Automated Supply Chain Logistics: All About the Data

To take supply chain logistics to the next level and incorporate AI intelligence, the data coming in throughout the supply chain needs to be reliable, consistent and accurate.

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When it comes to getting goods from one place to another, the supply chain has a large number of players and many moving parts. No one party handles the entirety of it – there are distribution centers, carriers, ground handlers, crossdock/CFS operations and a variety of trucking companies that handle cargo through their facilities and conveyances before arriving at the final destination.

Each of these different companies have their own way of handling cargo, recording the activity and providing visibility to the tracking data. Further adding to the complexity, even within one company, operational processes and systems can vary from country to country.  With so many parties involved in the process there is really no single source of truth for tracking data. 

To manage the complexity, tracking agents, yes there are such people with this responsibility, use their internal systems populated with integrated data, validated and updated by carrier or terminal websites, further vetted by email requests, and when necessary, by phone call. To keep track of the different threads of communication and updates, often tracking is moved off-line and maintained in a spreadsheet. And while attempts have been made to automate and seamlessly integrate various computer systems, if the data is wrong or incomplete to begin with at any single stage of the process, human intervention is still needed. This results in excess time spent, cargo delays, lost items and ultimately unhappy customers.

Today companies spend a lot of time, energy and money on tracking shipments to provide good information to their customers. The job necessitates intimate knowledge of which carriers and geographies provide reliable tracking data. The reality is this industry requires a lot of human intervention trying to piece together a puzzle that ultimately tells the customer where their cargo is.

To ever get to a single source of tracking data means generating that data in a whole new manner. And to even take supply chain logistics to the next level and incorporate AI intelligence, the data coming in throughout the supply chain needs to be reliable, consistent and accurate.

Until recently there were no significant technology advancements to really make this possible. Now with the availability of smart labels and the advances in IoT batteries, getting to this single source of truth at a piece level can happen and make measurable impacts on logistics.

For logistics data to be complete and reliable, shipments need to be tracked consistently throughout the supply chain– it cannot just happen on one leg of the journey. Cargo forwarders, crossdock facilities, carriers and others need to be onboard to standardize the tracking of every piece of a shipment across the different modes of air, ocean, rail and ground, around the globe.

Bluetooth and 5G labels can now be adhered to each piece of a shipment and provide alerts the moment a shipment arrives or departs a warehouse or waypoint, or an exception is detected. They also generate inventory counts, providing a complete warehouse audit in real time. Logistics providers and cargo forwarders can finally know where every piece is in the supply chain with 100% accuracy.

Once data is being collected in a complete and consistent way throughout a shipment’s journey at the piece level, problems can be addressed in real time.  For example, if there is a 5-pallet shipment on route to a warehouse in Ohio or Poland and one pallet gets left behind at a cross dock facility, warehouse operations can be notified in real time that a piece was left and to correct the short shipment immediately. Whereas previously, the missing pallet can go unnoticed for days with the customer complaining of a short shipment and all parties involved having to perform physical searches and consulting CCTV to see where the pallet went missing and who was responsible for the short shipment.  

Having reliable data in place means you can apply advanced routing capabilities, such as building AI agents with sophisticated logic to reroute a shipment through a different port if that port is congested and will delay the expected delivery date. But if your underlying data is suspect, you can’t trust that the system is telling you where something really is and can’t build advanced algorithms or AI agents on top of it.

Companies need to have reliable data throughout the supply chain – no matter the mode of transportation, the type of shipment, or the geography. It should all be consistent and treated the same. Smart labels and IoT are a big step toward getting one reliable source of truth of tracking data at any given point in the supply chain and are the first step the industry needs to take before considering applying other forms of automation and AI to the process.