Decision support systems constitute a class of computer-based information systems including knowledge-based systems that support decision-making activities.
Decision Support Systems (DSS) are a specific class of computerized information system that supports business and organizational decision-making activities. A properly-designed DSS is an interactive software-based system intended to help decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make decisions.
Typical information that a decision support application might gather and present would be:
an inventory of all of your current information assets (including legacy and relational data sources, cubes, data warehouses, and data marts),
comparative sales figures between one week and the next,
projected revenue figures based on new product sales assumptions;
the consequences of different decision alternatives, given past experience in a context that is described.
Classifying DSS
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 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: 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 agents technologies are called Intelligent Decision Support Systems (IDSS).
Benefits of DSS
Improves personal efficiency
Expedites problem solving
Facilitates interpersonal communication
Promotes learning or training
Increases organizational control
Generates new evidence in support of a decision
Creates a competitive advantage over competition
Encourages exploration and discovery on the part of the decision maker
Reveals new approaches to thinking about the problem space
(http://en.wikipedia.org/wiki/Decision_support_system)
Decision Support Systems (DSS) are a specific class of computerized information system that supports business and organizational decision-making activities. A properly-designed DSS is an interactive software-based system intended to help decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make decisions.
Typical information that a decision support application might gather and present would be:
an inventory of all of your current information assets (including legacy and relational data sources, cubes, data warehouses, and data marts),
comparative sales figures between one week and the next,
projected revenue figures based on new product sales assumptions;
the consequences of different decision alternatives, given past experience in a context that is described.
Classifying DSS
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 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: 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 agents technologies are called Intelligent Decision Support Systems (IDSS).
Benefits of DSS
Improves personal efficiency
Expedites problem solving
Facilitates interpersonal communication
Promotes learning or training
Increases organizational control
Generates new evidence in support of a decision
Creates a competitive advantage over competition
Encourages exploration and discovery on the part of the decision maker
Reveals new approaches to thinking about the problem space
(http://en.wikipedia.org/wiki/Decision_support_system)
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