Model and methods of information support for automating management and decision-making processes in trade-and-production enterprises

In the context of digitalization and increasing complexity of production and sales chains in trade-and-manufacturing enterprises, management effectiveness is constrained not only by regulations and management models but also by the degree of automation in the preparation of managerial decisions and by the quality of data used within planning, procurement, production, warehouse logistics, and sales loops. Purpose of the study is to develop a model and methods of information support for the automation of management and decision-making processes that ensure a reduction of the “event – decision – action” cycle and deliver a measurable economic effect in terms of service level, inventory performance, and labor costs. Materials and methods. The study applies a systems approach to the management of organizational and production systems, concepts of management information systems and decision support systems (MIS/DSS), methods for formalizing data and data quality requirements, as well as approaches to data quality assessment (ISO/IEC 25012) and data governance. Results. A management model for a trade-and-manufacturing enterprise is proposed in the form of a closed-loop control system with feedback, in which management information support (ERP/MES/WMS/CRM, data integration and MDM, corporate data warehouse and data marts) and the DSS layer act as a functional mechanism for automating the stages of monitoring, deviation analysis, decision preparation, and execution control. Measurable requirements for mana¬gement information are formulated, including timeliness, completeness, accuracy, consistency, interpretability, and security. A reference architecture of management information support (ERP/MES/WMS/CRM – integration/MDM – DWH/data marts – BI/DSS) is developed, with explicit identification of the execution layer (BPM/Workflow) and data quality monitoring mechanisms. Data quality metrics and management performance indicators are proposed, linking data defects to decision-making risks and financial losses. A decision-oriented methodology for designing management information support systems is presented, including the decomposition of key decisions, a “decision – data – requirements” matrix, source system audit, KPI semantic layer design, implementation of data governance regulations, and effect assessment. An applied case of inventory management and production planning is presented, demonstrating the use of the proposed model for scenario generation and execution control. Conclusion. It is shown that systematic data quality management and architectural integration of management information support with DSS increase the soundness of managerial actions and enable quantitative assessment of automation effects through the reduction of stockout losses, release of working capital tied up in inventories, and reduction of labor costs for manual reconciliation and reporting.