Since the dawn of the internet, the ability to collect data has increased at an astounding rate. In 2008 the number of digital information pieces (bits) surpassed the number of stars in our universe. Since the introduction of GPU (Graphics Processing Unit) to the logistics industry, the use of big data has been enhanced dramatically. GPU allows companies to process large amounts of data, advanced analytics performance, and use AI (Artificial Intelligence).  

Big Data collection continues to double itself every two years, but does the logistic Industry know how to use it and where does all this data come from?

Big Data Sources for The Logistics Industry:

• Traditional enterprise data collected from operational systems
• Traffic & weather data collected from sensors, monitors, and forecast systems
• Vehicle diagnostics, driving patterns, and location information
• Financial business forecasts
• Advertising response data from all forms of digital advertising and marketing
• Website browsing pattern data
• Social media data collected through the vast array of platforms now available

1. Big Data Saves Money by Optimising Travel Routes

There are 3 main ways that big data can impact travel routes:

• Avoids late shipments by improving travel routes used by logistics companies.
• Saves money by minimising resources used to deliver shipments and allowing for more accurate resource estimates.
• Minimises the company’s carbon footprint by finding shorter routes using less fuel.

2. Last Mile Supply Chain Efficiency

It is well known in the logistics industry that “The Last Mile” of the shipping supply chain is very inefficient, often costing 28% of the total delivery cost. 

The good news is that last mile analytics are generating very useful data for logistics companies. Because of the low-cost convenience of fast mobile internet and GPS-enabled smartphones, as well as the spread of the internet through sensors and scanners, merchants can see the delivery process take place from start to finish, including the last mile!

3. Fresh Goods Arrive Fresh

The challenge of shipping perishable goods is made easier with the use of big data. Temperature sensors can alert drivers and managers of important information, traffic reports can help get a delivery to its destination faster, and roadworks can be avoided and all using a central routing computer.

4. Reliability Will Be More Transparent

Sensors have become more common in transportation and throughout the supply chain. These provide data facilitating greater transparency than has ever been possible.

Transparency is of great value to shippers, carriers, and customers. The sooner a carrier is aware a shipment is going to be late, the easier it is to prevent a bottleneck further down the supply chain. In turn, this information can be used by carriers to negotiate with shippers who are consistently late with deliveries. 

5. Automation and AI Capabilities

Big data combined with automation technology and the Internet could potentially turn logistics into an entirely automated process. Big data allows automated systems to function through intelligently routing many different data sets and data streams.

Some companies are already using robots to grab items from shelves, drones for fast delivery and there are even test runs for self-driving vehicles. 

Of course, we will always need a human component but we are on the edge of a huge change in the logistics industry. Forward-thinking logistics companies are already benefiting from big data using resources.