Design and application of data analytics in an internet-of-things enabled warehouse

Abstract

Purpose While several warehouses are now technologically equipped and smart, the implementation of real-time analytics in warehouse operations is scarcely reported in the literature. This study aims to develop a practical system for real-time analytics of process monitoring in an internet-of-things (IoT)-enabled smart warehouse environment. Design/methodology/approach A modified system development research process was used to carry out this research. A prototype system was developed that mimicked a case company’s actual warehouse operations in Indonesia’s manufacturing companies. The proposed system relied heavily on the utilization of IoT technologies, wireless internet connection and web services to keep track of the product movement to provide real-time access to critical warehousing activities, helping make better, faster and more informed decisions. Findings The proposed system in the presented case company increased real-time warehousing processes visibility for stakeholders at different management levels in their most convenient ways by developing visual representation to display crucial information. The numerical or textual data were converted into graphics for ease of understanding for stakeholders, including field operators. The key elements for the feasible implementation of the proposed model in an industrial area were discussed. They are strategic-level components, IoT-enabled warehouse environments, customized middleware settings, real-time processing software and visual dashboard configuration. Research limitations/implications While this study shows a prototype-based implementation of actual warehouse operations in one of Indonesia’s manufacturing companies, the architectural requirements are applicable and extensible by other companies. In this sense, the research offers significant economic advantages by using customized middleware to avoid unnecessary waste brought by the off-the-shelves generic middleware, which is not entirely suitable for system development. Originality/value This research’s finding contributes to filling the gap in the limited body of knowledge of real-time analytics implementation in warehousing operations. This should encourage other researchers to enhance and develop the devised elements to enrich smart warehousing’s theoretical knowledge. Besides, the successful proof-of-concept implementation reported in this research would allow other companies to gain valuable insights and experiences.