For the Center for Development Research (ZEF) at the University of Bonn, Forsit developed a data-driven early warning platform to identify global risks in the area of food and nutrition security. The goal was to translate scientifically grounded indicators into a web-based system that provides decision-makers at international and national levels with up-to-date risk assessments.

At the core of the platform is a multi-level indicator system that visualises risks using a clearly defined traffic light model. Four central modules – price volatility, price transmission, global supply risks, and a news/hotspot tool – aggregate international data sources and calculate global as well as country-specific risk levels. Data processing is fully automated: external data is imported, processed through analytical programmes, and the results are stored and visualised in a structured manner.

Interactive world maps, time sliders, and country-specific detail pages provide access to current and historical risk values. In addition, the platform makes calculated data available via an API in machine-readable form and automatically generates alert notifications via social channels when risk levels rise.

The result is a modular, scalable web infrastructure that translates complex scientific calculation models into a user-friendly, transparent, and operationally deployable early warning system.