Directional derivatives of reflection maps arise in several seemingly unrelated problems in the study of stochastic networks, including sensitivity analysis of performance measures, diffusion approximations for time‐dependent networks, and optimal control of fluid approximations. In certain contexts, they admit an interpretation as a certain Malliavin derivative. We provide a useful characterization of directional derivatives for a general class of reflection maps and describe some applications.