Trucking and big data: When data meets the road

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  Quantumrun Foresight
• July 25, 2022

Insight summary

The trucking industry is increasingly utilizing big data and artificial intelligence (AI) to enhance safety, efficiency, and decision-making. This technology shift enables better management of logistics, predictive vehicle maintenance, and improved customer service. These advancements are also leading to smarter, more autonomous fleets and requiring new infrastructure and cybersecurity measures.

Trucking and big data context

The COVID-19 pandemic, while slowing down many sectors, had an unexpected effect on freight services. Trucking companies began to recognize the importance of big data in enhancing their operations. This shift was driven by the need to adapt to changing market demands and ensure efficient service delivery. Big data, in this context, serves as a pivotal tool for optimizing routes, managing inventory, and improving overall logistics efficiency.

Big data in the trucking industry comprises a wide array of information sources. These sources include sensor logs, cameras, radar systems, geolocation data, and inputs from mobile phones and tablets. Further, technologies such as remote sensing and the Internet of Things (IoT), particularly communications between vehicles and infrastructure, contribute to this data pool. This data is complex and voluminous, often appearing random and unstructured at first glance. Yet, its true value emerges when AI steps in to sift through, organize, and analyze these data streams.

Despite the potential benefits, many trucking companies often struggle with understanding the intricacies of big data and implementing effective strategies to harness it. The key lies in transitioning from mere data collection to advanced stages of data utilization, including moving from basic observation to detailed diagnostics, followed by predictive analysis. For transportation companies, this progression means developing a comprehensive transportation management system that can also optimize the performance of their entire vehicle fleet.

Disruptive impact

Telematics, encompassing technologies like the Global Positioning System (GPS) and onboard diagnostics, is a key area where big data is exceptionally valuable. By monitoring vehicle movements and driver behaviors, telematics can significantly enhance road safety. It helps identify risky behaviors such as drowsiness, distracted driving, and erratic braking patterns, which are common causes of accidents leading to financial losses averaging USD $74,000 and damaging a company's reputation. Once these patterns are pinpointed, they can be addressed through targeted driver training and technological upgrades in fleet vehicles, such as advanced braking systems and road cameras.

In freight and logistics, big data analysis plays a crucial role in strategic decision-making. By examining freight patterns, companies can make informed decisions about pricing strategies, product placement, and risk management. Moreover, big data aids in customer service by organizing and analyzing customer feedback. Recognizing repetitive complaints allows companies to swiftly address issues.

Another significant impact of big data in the trucking industry is in the maintenance of vehicles. Traditional approaches to vehicle maintenance often rely on predetermined schedules, which may not accurately reflect the current condition of the equipment. Big data enables a shift to predictive maintenance, where decisions are based on the actual performance of vehicles, detected through data analytics. This approach ensures timely interventions, reducing the likelihood of breakdowns and extending the lifespan of the fleet. 

Implications of trucking and big data

Wider applications for big data use in the trucking and freight industry may include:

• Enhanced integration of AI with trucking fleets, leading to more efficient and autonomous vehicles capable of adapting to various scenarios.


• Development of specialized infrastructure, including sensor-equipped highways, to support IoT technology in trucking, enhancing real-time monitoring and data collection.


• Increased investment in telematics and big data management software by supply chain companies, focusing on cybersecurity to protect against threats that could disrupt transportation networks.


• Reduction in emissions from the trucking industry as big data enables more efficient route optimization and the use of autonomous vehicles reduces fuel or electricity consumption.


• Potential increase in the overall use of transportation networks as they become more efficient, possibly offsetting the environmental benefits gained from emission reductions.


• Creation of new job roles focused on data analysis, cybersecurity, and AI management in the trucking and logistics sectors.


• Changes in trucking business models, emphasizing data-driven decision-making and technology integration, leading to heightened competition and innovation in the industry.

Questions to consider

• How else do you think big data can improve freight services?


• How can IoT and AI change how goods are delivered in the next five years?