While the objective of structural design is to achieve stability with an appropriate level of safety, the design of structural health monitoring (SHM design) is performed to identify a configuration that enables acquisition of data with an appropriate level of precision in order to understand the condition state of a structure. Nevertheless, a practical and standardized approach for SHM design is not fully available. In this contribution, we address SHM design by proposing a method for the estimation of the effectiveness of SHM (monitoring effectiveness) based on information available a priori-i.e. before the acquisition of data from sensors. The proposed method is developed with the aim of easing SHM design in real-life settings and maintaining an analogy with structural design. The expected monitoring effectiveness relies on the calculation, performed a priori, of the variance that will affect the estimate of a target variable a posteriori. Since no real observations are available a priori, the estimation of variance is carried out by considering the observations as a random variable. With the aid of two real-life applications, we show how the proposed method can be used in order to evaluate a monitoring system.