Original Research

The impact of big data and business analytics on supply chain management

Hans W. Ittmann
Journal of Transport and Supply Chain Management | Vol 9, No 1 | a165 | DOI: https://doi.org/10.4102/jtscm.v9i1.165 | © 2015 Hans W. Ittmann | This work is licensed under CC Attribution 4.0
Submitted: 13 November 2014 | Published: 07 May 2015

About the author(s)

Hans W. Ittmann, Institute for Logistics and Transport Systems Africa, University of Johannesburg, South Africa

Abstract

Background: Change is inevitable and as supply chain managers prepare for the future they face many challenges. Two major trends over the last few years are the growing importance of ‘big data’ and analysing these data though ‘analytics’. The data contain much value and companies need to capitalise on the variety of data sources by in-depth and proper analysis through the use of ‘big data’ analytics.

Objective: This article endeavours to highlight the evolving nature of the supply chain management (SCM) environment, to identify how the two major trends (‘big data’ and analytics) will impact SCM in future, to show the benefits that can be derived if these trends are embraced and to make recommendations to supply chain managers.

Method: The importance of extracting value from the huge amounts of data available in the SCM area is stated. ‘Big data’ and analytics are defined and the impact of these in various SCM applications clearly illustrated.

Results: It is shown, through examples, how the SCM area can be impacted by these new trends and developments. In these examples ‘big data’ analytics have already been embraced, used and implemented successfully. Big data is a reality and using analytics to extract value from the data has the potential to make a huge impact.

Conclusion: It is strongly recommended that supply chain managers take note of these two trends, since better use of ‘big data’ analytics can ensure that they keep abreast with developments and changes which can assist in enhancing business competitiveness.


Keywords

Big Data; Business Analytics; Supply Chain Management

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