This is the post-print (i.e., it is the authors’ final draft, post-refereeing, and is therefore the authors’ accepted manuscript) of the article: Wood, L. C., Reiners, T., & Srivastava, H. S. (2017). Think exogenous to excel: Alternative supply chain data to improve transparency and decisions. International Journal of Logistics: Research and Applications, 20(5), 426-443. http://dx.doi.org/10.1080/13675567.2016.1267126 The final copy from the publisher (with pagination for citations) is available at: http://dx.doi.org/10.1080/13675567.2016.1267126 Think Exogenous to Excel: Alternative Supply Chain Data to Improve Transparency and Decisions Lincoln C. Wood 1. Graduate School of Management, the University of Auckland, Auckland, New Zealand Private Bag 92019, Auckland 1142, New Zealand +64 9 923 5820 L.Wood@auckland.ac.nz 2. Curtin University, Bentley, Western Australia, Australia. Torsten Reiners Curtin University, Bentley, Western Australia, Australia. +618 9266 7642 T.Reiners@cbs.curtin.edu.au Hari S. Srivastava Auckland University of Technology, Auckland, New Zealand Private Bag 92006, Auckland 1142, New Zealand +649219999- ext. 5917 hari.srivastava@aut.ac.nz Abstract: Efficient decisions along the supply chain have traditionally demanded sophisticated information sharing processes. Even with decades of research on theoretical and practical developments on integrating systems and stakeholders, in practice, we still seem to struggle to achieve full transparency and mitigate inefficiency challenges. We explore the emerging sentiment analysis technique to augment sales and operations planning (S&OP) with currently unavailable exogenous information. Even though sentiment analysis has gained traction, a comprehensive application in supply chains has not yet been attempted. Relevant topics are reviewed to allow an examination of the key relationships in a process framework, grounded in dual-process and bullwhip effect theory. Our proposed conceptual framework extends our conception of sentiment analysis integration to improve supply chain decisions and performance. The framework addresses managers interested in developing additional analytical capabilities and researchers to initiate further empirical research on the potential held by sentiment analysis in supply chain research. Keywords: supply chain management, sentiment analysis, bullwhip effect, information sharing, collaboration.