One of the key aims of Industry 4.0 is to create more responsive systems. Responsiveness and adaptation enable coping with new market requirements or introducing new products, as demonstrated by the challenges posed by COVID-19. Despite the economic and sustainability benefits, practitioners often only consider adapting their systems for limited cases. They rely on simple, intuitive estimates of adaptation metrics and do not optimize these milestone decisions, leading to missed opportunities. Currently, there are no reliable methods for measuring system adaptability, quantifying the effort required to adapt it from one state to another, or optimizing the adaptation decision. This paper proposes a comprehensive adaptation framework based on complexity index quantification, graph network estimation, and multi-objective optimization. The framework outlines three approaches for estimating efforts in adapting the physical system design, upgrading control software, and optimizing the adaptation decision. The application on a lab-sized cell demonstrates the framework’s ability to estimate the adaption processes metric and generate a set of optimized cell states. The application reveals potentials for improvement and extension of the three approaches.