Reference
Scheuffele, M., Bayrle-Kelso, N., & Brecht, L. (2022). Data-Driven Foresight in Life Cycle Management: An interview study. Paper presented at the ISPIM Connects Athens, Athens, Greece.
Publication type
Paper in Conference Proceedings
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.
Persons
Organizational Units
- Liechtenstein Business School
- Entrepreneurship
- Technology & Innovation