The increasing sophistication of the automotive market and the constant change in customer requirements increases companies’ concern to ensure efficient internal logistic flows in line with Just-In-Time philosophy and Lean principles, to deal with wastes and variability. Variability arises from the growing differentiation of products, from the adoption of multi and mixed model assembly lines, and from the uncertainty in customer demand resulting from the worldwide outbreak of COVID-19. Considering the automotive supplier company as research subject, several problems were found to be compromising the efficiency of one of its in-plant parts’ feeding systems, the most critical problem being the lack of planning and management of resources (human and material) needed to perform the logistic service. Through Action-Research methodology stages, the actions taken culminated in the development of a simulation and decision-support tool for the component supply system resource management and efficiency improvement. The simulations made revealed reliable and adjusted results of workload and workforce to face the variations in customer demand and the existing product mix. After the tool creation, resource planning and balancing was no longer based on managers experience and empirical knowledge only but based on scientific knowledge: concise and reliable data from information systems, measurements, study of times, and literature review on in-plant milk run systems, lean, just-in-time and continuous improvement techniques.