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Intelligent ERP for SCM agility and graph theory technique for adaptation in automotive industry in India

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Abstract

A supply chain's performance is determined by its capacity to stay market-sensitive while maintaining network integration. The challenges in remaining market sensitive are in designing, analyzing, and maintaining a supply chain to its optimum performance where a few strategic aspects of supply chain control the entire processes. With the emergence of the new business era of Big Data Analytics and its interoperability with ERP as an effective Business Intelligence tool I-ERP (Intelligent ERP) that ensures agility of supply chain as one of its primary qualities for expanding market share and maintaining survival is becoming a need in the volatile and complex supply chain network. The emphasis now is on adaptability of ERP with Big Data Analytics such as Machine Learning and Predictive analysis technique in the supply chain in Automotive industry in India by addressing manufacturing/business needs proactively. This paper is to identify the factors that contribute for the supply chain management to remain agile within the automotive industry through empirical data and an attempt has been made to comprehend the ability of SCM to remain agile with the interoperability between Big Data Analytics and ERP through a review of the literature. Identify the challenges in implementing the interoperability and propose technique based on graph theory for future research, IT and supply chain managers consideration.

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    Paul Jayender & Goutam Kumar Kundu

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Jayender, P., Kundu, G.K. Intelligent ERP for SCM agility and graph theory technique for adaptation in automotive industry in India. Int J Syst Assur Eng Manag (2021). https://doi.org/10.1007/s13198-021-01361-y

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