Perilous Decisions Humanitarian Security and Risk Management in a Complex World

For the past 20 years, attacks against humanitarian staff have drawn increasing attention in the media and among academics and practitioners. Recently, high profile attacks against organizations such as Médecins Sans Frontières in Syria and Afghanistan have underscored the insecurity confronting humanitarian organizations. While most attention has focused on how external actors have increasingly targeted humanitarian organizations, few studies have examined the security decision-making processes within organizations. This research addresses the gap in the literature on humanitarian security decision-making by focusing on the internal dynamics that influence security related decisions. The research develops and applies the Organizational Security Risk Management Model based on theories of organizational decision-making in order to assess how certain behavioral and organizational characteristics influence decisions related to security management. The research identifies individual factors that seem to affect decision-makers’ perceptions and framing of security issues and describes and explains how organizations categorize and manage risk. The results indicate that organizational characteristics (funding source, size, structure, and mandate) affect strategic, tactical, and operational decisions such as the rigidity of policies, the role of the security manager or advisor, and level of autonomy in the field. Furthermore, the results indicate that decision-makers (security managers and advisors) often share similar backgrounds, such as exposure to a natural or manmade disaster as well as some affiliation with the United Nations, which likely shaped their views on security management. The results also suggest that organizations use similar processes to assess risks, but decisions to mitigate the various risks can transfer those risks recipients and local partners. The results also show how organizations in differing situations with varying levels of complexity can arrive at similar decisions