Optimal Incentive Contract with Endogenous Monitoring Technology

Recent technology advances give firms more flexibility to utilize employee performance data at a reduced and yet significant cost. This paper develops a theory of optimal incentive contracting where the monitoring technology that governs the above described procedure is part of the designer’s strategic planning. In otherwise standard principal-agent models with moral hazard, we assume that the principal can partition the agent’s raw performance data into any finite categories and pays for the quantity of information that the output signal carries. Through analysis of the trade-off between providing the agent with incentives and saving the cost of data utilization, we obtain characterizations of the optimal monitoring technology such as information aggregation, strict MLRP, likelihood ratio-convex performance classification, group evaluation as a best response to high monitoring cost, and dividing resources across the assessments of various tasks according to the agent’s endogenous tendencies to shirk. We examine the implications of these results for workforce management and firms’ internal organizations.