Planning the multitude of spare parts supply chain's activities, characterized by intermittent demand combined with multi-echelon inventories involves considering highly stochastic processes. Thus, planning results do not achieve the same preciseness as of regular products supply chains. Recent research argues that referred preciseness can be enhanced by using improved demand forecasts which incorporate condition monitoring information. This work conceptualizes a simulation model for evaluating different spare parts planning methods, thus validating if improved forecasting may enhance planning quality. Simulation provides the capability of comparing different scenarios which allow for the aimed validation. The findings are substantiated through a real-world case.