Companies need to deliver innovative new products in order to compete in the global market successfully. Customer preferences as well technologies are highly dynamic that continuous ideation is required in the fuzzy Front End of product development, where suitable ideas have to be selected to initiate object innovation. The fuzzy Front End is mainly unorganized in companies, and there is a lack of a consistent taxonomy in the literature covering all aspects in the fuzzy Front End for successful product innovation. Consequently a model describing the pillars of the fuzzy Front End with respect to object innovation is synthesized here based on evidence from the industry supported by a systematic literature review, which shall support practitioners and researchers in the successful evaluation of innovation ideas.

If the dynamic fuzziness of the Front End (FE) part of New Product Development (NPD) cannot be treated in a timely manner, fuzziness accumulates over other parts of NPD hence NPD can result in costly mistakes. The authors tried to remedy this strategically critical problem by implementing mainstream theoretical/methodological approaches, but they found inherent weaknesses of each. The purpose of this study is to bring an objective and intelligent decision-making model to FE so as to lessen fuzziness of it. Model quantizes ideas based on pillars, and re-clusters them with every new idea addition thanks to combining non-mainstream approaches like K-means, distance-based algorithm with gravitational theory inspiration, an accumulation of idea and an exponential function. Study showed that fuzziness of FE can be lessened by quantizing, and objectively managing. The founded core reasons of fuzziness can guide practitioners and authors for better understanding and coping with fuzziness of FE; moreover, the model can be used by companies. Introducing an objective and intelligent decision-making model working like a human brain to FE is a unique idea that has not been tried ever before.

No abstract