At a minimum, compliance decision support systems should include word processing, database, spreadsheet, and modeling capabilities. Of these capabilities, modeling is crucial to reducing response uncertainty regarding circumstances that require a compliance decision. Rudimentarily, a model is comprised of variables and objectives; where the structure must reflect the purpose for construction. The variables in a quantitative model constitute a mathematical description of the relation between elements that can be classified as: decision, intermediate, or output variables. Decision variables are controlled by the decision maker and vary in accordance with the alternative selected. Whereas, intermediate variables link decisions to outcomes; thus functioning as consolidation variables. Lastly, output variables measure decision performance, and are referred to as ‘attributes’.
“View Part I of the Compliance through Automation: Decision Support Systems series here“