Abstract
Big data, advanced analytics, and in-memory database technology are on the agenda of top management since they are seen as key enablers for enhanced business decision-making. In this paper, we provide a comprehensive perspective on applications of in-memory analytics in the field of supply chain management (SCM) that use the aforementioned concepts. Our contribution is threefold: First, we develop a top-down framework to position in-memory analytics applications against extant IT systems in SCM. Second, we conduct a bottom-up categorization of 41 in-memory analytics applications in SCM to provide supporting empirical evidence of the efficacy of the framework. Third, by contrasting top-down and bottom-up perspectives we derive implications for research and industrial practice.
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