| Decision Support Systems |
Article Index for Decision |
Website Links For Decision Support |
Information AboutDecision Support Systems |
| CATEGORIES ABOUT DECISION SUPPORT SYSTEM | |
| information systems | |
| decision theory | |
|
DEFINITIONS Because there are many approaches to decision-making and because of the wide range of domains in which decisions are made, the concept of ''decision support system'' (DSS) is very broad. A DSS can take many different forms. In general, we can say that a DSS is a computerized system for helping make decisions. A decision is a choice between alternatives based on estimates of the values of those alternatives. Supporting a decision means helping people working alone or in a group gather intelligence, generate alternatives and make choices. Supporting the choice making process involves supporting the estimation, the evaluation and/or the comparison of alternatives. In practice, references to DSS are usually references to computer applications that perform such a supporting role.Alter, S. L. (1980). Decision support systems: current practice and continuing challenges. Reading, Mass., Addison-Wesley Pub. The term ''decision support system'' has been used in many different ways (Alter 1980, Power, 2002) and has been defined in various ways depending upon the author's point of view Druzdzel, M. J. and R. R. Flynn (1999). Decision Support Systems. Encyclopedia of Library and Information Science. A. Kent, Marcel Dekker, Inc.. Finaly Finlay, P. N. (1994). Introducing decision support systems. Oxford, UK Cambridge, Mass., NCC Blackwell; Blackwell Publishers. and others define a DSS rather broadly as "a computer-based system that aids the process of , especially developed for supporting the solution of a non-structured Management problem for improved Decision Making . It utilizes data, provides an easy-to-use Interface , and allows for the decision maker's own insights." Other definitions fall between these two extremes. For Little Little, J.D.C.(1970, April). "Models and Managers:The Concept of a Decision Calculus." ''Management Science'', Vol.16,NO.8, a DSS is a "model-based set of procedures for processing data and judgments to assist a manager in his decision-making." For Keen and Scott Morton Keen, P. G. W. (1978). Decision support systems: an organizational perspective. Reading, Mass., Addison-Wesley Pub. Co. ISBN 0-201-03667-3, a DSS couples the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions ("DSS are computer-based support for management decision makers who are dealing with semi-structured problems"). Moore and Chang Moore, J.H.,and M.G.Chang.(1980,Fall)."Design of Decision Support Systems." ''Data Base'',Vol.12, Nos.1 and 2. define DSS as extendible systems capable of supporting ad hoc data analysis and decision modeling, oriented toward future planning, and used at irregular, unplanned intervals. For Sprague and Carlson Sprague, R. H. and E. D. Carlson (1982). Building effective decision support systems. Englewood Cliffs, N.J., Prentice-Hall. ISBN 0-130-86215-0, DSS are "interactive computer-based systems that help decision makers utilize data and models to solve unstructured problems." In contrast, Keen Keen, P. G. W. (1980). Decision support systems: a research perspective. Decision support systems : issues and challenges. G. Fick and R. H. Sprague. Oxford ; New York, Pergamon Press. claims that it is impossible to give a precise definition including all the facets of the DSS ("there can be no definition of ''decision support systems'', only of ''decision support''"). Nevertheless, according to Power Power, D. J. (1997). What is a DSS? The On-Line Executive Journal for Data-Intensive Decision Support 1(3)., the term ''decision support system'' remains a useful and inclusive term for many types of information systems that support decision making. He humorously adds that every time a computerized system is not an on-line transaction processing system ( OLTP ), someone will be tempted to call it a DSS. As you can see, there is no universally accepted definition of DSS. Power, D.J. A Brief History of Decision Support Systems DSSResources.COM, World Wide Web, version 2.8, May 31, 2003. ''Recommended reading:'' Druzdzel and Flynn (1999), Power (2000), Sprague and Watson (1993), the first chapter of Power (2002), the first chapter of Marakas (1999), the first chapter of Silver (1991), the first two chapters of Sauter (1997), and Holsaple and Whinston (1996). A brief history In the absence of an all-inclusive definition, we focus on the history of DSS (see also PowerPower, D.J. A Brief History of Decision Support Systems DSSResources.COM, World Wide Web, version 2.8, May 31, 2003.). According to Keen and Scott Morton , the concept of decision support has evolved from two main areas of research: the theoretical studies of organizational decision making done at the Carnegie Institute Of Technology during the late 1950s and early 1960s, and the technical work on interactive computer systems, mainly carried out at the Massachusetts Institute Of Technology in the 1960s. It is considered that the concept of DSS became an area of research of its own in