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Impact of Big Data on Supply Chain Management

“According to sources, 64% of supply chain executives consider big data analytics a disruptive and important technology, setting the foundation for long-term change management in their organizations.”

With the advent of technology, companies today have become more data-centric.  New strategies are designed to study and analyse the data and conclude insights, and thus advancing the very use of Big Data as a critical business capability.

What is Big Data?

In layman’s term Big data is providing supplier networks with greater data accuracy, clarity, and insights, leading to more contextual intelligence shared across supply chains. Read on to find out the impact of Big Data on Supply Chain Management. 

Impact of Big Data on Supply Chain Management

Big data analysis is reshaping the supply chain management for the better. With supply chains becoming more and more complex, the data increases by means of volume, variety and velocity. This technology helps produce both qualitative and quantitative improvements in supply chain operations around the globe.                                       

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Impact of Big Data on Supply Chain Management and why it is the next Big thing:

  1. Usage of big data analytics can optimize distribution, production system and logistics.
  2. Forecasting of demands and its patterns can be understood, which would help in developing the service. The data can be shared with the other partners in the supply chain.
  3. Provides better customer segment base to improve positioning of products or services.
  4. Sharing of knowledge within complex supplier networks
  5. Products, assets, and installations can be maintained by engaging in preventive maintenance.
  6. Internet of Things and production sensors will enable the supply chain team to develop almost real-time supply from the dynamic data feeds.
  7. Delivery networks can be optimized and merged by using geo-analytics.
  8. One can gain better contextual intelligence regarding the tactics, strategies, and operations used in supply chain that eventually impact the financial goals.
  9. Starting from production, inventories to transit time more precise information on operation can be gained.
  10. Pricing model can be created to achieve the maximum profit margin by using of both external and internal consumer data. Predictive analytics can be also used for forecasting a product’s demand and determine its pricing.    

Impact of Big Data on Supply Chain Management

Supply chain analytics is not a new – aged concept. However, its capability to come up with meaningful insights with massive inputs is changing the logistics landscape; the technology is allowing firms to exploit massive, and formerly complex, unstructured data sets. Presently, a mere percentage of supply chains use big data. Hence, the impact of Big Data on Supply Chain Management is yet to be felt. However, Annual Third-Party Logistics Study revealed that big data is the next big thing in the running of the supply chains for improving their operation. All we should do it is wait and let big data take the big leap and revolutionize this space.  

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