Project overview
In an era of rising geopolitical instability, humanitarian supply chains face unprecedented uncertainty, demanding fast, effective decision-making under pressure. This research challenges the dominance of probabilistic, data-driven models in crisis response, proposing that non-probabilistic, instinctual decision-making—though often overlooked—can offer superior performance when data is scarce or unreliable. Using a mixed-methods approach that combines Bayesian modelling, simulations, and expert interviews, the study demonstrates the contextual advantages of intuitive strategies in humanitarian logistics. The findings have broad practical implications for sectors like defence and emergency healthcare, and call for a balanced, hybrid approach to decision-making that values both data and human judgment. Policy recommendations highlight the need for centralized command structures in scenarios requiring rapid instinctual responses, refining existing calls for flexibility in humanitarian operations. This work contributes to theory, practice, and policy by rethinking how decisions are made under extreme uncertainty.
