Tuesday, March 15, 2011

DECISION SUPPORT SYSTEMS (DSS)
A general decision system


  • Decision-support systems ("DSS") are specifically designed to help management make decisions in situations where there is uncertainty about the possible outcomes of those decisions.

  •  DSS comprise tools and techniques to help gather relevant information and analyse the options and alternatives.

  • DSS 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, personal knowledge, or business models to identify and solve problems and make decisions.
  • Typical information that a decision support application might gather and present are:
~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



TYPES OF DECISION SUPPORT SYSTEM MODELS


  • Decision Support Systems that just collect data and organize it effectively are usually called passive models. They do not suggest a specific decision, and they only reveal the data. An active decision support system actually processes data and explicitly shows solutions based upon that data. While there are many systems that can be active, many organizations would be hard pressed to put all their faith into a computer model without any human intervention.
  • A cooperative Decision Support System is when data is collected, analyzed, and then given to a human who helps the system revise or refine it. Here, both a human and computer component work together to come up with the best solution.
  • While the above DSS model considers the user’s relationship, another popular DSS model sees the mode of assistance as the underlying basis of the DSS model. This includes the Model Driven DSS, Communications Driven DSS, Data Driven DSS, Document Driven DSS, and Knowledge Driven DSS.


  • A Model Driven DSS is one in which decision makers use statistical simulations or financial models to come up with a solution or strategy. Though these decisions are based on models, they do not have to be overwhelmingly data intensive.

  • A Communications Driven DSS model is one in which many collaborate to come up with a series of decisions to set a solution or strategy in motion. This model can be in an office environment or on the web.
  • A Data Driven DSS model puts its emphasis on collected data that is then manipulated to fit the decision maker’s needs. This data can be internal or external and in a variety of formats. It is important that data is collected and categorized sequentially, for example daily sales, operating budgets from one quarter to the next, inventory over the previous year, etc.
  • A Document Driven DSS model uses a variety of documents such as text documents, spreadsheets, and database records to come up with decisions as well as further manipulate the information to refine strategies.
  • A Knowledge Driven DSS model uses special rules stored in a computer or used by a human to determine whether a decision should be made. For instance, many day traders see a stop loss limit as a knowledge driven DSS model. These rules or facts are used in order to make a decision.


In my opinion, decision support system enables the managers to respond quickly and make a good decision in order to be remain competitive with others companies and also market changes in this uncertain world.


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