Decision Calculations

Basic involve ordering the importance of decision criteria and scoring various functions of the decision alternatives . In a nutshell, the score value combines the best available information and the user preference. The basic calculation is the total of all scores x weight.

Results are tallied in a score sheet, or weighted matrix. One example might be scoring the impacts of particular decision alternatives . Each option is listed in the vertical axis, and decision criteria is listed in the horizontal axis, opposite of each alternative. Each cell, or intersection, will contain the score. Complex models will depict the results graphically. The matrix is a method to quantify impacts wiht the best available knowledge. This scores or rankings can be derived from databases, models, and expert opinions.

Weighted matrixes add a third dimension. The user preferences determine weights of the alternatives. This is a type of "importance" ordering. Many weighting combinations are possible. Decision Making can be complex, and automated systems using this approach are said to use linear programming techniques to solve the answer or issue.

Weights are assigned using an important order. Options may be organized in an equal manner (simple list), or in hierarchical order, or groupings. An example might be economic, social, cultural or environmental groupings.

Steps in this process include defining the criteria, defining the options, setting the importance of the criteria and prioritizing the criteria. When results are obtained, the decision maker or team may adjust the ranking of criteria. At this point, sometimes an error or flaw in the decision calculation process becomes obvious. Adjustments may be needed to adjust score shapes. Additional criteria or options may be added for the decision calculations.

After this has been completed, a risk analysis may be performed to judge the viable alternatives. A group discussion may be held to discuss the outcomes. These two steps are common in any business or management type decision.

Common applications of such matrices, are choices between technology solutions, resource use planning, infrastructure evaluations, project selection and evaluation, selection of tenders, etc.