Tomsk, Russian Federation
Modern manufacturing enterprises operate under conditions of growing data volumes, increasing complexity of financial and operational processes, and higher requirements for timely managerial decision-making. In the context of business scaling, traditional approaches to analysis based on fragmented data sources and manual data processing lead to fragmented analytics, limited comparability of indicators, and an increased cost of managerial errors. The article examines an approach to designing an integrated system of financial and operational analytics aimed at supporting data-driven management of operational efficiency at a manufacturing enterprise. The proposed architecture integrates data from various sources, including the 1C accounting system and electronic reference directories, into a single analytical environment based on a business intelligence platform (BI platform). The developed system provides data processing, transformation, and visualization of financial and operational indicators, including revenue, operating profit, working capital, accounts receivable, inventory turnover, and operating cash flow. Particular attention is paid to ensuring the comparability of indicators and the verification of analytical calculations. The study shows that the implementation of an integrated analytical system makes it possible to reduce manual data processing, increase the transparency and verifiability of calculations, and provide analytical support for managerial decision-making. The results form a basis for further development of an intelligent system for managing operational efficiency.
financial and operational analytics, business intelligence systems, data integration, data-driven management, operational efficiency, working capital, data quality, management reporting, Power BI, analytical system architecture
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