Design in general is about increasing the information of the product/system. Therefore it is natural to investigate the design process from an information theoretical point of view. In this paper the design process is described as an information transformation process, where an initial set of requirements are transformed to a system specification. Performance and cost are both functions of complexity and refinement, which can be expressed in information entropy. There are essentially two ways of increasing the information content in a system. One is to reduce tolerances in the design parameters. The other way is to increase the design space, by introducing more features into the design. Both of these aspects of increasing information content are discussed through the establishment of a formal framework. In this way, the relationship between concept refinement and design space expansion can be viewed in information theoretical terms. The information theoretical model is demonstrated on examples. The model has practical implications for the balance between number of design parameters, and the degree of convergence in design optimization. It can also be used to give a rough estimate of number of parameters that are needed for a specified degree of accuracy in the optimization result, or the number of parameters that are meaningful to use under uncertainty.