<p>Capacity-constrained make-to-order firms often face delivery and quantity deviations that cannot be fully recovered within the available production windows. In such settings, the managerial problem is not only to improve operational performance but also to understand how bounded execution responses buy time, preserve service, and redistribute unresolved burdens across time, quantity, capacity, and recovery mechanisms. This study examines this problem through a case-grounded discrete-event simulation of a constrained make-to-order (MTO) production system. The design separates the two analytical layers. First, an AS-IS replay was used for behavioral validation under the historical order stream and to formalize the AS-IS operating rules. Second, a replicated 2³ factorial experiment compares eight policy combinations defined by minimum planned lead time, shipment shortfall tolerance, and limited capacity flexibility. The AS-IS replay reproduces the structural burden of the focal system, including low delivery reliability, long flow time, backlogs, unfinished work, and completion-order exposure. The factorial results identify capacity flexibility as the dominant lever across requested-basis on-time delivery, fill rate, shipped quantity, flow time, backlog, unfinished work, and Economic Performance Proxy. Shipment shortfall tolerance reduces completion exposure and end-state burden; however, its marginal effect becomes smaller when flexible capacity is already active. Overall, this study contributes a simulation-based decision-support approach that interprets policy effects through the lens of physical operational improvement versus managerial burden redistribution in constrained production.</p>