Applications of Big Data Analytics in Supply Chain Management: Findings from Expert Interviews

Abstract

The increased amount of data being generated in virtually every context provides huge potential for a variety of organisational application fields, one of them being Supply Chain Management (SCM). The possibilities and use cases of applying this new type of data, i.e. Big Data (BD), is huge and a large body of research has already been conducted in this area. The current paper aims at identifying the understanding and the applications of BD not from an academic but a practitioners’ point of view. By applying expert interviews, the main aim is to identify (i) a definition of Big Data from SCM practitioners’ point of view, (ii) current SCM activities and processes where BD is already used in practice, (iii) potential future application fields for BD as seen in SCM practice and (iv) main hinderers of BD application. The results show that Big Data is referred to as complex data sets with high volumes and a variety of sources that can't be handled with traditional approaches and require data expert knowledge and SCM domain knowledge to be used in organisational practical. Current applications include the creation of transparency in logistics and SCM, the improvement of demand planning or the support of supplier quality management. The interviewed experts coincide in the view, that BD offers huge potential in future SCM. A shared vision was the implementation of real-time transparency of Supply Chains (SC), the ability to predict the behavior of SCs based on identified data patterns and the possibility to predict the impact of decisions on SCM before they are taken.