Strategic and Technology Foresight in Product Lifecycle Management - With a holistic approach to trend analysis towards the lifecycle-encompassing foresight process

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Type and Duration

PhD-Thesis, since October 2023

Coordinator

Institute for Entrepreneurship

Main Research

Growth and Complexity

Description

Discontinuities in the market create space for new disruptive business opportunities. A promising approach for companies to proactively identify and seize future competitive advantages is Data Driven Foresight. By using different data sources from various influential perspectives, Data Driven Foresight can derive solid statements about trend-driven developments in the future. As technology and product life cycles accelerate, industrial firms are increasingly faced with the need to incorporate foresight activities into their Life Cycle Management to support decision making at every life cycle stage. The PhD project provides for the research and development of a novel approach for Data Driven Foresight in Life Cycle Management. In doing so the entire technology lifecycle has to be covered by trend forecasting, so that planning uncertainty in innovation processes is reduced to a minimum.

PhD-Student

Marie Scheuffele, MSc

Supervisor

Prof. Dr. Leo Brecht

Co-Supervisor

Prof. Dr. oec. Sigvald Harryson