Decision Support System (DSS) – Components, Application

Understanding The Decision Support System (DSS) With the progress made in the fields of computer sciences & information technology, the big organizations are not far away from their technical advancements. We had read about Expert Systems earlier at Expert Systems.

Now, let us understand another very important Support System which are used by various MNC’s – The Decision Support System.

What is Decision Support System (DSS) ?

A Decision Support system is a Computer based Information System that supports organization decision making activities. DSS supports planning and decision making process in an organization. DSS collects information from various sources to serve the decision needs of the organization.

DSS basically collects data and shape data as per the requirements to produce meaningful decisions. DSS helps to solve unstructured problems and thus helps to improve quality of decision making. DSS acts differently with different things therefore there is no universally accepted definition of DSS.

The best thing about DSS is it supports human decision making rather than providing a means to replace them. DSS are easy to use and they don’t require intensive training, the user should only understand the problems well.

Characteristics of DSS:

  • DSS supports decision making.
  • DSS solves relatively unstructured problems.
  • DSS provides friendly Computer interface.
  • DSS are flexible & adaptable.
  • DSS are more user friendly and can also be used to solve structured problems.
  • DSS may update themselves as per the requirement and thus they are said to be extensive.

Components of DSS:

USER: The users of DSS are generally managers having an unstructured problem with not a very easy solution. Managers may be either at top level or middle level. DSS should provide managers with optimum solution.

DATABASES: In order to make appropriate decisions DSS require adequate information. The Information is stored in database. DSS includes both Routine & Non-Routine information from various sources. DSS gathers information from both Internal as well as External Databases.

External database may provide external information such as moves of Competitors, recent government policies, changing market conditions, Increasing or decreasing trend etc. Internal Database may provide internal information such as Raw material Consumption report, Daily Production Report, Debtors & creditors aging, etc.

PLANNING LANGUAGE: There are two types of planning languages used

General Purpose planning language: This language allows users to perform routine tasks such as retrieval of data.

Special Purpose planning language: They are limited in what they do, but they can do certain things better than General purpose planning language.

MODEL BASE:  Model Base refers to the brain of the DSS. The unstructured problem of the managers is handled over to the model base of DSS. Model base after performing various computations gives the fair decisions. There are various mathematical, financial, statistical functions stored in model base.

Application of DSS:

  • COST ACCOUNTING SYSTEM: Every organization requires reducing the cost of its operations and increasing both efficiency and profitability. DSS can help organizations in achieving the same.
  • CAPITAL BUDGETING SYSTEM: Every organization needs to ensure that they have taken appropriate investment decisions and their long term investment decisions will be beneficial for the organization.
  • BUDGET VARIANCE ANALYSIS: Variances determine the differences between standard performance required and actual performance of the organization. DSS helps organization to keep their actual performance far better than Standard performance required.

Advantages of DSS

  • DSS supports learning in an organization
  • DSS helps to improve thinking process in the organization
  • DSS solves unstructured problems and thus automates some part of managerial work.
  • DSS provides the organization a competitive edge which is much required.
  • Generates evidence in support of a decision.

Thus, DSS can be a great tool if operated efficiently.

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