A data-driven foresight differs from a vision in that its predictions are based on scientific findings on technology, demographics, regulations and much more. A promising approach for companies to proactively identify future competitive advantages is Data-Driven Foresight (DDF). By using different data sources from various perspectives, DDF can derive solid statements about trend-driven developments in the future.
As technology life cycles accelerate, industrial firms increasingly want to incorporate foresight activities into their Life Cycle Management to foster digital transformation.The researchers asked themselves: How do companies obtain their data for DDF in Life Cycle Management and what alternative data sources are recommended? Using a systematic literature review, they described the current data sources and classified them along the life cycle.
Twenty semi-structured expert interviews with practitioners from different types of companies show valid premises for data selection and for the practical implementation of DDF. Regarding this, a recognizable difference between technology leaders and followers exists, which opens another gap for future research.