the middle of the 1970s, before gaining in intensity during the 1980s. In the middle and late 1980s, Executive Information Systems (EIS), Group Decision Support System s (GDSS), and Organizational Decision Support System s (ODSS) evolved from the single user and model-oriented DSS. Beginning in about 1990, Data Warehousing and On-line Analytical Processing (OLAP) began broadening the realm of DSS. As the turn of the millennium approached, new Web-based analytical applications were introduced. It is clear that DSS belong to an environment with multidisciplinary foundations, including (but not exclusively) Database research, Artificial Intelligence , Human-computer Interaction , Simulation methods, Software Engineering , and Telecommunications . DSS also have a weak connection to the User Interface paradigm of Hypertext . Both the University Of Vermont PROMIS system (for medical decision making) and the Carnegie Mellon ZOG/KMS system (for military and business decision making) were decision support systems which also were major breakthroughs in user interface research. Furthermore, although Hypertext researchers have generally been concerned with Information Overload , certain researchers, notably Douglas Engelbart , have been focused on helping decision makers in particular. TAXONOMIES As with the definition, there is no universally accepted Taxonomy of DSS either. Different authors propose different classifications. Using the relationship with the user as the criterion, Haettenschwiler Haettenschwiler, P. (1999). Neues anwenderfreundliches Konzept der Entscheidungsunterstützung. Gutes Entscheiden in Wirtschaft, Politik und Gesellschaft. Zurich, vdf Hochschulverlag AG: 189-208. differentiates ''passive'', ''active'', and ''cooperative DSS''. A ''passive DSS'' is a system that aids the process of decision making, but that cannot bring out explicit decision suggestions or solutions. An ''active DSS'' can bring out such decision suggestions or solutions. A ''cooperative DSS'' allows the decision maker (or its advisor) to modify, complete, or refine the decision suggestions provided by the system, before sending them back to the system for validation. The system again improves, completes, and refines the suggestions of the decision maker and sends them back to her for validation. The whole process then starts again, until a consolidated solution is generated. Using the mode of assistance as the criterion, Power Power, D. J. (2002). Decision support systems: concepts and resources for managers. Westport, Conn., Quorum Books. differentiates ''communication-driven DSS'', ''data-driven DSS'', ''document-driven DSS'', ''knowledge-driven DSS'', and ''model-driven DSS''.
Using scope as the criterion, Power differentiates ''enterprise-wide DSS'' and ''desktop DSS''. An ''enterprise-wide DSS'' is linked to large data warehouses and serves many managers in the company. A ''desktop, single-user DSS'' is a small systems that runs on an individual manager's PC. ARCHITECTURES Once again, different authors identify different components in a DSS. Sprague and Carlson identify three fundamental components of DSS: ''(a)'' the Database Management System (DBMS), ''(b)'' the model-base management system (MBMS), and ''(c)'' the dialog generation and management system (DGMS). Haag ''et al.'' Haag, Cummings, McCubbrey, Pinsonneault, Donovan (2000). Management Information Systems: For The Information Age. McGraw-Hill Ryerson Limited: 136-140. ISBN 0-072-81947-2 describe these three components in more detail: The Data Management Component stores information (which can be further subdivided into that derived from an organization's traditional data repositories, from external sources such as the Internet , or from the personal insights and experiences of individual users); the Model Management Component handles representations of events, facts, or situations (using various kinds of models, two examples being optimization models and goal-seeking models); and the User Interface Management Component is of course the component that allows a user to interact with the system. According to Power , academics and practitioners have discussed building DSS in terms of four major components: ''(a)'' the User Interface , ''(b)'' the Database , ''(c)'' the model and analytical tools, and ''(d)'' the DSS architecture and network. Hättenschwiler Haettenschwiler, P. (1999). Neues anwenderfreundliches Konzept der Entscheidungsunterstützung. Gutes Entscheiden in Wirtschaft, Politik und Gesellschaft. Zurich, vdf Hochschulverlag AG: 189-208. identifies five components of DSS: ''(a)'' users with different roles or functions in the decision making process (decision maker, advisors, domain experts, system experts, data collectors), ''(b)'' a specific and definable decision context, ''(c)'' a target system describing the majority of the preferences, ''(d)'' a Knowledge Base made of external data sources, knowledge databases, working databases, data warehouses and meta-databases, mathematical models and methods, procedures, inference and search engines, administrative programs, and reporting systems, and ''(e)'' a working environment for the