The higher levels of abstraction. These techniques are

The setting is a competitive knowledge-rich world in which managers make decisions about what to do with their organizations’ resources.

Multitudes of decisions are made every day and range from those that are simple to those that are very complex. Every one of these decisions involves the use of knowledge of varying kinds and amounts, and many of them can benefit from the use of technology known as decision support systems. Management Science has developed mathematical models for use in DSS and provided evidence on the advantages of modeling in problem solving. Cognitive Science, especially Behavioral Decision Making Research has provided descriptive information that has assisted in DSS design and has generated hypotheses for DSS research. The following are some of the key characteristics of a DSS: a. Special purpose systems designed to solve recurring problems. b.

Support for semi-structured problems. c. Provides Decision Analysis Tools. d.

Allows user to examine alternative solutions. 2. Expert systems:Conventional programming languages, such as FORTRAN and C, are designed and optimized for the procedural manipulation of data (such as numbers and arrays). Humans, however, often solve complex problems using very abstract, symbolic approaches, which are not well suited for implementation in conventional languages. Although abstract information can be modeled in these languages, considerable programming effort is required to transform the information to a format usable with procedural programming paradigms.

One of the results of research in the area of Artificial Intelligence (AI) has been the development of techniques that allow the modeling of information at higher levels of abstraction. These techniques are embodied in languages or tools, which allow programs to be built that closely, resemble human logic in their implementation and are therefore easier to develop and maintain. These programs, which emulate human expertise in well-defined problem domains, are called expert systems.

The availability of expert system tools, such as CLIPS, has greedy reduced the effort and cost involved in developing an expert system. 3. Office automation systems:Office Automation is a core group of functionalities consisting of word processing, spreadsheet, presentation, office database, electronic forms, calendar/scheduler, electronic mail, web browser, virus scanner, backup utility, and operating system used to support day-to-day office operations. These generic software tools are used for general office functions not specific to any business area.

Other software such as collaborative groupware, file transfer, terminal emulation, etc., may be considered in the future as core component software. Office Automation is an extension of business tools available at the desktop to improve the flow of work and information. This extension relies upon a portion of shared resources such as networks, servers, end user devices, peripherals, and other utility applications to improve communication, automate business processes, speed of the flow of information, create a collaborative environment, and eliminate barriers (such as distance and time) to the access of information necessary to the business process. Office Automation tools are not specific to only one particular business area or are not an integral part of a business area application.

The following are some of the common usages of these systems within an organization. a. Develop Word Processing documents and facilitates Desktop Publishing. b.

Resource scheduling. c. Communication using Electronic/Voice Mail, Video-conferencing and Groupware.

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