Стратегії розвитку ланцюгів постачання на основі процесного управління та цифрової аналітики

English

Supply chain development strategies based on process management and digital analytics

Abstract. Introduction. The modern economy is undergoing a phase of deep digital transformation that fundamentally changes how supply chains are designed and managed. For Ukrainian enterprises in the post-war recovery period, the formation of flexible and resilient supply chains capable of rapid adaptation to market fluctuations, resource constraints, and infrastructure disruptions is of particular importance. Traditional supply chain management (SCM) strategies, focused primarily on cost efficiency and operational stability, are no longer sufficient to ensure responsiveness under conditions of turbulence and uncertainty. This necessitates the integration of process management, which provides structural transparency and process discipline, with digital analytics, which enables flexibility, predictive capability, and intelligent decision support. Purpose. The purpose of this study is to develop a conceptual model of adaptive supply chain development based on the integration of process management and digital analytics, aimed at enhancing the adaptability, resilience, and overall performance of enterprises operating in a dynamic market environment. Materials and methods. The research is grounded on modern process management standards – the SCOR Digital Standard and the APQC Process Classification Framework – and current approaches to digital analytics in logistics. The methodological framework includes systems analysis to determine the structure of supply chains as multi-level systems; comparative analysis for harmonizing process and analytical models; system decomposition for designing the conceptual model; logical modeling for visualizing interactions between processes, data, and strategic objectives; and expert evaluation for identifying key success factors in digital transformation of supply chain management. Results. The article substantiates that effective management of modern supply chains requires a shift from linear, efficiency-driven models to integrated adaptive systems. A conceptual model – “Adaptive Supply Chain Strategy” (ASCS) – is proposed, integrating three interrelated management layers: the process layer (standardization and orchestration of flows), the analytical layer (data collection, processing, and prescriptive analytics), and the strategic layer (alignment of analytics with strategic goals). The model creates a continuous feedback loop between operational processes and analytical insights, transforming supply chain management into a self-learning system. The ASCS model allows enterprises to reduce decision-making cycles, improve demand forecasting accuracy, lower logistics costs, and strengthen resilience against disruptions. The study outlines a step-by-step implementation mechanism – from diagnosing process and analytical maturity to developing digital twins of logistics processes and incorporating machine learning algorithms into supply chain planning. Sectoral examples (manufacturing, retail, agribusiness, and pharmaceuticals) demonstrate the universality and scalability of the model. The proposed ASCS model integrates the principles of process management and digital analytics into a unified adaptive framework for supply chain development. It provides a holistic platform for synchronizing data, processes, and strategic goals, enabling enterprises to enhance both efficiency and agility. The practical implementation of the model can contribute to the reconstruction and modernization of Ukraine’s logistics system, the formation of digital resilience in the national economy, and increased competitiveness in the global marketplace. Discussion. Future research should focus on the quantitative assessment of supply chain adaptability, the development of digital maturity indicators, and empirical testing of the ASCS model in Ukrainian enterprises across various industries. This will support the transition toward data-driven management and the establishment of a new paradigm for strategic SCM development.

Keywords: supply chain; process management; digital analytics; adaptive strategy; digital twins; artificial intelligence; SCM; resilience; flexibility; digital transformation