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Frequently asked question (FAQ)
A decision support system (DSS) is a computerized program used to support determinations, judgments, and courses of action in an organization or a business. A DSS sifts through and analyzes massive amounts of data, compiling comprehensive information that can be used to solve problems and in decision-making.
At a fundamental level, the hope has always been that our information and decision support systems will help decision makers monitor events, and evaluate, choose and act on alternatives as events actually unfold.
Users including managers, staff, customers, the general public, and workers in business, government and not-for-profit organizations.
The rational, analytical decision-making approaches often thwarted by political and self-interest decision making.
In some cases, a DSS has little impact on decision outcomes, but it may have other desirable benefits like faster decision making or reduced training costs for new decision makers. Some DSS actually increase the likelihood targeted users will make "good" decisions.
Decision support (DSS) can improve strategic planning and strategic control. Many organizations have not defined performance objectives and that limits possibilities. Setting measurable performance objectives is the first step toward using information technology to improve implementation of strategic plans.
The computing technology for creating realistic visual simulations has improved tremendously in the past 20 years. Today, Internet-based multi-user visual simulations like Second Life (www.secondlife.com) are creating excitement and interest in the possibilities of virtual reality for entertainment, e-business and education. My experiences suggest the possibilities for decision support are also exciting.
YES. Decision support is not a cure-all or a panacea. Researchers and managers often focus too much on the anticipated positive consequences of using a specific Decision Support System (DSS). Using a computerized system to support decision making can have anticipated and unanticipated negative consequences.
Generally, decision support theory identified bureaucratic managers as the primary business decision makers who needed and wanted computerized decision support.
IBM is heavily promoting a cognitive system named Watson in television ads. A major selling point is that "IBM Watson thinks with us to help outthink competitors." This claim positions IBM Watson as a business decision support system. Has Watson advanced to the point where this claim of "help outthink competitors" is true?
We researched over 50 tools for climate change planning. Of those, 58% were designed primarily to inform and engage, 38% enabled scenario planning, while just 26% supported decision analysis—comparing, analyzing, and ranking decision alternatives. (These functions were not mutually exclusive.)
The Primary Advantage of a Decision Support Tool is its ability to promote coordination and collaboration across city departments, organizations, sectors, jurisdictions, regions, and countries. More than anything, effectively mitigating and adapting to the global impacts of climate change will require sharing information and collaborating on solutions at every level.
An expert system approach for this kind of DSS is possible to implement considering two factors. Firstly, Expert systems are good at encompassing judgment and 'rules of thumb'. Secondly, the ability of the program to explain how the system came to a certain conclusion.
DSS can help farmers to solve issues related to crop productivity. DSS can help in better water management and optimized irrigation. A French research institute, Irstea (http://www.irstea.fr/accueil), has developed a software called "Pilot" which is capable of estimating future yields of crops based on climate conditions and irrigation.