Big Data Analytics In Supply Chain Analysis
INTRODUCTION
The success of supply chain planning process depends upon how closely supply is managed, demands are forecasted, inventories are optimized and logistics are planned. Supply chain is the heart of the retail industry vertical, and if managed efficiently, it drives positive business and enables sustainable advantage, Matthew A and Stanley E (2013). If we observe carefully, huge amount of data is getting generated at each and every stages of the supply chain. In today’s digital world we are generating around 200 Exabyte of data each year, Silva R, Bogdan F and Marcin R (2013). Organizations are increasingly questioning their own ability to realize full potential from the huge amount of data they have within their supply chain, Steve
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Since, it encompasses wide range of activities, which most of time transcend factories or national boundary, complex interdependencies are built into it. As the power base continues to shift from companies towards customers, customer demands have gotten more complex. Companies are looking at Big Data analytics to revamp their supply chain, thereby using Big Data Analytics as a strategic lever.
Companies are collecting vast amount of supply chain related data with help of technologies such as sensors, Barcode and GPS, Jacob House (2014). Big Data Analytics offers companies the ability to leverage on the enormous amounts of information driving their global supply chains, Harvard Business review, (2013). Companies are aware that Big Data can be leveraged at various levels of a business. This holds true for supply chain management also. The combination of large, high velocity and varied structure of big data and advanced analytics tools and techniques represents the next frontier of supply chain innovation, Libor K, Christian G, and Michele B
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They all are eager to take advantages that these solutions may bring. This is true for retail sector as well. Big data analytics has the ability to provide actionable insights retail sector has been looking for long time. These insights can be utilized as a guide for internal decision-making in a wide variety of capacities. Big data analytics’ influence is both growing and expanding into various sectors. We can clearly see this trend for the retail sector also. Few of retail companies are now relying heavily on these
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