With an aging infrastructure and complexifying grid, sensors become essential to monitor the state of power system components. They are part of the evolution of power grids into smarter grids, as well as of the development of digital twins. Currently, sensors are largely absent from distribution grids. While much research literature exists in optimal sensor placement with cost minimization under performance constraints, few publications quantify the profitability of such sensors for distribution grid operators (DSOs). This work aims to bridge this gap and to offer a novel methodology that enables DSOs to assess if and where sensors would be profitable in the context of asset management. The methodology is based on modeling the effects of sensors on maintenance activities and then on grid reliability. We formulate a binary non linear optimization problem, and apply it to study the case of sensors that monitor the condition of power lines. Results show that sensor profitability depends on several factors including i) the component age, ii) the current replacement practice, and iii) the component importance. Thus, this work gives a tool for DSOs to decide whether and where to invest into sensors.