End of Day Distracted Driving Elevates Your Risk for a Crash

Distracted Driving By the Numbers

We all have heard the distracted driving statistics: you are 23 times more likely to be involved in a collision when texting and driving; you travel the length of a football field in the time it takes to read one text; 20% of all crashes with injuries involve a distracted driver. But what you might not have heard is that distracted driving can become even more dangerous when it happens at the end of the workday. Here is what the research, and CEI’s own industry benchmark data tells us.

The Time of Day When Accidents Happen

Based on the latest statistics from the National Safety Council, 43% of all fatal crashes occur between 4:00 pm and midnight, with the largest portion occurring between 4:00 pm and 8:00 pm. This is the time that most drivers are ending their workday, and more likely fatigued.

Over the past three years, CEI’s own fleet collision statistics bears this out. Our numbers show there is a 22.5% rise in all preventable auto accidents occurring in the afternoon hours.  This supports the trend of more crashes occurring later in the day and why it even more critical to eliminate distractions.  This trend continued through 2020, a year when less vehicles were commuting at the end of a workday, yet collisions still increased in the afternoon hours.

CEI Stats on preventable accidents by time of day

Impact of Fatigue on Reaction Time

Fatigue has been shown to cause an increase in Human Reaction Time (HRT), especially when we need to make quick decisions.  A 2017 scientific study published in the Healthcare Technology Newsletter, showed that HRT for recognition tests, (where subjects had to make a cognitive decision to visual stimuli before reacting), increased between 60% and 87% when subjects were tested at the end of the day versus at the start of the day.[i]

The reason for the increased risk when both fatigue and distraction are present is simple: both impact the cognitive processing time.

The “Attentional Blink”

According to study results from the American Psychological Association, delays in mental processing time increased when switching to complex and unfamiliar tasks.[ii]  Our brains lose portions of a second each time we switch between tasks and our brains need to refocus. This experience, known as an “attentional blink”, can have serious consequences in lengthening reaction time when driving.[iii]  Even the simplest behaviors such as changing the radio, reaching for a drink or have a conversion with other passengers in the vehicle, will lengthen reaction time and increase the risk of a collision.

What Fleets Can Do

Ensuring that each driver remains focused on the road while operating their vehicle should not be an option, but part of an overall safety culture that provides the necessary tools (Safety Policy, Assessment and Training).  Likewise, driver wellness is an important part of keeping drivers fit, and safe, to drive and is getting serious attention from fleets today.

If you would like learn about specific actions your fleet can take to address these matters, please contact us and we’ll connect you with one of our Risk and Safety experts who can assist you.  Our mission at The CEI Group is to help you get your drivers home safely every day.


[i] Abbasi Kesbi, Reza & Memarzadeh-Tehran, Hamidreza & Deen, M.J.. (2017). A Technique to Estimate the Human Reaction Time Based on Visual Perception. Healthcare Technology Letters. 4. 10.1049/htl.2016.0106.

[ii] https://www.apa.org/research/action/multitask

[iii] Kendra Cherry.  (July 24, 2020).  What Is Attentional Blink?.  Verywellmind.com https://www.verywellmind.com/what-is-attentional-blink-2795017

Cybersecurity: How Well Protected Is Your Company Against the Rising Tide of Malicious Disruption?

My theme in this continuing blog is that business disruption – the kind that results from a continuous strategic embrace of cutting-edge technology – is not just a good thing, but a requirement. Call it creative destruction. But there’s another kind of technology-powered disruption that is simply destructive: the hacking of an organization’s digital infrastructure.

How pervasive is the threat? Consider the following:

• Computer Ventures, a researcher and publisher covering the global cyber economy, estimates that cyberattacks cost the global economy $3 trillion in 2015, a figure is likely to double to $6 trillion a year by 2021.
• PWC, the accounting and consulting firm, says that 32 percent of U.S. organizations were victims of cybercrime in 2016, and projects that 34 percent will have become victims by the end of 2018.
• Microsoft estimates that average cost of a data breach to a business is $3.8 million, and that the average attacker resides in a network for 146 days before being detected.
• A University of Maryland study found that hackers were attacking computers and networks “at near-constant rate”, with an average of one attack every 39 seconds.

U.S. consumers and businesses of all sizes are being targeted, by individuals, organized crime and even state-sponsored agencies. What they’re after is consumer personal data, credit card numbers, login credentials, access to funds, technology and intellectual property, ways to cripple operating systems and – in a recent and rapidly growing trend – ransom to restore them.

The lure of rich bounty from cybercrime has attracted some of the brightest rogue minds and hostile regimes, and they’re widely believed to be working on the cutting edge of digital technology. In addition to the fact that hundreds of thousands of new viruses and other kinds of computer malware are created every day, a concern is that some hostiles are working on quantum computers that could hack the most sophisticated encryption systems while being invulnerable to hacking themselves.

As bad as 2017 and 2018 were, 2019 is likely to even worse, as the following evolving and emerging threats are gaining momentum (my thanks here to the Lazarus Alliance):

Phishing Schemes. Nearly all successful cyber-attacks begin with a phishing scheme. Business email compromises, a highly targeted spear phishing attack, are responsible for more than $12 billion in losses globally.

Cloud Cyber Security Threats. Cloud computing has transformed the ways in which we live and conduct business, but it has also given hackers a broader attack surface and created a host of brand-new cyber security threats and vulnerabilities, from cloud malware to misconfigured Amazon Web Service (AWS) buckets. Cloud security must be addressed differently than on-premises security, and solid cloud security starts with a secure cloud migration.

