Naturalistic decision making through argumentation: Resolving labour disputes

Publisher: John Wiley & Sons Inc

E-ISSN: 2044-8325|88|2|364-381

ISSN: 0963-1798

Source: JOURNAL OF OCCUPATIONAL AND ORGANIZATIONAL PSYCHOLOGY, Vol.88, Iss.2, 2015-06, pp. : 364-381

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Abstract

Naturalistic decision making (NDM) research has been successful in describing fast, intuitive decision‐making by experts in complex, time‐pressured situations. However, less is known about how experts make naturalistic decisions when they think analytically. Previous research suggests that this process involves constructing a story of the situation to explain and simulate the consequences of decisions, but we hypothesize that explicit argumentation is valuable when it is necessary to demonstrate the accuracy of a decision and to explicitly resolve inconsistent and uncertain information. This study investigates analytic NDM by contrasting experts and novices resolving labour disputes. Fifty expert and novice labour officers resolved labour cases whilst thinking aloud. The verbal protocols were analysed using Toulmin's argument model. Expert decision‐makers made more accurate decisions, used more warrants (in other words, reasoned justifications) during the decision process, and increased use of warrants was associated with accurate decision‐making. In addition, a decision aid was developed in the form of a checklist that encouraged decision‐makers to explicitly consider components of the argument. This increased the frequency of warrants and the decision accuracy of both novice and expert decision‐makers. Together, these findings imply that accurate and expert analytic decision‐making in this domain involves a process of argumentation and in particular the use of explicit warrants linking evidence to conclusions.Practitioner pointsAnalytic naturalistic decision making in this domain involves argumentationSuperior decision accuracy arises from exploring more reasoned justificationsA checklist encouraging all components of the argument to be made explicit improves decision accuracy in both novice and expert decision‐makers.