Global SafeDrive Alliance™ To Demo Interactive Global Data Reporting Dashboard At 2017 NAFA Conference



Trevose, PA, April 17, 2017 – The Global SafeDrive Alliance™, formed by three leading fleet driver safety companies, to deliver the first turnkey, fully integrated multinational fleet safety program, will demonstrate its new global reporting dashboard at its booth #140 at the NAFA Institute and Expo. The conference runs from 4/23 – 4/26 at the Tampa Convention Center in Tampa, Florida.

The CEI Group, Inc., CEPA SafeDrive, and VVCR International formed the alliance last fall, and development of the global reporting tool addresses a significant challenge for multinational fleet managers, says Fernando Cammarota, CEO of CEPA International.

The global reporting platform includes reports on accident rates, injuries, accident types, preventable vs. non-preventable accidents, driver training compliance rates and customized benchmarking criteria, among others. Regional and local reports are accessible through pertinent alliance member links.

Global SafeDrive Alliance Dashboard
Global fleet performance reports can be viewed
from the Alliance’s reporting dashboard.

Representatives from each Global SafeDrive Alliance member will be on hand at the NAFA conference to discuss and present all aspects of the global reporting portal.

About CEI
CEI, a fleet driver management company, is a leading provider of technology-enhanced driver safety, fleet risk management, and vehicle accident services. DriverCare™ Risk Manager, CEI’s online safety service, centrally houses all of the tools and information used to create risk levels for drivers and managers. Always evolving the DriverCare product lineup, CEI leverages the latest technologies in ways that save fleet managers and driver’s time, while also finding the drivers who need to improve. Using continuous monitoring, telematics, and prescriptive analytics allows CEI to find “hidden” at-risk drivers before they run into problems. CEI consults with clients to help provide solutions that change driver behavior and reduce accidents.

Founded in 1983, CEI has headquarters near Philadelphia, PA, and field sales offices in Trevose, PA; Tulsa, OK; Atlanta, GA; Dallas, TX, and Minneapolis, MN. In 2000, CEI launched its DriverCare™ solution, which includes fleet risk management, MVR ordering and compliance, on-line and behind-the-wheel driver safety training
and a safety newsletter. For more information about CEI, please visit .

About CEPA SafeDrive
Based in Brazil and with offices in five countries, CEPA (Centro de Prevención de Accidentes) has been a leader in Fleet Safety in 28 countries across Latin America and the Caribbean since 1987. Specialists in road safety and risk management, it has developed and operated programs for small, medium and large fleets for all classes of vehicles, from sedans to buses, vans, trucks and motorcycles. For more information, please
visit .

About VVCR International
Headquartered in the Netherlands, Europe, VVCR International has been a leading driver training and fleet risk management business since 1972. Today, it has customers in more than 95 countries and provides solutions in over 35 languages. VVCR specializes in using behavior-based, scientifically proven methodologies to deliver consistent and quality-controlled global driver safety programs, with special experience in Europe, the Middle East, Africa and the Asia-Pacific region. For more information, please visit .

# # #

Any questions regarding this release can be directed to
Kevin Reilly, Editorial Communications Manager, The CEI Group, Inc.
Office: (215) 485 – 4241
Mobile: (267) 453 – 1862
4850 E Street Rd. #200
Feasterville Trevose, PA 19053

Attacking a Fleet’s Pain Points with Targeted Training Provides Short-Term Milestones on the Long Road to Total Fleet Safety

March 2017

Driving down accident rates requires a great deal of time and patience, but what is a fleet manager to do when faced with the expectation of providing results within a single year? Typically, it takes at least three years for a fleet to bring their accident rates down by any significant measure. The long wait is not for lack of trying, but fleets need time to introduce training to their drivers in incremental stages. If training is overloaded, it would be foolish to expect the drivers to have a high retention rate for that knowledge.

