In the complex ecosystem of corporate management, the design of incentive contracts is often treated as a blend of art and science. Executives frequently rely on intuition, historical precedent, and professional experience to decide how to motivate their workforce, assuming their expertise allows them to accurately forecast which compensation structures will drive the best results. However, a groundbreaking new study, published as Working Paper 35788 by the National Bureau of Economic Research (DOI: 10.3386/w35788) in October 2026, suggests that this confidence may be misplaced. The research indicates that while managers are adept at identifying and avoiding objectively poor incentive schemes, they suffer from a significant, systematic blind spot when it comes to identifying the most effective ones.
The study, which synthesizes a survey of managerial beliefs with a large-scale field experiment, provides a rare, empirical look at the gap between executive perception and economic performance. By randomly assigning agents at the market level to various expenditure-equivalent incentive schemes—contracts that cost the firm the same amount but structure rewards differently—researchers were able to isolate the impact of contract design on productivity and profitability. The results reveal a striking disconnect: the contract that generated the highest financial returns for the firm was frequently overlooked or ranked poorly by the very managers tasked with choosing it.
The Profitability Gap
At the heart of the findings is the discovery that incentive design is a primary, yet often misunderstood, lever for firm performance. In the field experiment, the best-performing incentive contract delivered a staggering 55% increase in weekly firm profit compared to the status quo. This is not a marginal gain; it represents a fundamental shift in output that could, if scaled across a larger organization, transform the financial trajectory of a business.
Yet, despite this dramatic performance boost, the managers surveyed in the study consistently underestimated the potential of this top-tier contract. When asked to predict the efficacy of various schemes, they favored options that yielded far more modest results. This leads to an unsettling conclusion: firms may be leaving massive amounts of value on the table, not because they lack the budget for better incentives, but because the decision-makers at the helm are fundamentally misjudging the behavioral impact of the structures they implement.
The study also found that this failure in judgment was not universal across the spectrum of contract types. While managers were poor at identifying the "stars," they were surprisingly reliable at identifying the "duds." The worst-performing contracts were correctly predicted to be ineffective by the managers. This suggests a form of "asymmetric cognitive failure"—managers are excellent at filtering out bad ideas but lack the foresight to recognize truly high-impact, transformative incentive models. They are effective at avoiding failure, but they are systematically biased against the very strategies that would drive exceptional success.
The Theoretical Benchmark
To understand why managers struggle to identify high-performing contracts, the researchers compared managerial predictions against the forecasts generated by standard contract theory. Contract theory, the academic framework used by economists to model how incentives influence behavior, generally assumes an "unbiased textbook principal"—a theoretical decision-maker who understands the nuances of labor supply and risk responses perfectly.
Interestingly, the study found that this textbook model often outperformed the managers. The theoretical principal was able to rank the contracts correctly, or at the very least, identify the profit leader with a high degree of accuracy. When the theoretical model did fail, its errors were strikingly similar in nature and scale to those made by the managers. This suggests that the difficulty in predicting incentive outcomes is not merely a failure of human intuition, but a reflection of the inherent complexity involved in predicting how human behavior responds to different pay-for-performance structures.
The research indicates that the performance differences observed across the contracts are driven by a complex interplay of labor-supply responses—how much effort an individual is willing to exert for a given reward—and risk responses, or how workers react to the uncertainty of potential earnings. Because different incentive structures shift the burden of risk differently between the firm and the employee, predicting the outcome requires a sophisticated understanding of both the average worker’s effort elasticity and their risk aversion. Managers appear to be operating on a heuristic level, missing the second-order effects of these incentive designs, whereas the economic models—while not infallible—account for these dynamics more robustly.
The Role of Complexity and Hierarchy
The research further delves into the variables that influence how accurately a manager can predict these outcomes. It highlights that managerial predictability is not a static trait; it varies significantly depending on the complexity of the contract and the position of the manager within the corporate hierarchy.
As incentive structures become more intricate—incorporating thresholds, caps, variable bonus structures, or group-based performance metrics—the ability of managers to forecast their impact degrades. The cognitive load required to model how an agent will respond to a complex, non-linear incentive structure appears to exceed the limits of intuitive managerial decision-making. Furthermore, the study notes that hierarchy plays a role. Those in higher managerial positions, who may be more removed from the day-to-day operations of the workforce, often possess different, and sometimes less accurate, perceptions of how their subordinates will react to shifts in compensation.
These findings carry significant implications for organizational design. If managers cannot accurately judge the efficacy of their own incentive programs, then the process of contract design becomes a potential liability. It suggests that firms should perhaps rely less on the intuition of senior leadership and more on rigorous testing and data-driven piloting of compensation models. The "status quo" bias, which sees firms sticking to familiar pay structures simply because they are understood, may be acting as a barrier to innovation and growth.
Implications for Future Strategy
The study’s findings regarding the 55% profit increase from a top-performing, yet overlooked, contract serve as a wake-up call for firms currently relying on traditional or legacy incentive schemes. It highlights a critical, often overlooked limitation in managerial cognition: the systematic underestimation of high-upside incentive models.
As the corporate world becomes increasingly data-reliant, the reliance on "managerial gut feeling" regarding human resources and compensation is coming under greater scrutiny. The research suggests that the path forward involves a move toward experimental economics within the firm—treating incentive structures like product features that require A/B testing rather than as settled policy decisions. By embracing this approach, firms may be able to overcome the cognitive limits that currently keep them tethered to suboptimal performance.
The work also underscores the value of economic theory. While it is common to contrast "academic" models with "real-world" management, the study demonstrates that the theoretical frameworks developed by economists can provide a more reliable map for decision-making than pure intuition. The "unbiased textbook principal" may not be perfect, but it offers a systematic approach to evaluating trade-offs—specifically regarding labor supply and risk—that managers appear to be missing.
Ultimately, the research provides a sobering but optimistic outlook. It identifies a clear, quantifiable, and addressable inefficiency in how firms manage their most important asset: their people. By acknowledging that managerial intuition has systematic blind spots, companies can begin to implement more robust, data-backed processes for incentive design, potentially unlocking the significant performance gains that are currently being left on the table. The study concludes that the future of competitive firm performance may rest not just on the brilliance of the business strategy, but on the intellectual humility required to admit that human cognition is limited when it comes to predicting the complex human responses that drive organizational success.
