The use of enterprise resource planning (ERP) is becoming increasingly prevalent in many modern manufacturing supply chains. However, knowledge of their performance when perturbed by several significant uncertainties simultaneously is not as widespread as it should have been. This chapter presents the developmental and experimental work on modelling uncertainty within an ERP multi-product, multi-level dependent demand manufacturing supply chain in a simulation model developed using ARENA/SIMAN. To enumerate how uncertainty affects the performance of an ERP-controlled manufacturing supply chain, the percentages of finished products delivered late (FPDL) and parts delivered late (PDL) are measured. Sensitivity analysis shows that PDL gives a more accurate effect. Simulations results are analysed using analysis of variance (ANOVA), which identifies four uncertainties namely late delivery from suppliers, machine breakdowns, unexpected/urgent changes to machine assignments, and customer design changes significantly affect PDL. Some uncertainties are found significantly interactive in two and three-way. They produce either knock-on and/or compound effects, a factor not generally recognised as a criterion for decision-making.