Organisational and methodical approaches to building the information-analytical subsystem of strategic management of industrial resilience

Анотація

The paper substantiates and develops the architecture of the information-analytical subsystem of strategic industrial resilience management (IAS SIRMS) as a closed adaptive analytical contour integrating eight interrelated functional blocks: information, indicator, methodical, model-analytical, interpretational, managerial, monitoring-corrective, and adaptive-regulatory. The architecture ensures a sequential transition from data collection to indicator system formation, application of methodical procedures, construction of analytical models, interpretation of results, development of managerial decisions, and monitoring with subsequent correction through a feedback mechanism. Nine methodical principles of the subsystem are defined: integration of the spatial-network industrial structure into the assessment system; multi-level indicator assessment across micro, meso and macro levels; combination of indicator, model and scenario analysis; integral assessment of functional capacity using the industrial-logistics axis strength indicator (Sa); typology and classification of regional industrial zones (RIZ) and industrial-logistics axes (ILA); differentiation of managerial decisions; adaptive feedback cycle; alignment with circular transition goals; transparency of analytical procedures. A seven-stage concept for building the subsystem is proposed, grounded in six core principles: systemic coherence, spatial-functional integration, adaptability, indicativeness, multi-level character, and goal orientation. A five-level organisational-managerial configuration is substantiated with clearly defined responsibilities at national, mesoregional, regional, analytical-methodical and digital-informational levels. The proposed approaches enable the transition from fragmented information provision to a systemically organised analytical contour for evidence-based strategic industrial resilience management under circular transition and multi-crisis transformations.

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