The Best Thinking in Business Analytics from the Decision Sciences Institute

3. De-Bias Techniques for Better Decision Quality

—LeeAnn Kung, Rowan University

—Dianne Hall, Auburn University

—Hsiang-Jui Kung, Georgia Southern University

Abstract

This paper analyzes the effects of data presentation on decision making using probabilistic data. It is well documented in the decision sciences literature that humans have difficulty intuitively assessing probabilistic data to make sound decisions. It is also known that decision makers are influenced by how data is presented. This paper presents a model of how decision makers are subject to anchoring effects when presented with probabilistic data. We then test various techniques to mitigate the anchoring bias. We found that providing domain knowledge (i.e., a formula to guide ...