Covariance processing of data and spectra has established itself among the computerbased NMR spectroscopy methodologies to increase sensitivity and resolution and to facilitate spectral analysis. While homo-correlations yield two-dimensional (2D) diagonally symmetric or antisymmetric spectra, hetero-covariance transformations allow to transfer NMR chemical shift information to other spectroscopic techniques, such as near infra-red or Raman. This is visualized as a 2D correlation map, provided a common indirect or perturbation domain, such as time, concentration change, and pressure. Covariance spectra can be generated as synchronous or asynchronous maps. The synchronous map relates the signals of species, e.g., educts and products. The asynchronous spectrum allows to derive the sequential order in which such species occur relative to each other. After a theoretical introduction into covariance NMR, its application in process analytical technology is discussed for wine fermentation, a radical polymerization reaction, a continuous process ethanol production using immobilized yeast, and a Knoevenagel condensation in a microreaction system. The covariance approach is extended toward two perturbation variables and quantitative relationships through PARAFAC kernel analysis and is illustrated for the preparation of polylactic acid nanocomposites. The advantages and added values of using synchronous and asynchronous spectra to gain process knowledge and control are demonstrated.