This brings us to our biggest question: what is the best method to drive down accident rates with a lasting impact that can begin to take hold in the short term? We will start with short term solutions to pain points and work our way into methods that will help make training stick.
Finding Short Term Milestones

The best way to see year-end results is to pinpoint the types of accidents that are hurting a fleet the most. These recurring accidents are a fleet’s pain points, and if the fleet doesn’t address these pain points, they will never fully realize their long-term safety goals. As a prime example, I will detail how one sales fleet of mostly sedans was able to drive down rear end collisions over the course of a year through a targeted campaign, and how they look now.

This fleet asked CEI to take a look at their accidents to find any broad sweeping trends in their fleet’s overall accident history. Research found that this fleet had 20% of their claims stemming from rear-end accidents. To be fair, national data points out that rear-end collisions in the United States tend to make up about a third of all accidents.

In an effort to combat the large swath of accidents occurring from rear-end collisions, CEI built a custom module for the fleet to address the issue. The module was titled, “Avoiding Rear-End Collisions – What You Can Do” and was administered to the entire fleet with a one month grace period for all drivers to complete the module.

Some of the topics covered in the module included defensive driving techniques like coming to a stop at 30% braking power, being sure to avoid distracted driving, and always using turn signals. While these practices seem obvious, many drivers forget these tactics during their daily commutes. Whenever training is assigned for driving it is important to remember that the skills must be practiced every time the driver gets behind the wheel before the training can fully take hold.

Results After a Full Year

Twelve months after every driver completed the training module there was a marked decrease in rear-end accidents, from 20% down to 16%. During this time, the fleet’s overall claims actually increased, but it was clear that the drivers had applied the lessons taught regarding rear-end collision avoidance. The best improvement was the tremendous reduction in preventable rear-end incidents, at a 30% reduction. Non-preventable rear-end collisions also went down 14% during the same period. The reductions prove that focusing on one pain point in the fleet’s overall behavior can have a positive effect.

Avoiding Regression by Making Training “Sticky” Can Take Multiple Attempts

Lasting, long-term reductions in accident rates are only possible if the training has a certain level of “stickiness.” Unfortunately, even when drivers take the lessons learned in training and apply them every day behind the wheel, they can still end up regressing back to old habits on a long enough timeline. This idea of regression is supported by the work done by our prescriptive analytics partner, Dr. Feng Guo of the Virginia Tech Transportation Institute.

Dr. Feng Guo has spent his career studying the way people drive in the hopes of being able to alert individual drivers, and in a fleet’s case, their managers, when they are at a high risk of collision in the future. The model he has created uses five years of MVRs and accident histories in conjunction with national highway statistics to see the big picture of a driver’s habits. His stance is that when training is administered drivers can keep the message top of mind for a while, but the drivers will eventually become complacent. It is that complacency that leads to mistakes in the driver’s seat.

So, did the sales fleet from our example keep their rear-end collision rates down? No. The fleet saw their accident rate creep back up to 22% of total claims since they passed the year mark. In response, CEI worked with the fleet to get the drivers back on track. In addition to prescribing the training again, we recommended increased communications between management and drivers about road safety and to start meetings off with a safety briefing. Drivers are also being encouraged to share their road experiences with each other, whether it was an instance where they properly executed their defensive driving training or times that they saw other drivers coming dangerously close to a rear-end collision due to miscommunication.

Not enough time has passed to see if the effects of this second round of training with increased communication will right the ship, but we will monitor their progress. Overall, this case shows that targeted training for specific pain points can be useful, but drivers will likely regress if they never see that message again. Regularly prescribed the training module again at 9- to 12-month intervals is the key to driving down accident rates and making the new habits stick. Keeping drivers engaged on a month to month basis with different safety lessons is paramount in helping employees become well-rounded drivers.

By Kevin Reilly, Editorial Communications Manager, The CEI Group, Inc.

Updating Your Safety Culture in the Age of ‘Big Data’

February 2017

As more fleets upgrade their safety programs with emerging technologies, particularly telematics and prescriptive analytics services, it is important for fleet managers to consider how these technologies will fit into and shape their safety culture. Knowing how these big data technologies function, as well as their varied reporting options, is the first step. Next, is the need to set realistic short- and long-term goals.


