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Understanding the Challenges and Possibilities of Transportation Company Data

As wider adoption of advanced technology continues to transform transportation companies into data companies, new challenges are emerging. Data management, analysis and visualization are just a few of the capabilities that have quickly become essential for businesses to master in order to stay competitive in the connected supply chain.

According to a 2023 survey from McKinsey & Company, “Both shippers and providers have grown their investments in digital logistics since 2020, across all technologies. Some 87 percent of shippers reported maintaining or growing their technology investments since 2020, and 93 percent said they plan to maintain or increase their spending over the next three years.” How can transportation companies make the most of that technology investment and the mountains of data it will produce?

Understanding the Data Sources

Transportation companies of all sizes continue to adopt and use technology to improve productivity, efficiency, service and safety with an eye toward growth and profitability. As a result, the amount of data generated by technology use continues to grow. There are also many data sources that are external and ancillary to the transportation business—think state and federal government agencies and insurance providers, among others—that generate and use data received by companies and that affect the company’s ability to operate successfully and profitably. 

The trend in transportation is clear: data is changing the transportation game, and the rewards of effectively understanding and using the right data, whether it is generated internally or externally, can be substantial. Think about the data transportation businesses generate or access on a regular basis. When hiring drivers, trucking companies obtain employment history information from past employers, prior accident history from various sources, drug and alcohol testing history from the national clearinghouse, MVRs from State agencies, pre-employment screening program (PSP) reports from FMCSA and criminal and credit history reports, among others.

On a regular basis during a driver’s tenure, companies generate or receive driver hours of service and ELD data, driver scorecard data, information from CDL license notification systems, fuel mileage reports, video data on captured events, pickup and delivery time reports and customer feedback among others. Regarding vehicles, companies generate telematics reports that include vehicle location, speed, acceleration, hard braking, etc., sensor data from advanced driver assistance systems, transponder and bypass system reports, tolled highway reports, vehicle fault codes, driver-vehicle inspection reports and maintenance and repair records just to name a few.

On the operating side, companies generate on-time data and reports, empty mileage reports, OS&D data, fueling and fuel economy reports, customer service reports, financial reports, internal audit reports and CSA-related reports and data among many others. 

Adapting to the Data-Driven Reality

The volume of data generated is just one of the management challenges transportation companies face. This challenge is compounded by the fact that many data points are generated, received and used in different parts of an organization.

For example, much of the driver data is generated in the safety and human resources departments, the vehicle data is generated in the maintenance department (and perhaps by outside maintenance and repair vendors) and the operational data and reports are created and received by the operations and finance departments. Adding further to the data management challenge is the frequency with which data is received, whether it is throughout the business day, weekly, monthly or irregularly.

As DHL put it in a recent article titled, “Big Data in Logistics: What Is the True Value of Data?”: “Data is initially just a raw material like rough diamonds – its value is inherent, but without systematic processing it is as worthless as a rough diamond is unsuitable for a diadem. The data information must be merged with experience and expertise to generate exploitable knowledge via big data analytics.”

There are many ways transportation companies successfully manage their data and it’s likely there is no single formula for success.  However, there are a few strategies successful companies have employed. For example, a common approach for many is to create an internal data management team that is tasked with cataloging the many data sources and data points generated throughout the organization. Oftentimes these data management teams are intentional and structured about how they approach their tasks and develop an overarching data management plan to include retention and purging policies.

Prioritizing the data and determining which data points support the company’s key performance indicators is another common approach and task for the team. An outcome of this strategy is often a determination of which data are ‘actionable’ and which data points likely fall into the ‘noise’ category.  Integrating actionable data from various parts of the organization, and from various platforms (think HR, safety and maintenance), into a single data dashboard often helps in benchmarking and assists management in visualizing trends, and to make decisions based on them.

This strategy is often coupled with a consistent cadence for data collection, reporting and trend analysis. And, creating an awareness and communications campaign along with training for drivers and staff that focuses on the prioritized, actionable data drives everyone in the same direction with a consistent and transparent set of goals and objectives.

Moving Forward

Simply put: the amount of data modern transportation companies are generating is a lot to take in, and quickly becomes overwhelming. It’s clear that data management challenges for transportation businesses can be substantial. But there’s great opportunity for enhanced safety, productivity and operational efficiency.

From preventative maintenance to route planning, safety training to customer satisfaction, the data a company generates has tremendous potential to apply important insights gleaned from the data a company produces. Businesses that understand how important data management is, and those that successfully navigate data challenges by integrating platforms and using strategies to focus on meaningful and actionable data will continue to gain an advantage in the marketplace and differentiate themselves from their competitors.

Want to make the most of your data? Contact us to learn how Trimble Connected Cloud can integrate your systems to provide you a single point of insight and analytics.

About the Author

Stephen A. Keppler - Co-Director, Scopelitis

This piece was produced in collaboration with Stephen Keppler, Co-Director of Scopelitis Transportation Consulting LLC. Stephen has more than 30 years of transportation industry experience, including time as an investigator, inspector and policymaker for the Federal Highway Administration’s Office of Motor Carriers (predecessor to the FMCSA). He has also held executive leadership positions at the Intelligent Transportation Society of America, the Commercial Vehicle Safety Alliance and the Intermodal Association of North America. Follow him on LinkedIn or get in touch at