Card-based systems can be simple yet effective means of controlling production. But existing solutions, such as Kanban, do not typically apply to the job shops often found in make-to-order companies. In response, a card-based approach to Workload Control known as COBACABANA – COntrol of BAlance by CArd-BAsed NAvigation – has been proposed in the literature. But although COBACABANA appears to be a leading card-based solution for job shops, the original approach has shortcomings that limit its applicability to practice. In this paper, we refine COBACABANA to facilitate its implementation: first, by reducing the number of cards that have to travel with an order to one per operation – as a large number of cards were needed to represent all possible processing times in the original approach – and, second, by updating the approach based on advances in Workload Control theory. We then use a job shop simulation model to evaluate the performance of the refined method. Results demonstrate the potential of COBACABANA to significantly improve throughput time, percentage tardy and mean tardiness performance. We also show how the estimation of expected processing times at release can be simplified by allowing the workload contributions of orders to be grouped into simple classes (e.g. small, medium and large) without a significant deterioration in the effectiveness of the approach. Given its simplicity, and the familiarity of practitioners with card-based systems like Kanban, COBACABANA represents an important means of embedding the principles and benefits of Workload Control in job shops in practice.