Generally, drivers know how to drive safely, but throughout a busy work day, as the road distractions creep in, safety often takes a back seat. Telematics can be helpful in this area to act as a behavior change agent by continuously recording and reporting a driver’s actions. As a fleet manager, you will now become aware that a driver has a series of rapid accelerations and harsh braking episodes that could lead to an accident. Having access to a stream of information on erratic driving behavior allows a manager to take action with prescribed training. It also allows a driver to keep in mind those habits that they need to change.

Predictive and Prescriptive Analytics

Predictive models provide managers with the probabilities of an accident for the driver and are more accurate than classic risk grouping formulas that utilize only three years’ worth of MVR and accident history. Prescriptive analytics solutions combine predictive prognostication with recommended actions to reduce the probability of an accident using five years’ worth of MVR and accident history, driver demographics, national highway and traffic data, and more.

The difference between predictive and prescriptive analytics is the ability to take the actionable data and prescribe appropriate courses of action to rectify driving behavior to prevent a collision.

Tailoring Technologies for Specific Needs

Optimizing telematics and prescriptive analytics for driver safety is a case-by-case matter. Since every safety culture differs from fleet to fleet, it is vital to have the ability to tailor these tools for a fleet in a way that benefits drivers and managers up and down the chain of command. The manager of a small fleet may want to have an alert come in every time a driver breaks the posted speed limit by 5 miles per hour. But, a larger fleet may find that system to be too much and set an alert only for drivers who break the posted speed limit 20 times or more in a given week.

An often-overlooked policy for any fleet safety program: Keep both drivers and their managers updated on a driver’s risk assessment and events. Tailored alerts open up yet another means of communication to impart safety policy and to change driver attitude and behavioral change.

Active discussion allows drivers and managers to buy-in to these big data technologies that may have seemed too intrusive or time consuming to use just a few years ago. Full buy-in from drivers and managers is crucial to sustained improvements in a fleet’s driving safety culture.

Reasonable Goal Setting

Setting reachable goals is often the hardest part to successfully integrate big data technologies. With telematics, for instance, the first few months of technology adaptation may be rocky. Managers will want to correct and discipline drivers right away for the high number of bad driving habits their drivers will display. Still, it will take time for drivers to respond to data that shows them their bad habits, and managers need to realize that bad habits die hard.

Use of these big data technologies to improve a safety culture takes a long-term commitment and a series of small, reachable milestones to hit along the way. The reward for such commitment is seen in a multitude of ways such as less vehicle and driver downtime, savings in overall accident repairs and tune-ups, and most importantly fewer injuries for drivers. Telematics and predictive/prescriptive analytics technologies are shaking up the fleet industry. Now is the time to adopt.

By Kevin Reilly, Editorial Communications Manager, The CEI Group, Inc.

Prescriptive Analytics — Moving Past Predictions

January 2017

Predictive Analytics is nothing new, but the application of predictive techniques has been seeping into every facet of business and government operations. The market for predictive analytics technologies tripled, from 11 billion to 35 billion dollars, from 2000 to 2012. It is now estimated that the US alone will need 190,000 more analytics experts and 1.5 million more data-literate managers by 2018. These figures are derived from FICO analytics.

In the past few years, however, even predictive analytics is progressing. It has given way to prescriptive analytics. This change is more than wordplay, introducing a more proactive approach to data analysis. For fleet safety decision-makers, a prescriptive approach introduces a customized process for effectively identifying and remediating hidden high-risk drivers within a specific organizational culture.

Fleet Application of Analytics
Prescriptive analytics in fleet management helps take some of the guesswork out of budgeting for repair costs and allows fleet managers the opportunity to work with drivers towards accident prevention. Managers and drivers can work together to improve safe driving techniques. This has an effect on driver behavior that leads to better driver retention rates.

