A Cognitively Based Functional Taxonomy of Decision Support Techniques

Abstract

The Decision Support Systems (DSS) field has grown rapidly, drawing technology from many disciplines and pursuing applications in a variety of domains but developing little underlying theoretical structure and poor linkage between research and practice. This article presents a classification scheme for DSS techniques that provides a common theoretical framework for DSS research and also structures and simplifies the process of designing application systems. The classification system is functional, grouping DSS techniques according to their ability to provide similar kinds of support (i.e., functions) to a human decision maker. It is also cognitively based, defining the kinds of support that decision makers need in terms of architectural features and procedural aspects of human cognition. The classification is expressed as a taxonomy, encompassing six primary classes of decision support techniques representing the six general kinds of cognitive support that human decision makers need. The six classes are process models, which assist in projecting the future course of complex processes; choice models, which support integration of decision criteria across aspects and/or alternatives; information control techniques, which help in storage, retrieval, organization, and integration of data and knowledge; analysis and reasoning techniques, which support application of problem-specific expert reasoning procedures; representation aids, which assist in expression and manipulation of a specific representation of a decision problem; and judgment amplification/refinement techniques, which help in quantification and debiasing of heuristic judgments. Additional distinctions are provided to distinguish the individual techniques in each of these primary categories. The taxonomy also has practical use as a design aid for decision support systems. The kinds of decision support needs represented by the taxonomy are general and can be used to guide the analysis and decomposition of a given decision prior to decision aid design. Specific needs for assistance can then be tied to specific computational techniques in the taxonomy. Methodological suggestions for using the taxonomy as a design aid are given.