Data-Driven Towards the Future - Tapping Innovative Data Sources for Technology Foresight
Project Description
Data-driven foresight is a specialized discipline within strategic and technological foresight that leverages diverse data sources from different perspectives and applies big data analytics to identify emerging (technology) trends at an early stage. The goal is to support companies and their decision-makers in anticipating future developments and preparing proactively for expected change based on data-driven insights. At the heart of this approach lies the identification of young, promising fields of innovation – areas in which technology-leading companies can still seize first-mover advantages, gain competitive edge, and help shape the future. While scientific
publications and patents have long been established as valuable yet traditional data sources for such (technology) trend studies, more unconventional semi-structured data sources – such as online job postings – also hold great potential for data-based trend detection. This project builds on insights gained from the project leader’s ongoing doctoral research on the use of online job postings data for strategic and technological foresight and further investigates their
versatile application possibilities in corporate futurology
publications and patents have long been established as valuable yet traditional data sources for such (technology) trend studies, more unconventional semi-structured data sources – such as online job postings – also hold great potential for data-based trend detection. This project builds on insights gained from the project leader’s ongoing doctoral research on the use of online job postings data for strategic and technological foresight and further investigates their
versatile application possibilities in corporate futurology
Relevance to Liechtenstein
The proposed Young Talents project and its associated research offer the Principality of Liechtenstein the opportunity to gain visibility in the international scientific foresight discourse, while also enabling local companies to benefit from knowledge exchange and transfer in this area. The trend studies planned within the project are of particular relevance to the country and its economic stakeholders, as topics such as AI technologies and labor market developments, but also big data analyses of unconventional data sources, affect all sectors of Liechtenstein's economy and are of strategic interest to innovation-leading companies. Job posting analyses on future-oriented research questions with an explicit reference to Liechtenstein are planned for the proposed project and can provide valuable insights into current (technology) trend developments relevant to the local business environment.
Scientific, Economic and Societal Impact
The application relevance for business practice in general lies in the direct applicability of the project's findings in relation to data-driven foresight. In this regard, there is a constant need for further professional training on new foresight data sources, innovative methodologies, and their integration into established foresight processes, as the continuous exchange with regional industry representatives shows. Additionally, the practical relevance is also evident in the cooperation with the Fraunhofer Institute for Technological Trend Analysis (INT), which, as part of the Fraunhofer-Gesellschaft, is strongly focusing on application-oriented research and from which the Principality of Liechtenstein can also benefit through cross-border cooperation.
