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Big Data Analytics In Supply Chain

by Guest Writter
Jim Taylor, Vice President, Information Technology, Transportation Insight

The supply chain is gaining in complexity at an alarming rate, creating a deluge of information overload from data generated within supply chain processes. Companies are using Big Data to better understand these massive amounts of data associated with processes and costs related to procurement, manufacturing, distribution, customer service, inventory deployment, freight payment/audit and more. Third-party logistics (3PL) providers are in an ideal position to help their clients harness the power of Big Data and identify relevant and actionable information.

In a recent study by Capgemini Consulting, shippers were asked where they were applying their Big Data initiatives. Fifty-six percent have initiatives in transportation management (planning); 54 percent in supply chain planning; 53 percent in network modeling and optimization; and 51 percent in advanced analytics. When Capgemini analysts unveiled this study at CSCMP, they emphasized that shippers (97 percent) and 3PLs (93 percent) feel strongly that improved, data driven decision making is essential to the future success of their supply chain activities and processes. This shows that shippers get Big Data, and they expect their 3PLs to provide solutions for managing Big Data.

Big Data allows companies to make money from the insights gained. You can analyze the data collected within your supply chain network to discover improved shipment consolidation strategies, determine where inventory should be located, better understand customer purchasing strategies, and much more. Bringing together relevant data from more and more channels is allowing supply chain executives to make better decisions to meet changing customer demands.  For example, if a company’s distribution centers are located in Georgia and Ohio, what are its best service options if demand increases in New England? By utilizing actionable data derived from historical shipment information and running what-if scenarios with regional data and characteristics, the company can assess whether to expand service in existing facilities or open a new DC in closer proximity to serve the area of increasing demand. The result is a more responsive and efficient supply chain, meeting customer demand faster and at lower cost.

Having real-time supply chain information such as accurate freight rates, shipment tracking and optimal shipment routing empowers supply chain professionals to make data-driven decisions at the day-to-day level. When a company executes a shipment, factors such as its destination, required delivery date, weight, dimensions and freight class come into play. Actionable data gives shippers visibility to multiple options based on shipment characteristics. ABC Carrier might have a lower rate under minimum shipment requirements. In contrast, XYZ Carrier might have a greater discount for shipments exceeding minimum shipment status. Having access to this data allows shippers to make smarter cost- and service-based decisions, saving money and positively enhancing the customer experience.

3PLs can combine data from different data sources, such as procurement or bid data, transactional shipping records, and policies and best practices. Drilling down into this combined data provides a wealth of information for which to make decisions that set you above the competition. For example, you can determine:

  • Price comparisons and alignment
  • How to best manage fuel
  • KPIs of transportation and supply chain partners
  • Standardization of processes
  • Continuous improvement needs and programs
  • Customer service level requirements and performance to plan
  • Buyer Market Identification
  • Facility Locations
  • Business Trends
  • Strategic insight into seasonal effects
  • Cost to Market and Cost to Serve Analysis

Big Data is here to stay. Industry analyst firm Gartner predicts that by 2015, 4.4 million IT jobs globally will be created to support big data, generating 1.9 million IT jobs in the United States. The goal of utilizing Big Data should be to see it as a way to turn information into revenues. Using a 3PL with expertise in Big Data will foster this goal.


About the Author

Jim Taylor is Vice President of Information Technology at Transportation Insight, a leading third party logistics provider (3PL) which offers a bundled transportation management solution including carrier sourcing, TMS, freight bill payment and audit and business intelligence.  Through his stellar career, Jim has held key management positions with Ryder Supply Chain Solutions, Total Logistic Control, ABX Logistics and DHL/Exel, providing senior leadership in the development of technology-based solutions for clients of all sizes and shapes. Jim knows the importance of hard work and sacrifice, as he joined the United States Marine Corps, eventually becoming Captain after acquiring a degree in International Affairs from the University of Nebraska.

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