Augmentation of measurements is widely employed across various measuring systems to improve the precision of model parameter solutions. Such augmentation typically consists of two systems of observation equations: (1) the provider (server) system and (2) the user (client) system. Rather than solving these two systems of equations jointly, a two-step strategy is often adopted to sequentially compute the desired solutions. In the first step, the provider system of equations is solved to generate a set of corrections. In the second step, the corrections are transferred to the user to determine user-specific parameter solutions. The rationale behind this strategy is to reduce the computational load involved in the required data processing. In this contribution, we review and study the statistical interpretation of provider-derived corrections. It is shown how Best Linear Unbiased Prediction (BLUP) emerges when solving augmented linear(ised) systems of equations. A link between BLUP and interpolated corrections is established, addressing why care must be exercised when incorporating the uncertainty of the corrections into the user estimation process.