The characterization of acoustic sources typically involves the retro-propagation of the acoustic field measured with a microphone array to a mesh of the surface of interest, which amounts to solve an inverse problem. Such an inverse problem is built on the basis of a forward model prone to uncertainties arising from mismatches with the physics of the experiment. Assessing the effects of these unavoidable uncertainties on the resolution of the inverse problem represents a challenge. The present paper introduces a practical solution to measure these effects by conducting a sensitivity analysis. The latter provides a mean to identify and rank the main sources of uncertainty through the estimation of sensitivity indices. Two inverse methods are investigated through the sensitivity analysis: Beamforming and Bayesian focusing. The propagation of uncertainties is carried on numerically. The consistency between the real experiment and its numerical simulation is assessed by means of a small batch of measurements performed in a semi-anechoic chamber.