In the course of disruptive political, economic or social crisis events, it may be necessary for those ministries with economic governance competencies (BMAW, BML and BMK) as well as provinces and municipalities to fulfil their legal duty and implement economic governance measures in their respective areas of responsibility. The experience of fighting the pandemic has shown obvious vulnerabilities here:

• Departments lack sufficiently detailed market information of critical goods and services as well as the respective supply chains behind them for the development of accurate measures.
• Beyond the identification of critical infrastructure operators, there is no sufficient definition of system- or supply-relevant companies that can be selectively supported by the public administration in their resilience in crisis situations. The NIS2 Directive of the European Union addresses this problem, but it is necessary to transfer and detail these approaches to the Austrian situation.
• There is a need for coordinated and accepted concepts on system- or supply-relevant goods, services or raw materials and their compositions, especially dependencies, preconditions, alternatives, and cascade effects.
• Analysis of the control potential of available, derivable, and usable data for setting administrative and political decisions.
• Early recognition of shortage situations already based on the data and possible combinations to increase the efficiency of any countermeasures.

The project picks up on the current efforts in the BMAW to establish a conceptual data-driven shortage radar and addresses closing the identified data gap. Through the open and transparent design of a possible dynamic data architecture, the economic steering measures can be evidence-based, whereby their effects over the term should in turn be reflected in the data. The population will be informed about possible restrictive measures in the crisis situation and will be able to verify the effects.

The project first analyses the current pain points of the demand side in economic crisis situations and highlights in particular the generalized supply chain risks. This is followed by a comprehensive data identification and analysis (critical goods and services, system- and supply-relevant companies, etc.) in order to identify possible relevant structured information that is essential for steering decisions. However, the project will avoid collecting specific data from value networks on specific products or services. A conceptual data model will then be developed that can be the starting point for novel technological approaches – such as artificial intelligence, network analysis methods and anomaly detection. The data model will not be complete and comprehensive, but future data requirements can be formulated, which in their overall representation can represent a sufficient data basis. This data model will be subject to interactions, for example with regard to data management, access permissions, monitoring, information security as well as the actors involved. A legal analysis to ensure societal, social and cultural interests as well as the exemplary construction of a demonstrator round off the research project.

• Partner: AIT Austrian Institute of Technology GmbH (Koordinator), Bundeskanzleramt
• Projektlaufzeit: 11/2013 – 10/2025
• Förderprogramm: KIRAS Sicherheitsforschung – Auschreibung 2022/2023, 3.1.1 Datengetriebener Mangelradar für die wirtschaftliche Krisenvorsorge