Learning under Uncertainty: Networks in Crisis Management

TLDR

Learning in crisis networks faces fundamental difficulties. The article investigates how networks learn under high uncertainty. The study analyzes a crisis response network for an exotic animal disease outbreak, detailing how it learned structural frameworks, roles, and problem‑solving through virtual learning, forums, past experience, information systems, and peer exchange. The network’s use of standard operating procedures and a command‑control structure reduced institutional and strategic uncertainty.

Abstract

This article examines learning in networks dealing with conditions of high uncertainty. The author examines the case of a crisis response network dealing with an exotic animal disease outbreak. The article identifies the basic difficulties of learning under crisis conditions. The network had to learn most of the elements taken for granted in more mature structural forms—the nature of the structural framework in which it was working, how to adapt that framework, the role and actions appropriate for each individual, and how to deal with unanticipated problems. The network pursued this learning in a variety of ways, including virtual learning, learning forums, learning from the past, using information systems and learning from other network members. Most critically, the network used standard operating procedures to provide a form of network memory and a command and control structure to reduce the institutional and strategic uncertainty inherent in networks.