Ch. 1
Supporting Business Decision-Making

Chapter Contents Previous Page Next Page

Prior to the mid-1960s, it was not cost effective to build large-scale information systems. The first Management Information Systems (MIS) were developed at about that time in large companies. MIS focused on providing managers with structured, periodic reports. Much of the information was from accounting and transaction systems.

In the late 1960s, a new type of information system became practical – model-oriented DSS or management decision systems. Two DSS pioneers, Peter Keen and Charles Stabell (1978), claim the concept of decision support evolved from "the theoretical studies of organizational decisionmaking done at the Carnegie Institute of Technology during the late 1950s and early '60s and the technical work on interactive computer systems, mainly carried out at the Massachusetts Institute of Technology in the 1960s." Table 1.1 summarizes major developments in the evolution of Decision Support Systems concepts.

In 1971, Michael S. Scott Morton’s book Management Decision Systems: Computer-Based Support for Decision Making was published. In 1968-69 Scott Morton studied how computers and analytical models could help managers make a key decision. He conducted an experiment in which managers actually used a Management Decision System (MDS). Marketing and production managers used an MDS to coordinate production planning for laundry equipment. Scott Morton's research was a pioneering implementation, definition and research test of a model-based decision support system.

T.P. Gerrity, Jr. focused on Decision Support Systems design issues in his 1971 Sloan Management Review article titled "The Design of Man-Machine Decision Systems: An Application to Portfolio Management". His system was designed to support investment managers in their daily administration of a clients' stock portfolio. DSS for portfolio management have become very sophisticated since Gerrity began his research.

In 1974, Gordon Davis, a Professor at the University of Minnesota, published his influential text Management Information Systems: Conceptual Foundations, Structure, and Development. He asserted the MIS concept was "a substantial extension of the concepts of managerial accounting taking into consideration the ideas and techniques of management science and the behavioral theories of management and decision making (p. 8)."

Davis defined a Management Information System as "an integrated, man/machine system for providing information to support the operations, management, and decision-making functions in an organization. The systems utilize computer hardware and software, manual procedures, management and decision models, and a database (p. 5)."

Davis's Chapter 12 titled "Information System Support for Decision Making", and Chapter 13 titled "Information System Support for Planning and Control" created the setting for the development of a broad foundation for Decision Support Systems research and practice. MIS was in many ways beginning to converge with DSS concepts.

By 1975, J. D. C. Little was expanding the frontiers of computer-supported modeling. Little's DSS called Brandaid was designed to support product, promotion, pricing and advertising decisions. Little, in his Management Science article titled "Models and Managers: The Concept of a Decision Calculus" identified criteria for designing models to support management decision--making. His criteria included: robustness, ease of control, simplicity, and completeness of relevant detail.

Peter G. W. Keen and Michael Scott Morton's DSS textbook titled Decision Support Systems: An Organizational Perspective was published in 1978. Their text provided a comprehensive behavioral orientation to DSS analysis, design, implementation, evaluation and development.

In 1980, Steven Alter published his doctoral dissertation results in a book titled Decision Support Systems: Current Practice and Continuing Challenge. Alter's research expanded the framework for our thinking about management DSS. His case studies provided a firm descriptive foundation for identifying Decision Support Systems.

Bonczek, Holsapple, and Whinston’s (1981) book, Foundations of Decision Support Systems, created a theoretical framework for understanding the issues associated with designing Decision Support Systems. They identified four essential "aspects" or components common to all DSS: 1. A language system (LS) - all messages the DSS can accept; 2. A presentation system (PS) - all messages the DSS can emit; 3. A knowledge system (KS) -- all knowledge the DSS has stored and retained; and 4. A problem-processing system (PPS) -- the "software engine" that tries to recognize and solve problems during use of the DSS.

The book Building Effective Decision Support Systems by Ralph Sprague and Eric Carlson (1982) was an important milestone. It provided a practical, understandable overview of how organizations could and should build DSS. Although the book created some unrealistic expectations, the problem was more the limits of the existing technologies for building DSS than the limits of the concepts Sprague and Carlson presented.

In the mid-1980s, academic researchers developed software to support group and organizational decision-making (cf., DeSanctis and Gallupe, 1987). For the next 10 years, many research studies examined the impacts and consequences of GDSS.

Executive Information Systems (EIS) evolved from the single user Model-Driven Decision Support systems and improved relational database products. The first EIS used pre-defined information screens and were maintained by analysts for senior executives. Beginning in about 1990, data warehousing and On-Line Analytical Processing (OLAP) began broadening the realm of EIS and defined a broader category of Data-Driven DSS (cf., Dhar and Stein, 1997).

Today, a number of academic disciplines provide the substantive foundations for Decision Support Systems development and research. Database researchers have contributed tools and research on managing data and documents. Management Science and Operations Research have developed mathematical models for use in Model-Driven DSS and provided evidence on the advantages of modeling in problem solving. Cognitive Science, especially Behavioral Decision-Making research, has provided descriptive and empirical information that has assisted in DSS design and has generated hypotheses for DSS research. Some other important fields related to DSS include artificial intelligence, human-computer interaction, software engineering, and telecommunications.