System dynamics modeling of humanitarian relief operations: Balancing provision of relief and recovery with capacity building in humanitarian operations

Against the backdrop of over two hundred thousand people dead or missing and millions of people homeless after China's massive earthquake and Myanmar devastating cyclone, forecasts estimate that natural and man-made disasters are likely to increase five-fold both in number and impact over the next 50 years. Hence, the need for disaster relief provided by humanitarian organizations during disasters should continue to increase.

At the same time, humanitarian organizations face increased challenges scaling capacity, improving operational efficiency, reducing staff turnover, improving institutional learning, satisfying increasingly demanding donors, and operating in increasingly challenging environments, with poor or inexistent infrastructure, high demand uncertainty and little time to prepare and respond. To address such challenges, managers in humanitarian organizations must understand the complexity that characterizes humanitarian relief efforts to learn how to design and manage complex relief operations.

Yet, learning in such complex and ever changing environments is difficult precisely because managers seldom confront many of the consequences of their most important decisions. Effective learning in such environments requires methods and tools that allow managers to capture important feedback processes, accumulations, delays, and nonlinear relationships, visualizing complex systems in terms of the structures and policies that create dynamics and regulate performance. The system dynamics approach provides managers with a set of tools that can help them learn in complex environments. These tools include causal mapping, which enables managers to think systemically and to represent the dynamic complexity in a system of interest, and simulation modeling, which permits managers to assess the consequences of interactions among variables, experience the long-term side effects of decisions, systematically explore new strategies, and develop understanding of complex systems