Today, Ali Shafqat successfully defended his PhD thesis titled “Managing unplanned design iterations in new product development: An approach using risk management, resilience and organizational learning”.

Ali is one of the few and proud dual-degree PhD students between DTU and NTNU - so he will receive a degree from both organizations.

I am copying the popular science summary below. His thesis will eventually be available through the DTU Libraries.

Congratulations Ali and well done!!!

Popular Science Summary

Most new-product development (NPD) engineering projects encounter uncertainties from rapidly shifting market demands and developing technologies resulting in requirements change and the organization's ability to implement state-of-the-art processes reliably. This complexity triggers unplanned design iterations in the engineering design phase of the NPD process. These unplanned design iterations can be assumed to be the occurrence of a specific class of NPD project risks. Unplanned design iterations ultimately cause failures in reaching cost, schedule, quality, and customer satisfaction targets.

Today's organizations utilize traditional risk management practices to mitigate risks in NPD projects. However, even with mitigation actions in place, projects still struggle to manage NPD project risks.

Therefore, this PhD thesis explored the utilization of risk management, resilience, and organizational learning in managing unplanned design iterations risk in the design and development of new products.

To achieve this aim, we used different research methods including literature review, case study, crosssectional interviews and survey.

The empirical findings of this PhD thesis suggest that risk management processes must be tailored according to the contextual factors of the NPD projects to manage unplanned design iterations. The overlap of risk management-based and resilience-based approaches is required to treat known and unknown NPD project risks that may cause unplanned design iterations. The thesis's findings recommend developing a structured approach for selecting suitable learning methods for managing unplanned design iterations after their occurrence. Finally, the thesis's findings suggest establishing a systematic approach for capturing newly generated knowledge in the resolution of the unplanned design iterations employing organizational learning.