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Big data - real time fact-based decision: the next big thing in supply chain

Big data - real time fact-based decision: the next big thing in supply chain Big data has become the life blood of the organisations. Organisations are gaining an understanding that if all the data that streams into businesses are captured and analysed, then they may prove to be a valuable source of information. The thought of data creating value is not new; businesses have always wanted to derive insight from data for making real time, fact-based decisions. In the domain of supply chain, companies are using big data analytics to manage activities like warehousing, transportation, inventory management, delivery, demand forecasting and scheduling. For this they are applying various data analytics tools and techniques. The aim of this paper is to explore all these application in detail and identify the tools and techniques that are used across upstream and downstream supply chain and develop a theoretical framework of application of big data in supply chain management (SCM). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Business Performance and Supply Chain Modelling Inderscience Publishers

Big data - real time fact-based decision: the next big thing in supply chain

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1758-9401
eISSN
1758-941X
DOI
10.1504/IJBPSCM.2019.100853
Publisher site
See Article on Publisher Site

Abstract

Big data has become the life blood of the organisations. Organisations are gaining an understanding that if all the data that streams into businesses are captured and analysed, then they may prove to be a valuable source of information. The thought of data creating value is not new; businesses have always wanted to derive insight from data for making real time, fact-based decisions. In the domain of supply chain, companies are using big data analytics to manage activities like warehousing, transportation, inventory management, delivery, demand forecasting and scheduling. For this they are applying various data analytics tools and techniques. The aim of this paper is to explore all these application in detail and identify the tools and techniques that are used across upstream and downstream supply chain and develop a theoretical framework of application of big data in supply chain management (SCM).

Journal

International Journal of Business Performance and Supply Chain ModellingInderscience Publishers

Published: Jan 1, 2019

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