Condition monitoring plays a crucial role in improving system failure resilience, preventing tragic consequences brought by unexpected system failure events, and saving the consequential high operation and maintenance costs. Continuous condition monitoring systems have been applied to diversified engineering systems for well-informed operational decision-makings. Although research has been devoted to predicting system states using the continuous data flow, there still lacks a systematic decision-making framework for system designers to assess the value of such monitoring systems at the design stage therefore making system design decisions on adopting monitoring systems to maximize the benefits. This paper constructs such a decision-making framework based on the value of information, with which system designers can evaluate expected operation cost reductions under specific operation modes considering the effectiveness of continuous monitoring systems in predicting system failures. Two case studies on a battery energy storage system and a mechanical system, respectively, are employed to illustrate the value evaluation of the monitoring information and the system maintenance process with the aid of different prognostic results based on the monitoring data. Case study results show that the value of monitoring systems will be influenced by the deviation among the equipment group, the accuracy of system-state prediction, and different types of costs involved in the operating process. The adjustment of maintenance actions based on monitoring and prognosis information will help improve the value of monitoring systems.