Leveraging data-driven decisions: a framework for building intracompany capability for supply chain optimization and resilience
通过访谈油气行业和物流供应链伙伴，研究企业如何将大数据转化为有价值信息以管理供应链风险并创造经济价值，提出了一个构建内部能力的实用框架。
Purpose Companies 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/approach Information 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. Findings Findings illuminate how companies can build internal capability to more effectively manage SC risk, optimize operating assets and drive employee engagement. Research limitations/implications The 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 implications Guidance 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/value This 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.