The use of Industrial Internet of Things (IIoT) technologies in various industrial sectors has resulted in the generation of large volumes of data that can be analyzed using analytics tools to improve firm performance. However, there is a gap in our understanding of the capabilities that companies need to create business value through data analytics in IIoT environments. Although previous research has extensively investigated general data analytics capabilities, the literature on these capabilities cannot be simply transferred to IIoT settings due to the unique characteristics of the IIoT. In this paper, we aim to contribute to our understanding of this phenomenon by identifying the capabilities required for IIoT data analytics. Firstly, we identify data analytics capabilities from existing literature. Next, we investigate the relevance of these capabilities in the context of IIoT, while also identifying novel capabilities that are specific to IIoT, by conducting 16 expert interviews within nine organizations. We identify a set of 24 capabilities for data analytics in IIoT, which we classify into an integrative framework. The proposed framework can assist industrial companies dealing with the complexities and uncertainties associated with IIoT data analytics initiatives.
Bagheri, Samaneh and Dijkstra, Jesse, "CAPABILITIES FOR DATA ANALYTICS IN INDUSTRIAL INTERNET OF THINGS (IIOT)" (2023). ECIS 2023 Research Papers. 416.