Decision Support Systems

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Many businesses are faced with situations that need critical analysis, compilation of raw data, circulation of precise documents and effective utilization of computer systems. Frito Lay is an example of a company who implemented various decision support systems (DSS) into their business model. A DSS is a “highly flexible and interactive IT system that is designed to support decision making when the problem is not structured.” (Haag, Cummins p.162) Managers require information to guide their organization in the right direction. DSS increases productivity, efficiency, and enhances understanding of business processes. DSS helped carve their business success, facilitate management making qualitative decisions, and turned their raw data into valued information that was needed by employees and management. DSS assist the management and employees of Frito-Lay by delivering statistical and data retrieving systems. Employees of Frito-Lay also used DSS systems in searching information that was germane to their job function. The three main components of a DSS are model management, data management and interface management. “The model requests the information from the data management component, analyzes the information, and sends the results to the user interface management component, which in turn passes the results back,” (Haag, Cummins p.163) to the user.

There are many types of DSS systems and hybrid DSS systems. Four DSS systems that could be implemented in a business are communication driven, knowledge driven , data driven , and document driven . Hybrid DSS systems are computerized systems that take advantage of combined DSS systems. A DSS may present information graphically and may include an expert system or artificial intelligence (AI). Examples of the information a decision support application might gather and present are the following: “(a) Accessing all information assets, including legacy and relational data sources; (b) Comparative data figures; (c) Projected figures based on new data or assumptions; (d) Consequences of different decision alternatives, given past experience in a specific context.”(Power, D. 2009)

The communication driven DSS is designed to give internal teams and partners communication capabilities. “Its purpose are to help conduct a meeting, or for users to collaborate. The most common technology used to deploy the DSS is a web or client server.”(Power,D. 2009) Examples of communication driven DSS include chats and instant messaging software, online collaboration and net-meeting systems. Also, technologies “including LANs, WANs, Internet, ISDN, and Virtual Private Networks,” (Power,D. 2006) can be employed within an organization.

Knowledge based DSS is specially designed to create a 'knowledgebase' for employees or external partners. “The knowledge component consists of one or more expert (or other intelligent) systems or it draws expertise from the organizational knowledge base.” (Turban et al, 486) Unlike communication driven DSS, knowledge based DSS is not created exclusively for communication purposes. However, this complex DSS system provides technical and complex answers to real life business problems.

Data-driven DSS is dissimilar to a knowledge based DSS, but emphasizes access and manipulation of integral internal company data and external data. Data is used to query a data base or data warehouse, and is “deployed via a main frame system, client/server link, or via the web.” (Power,D. 2006) An example of data-driven DSS is Geographic Information System (GIS). A Graphical Information System “is a decision support system designed specifically to analyze spatial information.” (Haag, Cummings. P.166) The graphical data demonstrated by the GIS is used to analyze roads, sewer systems, paths of hurricanes, free ways, traffic, or any graphical data that can be statistically represented.

Document-driven DSS is also dissimilar to the other 3...
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