Effective organizations configure their internal resources and capabilities to meet environmental demands (Andrews 1971, Barney 1991, Grant 1991, Lawrence and Lorsch 1968, Peteraf 1993, Thompson 1968). Information-processing (I/P) models of organizations prescribe organizing to provide an I/P capacity sufficient to deal with the communication requirements generated by the environment, described in information-based terms such as complexity and uncertainty (e.g, Driver and Streufert 1969, Galbraith 1973, Tushman and Nadler 1978). These models, while useful, have two shortcomings. First, organizations process knowledge as well as information (Demsetz 1988, Grant 1996a, Kogut and Zander 1992, Penrose 1959, Spender 1996, Teece 1980). While I/P models assume an ability to interpret messages uniformly and unambiguously, in actuality, events can range widely in meaningfulness and explicability depending on an organization’s intellectual resources. Second, uncertainty, complexity, and similar terms used to describe the perceived determinacy (or indeterminacy) of the environment have been inconsistently defined in the literature (Zack and McKenney 1988). This paper describes a taxonomy of "knowledge problems" addressing these issues. To provide a broader and more coherent description of the environment in knowledge-based terms, I propose the attributes complexity, uncertainty, ambiguity, and equivocality. I argue that each poses a unique challenge and opportunity for applying information technology.