The usage of impact-based forecasting: a sensemaking approach

Project members: Kees Boersma, PhD and Sterre Bierens, MSc (Vrije Universiteit Amsterdam, ISR) and Marc van den Homberg, PhD (The Netherlands Red Cross) with students and partners.

Humanitarian Organisations are increasingly interested in the impacts of extreme events (such as typhoons, hurricanes and flooding) rather than in forecasting the hazard itself. Knowing the repercussion of natural hazards can help to prepare and mitigate their consequences. Therefore, the user needs change from a (meteorological) forecast towards impact-based forecasting. Currently there are impact-based forecasts that predict the effects of extreme weather. However, there are not many examples of operationalized impact-based forecasting systems. One example is the forecast-based financing (FbF) project of the Red Cross: 510, a programme that enables access to humanitarian funding for early action based on in-depth forecast information (‘big data’) and risk analysis. The goal of FbF is to anticipate disasters, prevent their impact, if possible, and reduce human suffering and losses by cash-transfer programmes. To make impact-based forecasts more functional it is essential to know what the local, decision maker’s information needs are, how they should be generated and how the communicated information is interpreted and enacted.

The objective of this project is to understand more thoroughly how communicated impact-based forecasts are made sense of by local organizations and potential affected communities receiving the forecasts. Sensemaking is the practice of explaining how individuals or communities perceive, understand and enact impact-based forecasting. The assumption is that when gaining insights in the sensemaking of generated and received data, actions can be better aligned to the local needs. Next to sensemaking we study how the collected and received data is translated into actual practices and by whom (ownership). This includes an understanding of the social-political context of the local community. Illuminating the action undertaken as an outcome of the impact-based data can result in an increased adequacy of impact-based forecasts.

Main research questions:

1. How can the information needs of local actors be integrated into impact-based forecasting in order to improve forecast based-emergency management?
2. How do the various stakeholders make sense of communicated data by FbF, and what are the consequences for the way the data is translated into concrete local practices?