Technology Solutions in Freight Management

Understanding Technology’s Role in LTL Shipping

Technology in LTL shipping helps enhance efficiency, visibility, and cost management while streamlining LTL operations and improving service reliability for both shippers and carriers. 

Shippers have access to a huge array of tech options today, and the number of solutions available is only growing. Understanding the role they each play in LTL shipping, as well as which to choose, can be intimidating. 

Examples of freight tech include: 

• Transportation Management Systems (TMS) – Helps shippers and 3PLs plan, execute, and optimize LTL shipments while tracking costs and performance.

• Application Programming Interfaces (APIs) – Enables real-time rate quoting, carrier selection, and tracking integration between shippers, carriers, and logistics providers.

• Electronic Data Interchange (EDI) – Facilitates automated communication between shippers, carriers, and customers for load tenders, invoicing, and status updates.

• Real-Time Tracking & Telematics – Uses GPS and IoT sensors to monitor shipment locations, estimated arrival times, and environmental conditions (e.g., temperature-sensitive freight).

• Artificial Intelligence (AI) & Machine Learning – Enhances route optimization, predictive pricing, and demand forecasting to reduce costs and improve efficiency.

• Load Optimization Software – Helps maximize trailer space utilization by analyzing freight dimensions, weight, and stacking configurations.

• Automated Freight Auditing & Payment Systems – Ensures accurate billing and reduces errors by matching invoices with shipment data.

• Warehouse & Dock Management Systems – Streamlines LTL freight handling, cross-docking, and scheduling at distribution centers.

Taken individually, each piece of freight tech is unique, but by looking at the bigger picture, we can see that all of them are geared toward addressing a common set of challenges for shippers. The simplest way to understand the role of freight tech is in terms of what problem they are designed to solve.

• Lack of Location Data – APIs and AI can address a lack of location data, among other things. AI fuels software like Shiplify, determining location attributes with a high degree of accuracy, while APIs help you integrate that data into your other systems. 

• Outdated Information – Real-time tracking and telematics to provide up-to-date information and transparency around shipment locations, movement, and arrival times. EDI can communicate these updates automatically. 

• Inaccurate Billing – Automated freight auditing and payment systems do the manual work of double-checking invoices against shipment data, sometimes supplemented by AI and machine learning. 

• Wasted Space – Both TMS systems and load optimization software can help shippers get the most out of their truckloads by helping plan shipments, analyzing the items being shipped, and making recommendations to assist in configuring the items most efficiently.

• Shipping Inefficiency – Any stage of the supply chain has the potential for inefficiency, but shippers are most affected by inefficiency in route planning and delivery. TMS systems are designed to help optimize routes, while warehouse and dock management systems assist in streamlining the processes involved in delivery.

• Disjointed Tech Stack – This is where APIs really shine, creating integrations between solutions (e.g. between your TMS and real-time tracking programs) as well as between the parties involved in the process. APIs transform your communications solutions into a holistic system that is greater than the sum of its parts. 

When it comes to freight challenges, so many of the most common issues are intertwined, overlapping and feeding into each other; when one part of your system falls short, the rest is at risk. This is why so many freight tech solutions have significant overlap, often supplementing each other—because the ideal outcome is a unified system that serves every part of the shipping process. From planning the way boxes will be loaded onto the truck to scheduling deliveries at distribution centers, a high-quality tech stack can create a shipping process that is transparent, streamlined, and accurate. 

Evolution of Freight Technology

1950s – 1970s

• Warehouse Automation originated in the 1950s, became more widely adopted in the 1960s, and saw the introduction of computer-based solutions in the 1980s.

• Electronic Data Interchange (EDI) has its roots in the 1960s and rail transportation.

• Transportation Management Systems (TMS) were developed in the 1970s, and adoption was facilitated throughout the 1980s by the spread of ERP systems. Cloud computing increased adoption even further in the 2010s.

1980s – 1990s

• GPS Tracking emerged in the 1980s and was first used by civilian companies for vehicle fleets in the 1990s, albeit at a steep cost of entry.

• Telematics Systems were invented in the 1960s but not used in freight as we understand it until the 1990s. 

2000s

• Internet of Things (IoT) integration began with the development of RFID chips in the early 2000s and has advanced significantly with the rise of more advanced tracking and monitoring systems.

• Autonomous Vehicles were functional by the 1990s and used for hauling by the mid-2000s, though they would not be used for freight delivery until the later 2010s.

2010s

• Mobile Applications were originally developed in the 1990s, but the advent of smartphones and mobile data ushered in their use in freight operations.

• Online Package Tracking was heralded by free email updates on shipments in the 2010s, eventually evolving into the real-time monitoring used today.

• Big Data Analytics gained a foothold in the shipping and logistics industry in the 2010s as companies began to understand the value of collecting and analyzing large data sets.

• Blockchain Technology began to be used in the supply chain industry to tokenize transaction-related data in the late 2010s and early 2020s.

• Location Types Identification was pioneered by Shiplify in the 2010s, along with their first API.

2020s

• Dock + Forklift Identification was introduced by Shiplify, marking the next step toward its current offerings of real-time, AI-powered location data.

• AI/Advanced Machine Learning, which dates back to the 1950s in its earliest iterations, caught on and began to be leveraged to its current potential for freight in the 2020s. The full scope of its potential is still being explored today.