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. Introduction to Decision Support System

 A brief history of Decision Support Systems

Decision Support Systems have evolved over the past three decades from simple model-oriented systems to advanced multi-function entities. During the 1960’s, most Decision Support Systems were fairly based on powerful (and expensive) mainframe computers which provided managers with structured, periodic reports. MIS theory developments during the 1970’s saw Decision Support Systems evolve into more elaborate computer-based systems that supported production, promotion, pricing, marketing and some logistical functions. By early 1980’s Decision Support Systems enjoyed more interests from academics and the framework for Decision Support Systems was greatly expanded by the end of the decade. It was only during the 1990’s that a paradigm shift occurred in Decision Support Systems and more complex systems, which incorporated, advanced database technology and client/server capabilities, were emerging from many areas in business processes. As many organizations started to upgrade their network infrastructure, object oriented technology and data warehousing started to make its mark on Decision Support Systems. The rapid expansion of the Internet provided additional opportunities for the scope of Decision Support Systems and consequently many new innovative systems such as OLAP and other web-drive systems were developed.

1.2 Systems definition 

According to Sprague and Watson (1996) conceptual models or frameworks are crucial to understanding a new and/or complex system. They define DSS broadly as an interactive computer based system that help decision-makers use data and models to solve ill-structured, unstructured or semi-structured problems.

DSS provides varying analysis without much programming effort and is usually directed towards non-technical users/managers. Managers main uses for a DSS includes searching, retrieving and analyzing decision relevant data to allow them to summarize main points which assist them in making more informed and educated decisions. Users often search for correlations between data without rewriting the underlying MIS or software application and most DSS allows graphic capabilities, which not only allows trend analysis and reporting for top executives, but also assists managers in mapping out conjoint analysis and alternative scenarios to answer “what if” queries. Consequently, DSS supports both tactical and strategic decisions and are employed to leverage manager’s expertise in a certain field.

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