INTELLIGENT DECISION SUPPORT SYSTEMS IN THE PROCESSING INDUSTRY

Abstract

This article examines the role of intelligent decision support systems (IDSS) as modern tools for improving management efficiency in processing industry enterprises during digital transformation. The relevance of applying such systems is substantiated amidst increasing production complexity, intensifying competitive pressure, market instability, and managerial uncertainty. It is shown that traditional approaches based on retrospective analysis and subjective experience increasingly fail to ensure an adequate level of justification, timeliness, and consistency in managerial actions.
The essence of IDSS is revealed as integrated analytical tools focused on comprehensive data processing to improve management quality. These systems ensure the formation of alternative scenarios, assessment of economic consequences, and support at strategic, tactical, and operational levels. The study substantiates that using intelligent systems enables a shift from reactive to proactive management, preventing negative deviations and achieving target economic indicators.
The paper analyzes IDSS applications in production management, resource provision, costs, and financial results. Their impact on reducing economic risks, optimizing resource use, and enhancing enterprise adaptability is examined. It is determined that IDSS contribute to management transparency, soundness of decisions, and long-term efficiency.
The significance of these systems is established as a vital component of the digital ecosystem, increasing economic resilience and competitiveness. The obtained results can be used to improve management systems and develop development strategies under the conditions of the digital economy.