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Purpose

This study investigates whether developing a new maturity model for New Product Development (NPD) is necessary or if refining existing models can more effectively support organizational improvement.

Design/methodology/approach

A Design Science Research approach was used, including a systematic literature review of 28 NPD maturity models, to identify common dimensions, trends and methodological limitations. Building on these insights, the CLIMB model was enhanced into CLIMB2 with added layers of structured assessment and AI-supported guidance.

Findings

The findings suggest that refining existing models, rather than creating new ones, can address critical shortcomings while ensuring usability and adaptability. CLIMB2’s integration of AI-driven recommendations advances maturity modeling from descriptive assessment to actionable guidance, offering organizations a structured, resource-efficient approach to improving NPD processes. A case study in a manufacturing firm confirmed the model’s practical value.

Research limitations/implications

Findings are based on one case study and a literature-based framework. Broader empirical validation across various industries is needed to generalize applicability and refine AI components.

Practical implications

CLIMB2 provides organizations with a resource-efficient, actionable tool for assessing and improving NPD processes. Its prescriptive guidance supports strategic decision-making and targeted capability development.

Originality/value

Rather than introducing a new framework, the study refines an existing one to enhance usability and effectiveness. CLIMB2’s integration of AI transforms maturity models from static assessments into dynamic decision-support tools.

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