The ‘explosion of data’ (Cukier and Mayer-Schoenberger 2013), facilitated by technological developments such as sensor and geo-locating devices, smartphones, the Internet of Things (IoT) as well as the associated metadata, has wideranging social, political, environmental, educational and economic implications (George, Haas, and Pentland 2014; van Knippenberg et al. 2015; George et al. 2016). The technology industry, managers, consultants and commentators have been quick to point to the potential of these data as a resource to contribute to competitive advantage and innovation opportunities for firms (McAfee and Brynjolfsson 2012; George, Haas, and Pentland 2014). Data constitute new raw materials for product and service development (Manyika et al. 2011) and needs to be sourced, generated, collected, stored and transformed by firms to lead to new value creation (Chen, Preston, and Swink 2015; Gupta and George 2016). In this context, understanding the role and flow of data in establishing competitive advantage becomes critical. Therefore, building on the theoretical and empirical foundations of the manufacturing Supply Chain (SC), we propose Data Supply Chain (DSC) to re-frame the SC in the context of the digital and knowledge economy and define DSC as a distinct type of SC along which data rather than material artefacts are moved, shared, re-configured and aggregated to provide both new opportunities for competitive advantage/business model innovation as well as management challenges (see Figures A1 and A2 in Appendix 1).1 The SC has become a well-established concept in operations management with strengthening theoretical and empirical foundations (Mentzer et al. 2001; Storey et al. 2006) and emergent disciplinary distinctiveness (Ellram and Cooper 2014). Mentzer et al. (2001, 4) provide a commonly accepted definition of the SC as ‘a set of three or more entities (organisations or individuals) directly involved in the upstream and downstream flows of products, services, finances, and/ or information from a source to a customer’. The purpose of SC Management is effectively and efficiently to procure raw materials, transform them and subsequently distribute finished products to end users (Borade and Bansod 2008). To date, research has focused primarily on the flow of physical materials through the SC wherein concern is expressed for raw material flow, inventory management and finished goods distribution (Ballou, Gilbert, and Mukherjee 2000), for example in the context of manufacturing and consumer goods (Burgess, Singh, and Koroglu 2006); however, little attention has been paid to the procurement, transformation and subsequent distribution of data artefacts within the SC context.