The Naturalistic Decision-Making process in big data environment: The case of a Police Information and Command Center (ICC)

Abstract

Naturalistic Decision-Making is a mainstream research paradigm to study decision-making
of experts confronted to dynamic and changing conditions, ill-defined goals and time
stress. For the last ten years, contributions encourage the analysis of human-technologyinteractions to refine our understanding of naturalistic decision-making. Drawing on this
perceptive, an inductive qualitative case study is completed to understand how experts police
officers in an Information and Command Center (ICC), facing with dynamic and changing
conditions, make decisions in big data environment. ICC daily produces an important
volume of varied and responsive data, which need to be verified. Police officers assemble
these data in situation, from unintegrated technologies. The case analysis shows two distinct
stages of decision-making process in big data environment: the upstream level of situational
awareness, complete or partial according to the circumstances, and the recognition process.
These results allow suggesting an integrated model of naturalistic decision-making, applied
to ICC Police officers in big data environment.