Using Big Data to Build Tomorrow’s Supply Chain Today
Q: How can transportation and logistics companies use big data to differentiate themselves?
A: Supply chain professionals in all industries and government sectors must transform their supply chain process to meet organizational strategies and goals. Information fusion breaks down the barriers spanning all demand-supply enterprises. A critical requirement is real-time, high-quality, reliable data and information that enable management action.
This approach provides procurement and logistics professionals sizeable cost savings and improvements in performance, speed, and agility. With a strategic data strategy, logistics companies can more effectively:
- Secure high-risk cargo
- Enable supply chain collaboration
- Enable asset, shipment, and personnel visibility
- Provide supply requirement and maintenance condition predictability
- Eliminate traffic congestion and environmental pollution
Q: What are some of the challenges for logistics and transportation companies related to big data?
A: Logistics supply chain networks not only optimize internal operations, but also interoperate with external networks. These logistics networks are analogous to internetworking, defined as the connecting of two or more distinct computer networks or network segments via a common routing technology, such as the Internet.
Designing, building, and operating this new class of networks makes it necessary to introduce a new framework we call “logistics internetworking.” Logistics internetworking ties together infrastructure, data, information, workflow, and even policy governance for interoperability.
Q: How can companies use mobile technology solutions to gather and interpret information to drive improvements in business performance?
A: Smart chips, microscopic computers, and sensors will permeate the physical supply chain, including items, pallets, containers, ships, trucks, and planes. New software will then automate processes and workflows that are now either paper-based or human-based.
This technological surge will close the gap with the logical or information supply chain, fusing the two into a cohesive neural supply chain.
In addition to data fusion, there is process fusion—such as standardizing processes and understanding the various interlinked processes. This provides operations visibility across the entire process chain, which can improve all logistics-related functions, such as:
- Distribution center sort optimization
- Back-haul activities
- Revenue and fuel management