Life Sciences Product/Service Development Process: Lesson Learned from Thailand Center of Excellence for Life Sciences (Public Organization)

Abstract

There is no argument on the benefit of innovation. Much evidence shows how innovation increase the value of the company; surpasses its outcomes, both product and service, and also improves the process’s efficiency. Many scholars proposed the model for creating innovation using the term “New Product (Service) Planning and Development Process: NPD process” by employing the inductive methodology, collected case studies and constructs to generate the models such as BAH Model and Stage-Gate Model, However, these models are still not crystalized and incompatible with business requirement, especially in high growth business like life science. There is evidence showing the general NPD process is not fit in the current situation of life sciences product/service development and should be modified to solve the problems. The portfolio management concept is the main principle of the idea screening phase. Ideas that were generated for the previous phase have been prioritized by correlation of market opportunity and operational feasibility and almost categorized as the star, cash cow, question and dog according to Boston Consulting Group: BCG recommendation. But the process cannot be applied with life sciences product/service, because it was selected by the readiness for operation such as good manufacturing practices (GMP) certification by food and drug association (FDA) approval. Although the company has the star category product/service, it cannot produce anything without FDA approval. As the above problem statement, A qualitative method and content analysis were used in this study to find a suitable process for the development of life sciences product/service. The study found a suitable process of development for life science products as pharmaceutical products and cosmetics. Although the results of the study derived from credible resources, quantitative methods are required to confirm the suitability and generalizability of the model in the future.