Big data and predictive analytics for supply chain and organizational performance
January 10, 2022
Big data and predictive analytics (BDPA) is an all-encompassing term for techniques destined to handle big data characterized in terms of high volume, velocity and variety (Duan & Xiong, 2015; Wang, Gunasekaran, Ngai, & Papadopoulos, 2016; Zhou, Chawla, Jin, & Williams, 2014). Big data can help address critical challenges of predictive analytics that refer to data capture, storage, transfer & sharing (i.e. system architecture), and search, analysis, and visualization (i.e. data analytics) (Chen, Chiang, & Storey, 2012; Duan & Xiong, 2015; Erevelles, Fukawa, & Swayne, 2016). BDPA can improve supply chain performance by improving visibility (Barratt & Oke, 2007), resilience and robustness (Brandon-Jones, Squire, Autry, & Petersen, 2014), and organizational performance (OP) (Schoenherr & Speier-Pero, 2015; Waller & Fawcett, 2013).
