Using analytical methods for scarce and uncertain data of humanitarian organizations

Recent research by the Zero Hunger Lab is oriented towards improving humanitarian operations worldwide through innovative network optimization methods. Valentijn Stienen’s PhD research concentrates on finding effective solutions to challenges faced by organizations involved in humanitarian aid, such as the United Nations Human Response Depot (UNHRD), Red Cross 510, PemPem, and the World Bank.

In his research, that links up with the UN’s Sustainable Development Goals (SDGs), Stienen identifies the challenges of data scarcity and uncertainty within humanitarian organizations. By developing new analytical methods and using scarce internal data supplemented by public data sources, Stienen has developed solutions for optimizing the numbers and locations of humanitarian response depots, finding optimal locations for water wells, and improving information on digital road networks by means of GPS trajectory data. Accurate information on road conditions is important for optimizing different decisions, for instance, on routing or allocation of resources.

Addressing the situation as a mathematical optimization problem

“My study is, among other things, about emergency relief, which mostly involves international organizations providing relief supplies to disaster areas. This includes tents, water, food, and hygiene kits. Humanitarian organizations often pre-position their stocks in humanitarian response depots. When disaster hits, they can get the supplies to the people who need them as quickly as possible. To make such a logistic process as efficient as possible, we try to find optimal locations for such depots. We first formulate the situation as a mathematical optimization problem with functions and equations. We then solve that problem by means of a computer model and then translate it back into a real scenario.”

Using public data

Stienen: “Combining internally collected data with public data sets can help address the challenges of data scarcity and improve decision-making. Two examples of public data sets used in my study include OpenStreetMap, which is used to retrieve information on roads, and Sentinel satellite information, which is used to compare satellite pictures of roads to estimate the average travel speed on those roads. Using public data is important to enhance the scarce and uncertain data of humanitarian organizations and solve large-scale analytical problems.”

Impact and future applications

“With this research, we want to improve the efficiency and effectiveness of humanitarian operations, taking data scarcity and uncertainty into account,” Stienen states. "Our findings offer valuable insights for humanitarian organizations and can have a positive impact on the way in which they provide aid to vulnerable communities worldwide. For instance, adding one response depot to the existing network of a humanitarian organization can save 33% of transport costs with the same maximal response time."

The research highlights the crucial role of scientific research in enhancing humanitarian operations and improving lives across the world. Stienen: “By looking at the objectives of the humanitarian organizations and the relevant restrictions, we can make a model that is as realistic as possible so the results can often be applied immediately.”