The present paper compares two multiblock techniques: the Common Components and Specific Weights Analysis (CCSWA) and the Multiple Co-inertia Analysis (MCoA). Both methods are used to (1) to investigate the relationships among various data tables and (2) to extract latent variables from information of different nature, reflecting different facets of a food product. Our objective is to study the ability of these methods to extract, from a set of data tables, latent characteristics which are representative of the whole modifications brought to a complex system (food product) by a modification of a given process factor. The comparison of these methods is based on the investigation of their conceptual framework by particularly highlighting new properties of CCSWA. Moreover, the two techniques of analysis are compared on the basis of a case study in cheese processing where each cheese sample is described by different kinds of measurements. Copyright © 2007 John Wiley & Sons, Ltd.