Decision Support System | What is Decision Support System | Decision Management System | Decision Support System Example | Decision Support Systems for Business Intelligence
A decision support system (DSS) is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization (usually mid and higher management) and help people make decisions about problems that may be rapidly changing and not easily specified in advance—i.e. Unstructured and Semi-Structured decision problems. Decision support systems can be either fully computerized, human-powered or a combination of both.
While academics have perceived DSS as a tool to support the decision-making process, DSS users see DSS as a tool to facilitate organizational processes. Some authors have extended the definition of DSS to include any system that might support decision-making and some DSS include a decision-making software component; Sprague (1980)defines a properly termed DSS as follows:
- DSS tends to be aimed at the less well structured, underspecified problem that upper-level managers typically face;
- DSS attempts to combine the use of models or analytic techniques with traditional data access and retrieval functions;
- DSS specifically focuses on features which make them easy to use by non-computer-proficient people in an interactive mode; and
- DSS emphasizes flexibility and adaptability to accommodate changes in the environment and the decision-making approach of the user.
DSSs include knowledge-based systems. A properly designed DSS is an interactive software-based system intended to help decision makers compile useful information from a combination of raw data, documents, and personal knowledge, or business models to identify and solve problems and make decisions.
Typical information that a decision support application might gather and present includes:
- inventories of information assets (including legacy and relational data sources, cubes, data warehouses, and data marts),
- comparative sales figures between one period and the next,
- projected revenue figures based on product sales assumptions.
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