Saving Trucking Costs: How Can Your Data Help?

Asparuh Koev
Asparuh Koev

Among all the industries in which AI technology will advance, trucking is set for a dramatic revolution. It is estimated that advanced analytics will save truckers $168 billion by optimizing routes and enhancing fuel efficiency.

However, AI is not some sort of magic silver bullet. Optimizing logistics with AI relies on leveraging data. With accurate data and robust data analytics software, industry leaders can fulfill transportation duties without losing profit, identify efficient driver behavior, and strengthen back-office activities to improve fleet KPIs. Here’s how.

Synchronize Data From TMS and Telematics

Moving trucks around without losing profit requires complete insight into transport costs. By monitoring telematics such as video dashcams and GPS trackers, logistics planners gain insights into optimal routes and can unravel the causes that led to costly delays. 

While telematics software provides logistics teams access to real-time data on road conditions, driver behavior, and truck location, transport management systems (TMS) provide historical data on operations, past trips, and current scheduling. 

However, having these systems siloed makes it easy to miss vital updates and leads to many time-consuming activities to comprehend truck location and adjust schedules accordingly. On top of that, some companies still rely on Excel and manual methods to keep track of some information, making operational data even more fragmented. According to Gartner, only 7% of supply chain leaders have the information they need to execute decisions in real-time.

Instead, logistics planners must centralize telematics and TMS data to cross-analyze insights in one place, visualizing the data using powerful analytics dashboards. With granular traffic and location details demonstrated in a user-friendly format, logistics planners can realize upcoming hurdles at a glance, enabling them to act in advance — and optimize routes to keep costs low. 

Leverage Data To Identify Points of Improvement for Drivers

Once logistics planners integrate their telematics data with their TMS, they can start assessing key transportation cost drivers. According to 2022 ISAAC research, driver behavior accounts for up to 30% of fuel costs. Therefore, improving driver performance can eliminate these expenses while increasing driver safety. 

Say truckers are breaking heavily and revving in traffic; they can dramatically bump up fuel costs — not to mention accelerating the wear and tear of tires. Analyzing driving patterns can determine the effects on trucks’ functionality while identifying best practices to help truckers drive safely. 

Logistics planners measuring driver behavior must look at KPIs, including on-time delivery, idle time, speed, mileage, and fuel consumption, among others. Understanding the relationship between these critical metrics will demonstrate how drivers can ensure timely delivery and be on top of their performance, whether in specific weather conditions or on lengthy trips. 

Strengthen Back Office Activities

It’s fair to say goods wouldn’t move without truck drivers; however, another more silent but crucial part of the team sits in the back office. 

Dispatchers, logistics planners, and bookkeeping staff must receive load instructions and look at everything from petrol bills to maintenance compliance to customer satisfaction. They rely on drivers to deliver goods on time, complete inspections, and document them. Therefore, calling drivers about missing or illegible paperwork and requesting updates on their load status comprise a big part of logistics planners’ day-to-day. Put simply, automation can help resolve administrative workflow disruption. 

Furthermore, the sales agents can automate some of their activities with the new developments in Generative AI. The AI system can receive requests for quotes, understand the human language behind them, and transform them into relevant and fair offers by cross-checking them with the financial system and historical contracts. Then, the sales agent can review the suggested offer and accept or amend it so it is confirmed with the client. In addition, it can also centralize the data gathering on the quote processing and identify the points of improvement while streamlining the sales process.

Contrary to popular belief, the human role becomes more vital in the face of automation since it takes experienced workers in the trade to know all the finer details — like equipping drivers with safety boots for heavy-duty vehicles — something that AI cannot do. For this reason, saving trucking costs with data is triple-fold: trucking companies need to invest in AI, centralize their data, access insights in the powerful dashboards, and train back office staff to govern these intelligent systems.

Automation is invaluable in boosting company productivity, reducing costs, and elevating customer satisfaction. Logistics planning teams who integrate live truck tracking data with TMS can streamline operations to maximize profits. They can assess the impact of delivery timeliness, receive updates in real-time to keep customers in the know, and schedule routes effectively to eliminate additional costs. 

Author Bio

Asparuh Koev is the CEO of Transmetrics, a Bulgarian tech company aiming to optimize logistics planning and asset management using the power of predictive analytics and artificial intelligence. He is a successful serial entrepreneur with Almost 20 years of experience with IT projects for leading logistics companies and a proven record of building companies and leading them to success. His extensive experience includes 12+ years in leading roles for Sciant AG and founding and managing IntelliCo Solutions AG. Asparuh holds a MBA from Vlerick Leuven Gent Management School in Belgium.

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Header Image by Marcin Jozwiak on Unsplash

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