Critical disruptive events affecting organisations worldwide have turned resilience into a strategic driver to achieve success. However, resilience is not a static concept, it implies dynamism and continuous improvement. When addressing enterprise and supply chain resilience, it is essential to analyse the cause-and-effect relations among three main components: awareness, prediction, and impact quantification. Although many approaches have been developed and implemented to enhance resilience in companies and supply chains, there is a need for a straightforward approach to interrelate these core components and facilitate their implementation. In this research, we introduce the Resilience Reinforcement Cycle aiming to address this gap. This conceptual framework integrates the mentioned main resilience components in a continuous improvement cycle based on reinforcement learning principles. It establishes analogies where decision-makers act as agents, operational flows represent the environment, actions correspond to models and techniques to strengthen the three components, and rewards are defined as the minimisation of the negative impact of disruptive events. The main objective of this research is to set the basis for a resilience continuous enhancement process working as a cycle that reinforces itself with newly implemented actions.