Big Data and AI changing the Face of Supply Chain Analytics


The enterprise adoption of big data analytics in supply chain management is a relatively recent development compared to other business areas, but is fast gaining traction in wide range of industries. The proliferation of unstructured datasets that may influence supply chain management has triggered the demand for Big Data technologies among businesses. Allocating shelf space at retail stores is a case in point where there is pressing demand for making sense of unstructured data for manufactures. Organizations world over are inclined to achieve the top-line growth focus on reducing the materials waste and improving forecast accuracy through machine learning technologies. Smart stock management system for warehouses and distribution centers rely on supply chain analytics and automatically alert restocking requirements. Supported by machine learning technologies, supply chain analytics is opening up promising prospects in inventory management and transportation logistics in industries such as retail, healthcare, consumer packaged goods, electronics, automotive, aerospace, and defense.

Advancements in sensors used in monitoring devices are expected to boost the market in the years to come. Efforts to augment the potential of database management tools are expected to accentuate the growth of the market. The innovative use of Big Data in supply chain management has led to fresh insights and has unlocked exciting prospects in industrial sectors in various developing and developed economies. The growing popularity of cloud-based solutions in supply chain analytics, notably among a growing number of small and medium scale enterprises, bodes well for the market. The staggering rise in manufacturing activities in a number of emerging economies, particularly in Asia Pacific, is expected to open abundant promising opportunities for market players. The rising adoption of supply chain analytics can be attributed to the substantial benefits they offer to end-use industries. The rising industry efforts on product innovations, especially in developed markets, is a notable factor accentuating the growth over the forecast period.

Supply chain optimization is gaining importance among organizations striving to lift customer experience, attain a stable business growth, and decrease the operational costs. Such organizations are incessantly executing solutions related to supply chain analytics in order to attain top-line progress, enhance productivity, and consolidate their market presence. These solutions are known for minimizing waste of materials, supporting network reconfiguration, enhancing forecast accuracy, elevating the level of services, and reducing inventory. With these benefits being highly acknowledged, the global market for supply chain analytics is anticipated to tread along a strong growth track. Supply chain analytics can also be deployed as on-premise solutions or cloud-based solutions.

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