The multichannel analysis of surface waves (MASW) method is a non-invasive surface wave method used to characterize the layering and stiffness of the subsurface. This study assesses the practical limitations of using the MASW method for detecting and resolving subsurface anomalies. The sensitivity of MASW dispersion data to the presence of subsurface anomalies is examined through various two-dimensional (plane-strain) finite-difference elastic wave-propagation simulations. These simulations were performed on models containing anomalies of varying size, stiffness, and depth. The misfit between the dispersion data from a model with an anomaly (treatment model) and the same model without an anomaly (control model) were compared as a quantitative means of discerning if the anomaly was reliably detectable (i.e., outside the bounds of common dispersion data uncertainty). Those models categorized as containing a detectable anomaly, based on their experimental dispersion data, were further studied to determine if the dispersion data could be inverted to accurately resolve the anomaly’s size, stiffness, and depth. To rigorously perform the inversions, the procedures recommended by the surface wave inversion workflow SWinvert were adopted. These inversion procedures involve using multiple large-scale global-search inversions to address the problem’s non-linearity and multiple layering parameterizations to address the problem’s non-uniqueness. Following the inversion process, the shear wave velocity (Vs) profiles from the single “best” trial model associated with each layering parameterization were compared to the 1D Vs profiles from the centerline of the true/control model using an error function to quantitatively assess the ability of the MASW method to accurately resolve subsurface anomalies. In this study, anomalies with lateral extents less than approximately ½ the MASW array length located at depths greater than 5 m could not be resolved accurately by using MASW, even when the anomalies were relatively thick (> 2 m) and the impedance contrasts were notably high (> 2). The ability of MASW to detect an anomaly of a given size, stiffness, and depth is summarized in normalized figures, which are intended as a feasibility tool for those seeking to use MASW for anomaly detection.