Big Data Technology.
Importance of Big Data in Supply Chain.
Benefits of Big Data in SCM (supply chain management)
Applications of Big Data in SCM...
Big data indicates the higher volume of data at a greater pace and a higher variety. Big data is the modern field in information technology that is responsible for predicting the needs and desires of a business. It can be defined as a novel generation of technologies and infrastructures intended to fiscally extract worth from extremely massive volumes of a broad amount of data, by facilitating greater pace capture, and analysis (Alexandru et al., 2016). It entails datasets which cannot be evaluated by the usual traditional data analysis tools further, it indicates the application of specified techniques and tools to manage massive datasets (Nasereddin, L-Khraishah, & Hakem, 2020).
As per Awwad et al. (2018), there is no doubt that the data generated is being progressively growing at a faster rate with the technological advancements across the organizations of the supply chain. Before the use of IT (Information technology), the information flow in the supply chain was documented in respect of physical documents. However, with the advent of IT tools, the preponderance of information flow related to the flow of resources is being accepted in form of digitally structured data. Additionally, it can be said that the volume of data gathered from several processes of the supply chain and the pace at which it is produced can be supposed as big data. Today, big data technology is assisting organizations in managing more responsive supply chains by analyzing market trends and customer perceptions. It is also enabling the prediction of supply chain linked activities strategically. In contemporary times, clients are more interested in getting real-time updates on product orders, its availability before purchasing it, and also to get access to the details of product manufacturing. In this regard, warehouse management can use big data to know the changes in consumer behaviour and the expectations of clients from the supply chain organizations (Sanders, 2016).
It is noteworthy that big data has a great potential for refining productivity and effectiveness and hence generating superior outputs (Acharya et al., 2018). The advantages of adopting big data technology in the operations of supply chain management are numerous and are illustrated below.
Acharya, A., Singh, S. K., Pereira, V., & Singh, P. (2018). Big data, knowledge co-creation, and decision making in the fashion industry. International Journal of Information Management, 42, 90-101.
Alexandru, A., Alexandru, C. A., Coardos, D., & Tudora, E. (2016). Big data: concepts, technologies, and applications in the public sector. Int J Comput Electr Autom Control Inform Eng, 10, 1629-1635.
Arunachalam, D., Kumar, N., & Kawalek, J. P. (2018). Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges, and implications for practice. Transportation Research Part E: Logistics and Transportation Review, 114, 416-436.
Awwad, M., Kulkarni, P., Bapna, R., & Marathe, A. (2018, September). Big Data Analytics in Supply Chain: A Literature Review. In Proceedings of the International Conference on Industrial Engineering and Operations Management, 418-425
Jain, A. D. S., Mehta, I., Mitra, J., & Agrawal, S. (2017). Application of big data in supply chain management. Materials Today: Proceedings, 4(2), 1106-1115.
Mohan, S. (2017). Big Data: Transforming Logistics and Supply Chain. International Journal of Pure and Applied Mathematics, 117(20), 911-916.
Nasereddin, H. H., L-Khraishah, H. A., & Hakem, H. (2020). Big Data Technologies in Supply Chain Management: Opportunities, Challenges, and Future Trends. International Journal of Management, 11(6).
Ranieri, L., Digiesi, S., Silvestri, B., & Roccotelli, M. (2018). A review of last-mile logistics innovations in an externalities cost reduction vision. Sustainability, 10(3), 782.
Sanders, N. R. (2016). How to use big data to drive your supply chain. California Management Review, 58(3), 26-48.
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