Supply Chain Visibility in Disrupted Environments: Analytics-Based Strategies for Inventory Accuracy and Lead-Time Resilience

Abstract

This review examines how analytics-enabled visibility can improve inventory accuracy and lead-time resilience within supply networks exposed to persistent disruption. Its purpose is to integrate conceptual, technological and managerial perspectives in order to explain how organisations can detect emerging risks, preserve reliable stock information and sustain delivery performance under volatile conditions. The study adopted a structured review approach, synthesising peer-reviewed literature on disruption sources, inventory control, big-data analytics, artificial intelligence, digital platforms, supplier collaboration and resilience-building strategies across global and African contexts. The findings show that effective visibility depends on timely, accurate and interoperable data rather than on technology acquisition alone. Inventory reliability is strengthened through continuous monitoring, disciplined transaction capture, statistical control and workforce accountability. Descriptive, diagnostic, predictive and prescriptive analytics enhance decision quality by identifying anomalies, forecasting shortages, estimating lead-time deviation and evaluating alternative responses. Radio-frequency identification, the Internet of Things, cloud systems, blockchain and digital twins further support traceability and data integration, although fragmented systems, weak governance, cybersecurity exposure and limited analytical capability frequently constrain their value. The review also finds that resilience is reinforced through supplier diversification, strategic buffers, flexible capacity, local sourcing, collaborative planning and alternative transport arrangements. The study concludes that visibility becomes operationally meaningful only when reliable information is converted into coordinated and timely action. It recommends phased digital transformation, stronger master-data governance, supplier capability development, workforce training, recurring stress testing and clearer accountability for disruption response. Future research should prioritise explainable artificial intelligence, scalable digital-twin applications, multi-tier disruption modelling and context-sensitive solutions for developing economies. These measures are essential for balancing cost efficiency with continuity, adaptability and customer service.