Shortcut methods for the rapid determination of the optimal steady-state operating policy for certain classes of chemical plants have recently been published [Ward et al., Ind. Eng. Chem. Res. 2004, 43, 3957; 2005, 44, 6729]. The purpose of this work is to investigate the implications of these optimal operating policies for the selection of control methodology and control structure design, and to demonstrate that the operating policies can be implemented dynamically. These methods can predict, using basic information about the process chemistry, whether a self-optimizing control structure will give good economic performance, or whether an explicit optimization layer will be required in the control hierarchy. When a self-optimizing control structure is sufficient, this methodology allows the engineer to anticipate which binary pairings between controlled and manipulated variables are optimal. When an optimizing control layer (e.g., MPC or real-time optimizer (RTO)) is required, the method suggests a low-order model that will capture the essential nonlinearities of the process and that can be used for the design of the optimizing controller. Dynamic simulations of two case studies confirm that the control methodologies and control structures, which are predicted best by the methods of Ward et al., do, in fact, give the economically best operation of the process, when implemented dynamically.