Warehouses are facing substantial challenges due to the COVID-19 context. In this regard, automation in the warehouse industry has become an emerging trend in the supply chain sector. However, there is no proper model to measure the maturity level of warehouse operations. This paper aims to provide a maturity scale model to measure the automation stage in the Sri Lankan warehouse context. This research uses qualitative and quantitative approaches to assess the maturity level. A refined maturity assessment model was developed using early literature and industry expert views. The study analysed data collected from five major warehouses in Sri Lanka, and those were modelled as ad-hoc, mechanisation (semi-automated), and fully automated stages of examining the overall maturity stage of the selected warehouses. The study findings reveal that the majority of selected Sri Lankan warehouses have developed soft-based automation practices. According to the study, chosen warehouses in Sri Lanka retain the stage of 1.93 in maturity scale, which means combining traditional manual processes with some part of automation. Further selected warehouse operations belong to the mature stage of ad-hoc level in the maturity scale of automation. It may dramatically move to the mechanisation stage with the globalised market dynamics. Further, the maturity model of the study provides a practical diagnostic tool that will help warehouses assess the warehouses' automation level in the Sri Lankan context.
Keywords: Automation of Warehouse Operations, Maturity Scale, Warehouse Automation Practices