Consider a typical workday. Much of what you do may rely on collaboration: information-sharing, brainstorming, or mentoring others. When productivity spills over in this way, your output often depends not only on your own effort but on the collective energy of those around you. Positive “peer effects”—like increased motivation from a high-performing colleague—can boost productivity, while negative influences, such as low morale from a disengaged teammate, can hold it back.
Companies are aware of these dynamics. They recognize that certain employees—those whose roles involve significant coordination or influence over others—hold strategic importance within the network of team relationships. These are the “central” workers whose actions create ripple effects. Incentivizing these workers effectively could mean better performance for the entire team and greater profits for the firm.
In Barcelona School of Economics Working Paper 1457, “Incentive Contracts and Peer Effects in the Workplace,” Marc Claveria-Mayol, Pau Milán, and Nicolás Oviedo-Dávila take a close look at these peer effects, revealing how the design of profit-maximizing pay structures goes far beyond job titles or individual targets. Instead, subtle team dynamics can play a major role in shaping how employees are incentivized and wages are designed. Bringing together contract theory and new insights on network interventions, the authors show how team dynamics reshape pay structures beyond individual incentives.
The Impact of Workplace Structure on Productivity, Incentives, and Profits
One important takeaway from their study is that the way peer networks are structured has a big impact on how effective contracts are designed. Workers who are more “central”—those who have more connections with well-connected peers—get bigger incentives, meaning they receive more performance-based pay. This approach links compensation to how well employees can boost productivity across the company, allowing these key workers to help improve the performance of others through their connections.
To illustrate their findings, the authors simulate two different hierarchical organizations: a tall firm with 6 levels and a (direct) span of control of 2, and a flat firm with 4 levels and a (direct) span of control of 4, as shown in Figure 1.
Consistent with empirical evidence and as shown in the left panel of Figure 1, the results show that variable-pay increases as we move up the organization and that this pay gap is more pronounced for flatter firms. In addition, the second panel shows that the distribution of total earnings (which includes variable and fixed-pay) has a longer right tail in flatter firms, where managers oversee more subordinates. Moreover, the wage gap between top earners is small in tall firms (blue bars) and much larger for flat firms (red bars), resulting in a steeper earnings profile in flatter organizations.
Designing Incentive Structures under Network Constraints
The researchers differentiate between cases where firms have comprehensive network information and instances where network insights are limited or where contracts cannot be customized based on social connections. When firms possess detailed knowledge of the network, they can create “personalized” incentives tailored to each worker’s individual influence. However, in many organizations, firms lack full visibility into peer relationships or are simply unable to structure formal contracts around an individual’s social ties. In these situations, the authors suggest a simplified “occupation-wide” incentive model, where workers in the same role receive standardized incentives based on the average influence of the group.
The study demonstrates how limiting contract personalization reduces firm surplus and can even lead to unemployment. Workers in less central roles, unable to benefit from their unique network influence, may opt out of employment altogether if incentives don’t meet their reservation utility.
Modularity and Team-Based Production
The paper also explores modularity—when organizations work through distinct, interdependent teams, or “modules,” that each contribute essential components to the final output. Such modular production is common in large firms, tech companies, and manufacturing, where various units or departments produce different key parts of a product.
The study finds that, within modular organizations, peer effects are less about influence across the entire firm and more about influence within each module. Employees who play crucial roles in these smaller, self-contained teams can receive more individualized incentives to ensure that each team’s component is produced efficiently.
This setup also means that incentives in modular firms are often focused on minimizing weak links. Since one team’s under-performance can impact the entire company’s output, organizations may focus on rewarding those who consistently contribute to their team’s success and foster reliable collaboration. In other words, the optimal strategy shifts from targeting highly-connected individuals towards balancing incentives across teams to prevent any single module from becoming a productivity bottleneck.
This modular focus on “team-specific” incentives reflects a trend in many industries where production relies on highly coordinated, interdependent tasks. It also shows how complex organizational structures can benefit from targeted incentives, ensuring that each module functions effectively within the larger firm ecosystem.
Policy and Practical Implications: Balancing Incentives and Equity
The findings offer crucial insights for policymakers and firms alike. Recent trends toward wage transparency and fairness norms are motivated by concerns over large pay disparities within organizations. In practice, companies lean toward standardized contracts to simplify administration or promote fairness. But the study cautions that treating all roles within the same job title identically may overlook the varying degrees of influence each employee has. Too much compression in wage structure could inadvertently lead to decreased productivity and even higher unemployment. Policymakers could consider these unintended effects when implementing pay regulations, particularly in sectors with high degrees of peer influence.
For firms, the study underscores the importance of aligning incentive structures with the organization’s network dynamics. Where feasible, firms should consider personalized contracts for highly influential workers to maximize firm-wide productivity. When contract personalization is limited, firms can use average measures of influence to set compensation, though they should be aware of potential inefficiencies and productivity losses in such cases.
Looking Ahead: Adapting Incentives to Modern Teams
As workplaces continue to evolve, so do the ways we work together, collaborate, and influence one another. With the rise of remote and hybrid work models, companies are navigating new territory where traditional hierarchies are becoming less relevant, and team dynamics are taking center stage. As firms continue to explore such novel work models, the visibility and influence of certain roles are likely to become even more pronounced. Recognizing and rewarding these dynamics might be crucial for keeping team morale high and enhancing productivity in the evolving workplace landscape. At the forefront of this shift, the rise of AI is adding a powerful new layer to contract design.
The rise of AI adds a new dimension to contract design. AI isn’t just automating tasks—it’s also becoming an influential “co-worker,” reshaping workflows, and affecting how people rely on and interact with each other. As AI systems take on collaborative roles, they shift the weight of influence within teams. Employees who manage or work closely with AI tools could become the new “central” figures, bridging human-AI interactions and driving team efficiency.
In this new landscape, incentives must adapt to reflect these evolving dynamics. By recognizing both human and AI-enhanced contributions, organizations can create a future-ready workforce that harnesses the best of collaboration—wherever it takes place, and whoever (or whatever) is involved. Organizations that adapt to this model may find they’re not only supporting individual achievement but also enhancing the collective strength of their teams.
