ABSTRACT
Most sciences begin in an observe-and-describe mode (e.g., biological taxonomies, early chemistry, etc.). Mechanistic explanations, prediction, and control follow later. Thus, Naturalistic Decision Making (NDM) research has described the problem and decision makers' strategies and responses. Many readers are familiar with some of the "classic" NDM stories, such as the rescue team leader who used mental simulation to solve the problem of how to successfully use a harness (Klein, 1998) and the fire ground commander who recognized the laundry chute fire had spread (Klein, 1993). These decision makers in the field used recognition and mental simulation to evaluate their options, not elimination-by-aspect (Tversky, 1972) or anchoring-and-adjustment (Einhorn & Hogarth, 1985). These are the stories that led researchers away from the normative and descriptive models of classical decision-making research. Now is the time to dig deeper in the existing data and to collect new data that support the more detailed analysis characteristic of more mature science.
