Decision-making in the design of cyber-physical manufacturing (CPM) systems is complex due to many decisional entities and their complex interactions that need to be appropriately modeled and analyzed. One approach to designing these systems is the goal-oriented inverse design (GoID), using which satisficing design solutions are sought in a top-down manner. In this approach, entity decisions are directed towards meeting the goals propagated inversely from the subsequent entity in the manufacturing sequence. However, achieving the goals in a top-down manner may not be feasible for certain scenarios due to the defined constraints, available bounds, and targets for an entity. This leads to design conflicts between the entities and loss in entity and overall system-level performances. In this paper, we propose an information-decision framework that allows designers to model entity decision-making in a goal-directed manner, detect potential conflicts between entities, and regulate entity-level decisions to achieve improved entity and system-level performances. The regulation of entity decisions is accomplished by modifying active design variable bounds (considering the sensitivity of the goals to design variables), active constraint limits, or both jointly. The efficacy of the proposed framework is tested using a hot rod rolling problem involving sequential decisions. Using the problem, we showcase the use of the framework in detecting and systematically managing conflicts while designing the material, product, and manufacturing processes involved. The framework is generic, facilitates the top-down sequential design of interacting entities, and promotes cooperative design decision-making to manage design conflicts.