Preventing accidents is more possible than ever, from a fleet risk management perspective, when a quality prescriptive model is used in conjunction with telematics data and training is provided for at-risk drivers. The data an analyst can collect from prescriptive modeling is called actionable data; the results show patterns that can be addressed immediately with training. Once training is assigned, alerts can be set to show that a driver has completed their training, creating a positive feedback loop between drivers and fleet management.

There is an abundance of predictive models in use across the fleet industry as of late, but whether these models can evolve to a prescriptive level will vary from fleet to fleet. In addition, the specific predictive model used, and its resulting effectiveness, will vary across companies, but most follow a fairly standard set of criteria. The majority of predictive models use MVRs (motor vehicle records), accident history, and traffic violations to create a risk profile for each driver within a fleet. Risk profiles most often assign a risk score to each driver based on their driving history, and most fleets categorize their drivers within multiple risk categories from safest to most at-risk.

How to Apply Prescriptive Analytics to Your Fleet
These prediction models still tend to trend the last three years of records for a fleet’s risk profile, but prescriptive models that track the last five years of available data are being implemented.

The higher the volume of data collected the more accurate the modeling, and newer prescriptive models looking back as far as five years through MVRs and incident reports prove to be most accurate. A five-year model has not been used to assign a risk level that can be used in a punitive manner; the purpose of a deeper, prescriptive model is to gain further ability to assign training to risky drivers that lead to accident prevention.

Effectiveness of a Five-Year Prescriptive Model
A sales client of CEI with 1,489 total vehicles, whose drivers log an average of 1,963 miles per month, used our prescriptive model for one year, and the results show a predicted number of 357 accidents for the year (24% accident rate) and the actual number of accidents for the year was 375 (25.2% accident rate). According to the AAA Foundation for Traffic Safety, the national average for miles driven per month ranges from 888- 1,095 miles. So, for a fleet whose drivers rack up nearly 900 more miles driven per month than the national average’s high end, a difference of 1.2 percentage points from predicted to actual accidents is exceedingly accurate. Also, the number of accidents becomes understandable for fleet managers from a risk management perspective, due to more time spent on the road.

Another client of CEI, with a service truck fleet of 8,855 vehicles, received our estimates 10 months ago that they would likely have 1,926 accidents within the next 12 months. CEI projects, based on the first 10 months of actual accident data, that by the end of the 12 months they will have had 2,155 accidents. That leaves us with a 2.5 percentage point difference from the 21.8% projected by predictive analytics to the 24.3% actual accident rate that we projected. (We are not provided with mileage from this fleet, and they are our first service fleet to test out our predictive analytics model, which explains the incomplete data set.)

The CEI Group’s traditional predictive analytics model has been able to help fleets reduce accidents by up to 35%, and with added knowledge of high-risk drivers from the five-year prescriptive analytics model, we expect that percentage to increase once fully implemented.

Measuring Success
Prescriptive analytics success can be measured in two ways. The first success metric is to see how accurate the model was in total accident prediction during the projected time frame. Even better, and this is really the crux of prescriptive analytics, is to look into whether or not any training is given to high-risk drivers, and if, after training, the actual number of accidents is lower than accidents from previous years and the predicted number of accidents.

Many drivers are at first skeptical about being closely monitored with telematics and prescriptive analytics. The opinion begins to shift when a driver is found not at fault in a collision due to irrefutable telematics data, or when a driver is given a training module and can note a difference in their driving behavior.

This is an exciting time in the Fleet Management world, and in business as whole, because of the emergence of new and improved technologies that save time and money in easily identifiable ways. All of these new technologies, including telematics and prescriptive analytics, are data driven, and they are often referred to with the umbrella term “big data.” It is time for all members of the fleet world to embrace big data, telematics, and prescriptive analytics in order to reap the rewards of saving time, money, and the lives of drivers.

By Kevin Reilly, Editorial Communications Manager, The CEI Group, Inc.


© 2020 CEI GROUP | Privacy Policy

Our Address The CEI Group
4850 East Street Road
Suite 200
Trevose, PA 19053