Three years ago, the impending natural gas shortage (Ukraine war) demonstrated how challenging it is to plan economic control measures (e.g. prescribed allocation of scarce natural gas to individual companies) without being able to forecast the resulting supply chain disruptions. Shortly after the COVID-19 pandemic, the potential threat of supply chain disruptions to the basic supply of the population – especially food – was once again clearly illustrated. In order to ensure Austria’s food supply security in the event of a crisis:
the affected companies must react as quickly as possible to supply chain disruptions (e.g. replace failed suppliers or missing employees, ensure transport capacities),
the responsible public institutions must intervene by providing support (e.g. keep border crossings open, provide additional logistics and labour) or control measures (e.g. decide on resource allocations).
In SYRI-Alert, we are developing a data-driven early warning system that can alert the responsible public authorities and companies to emerging threats at an early stage and forecast the resulting supply chain disruptions in the event of a crisis. The early warning system should enable public authorities to assess more quickly whether a crisis will trigger disruptions to the food supply chain, whether control measures are necessary and how these can be organised. At the same time, an early warning system enables companies to react more quickly to supply chain disruptions. This leads to a more dynamic restructuring of the food supply chain, which increases resilience and reduces supply chain disruptions. Market interventions can thus be minimised, while public institutions are equipped with a system-wide overview.

Scientifically, the early warning system is based on alerting companies to impending disruptions using non-accessible information about the state of their upstream supply chain through an intuitive and data-secrecy preserving “traffic light system”. The supply chain traffic light system (green = no interruption expected, orange = interruption possible, red = interruption imminent) is based on supply chain interruption forecasts from a cutting edge supply chain simulation model that is calibrated to daily data collected from the Austrian food supply chain. In order to recognise crises at an early stage, the early warning system can identify and classify threat scenarios for (inter)national supply chains early and systematically with the help of web scraping and natural language processing (NLP).
To this end, SYRI-Alert will overhaul the within Europe unique database and server infrastructure for the digital recording of product flows and stocks of crisis-relevant foodstuffs at article level (2/3 market coverage) that was developed in the FFG KIRAS project SYRI. The data collection and model development is only possible thanks to the unique interdisciplinary project consortium, consisting of the internationally leading research institutions CSH (simulation of supply chain disruptions), ASCII (data generation for identifying supply chain dependencies), FHOÖ (real-time visualisation of supply chains), WU (legal implications of digitalisation), AGES (networks of primary production), the key companies in the food supply chain, and the stakeholder ministries BML and BMAW, as well as AMA.
SYRI-Alert is intended to increase the resilience of the Austrian food supply chain by visualising (potential) disruptions in order to reduce food shortages in the event of a crisis and contribute to a significant improvement of our national food supply security. In this way, SYRI-Alert can make a decisive difference in terms of food supply security in the next crisis.