ClearConnect Solutions Blog

Predictive Analytics and Risk Management in Commercial Transportation

Big Data in Commercial Transportation

In 2019, the FMCSA’s mandate of Electronic Logging Devices (ELDs) essentially kicked off the rapidly developing use of data analytics in commercial transportation. Today telematics technology is delivering even greater amounts of useful data to fleets, insurance providers, and their underwriters. ClearConnect Solutions is mission-driven in providing this type of business intelligence to its clients.

“Something unexpected always happens on the road.”

Dave Heller, Senior VP of Safety and Government Affairs at Truckload Carriers Association

From his seat as Chief Technology Officer for VBE Technologies and as project-based Chief Software Architect for ClearConnect Solutions, Georg Kaufmann and the development team for ClearConnect Solutions create data analytics products for commercial trucking insurers and motor carriers. The team pairs vehicle telematics data – that records speeding, cornering, and braking actions of trucks; monitors driver behavior; and reports vehicle performance – with large data sets from the Federal Motor Carrier Safety Administration (FMCSA) and other reliable sources to identify, analyze, and predict risk in fleet operations. Proactive measures can then be implemented to mitigate those risks. 

“This movement towards more data collection will undoubtedly provide opportunities and solutions much like the ones we’re developing within ClearConnect Solutions to determine the probability of a crash based on hundreds of different data points. This, above all, will help save lives but also help drive down the insurance costs for the commercial transportation industry, more specifically for the fleets that operate the most safely.”

Georg Kaufmann, Chief Software Architect, ClearConnect Solutions

Data Sources to Identify High Driver Risk

Across the freight transportation industry, data analytics is evolving into a more valuable and necessary tool as the amount of reliable driver data grows. In fact, according to a research report, “Future of Commercial Vehicle Telematics Market…” the global commercial vehicle telematics market size is expected to grow from 5.4 billion USD in 2024 to 12.8 billion USD by 2030 – a 15.2% CAGR. 

Data sources that are used to build risk assessment and predictive analytics models for commercial fleets and their insurers may include not only vehicle telematics data, but also:

• Driver logs (from ELDs

• Fleet telematics

• Dash cameras

• Motor vehicle records (MVRs)

• Vehicle maintenance logs and past issues

• Historical incident and crash data

Additional data points outside of the vehicle, driver, and fleet may include real-time and historical weather conditions along routes, and historical and actual traffic data and road conditions. A 360-degree approach such as this with combined data provides a more accurate assessment of driver and fleet risk.

Benefits of Predictive Analytics in Fleet Management

A combined-data approach that results in more timely, accurate, and predictive analytics offers numerous benefits when it comes to managing risk.

Operational efficiency may improve when business intelligence helps fleets minimize delays due to traffic, weather, or mechanical issues.

Lower premiums can be negotiated when driver safety is proven through a well-documented, data-driven risk profile.

Accidents may be reduced. Data showing high-risk driving behaviors is key to predicting accidents. Addressing risky driving behaviors with targeted safety training and real-time alerts is proven to lower accident rates.

Insurers working with fleet operators recognize the significant role of data in fleet management. Predictive analytics can save lives as well as costs for insurance companies and trucking companies alike.

Risk Management Evolves in Commercial Trucking

The growing amount of data available to insurance providers, underwriters, and fleets allows for an evermore clear picture of real-time driver risk and an increasingly valuable methodology to manage that risk across a fleet. Risk management will become more targeted and predictive as the pool of quality data points – and our ability to connect and analyze those data points – grows.

In a Risky Business Season 1 episode with ClearConnect Solutions co-founder and President Scott Grandys in conversation with Dave Heller (Senior VP of Safety and Government Affairs at Truckload Carriers Association) the subject of safety, driver behavior and training was discussed. As new drivers come into the industry, data can provide a standard and profile to train to. The testing of new drivers, as well as experienced drivers, can help to see where they fit into the safety spectrum. Engaging with telematics technology is a key component of defining the standard.

“Data is the new oil,” says Heller. “This is the 21st century trucking industry, where we are now generating so much data that people (i.e., insurance industry, fleet operators) can define what their driving population should look like and what their safety performance should be.”

– Dave Heller, Truckload Carriers Association

Heller continues, “Predictive analytics is starting to evolve and impact trucking…we now have the technology to examine the data around safety performance. If you don’t do something about it, there is a propensity for something else to happen…..using the data presented we can instill a better driving population in our fleets…”

There is tremendous opportunity for improvement, where we have 50,000 accidents on our highways on a yearly basis…. let’s use the data to our strength and create better performing drivers in the safety area.” 

Risk mitigation strategies that can be developed based on analytics generated insights include:

• Driver training improvements and interventions that are targeted toward unsafe behaviors as suggested by the data.

• Better vehicle maintenance based on performance data that prevent equipment failure and/or breakdowns.

• Route optimizing to avoid road issues, weather problems, or areas of high risk for accidents.

• Safety regulations compliance monitoring.

• Better dispatching. Load assignments can be optimized considering route conditions or predicted driver fatigue issues.

Machine Learning Plus Big Data

The machine-learning, large data combination is key to effective predictive analytics. For software architect Georg Kaufmann, “it’s all wrapped up in gathering more data to feed the machine so we can start to analyze the risk from a detailed fleet, truck, or driver perspective. Prior to these advances in telematics and technological solutions, this type of analysis was next to impossible,” says Georg. 

What does the future hold for carriers and trucking insurers in new technologies and the applications of data analytics? Kaufmann believes that with the combination of increasingly relevant data with the upside potential of machine-learning, we will begin to see how far off we are from our risk-scoring algorithms – and calibrate them with more accuracy. “When we have more data it will improve what we have…not only saving money, but more importantly saving lives.” Kaufmann continues, “Without a doubt the fleets and insurance companies unwilling to adopt the new technology and open their business to data collection and analytics will be left behind. Once insurance companies see fleets utilizing this technology and opening it up to companies like ClearConnect Solutions to provide risk insight against, rates will be impacted in a positive way for those fleets. Saying your fleet practices safe driving practices is one thing, showing it through your data, however, is going to be what separates the good from the bad. As fleets learn that their insurance costs could go down and their drivers will be better protected, they’ll be more inclined to invest in technology that helps to facilitate that.”

Costs and training time seem to be two obstacles to obtain widespread acceptance and adoption. Finding the path to help smaller fleets and owner-operators adopt the technologies and resultant safety benefits and savings may be a worthy endeavor across the delivery industry.

As Dave Heller observed, “Something unexpected always happens on the road.” The current trends in telematics technology generating higher volumes of data, combined with greater computing power, data overlay, machine-learning, and predictive analytics are all helping the trucking industry minimize the unexpected.

If you’d like to learn more about data analytics and predictive risk technology, contact Specialist Nick Rice at nrice@clearconnectsolutions.com.

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