Cross-Company Data Sharing Using Distributed Analytics

Systems, vol. 13, pp. 418

Abstract

Decision making in modern supply chain management relies heavily on data-driven decision support. Companies show a growing interest in building insights not only on data from within the company’s own boundaries, but also from collaborators and other actors in the market. While the topic of data and information sharing has been the focus of previous works, there has been a lack of studies focusing on practical implementations in the supply chain domain. Our aim is to conduct a technical feasibility study of data sharing in supply chain management. We analyze the requirements for cross-company data sharing in supply chains, and discuss existing technologies that enable such collaboration. We apply a distributed analytics framework that has already been implemented in the healthcare domain to a simulated use case of key performance indicator (KPI) exchange between supply chain actors. We find that the application is able to compute and exchange KPIs from the simulated companies’ datasets without requiring centralization of the databases. Furthermore, we find that the framework supports integration of data quality assessment and privacy preservation mechanisms. The application thus yields promising results with regard to technical feasibility. Factors that may facilitate scalability are discussed as directions for future research.

Authors 5

1. Soo-Yon Kim corresponding Aachen Data Stream Management and Analysis (DSMA)

   RWTH Aachen University

   Affiliation as printed

   Data Stream Management and Analysis, RWTH Aachen University, 52074 Aachen, Germany

2. Stefanie Berninger Aachen Institute for Industrial Management

   RWTH Aachen University

   Affiliation as printed

   Institute for Industrial Management at RWTH Aachen University, 52074 Aachen, Germany

3. Max Kocher Aachen Data Stream Management and Analysis (DSMA)

   RWTH Aachen University

   Affiliation as printed

   Data Stream Management and Analysis, RWTH Aachen University, 52074 Aachen, Germany

4. Martin Perau Aachen Institute for Industrial Management

   RWTH Aachen University

   Affiliation as printed

   Institute for Industrial Management at RWTH Aachen University, 52074 Aachen, Germany

5. Sandra Geisler Aachen Data Stream Management and Analysis (DSMA)

   RWTH Aachen University

   Affiliation as printed

   Data Stream Management and Analysis, RWTH Aachen University, 52074 Aachen, Germany