Decision Supporting Systems

Abstract

It has long been established [e.g., Newell, Simon 1972] that electronic data processing (EDP) and human decision makers complement each other in the sense that EDP is by far superior or more powerful in terms of data processing—in particular simultaneous and parallel processing—and the human is more capable, for instance, of communicating on the basis of incomplete data, in making judgments etc. The human decision maker needs the help of EDP in terms of information processing capacity and easy-access storage. But if EDP equipment is to be used for this purpose, decision problems must be modelled properly so that the models really represent the decision maker’s problems and can be understood by the machine. This normally implies that the decision maker himself knows how to solve the problem and that the solution algorithm can be modelled well enough to be programmed for the machine. In this case the solution procedure—like the information processing process called “decision”—is well defined on the machine and the data input into the program will fully determine the result of the process. We shall call such an EDP program or system Data-Based Decision Support System or, for short, DSS. Of course there are still problems for the decision maker, and the case in which all algorithmic features are well defined is only a limiting case. The decision maker still has problems with obtaining all the data and feeding them into the computer in the correct format.