Decision Support Systems for Prescriptive Knowledge Management
Decision Support Systems (DSSs) help managers make decisions in situations where human judgment is an important contributor to the problem-solving process, but where limitations in human information processing impede decision making. The goal of a DSS is to amplify the power of the decision makers without usurping their right to use human judgment and make choices. DSSs attempt to bring together the intellectual flexibility and imagination of humans with the speed, accuracy, consistency, and tirelessness of the computer (
DSSs may contain a number of subsystems, each with a specific task (see figure below). The first, and most important, is the subsystem composed of the decision maker(s). Decision makers are consciously diagrammed as part of the DSS because without their guidance, there is no DSS. The group negotiation management subsystem helps decision makers organize their ideas, formulate relationships surrounding issues and arguments, and refine their understanding of the problem and their own value systems. Examples of group negotiation tools include: the active response geographic information system (AR/GIS) and the issue-based information system (IBIS). Group negotiation tools are used to construct issue-based argument structures to clarify the values and preferences of group members in the attempt to reach group consensus. For example, IBIS uses formal argument logic (the logic of questions and answers) as a way to diagram and elucidate argumentative thinking. By asking and answering crucial questions, you can begin to better understand the problem and its solution set.
DSSs should specifically employ mechanisms by which the biological realities guide and, if appropriate, constrain the desires of the stakeholders. For example, compromise is not acceptable for some issues. If the productive capacity of an ecosystem is fixed, yet key stakeholders all want to extract a product from that ecosystem at a higher level, a compromise midway between the levels will be unsustainable.
The next major subsystem, spatial and non-spatial data management, organizes the available descriptions of the ecological and management components of natural resource management. Data must be available to support choices among alternative management scenarios and to forecast consequences of management activities on the landscape. There is a trade-off between an increasing number of goals that decision makers and stakeholders value and the high cost of obtaining data and understanding relationships that support these choices. Monitoring both natural and anthropogenic disturbance activities and disturbance-free dynamics of managed forest ecosystems are also extremely important if a DSS is to accurately portray the decision choices and their consequences. Barring blind luck, the quality of the decision cannot be better than the quality of the knowledge behind it. Poor data can lead to poor decisions. It is difficult to conceive of prudent natural resource management without an adequate biophysical description of the land base in question.
The next three subsystems—hypertext, knowledge-base, and simulation model management—deal with effectively managing knowledge in the many diverse forms in which it is stored, represented, or coded. These systems are covered in more detail in other pages. The simulation model management subsystem of the DSS is designed to provide a consistent framework into which models of many different origins and styles can be placed so that decision makers can use them to analyze, forecast, and understand elements of the decision process. The knowledge management subsystem of the DSS is designed to organize all available knowledge-based models in a uniform framework to support the decision-making process.
The software subsystems of a DSS, mentioned so far, help decision makers organize the decision problem, formulate alternatives, and analyze their future consequences. The decision methods management subsystem provides tools and guidance for choosing among the alternatives, for performing sensitivity analysis to identify the power of specific variables to change the rank of alternatives, and for recording the decisions made and their rationale.
There are many facets or dimensions that influence the decision-making process. The rational/technical dimension, which concerns itself with the mathematical formulation of the methods of choice and their uses, is the one most often encountered in the decision science literature. But there are others, including the political/power dimension and the value/ethical dimension.Decision makers might find themselves at any point along the political/power dimension bounded by a dictatorship (one person decides) on the one extreme and by anarchy (no one can decide) on the other. Intermediate positions are democracy (majority decides), republicanism (selected representatives decide), and technocracy/aristocracy (experts or members of a ruling class decide). Currently three approaches seem to be in use at multiple societal, temporal ,and spatial scales: management by experts (technocracy), management by legal prescription (republicanism), and management by collaboration (democracy). No one approach predominates. In fact, the sharing of power between these three approaches creates tensions which help make natural resource management a very difficult problem. In the context of natural resource management, the value/ethical dimension might be defined on the one extreme by the preservationist ethic (reduce consumption and let nature take its course) and on the other by the exploitation ethic (maximum yield now and let future generations take care of themselves). Various forms of the conservation ethic (use resources, but use them wisely) could be defined between these two extremes. The rational/technological dimension is defined by the normative/rational methods on the one hand and the expert/intuitive methods on the other. Numerous intermediate methods also have been described and used. The formal relationships between these dimensions affecting the decision process have not been worked out.
Informally, it is easy to observe decision-making situations where the political/power or value/ethical dimensions dominate the rational/technical dimension. Choosing an appropriate decision-making method is itself a formidable task that influences both the design of alternatives and the final choice. Many DSSs do not offer a decision methods subsystem due to the complexity and sensitivity of the subject matter. Unfortunately, providing no formal support in DSSs for choosing among alternatives simply places all the burden on the users and may make them more vulnerable to challenges of their process and choice mechanisms.
Encyclopedia ID: p1642
