The evolution of big data in logistics is allowing providers and shippers to access valuable information pertinent to their supply chain. However, harnessing this data and using it strategically is equally vital to achieve desired business solutions. Whether you’re a small business shipping within Canada, or a big box retailer with high volume international shipping orders, big data continues to expand opportunities, from forecasting ways to save money on shipping to a multitude of other applications.
Big Data in Logistics is King
Traditional data is a collection of information on the past year or month’s profits, salaries, freight rates, mileage and insurance. While big data in logistics is an extensive volume of real-time information using GPS tracking devices, sensor technology and other applications that detect everything from traffic at the next stoplight, to the dock loading time of your shipment, to a tire that suddenly needs air pressure. This prevents avoidable delays, enhances transit times, and increases safety measures. For example, Japan’s Fujitsu Laboratories has created a technology that analyses ship-related big data to estimate fuel efficiency, speed and other performance in real sea conditions, revealing under a less than five percent margin of error.
We know that increased sensor tracking and analytics dramatically aids in visibility and alleviates risk for both the shippers and their customers. Since approximately 1,679 shipping containers are lost each year, increased sensor technology and tracking data is a game changer, minimizing losses and ascertaining conditions that led to the loss, such as wind conditions or humidity. In the trucking industry the main reasons for loss or damaged goods include Collision, upset or overturn, theft, cargo handling or spoilage, so the increase of sensor data has potential to detect and reduce these risks.
Future Trucks and Ships
Big data can help shape the future development of ships and transport truck designs. Utilizing information from previous vehicles and vessel models, analytical data can be used to enhance safety features and create more robust and efficient designs that can sustain impact and veer from obstacles. There is also opportunity to use this data in conjunction with the development of autonomous ships and trucks, incorporating geographic coordinates and responding instantly to weather conditions and other metrics.