Reengineering of business processes of agroindustrial enterprises in conditions of through digital transformation

The article describes the high dynamism and uncertainty of the external and internal envi-ronment, which actualize the implementation of innovative technologies in the management of business processes in the agro-industrial complex (AIC). Attention is focused on the strategic nature of the transformation of agricultural production within the digital ecosystem. The perspective technologies of collection and processing of remote sensing data obtained from various satellite sensors, unmanned vehicles, weather stations; geographic information systems; global positioning systems are considered. The fundamental elements of reengineering of business processes in the context of digital transformation, the creation of control systems to control the development of agricultural crops using streaming processing of remote sensing data are considered. The factors of restraining and catalyzing production processes in AIC are substantiated, the features of the elements of the organization of the digital spatial environment are revealed, which largely determine the transition to a unified information support system for an agro-industrial enterprise. A structural and functional model of reengineering of business processes is proposed, aimed at ensuring sustainability in making managerial decisions. As part of the reengineering process, it is planned to create an information environment for an agricultural enterprise, consisting of interconnected procedures for merging information of its component functional systems: an automated monitoring system, a system for automated recognition of the specifics of the state of plant surface elements and an automated analytical decision support system for selecting agrotechnological techniques. Reengineering of business processes according to the proposed model will reduce risks in terms of compliance with time factors, increase production volumes and profitability of an agricultural enterprise due to the transition to digital technologies for automated collection and processing of big data, the ability to make decisions based on automated analytical systems and the ability to store in the knowledge base the generated chains of agro-technological operations for the needs of future periods.