter. The process ensures timeliness and fairness, such as correcting errors in sales records before payouts.
   
5. Improvement: Feedback from employees and performance data are regularly reviewed. If certain thresholds are consistently unattainable or if employees express dissatisfaction with the system, adjustments are made to improve the mechanism’s effectiveness.
   
6. Performance Measurement: Metrics such as overall sales growth, employee satisfaction, and changes in turnover rates are analyzed to assess whether the incentive mechanism is achieving its intended outcomes.

Contextual Considerations

The design and implementation of these infrastructure components depend on various factors, including the following.

• Feasibility of Monitoring: In the context of performance-based pay for a sales team, behaviors can often be effectively monitored using CRM software and sales tracking tools. These systems collect data on individual and team sales performance, though some aspects, such as the effort expended or informal collaboration, may remain inaccessible. Monitoring feasibility is discussed in Baker (1992), which examines the practical limitations of observing all relevant behaviors.
  
• Behavioral Distinction: Desirable behaviors, such as securing sales ethically and fostering long-term client relationships, can usually be identified through performance metrics and customer feedback. Undesirable behaviors, such as misrepresentation to clients or poaching others’ leads, may require additional oversight or whistleblowing mechanisms to identify accurately. Holmstrom and Milgrom (1991) emphasize the importance of distinguishing behaviors, particularly in multi-task environments.
  
• Cost of Monitoring: The expense of monitoring a sales team depends on the tools used. Advanced CRM systems and regular auditing can be costly but are often justified by the increased sales and compliance they promote. Simpler tools might reduce costs but risk missing critical details. Monitoring costs have been explored by Prendergast (1999), who analyzes trade-offs in designing incentive structures.
  
• Timing of Outcomes: The time between a salesperson’s efforts and the observable outcome (a completed sale) is typically short, which simplifies the alignment of behavior and rewards. However, for certain industries with longer sales cycles, this delay could complicate the timing of bonuses. The effect of time lags on incentives is examined in Gibbons and Murphy (1992).
  
• Understanding Causal Relationships: The causal relationship between behaviors (e.g., client outreach, product knowledge) and outcomes (sales) is usually well-understood in sales environments. However, external factors such as market conditions or product quality can also influence results, which needs to be accounted for in the incentive structure. Lazear (2000) provides a foundational discussion on how such relationships affect the design of performance pay.
  
• Nature of Incentives: Monetary rewards, such as bonuses, are the primary incentives in this example. They align well with sales team motivations but could be complemented by reputational incentives like public recognition to enhance effectiveness. Deci and Ryan (1985) discuss how intrinsic and extrinsic motivators interact in shaping behavior.
  
• Unanticipated Consequences: Performance-based pay could lead to unintended behaviors, such as overpromising to clients or prioritizing short-term sales over sustainable relationships. Mechanisms like client satisfaction surveys and ethical guidelines can help mitigate these risks. Kerr (1975) explores how poorly aligned incentives can lead to counterproductive behaviors.
  
• Preference Shifts: Introducing performance-based pay may alter preferences, encouraging team members to prioritize individual success over collaboration. Team-based rewards or mixed incentives can be used to balance individual and collective goals. Benabou and Tirole (2003) provide insights into how incentives influence social preferences and motivations.

Broader Implications

The design of an incentive mechanism must account for these considerations and integrate them into the broader framework of a organization’s decision governance. Specifications of an incentive mechanism are a critical part of decision governance. Thus, all questions raised here must be addressed in the context of designing and evolving the decision governance framework of the organization.

References

• Baker, G. (1992). “Incentive Contracts and Performance Measurement.” Journal of Political Economy, 100(3), 598-614.
• Benabou, R., & Tirole, J. (2003). “Intrinsic and Extrinsic Motivation.” Review of Economic Studies, 70(3), 489-520.
• Deci, E. L., & Ryan, R. M. (1985). Intrinsic Motivation and Self-Determination in Human Behavior. Springer.
• Gibbons, R., & Murphy, K. J. (1992). “Optimal Incentive Contracts in the Presence of Career Concerns: Theory and Evidence.” Journal of Political Economy, 100(3), 468-505.
• Holmstrom, B. (1979). “Moral Hazard and Observability.” Bell Journal of Economics, 10(1), 74-91.
• Holmstrom, B., & Milgrom, P. (1991). “Multitask Principal-Agent Analyses: Incentive Contracts, Asset Ownership, and Job Design.” Journal of Law, Economics, & Organization, 7(Special Issue), 24-52.
• Kerr, S. (1975). “On the Folly of Rewarding A, While Hoping for B.” Academy of Management Journal, 18(4), 769-783.
• Lazear, E. P. (2000). “Performance Pay and Productivity.” American Economic Review, 90(5), 1346-1361.
• Prendergast, C. (1999). “The Provision of Incentives in Firms.” Journal of Economic Literature, 37(1), 7-63.

Key Concepts

• Moral Hazard: The tendency of individuals or entities to take risks because they do not bear the full consequences of their actions. (Holmstrom, 1979)
• Adverse Selection: A situation where asymmetrical information leads to the selection of participants whose actions or characteristics may be detrimental to an organization. (Jensen & Meckling, 1976)
• Principal-Agent Problem: A conflict of interest arising when a principal delegates decision-making authority to an agent whose objectives may not align with those of the principal. (Holmstrom & Milgrom, 1991)
• Incentive Mechanism: A structured system designed to influence behavior through rewards and sanctions based on observed actions or outcomes.