Analytical Support for Managing the Financial Performance of Agricultural Enterprises in the Context of Digital Transformation

Abstract

Abstract: The article explores the theoretical, methodological, and applied aspects of analytical support for financial performance management in agribusiness enterprises amidst the digital transformation of the economy. It is substantiated that the increasing volume of information, the growing complexity of production and sales processes, rising risk levels, and environmental instability necessitate a transition from traditional, retrospectively oriented financial analysis approaches to integrated, digital-oriented information and analytical systems. Scientific approaches to interpreting the essence of digitalization are generalized, revealing the lack of a unified conceptual paradigm for its definition, which highlights the need to systematize the theoretical foundations of digital transformation in financial performance management. It is proven that the digitalization of agribusiness is a comprehensive transformational process aimed at automating business processes, optimizing resource utilization, improving information and communication links, and enhancing the competitiveness of enterprises. The role of the Information and Analytical System of Financial Performance Management (IASFPM) is substantiated as a key tool for making informed management decisions in real-time. IASFPM is defined as a complex of interconnected elements (people, technologies, processes, and data) that ensures the collection, processing, analysis, and interpretation of an enterprise's financial information, enabling agribusinesses to adopt a systematic approach to financial performance management by combining technological reliability with high-quality analytical insights. A typical structure for a digitalized IASFPM is proposed, including modules for data collection, storage, analytical processing, visualization, and information security. A conceptual model for the digitalization of IASFPM in agribusiness enterprises has been developed, reflecting the logical sequence of management decision-making based on the integration of internal and external data sources, modern digital technologies, and analytical modules. This model will contribute to strengthening the competitive positions of agricultural enterprises, increasing their adaptability to market changes, their capacity for innovation, and their investment attractiveness.