Today, survival data analysis is the foundation of all data manipulation, including enterprise network risk and supply chain management. However, enterprise network equipment, devices, and peripherals that do not perform properly endanger business process, data availability, and information flow for users. The importance of survival analysis relies on the dataset analysis approach to use. This article analyses incident data to forecast enterprise network risk and reduce business repercussions. The authors employed survival analytics for experimental risk analysis. One defined entirely by observed time and event occurrence. Data analysis can show how ineffective an organizational network is in real life. We can use predictive outcomes to speed up company networks, eliminate design risks, and save maintenance costs.