We illuminate the myriad of opportunities for research where supply chain management (SCM) intersects with data science, predictive analytics, and big data, collectively referred to as DPB. We show that these terms are not only becoming popular but are also relevant to supply chain research and education. Data science requires both domain knowledge and a broad set of quantitative skills, but there is a dearth of literature on the topic and many questions. We call for research on skills that are needed by SCM data scientists and discuss how such skills and domain knowledge affect the effectiveness of an SCM data scientist. Such knowledge is crucial to develop future supply chain leaders. We propose definitions of data science and predictive analytics as applied to SCM. We examine possible applications of DPB in practice and provide examples of research questions from these applications, as well as examples of research questions employing DPB that stem from management theories. Finally, we propose specific steps interested researchers can take to respond to our call for research on the intersection of SCM and DPB.

Purpose – The purpose of this article is to provide academics and practitioners a quantitative and qualitative analysis of the benefits, barriers, and bridges to successful collaboration in strategic supply chains. Design/methodology/approach – A triangulation method consisting of a literature review, a cross‐functional mail survey, and 51 in‐depth case analyses was implemented. Senior managers from purchasing, manufacturing, and logistics were targeted in the mail survey. The break down by channel category interviews is as follows: 14 retailers, 13 finished goods assemblers, 12 first‐tier suppliers, three lower‐tier suppliers, and nine service providers. Findings – Customer satisfaction and service is perceived as more enduring than cost savings. All managers recognize technology, information, and measurement systems as major barriers to successful supply chain collaboration. However, the people issues – such as culture, trust, aversion to change, and willingness to collaborate – are more intractable. People are the key bridge to successful collaborative innovation and should therefore not be overlooked as companies invest in supply chain enablers such as technology, information, and measurement systems. Research limitations/implications – The average mail‐survey response rate was relatively low: 23.5 percent. The case study analyses were not consistent in frequency across channel functions. Although the majority of companies interviewed and surveyed were international, all surveys and interviews were managers based in the US. Practical implications – This study provides new insight into understanding the success and hindering factors of supply chain management. The extensive literature review, the cross‐channel analysis, and case studies provide academics and managers a macro picture of the goals, challenges, and strategies for implementing supply chain management. Originality/value – This paper uses triangulation methodology for examining key issues of supply chain management at multiple levels within the supply chain.

The terminology “supply chain management” is used frequently in today’s materials management environment and is generally associated with advanced information technologies, rapid and responsive logistics service, effective supplier management, and increasingly with customer relationship management. Most materials managers are familiar with the supply chain mantra of “suppliers’ supplier to customers’ customer”. However, experience shows that few companies are actually engaged in such extensive supply chain integration. To obtain an accurate view of SCM as it is currently practiced, the experience and insight of industry managers engaged in supply chain initiatives was sought via a multi‐method empirical approach involving both surveys and case study interviews. The findings reveal that supply chain practice seldom resembles the theoretical ideal. Three different levels of SCM implementation are identified and a series of limiting factors are discussed. Managers must recognize the tension that exists between SCM’s competitive potential and the inherent difficulty of collaboration.

Purpose -The purpose of this paper is to understand how information technology (IT) is used to enhance supply chain performance. Design/methodology/approach -A large-scale survey and semi-structured interviews were used to collect industry data. Findings -Two distinct dimensions to information sharing -connectivity and willingness -are identified and analyzed. Both dimensions are found to impact operational performance and to be critical to the development of a real information sharing capability. However, many companies are found to have placed most of their emphasis on connectivity, often overlooking the willingness construct. As a result, information sharing seldom delivers on its promise to enable the creation of the cohesive supply chain team. Research limitations -Despite the extensive data collection, the research represents a snapshot of practice. Replication from a longitudinal perspective would help define how IT is evolving to enable supply chain management. Practical implications -A roadmap is presented to help guide IT development and investment decisions. Originality/value -The research presents a two-by-two matrix to help managers and academics understand the related nature of connectivity and willingness. A roadmap is presented to help guide IT development and investment decisions.

Despite substantial information technology (IT) investments, many organizations have failed to obtain hoped‐for improvements in supply chain (SC) performance. Therefore, we investigate the mechanisms through which IT influences SC performance. Specifically, we use the resource‐based view (RBV) of the firm to ascertain how IT can be exploited to obtain a distinctive SC advantage. We do this via a multimethod (survey and case‐study) approach at two periods of time. We use a nested structural equation model (SEM) to test six hypotheses. Likewise, we content analyze interviews to contextualize the SEM findings. Importantly, we find that investments in IT make their greatest competitive contribution when they enable a dynamic SC collaboration capability. The findings provide valuable insight to guide IT investments designed to improve SC performance.