The ENRESFOOD project aims to develop the user-friendly ENRESFOOD Dashboard that allows a) early identification of intentional and unintentional food safety and security threats through the use of drivers of change and related indicators, and b) actors in the chain to interact with each other to evaluate potential response and adaptation measures, and identify their possible trade-offs and conflicts for further discussion. The Dashboard shows information and data in a clear and visual way (like charts or alerts), so users can quickly understand what's happening and make decisions. It has an underlying Platform, enabling user interaction (via the Dashboard as front-end) through the linking of models, tools, and data. The Dashboard is designed, tested and validated in interaction with the intended users — risk managers, risk assessors and private actors of the food system — whose involvement ensures uptake after the project and ultimately increases the resilience of the food system to intentional and unintentional food safety and security threats.

The project applies a 5-step resilience concept: (1) early identification of a potential threat, (2) reducing its impact on system performance, (3) returning to normal system performance, (4) learning from the past, and (5) adaptation to the new situation. It combines multiple data sources (EFSA official data, open databases like Eurostat, internet data) with artificial intelligence and modelling, applied to two use cases: an unintentional safety contamination (mycotoxins) in the wheat supply chain and an intentional contamination (food fraud or terrorist attack) of the dairy/baby powder supply chain. Monte Carlo simulation and multi-criteria decision analyses evaluate potential resilience measures across cost, ease of implementation, effectiveness, and consumer acceptance. The project uses a multi-actor, co-creation approach to involve public and private stakeholders throughout, ensuring adoption of the Dashboard during and after the project.