Using outputs of a supply chain system dynamics model, neural networks’ pattern recognition capabilities and eigen value analysis are utilised to detect and analyse behavioural changes in the supply chain and predict their impact in the short- and long-term horizons on performances. Neural networks are used to detect changes in the supply chain behaviour at a very early stage of their occurrence so that an enterprise would have enough time to respond and counteract any unwanted situations. Then, the principles of stability and controllability are used to apply and make modifications to the information and material flows to avoid undesirable behaviours.