<p>This research addresses the increasing challenges due to the supply chain disruptions which are caused by growing uncertainties and complexities in the supply chain. The focus of this study is on demand disruptions, specifically sudden variations in customer demand that impact the entire supply chain network. The research introduces a Multi-stage Stochastic Discontinuous Nonlinear Programming (MSDNLP) model considering proactive and reactive strategies to manage demand disruptions in the supply chain. This model optimizes procurement and storage quantities of raw materials and offers a mitigation strategy for raw material shortages by incorporating outsourcing from emergency suppliers at a higher cost. The validation of the model is done through a case study of the supply chain of an Asafoetida manufacturing company in India, facing demand disruptions. The implementation of the stochastic model is performed using General Algebraic Modelling System (GAMS) software with the CONOPT solver. The impact of disruption is assessed using the Value of the Stochastic Solution (VSS) and the Expected Value of Perfect Information (EVPI) metrics. According to various problem instances analysed, the VSS metric indicates that by implementing the proposed stochastic model can lower the total cost of company by an average of 10.81 percent. Furthermore, the EVPI metric reveals that the proactive demand management planning and investment can reduce the total cost by up to 11.58 percent. Finally, the sensitivity analysis of the model is conducted using the Taguchi method, and managerial implications were derived.</p>