CASE STUDY

Transforming the Supply Chain: How Big Data Analytics Helped a Logistics Client to Reduce Delivery Time

Sep 1, 2017

In recent years, the supply chain environment has transformed from being only an infrastructure-based platform to a more data-driven network economy. With the rise of new technologies, the logistics industry has witnessed an explosion of data and devices. Thus, to retain their market shares, organizations in the retail landscape have started utilizing big data analytics to reduce costs associated with their processes. Also, with the influx of better technologies, organizations are leveraging the use of big data analytics to better understand their business processes and make timely-informed business decisions. Moreover, organizations also resort to the use of big data analytics to tap hidden patterns, identify market trends, and customer preferences. Through robust big data analytics, businesses across the logistics industry can gauge revenue opportunities, improve operational efficiency, and gain better traction over rivals. Big data analytics also helps players in the logistics industry analyze the prevailing data sets and draw conclusions from the obtained data to make informed business decisions.

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Quantzig’s team of big data analytics helps clients reduce costs by proactively reacting to inbound and outbound events. Moreover, clients can implement big data analytics to devise new strategies and strengthen their hold over the market. With the help of big data analytics, the client can also gain insights into the current market trends, customers’ buying patterns, and maximize ROI.

The Business Challenge

Like all other logistics company, a leading logistics service provider was facing predicaments in reducing the delivery time and inventory levels. The client wanted to devise a customer-centric approach to minimize the time allocated for the transportation of goods. The primary objective of the client was to leverage the use of big data analytics to enhance supply chain processes. Moreover, the client wanted to create a robust interoperability model to enable collaboration between different sectors such as manufacturers, suppliers, distributors, and retailers.

 

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Benefits of Big Data Analytics in the Logistics Industry

After obtaining detailed information into the logistics industry, the client was able to leverage the use of big data analytics to ensure better operational efficiency in terms of real-time route optimization. Also, the engagement helped the client enhance customer experience through robust customer loyalty management. The client was able to further devise new business models for small and medium-sized enterprises and gain relevant insights into the market trends, customer buying patterns, and maintenance cycles. Moreover, devising big data analytics helped the client understand the operations better and make timely informed business decisions.

Predictive Insights for the Logistics Industry

  • Analyze data sets and draw a conclusion about them to help organizations make informed business decisions
  • Leverage the use of data and devices such as GPS, RFID tags, sensors, and scanners
  • Deliver operational efficiency, safety and security, and customer experience
  • Increase transparency, optimize resource consumption and improve process quality and performance
  • Effectively track and reduce emissions across all related services
  • Implement real-time route optimization and provide instant driving updates to drivers

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