Orchestrating agile omnichannel supply chain planning through big data analytics and end-to-end visibility

Abstract

Global supply chains become increasingly complex due to various uncertainties associated with the constant flux. With more firms engaging in global trade, reaping the benefits of offshoring and outsourcing a multitude of business functions worldwide, the increasing complexity continuously tests each company’s supply chain resilience and agility. The advent of e-commerce makes omnichannel more critical for traditional retailers. Omnichannel supply chains introduce an increased operational complexity to the information flows than that of traditional supply chains, including the need to coordinate numerous sales channels, multiple net-work nodes and decentralised inventory. A lack of end-to-end visibility of information flows can result in poor demand-supply matching and eventually cause service loss concerning stockouts. Accordingly, this study uses big data analytics to explore the relationship between forecast accuracy and visibility. A company in the fast-moving consumer goods industry centred on the Association of South-east Asian Nations region is employed as the empirical case. Not only determining correlations between the transmitted forecasts and actual supply needs but also insights into the growing emphasis on the omnichannel supply chain are discussed. Analytical results indicate that end-to-end visibility of information is highly correlated with forecast accuracy of demand, supply and production planning. The developed framework assists businesses in understanding the complexities of omnichannel operations and the benefits of information consolidation. This enhances businesses’ predictive analytics capabilities to facilitate supply chain planning and thus improve overall supply chain agility.