Write short notes on Decision support systems

A Management Information System ICT Revision Questions and Answers

Decision support systems are computer-based information systems that provide interactive information support to managers and business professionals during the decision-making process. Decision support systems use:
• Analytical models
• Specialized databases
• Decision maker‘s own insights and judgments
• Interactive, computer-based modeling process to support the making of semistructured and unstructured business decisions

Decision support systems rely on model bases as well as databases as vital system resources. A DSS model base is a software component that consists of models used in computational and analytical routines that mathematically express relationships among variables. Examples include:
• Spreadsheet models
• Linear programming models
• Multiple regression forecasting models
• Capital budgeting present value models

Typically, a manager uses a DSS software package at his workstation to make inquiries, responses and to issue commands. This differs from the demand responses of information reporting systems, since managers are not demanding pre-specified information. Rather, they are exploring possible alternatives. They do not have to specify their information needs in advance. Instead they use the DSS to find the information they need to help them make a decision.

Using a DSS involves four basic types of analytical modelling activities:
• What-If Analysis: – In what-if analysis, an end user makes changes to variables, or relationships among variables, and observes the resulting changes in the values of other variables.
• Sensitivity Analysis: – Is a special case of what-if analysis. Typically, the value of only one variable is changed repeatedly, and the resulting changes on other variables are observed. So sensitivity analysis is really a case of what-if analysis involving repeated changes to only one variable at a time. Typically, sensitivity analysis is used when decision-makers are uncertain about the assumptions made in estimating the value of certain key variables.
• Goal-Seeking Analysis: – Reverses the direction of the analysis done in what-if and sensitivity analysis. Instead of observing how changes in a variable affect other variables, goal-seeking analysis sets a target value for a variable and then repeatedly changes other variables until the target value is achieved.

• Optimization Analysis: – Is a more complex extension of goal-seeking analysis. Instead of setting a specific target value for a variable, the goal is to find the optimum value for one or more target variables, given certain constraints. Then one or more other variables are changed repeatedly, subject to the specified constraints, until the best values for the target variables are discovered.



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