summer school in futures studies: data-driven & statistical approaches

The Summer School in Futures Studies: Data-Driven & Statistical Approaches offers an intensive three-day introduction to the theories, methods, and practical tools used to explore and anticipate possible futures. The programme combines conceptual foundations with hands-on methodological training, guiding participants through the entire anticipatory process—from horizon scanning and the identification of key drivers to Delphi-based investigations, data clustering, and scenario development.
Designed for a multidisciplinary audience, the Summer School integrates quantitative, qualitative, and foresight approaches, with particular emphasis on how data can support structured foresight. Participants will engage with key methods such as the Delphi method, scenario development, data clustering, and introductory approaches to hybridising forecasting and foresight.
Throughout the programme, the Summer School highlights the importance of methodological rigour in contexts characterised by uncertainty, complexity, slow- and fast-moving variables, shocks, and emerging patterns. By the end of the three days, participants will have developed a solid understanding of the relationship between forecasting, foresight, and strategic decision-making, while acquiring practical skills to support anticipatory intelligence in research, policy, and organisational settings.