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Abstract: Discontinuities in the market create space for disruptive business opportunities. 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 trenddriven developments in the future. As technology life cycles accelerate, industrial firms increasingly want to incorporate foresight activities into their Life Cycle Management. This raises the following research question: How do companies obtain their data for DDF in Life Cycle Management and what alternative data sources are recommended? By conducting a systematic literature review the state-of-the-art data sources are described and classified along the life cycle. Twenty semi-structured expert interviews with practitioners from industrial firms and consultancies 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.
Keywords: data-driven foresight; trends research; data sources; foresight methods; technology life cycles; life cycle management; literature review; expert interviews
1Introduction
"Why do we talk of foresight rather than vision? Vision connotes a dream or an apparition, and there is more to industry foresight than a blinding flash of insight. Industry foresight is based on deep insights into trends in technology, demographics, regulations, and lifestyles, which can be harnessed to rewrite industry rules and create new competitive space. While understanding the potential implications of such trends requires creativity and imagination, any "vision" that is not based on a solid foundation is likely to be fantastical." (Hamel and Prahalad 1994)
In their text "Competing for the Future", Hamel and Prahalad (1994) ask their readers whether their companies have a clear shared vision of what their own industry might look like in the future. Although this work dates back several years, the question seems more relevant than ever in the current global economic situation. If the past few years have made one thing clear, the market is inevitably changing and tomorrow's competitive advantages will be different from today's. However, just as discontinuities in the market can lead to uncertainty, they also offer scope for new disruptive business opportunities. Data-Driven Foresight is a promising approach for companies to proactively identify and seize future competitive advantages (Rohrbeck et al. 2015). Data-Driven...