An important attribute of a supply chain in a competitive and volatile market environment is the ability to respond rapidly to demand variation. A particularly relevant application is the forest products industry, where a promising strategy to improve the struggling business model entails the shift from commodity products toward high-value specialty products. A key implication is that new process and supply chain designs have sufficient capability to respond quickly to market changes, such that product availability is high. In this study, we develop a computational framework for dynamic operability analysis of process supply chains. A dynamic model of a multiproduct, multiechelon system supply chain system is developed, and incorporated within an optimization framework. A two-stage stochastic programming approach is applied for the treatment of demand uncertainty. A bicriterion optimization problem is formulated for generating the Pareto frontier between an economic and responsiveness criterion. Two case studies are presented to demonstrate the applicability of this framework.