The introduction of centralized and integrated Data Collection (DC) models has brought important process and product innovations, improving data quality and response rates for most of surveys. The new set-up and innovations have had a significant impact on the surveys of the agriculture sector which received a particular impulse in terms of efficiency. In general, the centralization of Data Collection aims to enrich the offer and quality of information produced, improving the efficiency of statistical processes. The resulting organizational structure is characterized by the clear separation between support services and thematic ones that are managed by statistical production. The new model limits the role of production structures only to the thematic aspects, while the transversal skills are assigned to specialized sectors. The introduction of an organizative set set-up characterized by thematic sectors on the one hand and service sectors on the other, prompted the "transversalization" of many services that are thus managed in a very specialized way. The result obtained consists in a standardization and harmonization of all the processes and in particular those related to data collection. The introduction of a specialized data collection also leads to the revision of the organizational structure devoted to Data collection processes and the redesign of many of the management procedures adopted. Before the adoption of these centralized models, the statistical processes were organized according to the classical "stovepipe" model, which involved independent statistical processes, not integrated, including all the necessary skills: statisticians, information technology experts, thematic experts, methodologists. This choice, although it was characterized by a high probability of achieving the set objectives, in terms of compliance with the Regulations and compliance with national dissemination plans, implied a very low overall efficiency level, due to redundant overlaps and lack of integration between the processes. The main trends underlying the centralization needs are the decreasing number of human resources assigned to the National Statistical Institutes, the greater degree of training and specialization of available human resources, the development of communication and information technologies, the computerization of the main survey units where the data are collected (companies, institutions, individuals and households), the need for greater consistency between the statistical indicators produced, in particular at the level of national accounting indicators. The new centralized management model for Data collection pushes to the maximum the possibilities of standardizing the processes, notably the DC field implementation processes, placing the unique limitation to the respect of the sector specificities related to the types of units involved (companies, households, individuals, institutions, farms) and the collection technique used (for example, use of a territorial network, intermediate bodies, etc.). The positive results, obtained following the introduction of centralized data collection, originate mainly in the standardization of data collection processes.