The recent global pandemic, geopolitical tensions, and the escalating physical risks from climate change have heightened concerns about the vulnerability of supply chains to disruption. Traditional approaches that rely on sector-level data have been shown to significantly underestimate the impacts of shocks, such as natural disasters, compared to firm-level analyses. However, firm-level data are typically proprietary and inaccessible. To address this gap, we present a methodology that generates realistic firm-to-firm networks using publicly available information. Simulations performed on the synthetic networks yield aggregate effects close to those obtained from real network data, although not in all scenarios the network is as important. We find in particular that shocks concentrated on fewer firms yield more discrepant results and are more difficult to predict. Overall, the method we present provides a suitable strategy for assessing the aggregate impact of shock scenarios when firm-level data is unavailable.