approach Prescriptive decision-making research focuses on how to make "optimal" decisions (based on the axioms of rationality), while descriptive decision-making research aims to explain how people actually make decisions (regardless of whether their decisions are "good" or optimal). Unsurprisingly, therefore, there are numerous situations in which decisions made by individuals depart markedly from the decisions that would be recommended by decision analysis. Some have criticized formal methods of decision analysis for allowing decision makers to avoid taking responsibility for their own decisions, and instead recommend reliance on intuition or "gut feelings". Moreover, for decisions that must be made under significant time pressure, it is not surprising that formal methods of decision analysis are of little use, with intuition and expertise becoming more important. However, when time permits, studies have demonstrated that quantitative algorithms for decision making can yield results that are superior to "unaided intuition". In addition, despite the known biases in the types of human judgments required for decision analysis, research has shown at least a modest benefit of training and feedback in reducing bias. Critics cite the phenomenon of paralysis by analysis as one possible consequence of over-reliance on decision analysis in organizations (the expense of decision analysis is in itself a factor in the analysis). However, strategies are available to reduce such risk. There is currently a great deal of interest in quantitative methods for decision making. However, many such methods depart from the axioms of decision analysis, and can therefore generate misleading recommendations under some circumstances, so are not truly prescriptive methods. Some of the most popular of such non-decision-analytic methods include fuzzy-set theory for the representation of uncertainties, and the analytic-hierarchy process for the representation of preferences or value judgments. While there may occasionally be justification for such methods in applications (e.g., based on ease of use), decision analysts would argue for multi-attribute utility theory as the gold standard to which other methods should be compared, based on its rigorous axiomatic basis. Although decision analysis has been frequently used in support of government decision making, it is important to note that the basic theory applies only to individual decision makers. There is unfortunately no axiomatic prescriptive theory comparable to decision analysis that is specifically designed for group or public-policy decisions. For more on this topic, see group decision-making for discussions of the behavioral issues involved in group decisions, and social choice theory for theoretical considerations