As a result of digitalization, data is collected at every level of production as an enhancer for decision-making. However, including more sensors to collect additional information does not directly contribute to increasing the system reliability but instead raises challenges for optimal data utilization. This work presents an evaluation approach based on FMSA (Failure mode and symptoms analysis) combined with FMECA (Failure mode, effects and criticality analysis) prioritization methods. The different methods are applied to a feed-drive system to evaluate the suitability of the currently implemented detection and monitoring techniques. The recommendations derived from the evaluation can be utilized to maximize confidence in the monitoring and to minimize the sensors utilization and data collection. Since the FMEA family of assessment tools present shortcomings such as bias and uncertainty associated with their results, this work also aims at mitigating these effects in obtaining the monitoring priority numbers and their respective categorization and prioritization.