Decision makers are often required to make decisions with incomplete information. In order to design decision support systems utilizing restrictiveness and guidance to assist decision makers in these situations, it is essential to understand how certain decision making strategies are affected by incomplete information. This talk investigates the role that heuristic strategies play in decision making under different conditions – paying particular attention to situations where information is lacking. The work seeks to understand, not how best to make decisions in these situations but given what psychology has revealed about the range of decision making strategies used by humans, what is the impact of this lack of information. Under what situations is it reasonable to expect that humans will use heuristics and make decisions with similar accuracy to more cognitively intensive strategies? The talk presents the results of a simulation measuring the accuracy and effort of take-the-best and Tallying alongside two analytic decision making strategies, weighted-additive and equal-weighting in scenarios with varying levels of total information, information imbalance, dispersion, and dominance. Implications for the design of decision support systems will be presented.