LAUSR

Abstract In a world where new product development (NPD) can differentiate winners from losers, reducing NPD cycle-times is a competitive agenda. For complex NPD projects, traditional planning techniques proved to be insufficient for dealing with uncertainty in the current business environment, often failing to provide realistic planning. This study contributes to both the literature and practice by proposing regression models to explore the potential of product complexity and prototyping lead-times for time prediction in NPD projects. Firstly, we identified an NPD reference that could help understand the NPD projects behavior for complex mechatronic products. Secondly, we developed validation procedures to calculate and test our variables. Specifically, several procedures were necessary to reach a value that represented a trade-off analysis of design issues to product complexity. Thirdly, we identified a company for sourcing data for a first falsifiability test to our models. The models presented results up to a 4% error rate, suggesting, compared to previous literature, that the variables explored in this research and how they were handled could provide good alternatives for managers to refine development plans and have more assertive launch dates for new products. Our main contribution is empirical evidence of the comparative influence of product complexity and prototyping manufacturing on time prediction for NPD projects. Researchers can derive further investigations on mathematical modeling or the way to calculate input variables.