IS design today is driven primarily by technical and functional requirements, and the economic implications for design are not yet well understood. This study argues that system design and architecture must reflect assessments of economic trade-offs besides satisfying technical/functional requirements. Modeling the economic performance structure behind IS design can highlight these trade-offs and help economically assess design alternatives. This study examines economics-driven design in the context of the Data Warehouse (DW). The DW environment is treated as a dynamic capability, providing the capacity for managing data resources and turning them into useful information products. These products contribute value when used for exploitative and/or explorative business processes. Recognizing possible uncertainties in usage, DW capacities are evaluated as real-option investments toward the development of a framework for modeling cost-utility effects of DW design decisions. This framework is used to evaluate important design scenarios along the layers of a DW stack architecture and optimize design outcomes accordingly.