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The objective of this article is to analyze the integration between the internal functions related to demand and supply processes. The studied object was an agribusiness company that uses digital technologies to operate its inbound logistics.

A case study was conducted in a global agribusiness company that went through a restructuring process with the implementation of a shared service center. In-depth interviews were conducted with employees from the demand and supply areas. The analysis involved description of cross-functional integration processes from the areas of demand and supply, the identification of technologies from Industry 4.0 present in the activities of those areas and their role in the integration process.

The analysis revealed the mediating role of technology in cross-functional integration, the presence of new integration factors and their impact on process performance. A framework was developed that describes the relationship between technology and integration factors, their impacts, and the implications for theory and practice.

Regarding this study, the focal company migrated its activities, which were previously isolated and dispersed across branches, to a centralized shared services unit. This research contributes by providing managers with elements to support their investment decisions in technologies that facilitate the integration process, mainly in the areas of planning and execution. It also contributes to the planning of processes, helping managers who are implementing or migrating activities and areas to new management structures.

This paper brings two new assumptions that may guide future investigations about cross-functional integration and its effects on demand and supply integration (DSI): (1) Digital technologies are able to support cross-functional integration in order to provide information integrity, team alignment, agile and assertive decision making within supply and demand processes; (2) Cross-functional integration, mediated by digital technologies, can generate agility and accuracy of information in the demand and supply processes. This accuracy and agility provide improvements in demand and supply process performance metrics, such as predictability, assertiveness, standardization, productivity and response time.