Warehouse Automation and Inventory Accuracy in Nigeria

Purpose: The purpose of this article was to analyze warehouse automation and inventory accuracy in Nigeria. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Recent studies in Nigeria indicate that warehouse automation improves inventory accuracy by reducing manual errors and enabling real-time data capture. Technologies like barcode scanning, RFID tagging, and integrated ERP systems have led to accuracy improvements of up to 12%. However, challenges such as limited technology access, insufficient training, and infrastructural constraints hinder full automation potential. Despite these barriers, incremental investments in automation yield significant operational gains, emphasizing the need for further technology integration and workforce development. Unique Contribution to Theory, Practice and Policy: Technology acceptance model (TAM), resource-based view & diffusion of innovation (DOI) theory may be used to anchor future studies on warehouse automation and inventory accuracy in Nigeria. Practitioners should leverage state-of-the-art monitoring technologies such as smart meters and IoT devices to capture detailed data on residential energy use. Policymakers must design incentive schemes, such as tax rebates and subsidies, to encourage the adoption of renewable energy and energy-efficient retrofits in residential areas.