In manufacturing, advanced measurement systems (e.g., 3D laser scanners) are continually being incorporated into modern quality control (QC) systems to provide high-density (HD) data. A significant amount of research efforts has been placed in the development of QC tools, such as Phase I and II statistical process control (SPC) approaches using HD data. However, the effectiveness of SPC tools highly depends on measurement system adequacy. The study of the quality and adequacy of a measurement system, known as measurement capability or Phase 0 in SPC applications, is a prerequisite to implementing any SPC tool; which has mostly been neglected for HD data. This paper proposes a holistic Gauge study approach for HD data obtained from 3D laser scanners (e.g. point clouds) by using spatial statistics data models. The main objectives of this work are two-fold: 1) Study how to analyse the repeatability and reproducibility of a point cloud and 2) Quantify the uncertainty associated with a point cloud under different factors involved in acquiring point clouds from 3D laser scanners.