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@article{DBLP:journals/tods/Donovan76,
author = {John J. Donovan},
title = {Database System Approach to Management Descision Support},
journal = {ACM Trans. Database Syst.},
volume = {1},
number = {4},
year = {1976},
pages = {344-369},
ee = {http://doi.acm.org/10.1145/320493.320500, db/journals/tods/Donovan76.html},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Traditional intuitive methods of decision-making are no longer adequate to deal with the complex problems faced by the modern policymaker. Thus systems must be developed to provide the information and analysis necessary for the decisions which must be made. These systems are called decision support systems. Although database systems provide a key ingredient to decision support systems, the problems now facing the policymaker are different from those problems to which database systems have been applied in the past. The problems are usually not known in advance, they are constantly changing, and answers are needed quickly. Hence additional technologies, methodologies, and approaches must expand the traditional areas of database and operating systems research (as well as other software and hardware research) in order for them to become truly effective in supporting policymakers.
This paper describes recent work in this area and indicates where future work is needed. Specifically the paper discusses: (1) why there exists a vital need for decision support systems; (2) examples from work in the field of energy which make explicit the characteristics which distinguish these decision support systems from traditional operational and managerial systems; (3) how an awareness of decision support systems has evolved, including a brief review of work done by others and a statement of the computational needs of decision support systems which are consistent with contemporary technology; (4) an approach which has been made to meet many of these computational needs through the development and implementation of a computational facility, the Generalized Management Information System (GMIS); and (5) the application of this computational facility to a complex and important energy problem facing New England in a typical study within the New England Energy Management Information System (NEEMIS) Project.
Copyright © 1976 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.