preparation, analysis, and documentation of decision alternatives. Marakas Marakas, G. M. (1999). Decision support systems in the twenty-first century. Upper Saddle River, N.J., Prentice Hall. proposes a generalized architecture made of five distinct parts: ''(a)'' the data management system, ''(b)'' the model management system, ''(c)'' the knowledge engine, ''(d)'' the user interface, and ''(e)'' the user(s). There are several ways to classify DSS applications. Not every DSS fits neatly into one category, but a mix of two or more architecture in one. Holsapple and Whinston Holsapple, C.W., and A. B. Whinston. (1996). Decision Support Systems: A Knowledge-Based Approach. St. Paul: West Publishing. ISBN 0-324-03578-0 classify DSS into the following six frameworks: Text-oriented DSS, Database-oriented DSS, Spreadsheet-oriented DSS, Solver-oriented DSS, Rule-oriented DSS, and Compound DSS. A compound DSS is the most popular classification for a DSS. It is a hybrid system that includes two or more of the five basic structures described by Holsapple and Whinston . The support given by DSS can be separated into three distinct, interrelated categories Hackathorn, R. D., and P. G. W. Keen. (1981, September). "Organizational Strategies for Personal Computing in Decision Support Systems." MIS Quarterly, Vol. 5, No. 3.: Personal Support, Group Support, and Organizational Support. Additionally, the build up of a DSS is also classified into a few characteristics. 1) inputs: this is used so the DSS can have factors, numbers, and characteristics to analyze. 2) user knowledge and expertise: This allows the system to decide how much it is relied on, and exactly what inputs must be analyzed with or without the user. 3) outputs: This is used so the user of the system can analyze the decisions that may be made and then potentially 4) make a decision: This decision making is made by the DSS, however, it is ultimately made by the user in order to decide on which criteria it should use. DSSs which perform selected cognitive decision-making functions and are based on Artificial Intelligence or Intelligent Agent s technologies are called Intelligent Decision Support Systems (IDSS). APPLICATIONS As mentioned above, there are theoretical possibilities of building such systems in any knowledge domain. Some of the examples is Clinical Decision Support System for Medical Diagnosis . Other examples include a bank loan officer verifying the credit of a loan applicant or an engineering firm that has bids on several projects and wants to know if they can be competitive with their costs. DSS is extensively used in business and management. Executive Dashboard and other business performance software allow faster decision making, identification of negative trends, and better allocation of business resources. A growing area of DSS application, concepts, principles, and techniques is in agricultural production, marketing for sustainable development. For example, the DSSAT4 package DSSAT4 (pdf) The Decision Support System for Agrotechnology Transfer , developed through financial support of USAID during the 80's and 90's, has allowed rapid assessment of several agricultural production systems around the world to facilitate decision-making at the farm and policy levels. A specific example concerns the Canadian National Railway system, which tests its equipment on a regular basis using a decision support system. A problem faced by any railroad is worn-out or defective rails, which can result in hundreds of derailments per year. Under a DSS, CN managed to decrease the incidence of derailments at the same time other companies were experiencing an increase. DSS has many applications that have already been spoken about. However, it can be used in any field where organization is necessary. Additionally, a DSS can be designed to help make decisions on the stock market, or deciding which area or segment to market a product toward. CHARACTERISTICS AND CAPABILITIES OF DSS Because there is no exact definition of DSS, there is obviously no agreement on the standard characteristics and capabilities of DSS. Turban, E.,Aronson, J.E., and Liang, T.P. Turban, E.,Aronson, J.E., and Liang, T.P.(2005). Decision Support Systems and Intelligent Systems. New Jersey, Pearson Education, Inc. constitute an ideal set of characteristics and capabilities of DSS. The key DSS characteristics and capabilities are as follows: # Support for decision makers in semistructured and unstructured problems. # Support managers at all levels. # Support individuals and groups. # Support for interdependent or sequential decisions. # Support intelligence, design, choice, and implementation. # Support variety of decision processes and styles. # DSS should be adaptable and flexible. # DSS should be interactive and provide ease of use. # Effectiveness balanced with efficiency (benefit must exceed cost). # Complete control by decision-makers. # Ease of development by (modification to suit needs and changing environment) end users. # Support modeling and analysis. # Data access. # Standalone, integration and Web-based. REFERENCES References not yet tagged in text
SEE ALSO
EXTERNAL LINKS
|
|
|