Despite significant advances in digital technology and artificial intelligence, most methods for New Product Development (NPD) have changed little. Today's engineering teams work interdisciplinarily and digitally, but tools, processes, and methods are still rooted in traditional, closed innovation models. This makes it challenging to harness the potential of modern data-driven working methods.
What are we working on?
We are developing a new generation of methods, strategies, and digital solutions that make NPD more open, knowledge-driven, and adapted to complex development processes.
Holistic knowledge management
We explore how data, models, tools, and human experience can be connected into a coherent knowledge ecosystem. The goal is to make it easier to capture, structure, and reuse knowledge across disciplines and development stages.
AI-assisted decision support
We investigate how generative and predictive AI can support engineers in transforming information into reliable decision support – faster, more transparently, and with higher quality.
Digital robustness and interoperability
We develop methods that enable tools, processes, and organisations to better withstand complexity and rapid technological changes. This includes new ways to ensure flow between systems, disciplines, and teams working in parallel.
Why is this important?
Product development now takes place in a landscape characterised by:
- increasing technological complexity
- requirements for circularity and new EU regulations
- large amounts of data across tools and lifecycles
- need for rapid learning and continuous innovation
Nevertheless, international studies show that the success rate in NPD has remained almost unchanged over the past 30 years. Success is not about one method, but about the ability to combine tools, processes, organisational practices and digital maturity into a holistic innovation capacity.
We address this gap through research that connects theory, practice, and empirical studies in close collaboration with industry partners.
Research objectives
Develop a next-generation knowledge platform for decision support
We are developing a platform that integrates theory, practice, processes, people, and tools. The platform will strengthen companies' ability to handle increasing complexity and better equip them to make fast and good decisions in various business and development contexts.
Research questions
- How can new digital tools – including generative AI – be adapted and integrated so they actually support the transformation of data and information into valuable knowledge in holistic NPD?
- How can organisations build robustness and adaptability in concurrent, digitally supported development processes, especially in situations characterised by high complexity and rapid technological change?
Would you like to know more or collaborate?
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