Incomplete Objectives in Decision Making: How Omitting Objectives Affects Identifying the Most Promising Alternative

Abstract Research has shown that decision-makers omit a significant number of their objectives when making a decision. This study examines the consequences of incomplete objectives on decision making, i.e., how does omitting objectives affect identifying the most promising alternative? We investigate this question using a dataset of 945 observed decisions. These decisions were developed by students using the decision-skills and training tool entscheidungsnavi.com. The tool guides students in a step-by-step process based on value-focused thinking, multi-attribute utility theory, and debiasing methods. Results show that omitting objectives significantly reduces the chances of identifying the most promising alternative. Hence, neglecting only 20% of the objectives is sufficient to mislead more than one in four decisions. We have found three factors that influence this risk of misidentifying the most promising alternative: (1) the weight of the omitted objectives; (2) the consensus on the best alternative across all objectives; and (3) the consensus on the ranking of all alternatives across all objectives.