The concept of a decision support system (DSS) is extremely broad and its definitions vary depending upon the author’s point of view. A DSS can take many different forms and the term can be used in many different ways.
In a more precise way, it can be defined as:
An interactive, flexible, and adaptable computer-based information system, 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.
DSS are computer-based support for management decision makers who are dealing with semi-structured problems. With respect to computer terminology it can be defined as:
Interactive computer-based systems that help decision makers utilize data and models to solve unstructured problems.
Though, it is impossible to give a precise definition including all the facets of the DSS. Nevertheless, the term decision support system remains a useful and inclusive term for many types of information systems that support decision making. Every time a computerized system is not an on-line transaction processing system (OLTP), someone will be tempted to call it a DSS. As it can be see that there is no universally accepted definition of DSS.
Additionally, the specifics of it is what makes it less generalized and more detailed. In addition, a DSS also is a specific Software application that helps to analyze data contained with a customer database. This approach to customers is used when deciding on target markets as well as customer habits.
History of DSS
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 systems (GDSS), and organizational decision support systems (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.
Historical development
The role of business information systems has changed and expanded over the last four decades. In the incipient decade (1950s and ’60s), electronic data processing systems could be afforded by only the largest organizations. They were used to record and store bookkeeping data such as journal entries, specialized journals, and ledger accounts. This was strictly an operations support role. By the 1960s management information systems were used to generate a limited range of predefined reports, including income statements (they were called P & Ls back then), balance sheets and sales reports. They were trying to perform a decision making support role, but they were not up to the task.
By the 1970s decision support systems were introduced. They were interactive in the sense that they allowed the user to choose between numerous options and configurations. Not only was the user allowed to customize outputs, they also could configure the programs to their specific needs.
The main development in the 1980s was the introduction of decentralized computing. Instead of having one large mainframe computer for the entire enterprise, numerous PCs were spread around the organization. This meant that instead of submitting a job to the computer department for batch processing and waiting for the experts to perform the procedure, each user had their own computer that they could customize for their own purposes. Many poor souls fought with the vagaries of DOS protocols, BIOS functions, and DOS batch programming.
As people became comfortable with their new skills, they discovered all the things their system was capable of. Computers, instead of creating a paperless society, as was expected, produced mountains of paper, most of it valueless. This information overload was mitigated somewhat in the 1980s with the introduction of executive information systems. They streamlined the process, giving the executive exactly what they wanted, and only what they wanted.
The 1980s also saw the first commercial application of artificial intelligence techniques in the form of expert systems. These programs could give advice within a very limited subject area. The promise of decision making support, first attempted in management information systems back in the 1960s, had step-by-step, come to fruition.
The 1990s saw the introduction of strategic information systems. This was largely because of developments in the subject of strategic management by scholars like M. Porter, T Peters, J. Reise, C. Markides, and J. Barney in the 1980s. Competitive advantage became a hot management topic and software developers were happy to provide the tools.
Applications
There are theoretical possibilities of building such systems in any knowledge domain.
One 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.
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. DSS has endless possibilities that can be used anywhere and anytime, for its decision making needs.
Zarfishan Batool
Dept. of Computer Science
University Of Karachi
Pakistan
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