Contemporary supply chains are vastly complex, and decisions made by actors have system-wide consequences that these might not be able to foresee. There are gaps between "best practice"-founded theory and actual practice in supply chains. To remedy this, we argue, the supply chain actors need to enhance systems knowledge. There is a need to support development of mental models about systemic structures in the supply chain. This is difficult, if not outright impossible, to achieve in real-life settings. A supply chain visualisation microworld engine has therefore been developed, which forms the basis of a learning arena that supports system learning for the supply chain actors. (Contains 5 figures, 2 tables and 1 note.)