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Data-Driven Foresight in Life Cycle Management: An Interview Study

In: Digital Disruption and Transformation

Author

Listed:
  • Marie Scheuffele

    (Universität Liechtenstein, Fürst-Franz-Josef-Strasse)

  • Niklas Bayrle-Kelso

    (Universität Liechtenstein, Fürst-Franz-Josef-Strasse)

  • Leo Brecht

    (Universität Liechtenstein, Fürst-Franz-Josef-Strasse)

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 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. 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 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.

Suggested Citation

  • Marie Scheuffele & Niklas Bayrle-Kelso & Leo Brecht, 2024. "Data-Driven Foresight in Life Cycle Management: An Interview Study," Springer Proceedings in Business and Economics, in: Daniel Schallmo & Abayomi Baiyere & Frank Gertsen & Claus Andreas Foss Rosenstand & Chris­topher A. (ed.), Digital Disruption and Transformation, pages 131-151, Springer.
    • Handle: RePEc:spr:prbchp:978-3-031-47888-8_7
    DOI: 10.1007/978-3-031-47888-8_7
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