Abstract

PurposeCompanies are turning to big data (BD) programs to help mitigate supply chain (SC) disruptions and risks that are increasing in frequency and severity. The purpose of this paper is to explore exactly how companies translate data into meaningful information used to manage SC risk and create economic value; an area not well researched. As companies are turning to big-data programs to help mitigate supply chain (SC) disruptions and risks that are increasing in frequency and severity, having the capability to internally integrate SC information is cited as the most critical risk to manage.Design/methodology/approachInformation processing theory and resource-based view are applied to support capability development used to make value-based BD decisions. Semi-structured interviews were conducted with leaders in both the oil and gas industry and logistics SC partners to explore each companies’ BD transformation.FindingsFindings illuminate how companies can build internal capability to more effectively manage SC risk, optimize operating assets and drive employee engagement.Research limitations/implicationsThe oil and gas industry were early adopters of gathering BD; more studies addressing how companies translate data to create value and manage SC risk would be beneficial.Practical implicationsGuidance for senior leaders to proactively introduce BD to their company through a practical framework. Further, this study provides insight into where the maximum benefit may reside, as data intersects with other company resources to build an internal capability.Originality/valueThis study presents a framework highlighting best practices for introducing BD plus creating a culture capable of using that data to reduce risk during design, implementation and ongoing operations. The steps for producing the maximum benefit are laid out in this study.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.