Use of Shadow IT Apps. More than 80 percent of employees admit to using unauthorized IT apps at work, which are known as shadow IT. Most of the time, their motivations aren’t malicious or negligent; they’re just trying to do their jobs better. However, shadow IT usage can be a serious compliance and cyber security threat. The best course of action is to open a dialogue with your employees to determine why they believe these shadow applications are better than your existing, vetted applications.

Cryptojacking. Cryptojacking malware, which allows hackers to hijack enterprise computer equipment for the purpose of “mining” cryptocurrencies, has become more common than ransomware. These attacks can be hard to detect, but they can be snuffed out by upping endpoint security and monitoring network traffic for unexplained spikes at odd times.

Ransomware. Cryptojacking malware may be more common today, but that doesn’t mean ransomware has fully gone away. While cryptojacking can waste energy and slow productivity of your systems, ransomware can stop you dead in your tracks.

Unsecured Internet of Things (IoT) Devices. A recent Mozilla report shows that there may be up to 30 billion IoT devices by 2020. Both the public and private sector are scrambling to secure the Internet of Things. In recent weeks, the National Institute of Standards and Technology released guidelines for securing medical IoT devices, and Microsoft launched a public review of its new solution for developing secure smart devices. Ask your IT team how many things really need to be connected and automated before adopting them, and always look to secure these devices with regular updates and passwords.

What business leaders must do

Cyber defense is critical to every business, and it’s too important for senior executives not to be familiar and up-to-date on cyber threats and counter-measures, especially those in charge of companies that may not have invested enough in computer security in recent years. A sound approach to cyber security rests on two key practices: an ongoing review and dialog between CEOs and their Chief Information Officers about the organization’s security technology, and a continuing program to educate all employees about cyber threats and the organization’s computer security policy.

Millennials Are Disrupting Business…In a Positive Way!

For the past decade or so, the press has been filled with stories about how difficult millennials are to manage. We’re talking about people born approximately between 1980 and 1996, and the complaints about them are legion: They lack a work ethic, question and disrespect authority, are needy, and want to be pampered.

The description sounds like a nightmare. But as a business leader for a number of years, that negative portrayal doesn’t fit. That’s not to say I haven’t come across individual employees with those traits, but I don’t think they are any more prevalent among people between the ages of 22 and 38 than they are among any other age group.

The reason I don’t share the negative perception of millennials is because I’ve seen a very different type of millennial.

First, let’s cite some statistics. Today, millennials constitute the single largest block of employees, accounting for 36 to 38 percent of the total U.S. workforce. By 2025, some estimate they’ll account for as much as 75 percent of it.

Yes, millennials are different from previous generations, but in ways that should excite businesses. For one thing, they’re the most highly educated generation in U.S. history: a higher percentage of them have graduated from high school, as well as attended and graduated from college, than any generation before them. They’re also the most tech-savvy generation, many having never known a time when the Internet didn’t exist. Put these two facts together, and it’s no wonder that they want full information and expect the companies they work for to be more transparent, responsive and forward-thinking.

Gallup offered some clues as to how companies could make them more dedicated and engaged, finding:

• 72 percent of millennials who strongly agree that their managers help them set their performance goals are engaged.

• Nearly 70 percent are also engaged when their direct managers help them prioritize their tasks and responsibilities.

I have to cite my current company, CEI, as an example. CEI has been named as one of the best places to work in the Philadelphia area or the state three times, and twice cited as a “psychologically healthy workplace”.

When I read lists of what millennials want and need, I asked myself if they seemed unrealistic. Here are some of their biggest concerns:

• Open and frequent face-to-face communications with their managers.
• A workplace culture that emphasizes and rewards teamwork and creativity, not just output statistics and results.
• Thorough training that demonstrates how their role supports the company’s strategy and goals.
• Mentoring and coaching that prepares them for advancement in their careers.
• Flexibility for employees to achieve work-life balance, including the ability to work on a “flex-time,” job-sharing and remote access basis.

These are all values that add to work-life balance and a feeling of fulfillment in the workplace – something we all want, regardless of age. I believe the best companies already do these things, which is extremely valuable when considering how expensive it can be to train new employees. A new hire costs 1.25 to 1.4 times the base salary for the position, all while their productivity takes time to ramp up. Simply put, businesses cannot afford to continue with the status quo, or this highly educated and skilled sector of the workforce will move on to other companies that have adapted to these needs.

When we think of disruptive leadership, it can be easy to think only in terms of how technology can disrupt, but disruption can also mean changing the business culture. I urge any leader holding on to a negative view of millennials to embrace these change agents who are more likely to question accepted practices, to disrupt the status quo, and to help take the company to the next level.

The 21st Century’s Mega Disruptor: Machine Learning

Of all the technological advances mankind has achieved over the millennia that have changed the way we live and work, Machine Learning (ML) may well prove to be the one with the most powerful and disruptive effects. And while one application – autonomous vehicles – is still in its infancy, ML applications in many other business applications are already here and more are on the way.

ML grew out of the computer science of artificial intelligence (AI). Broadly speaking, AI refers to computers programmed to perform tasks that normally require human intelligence, like recognizing images and speech and making decisions. As remarkable as that is, ML goes one step further: it creates computers that can learn from experience and actually improve their performance.

Another way of putting this has to do with the way ML tames Big Data. We’re all familiar with the Big Data challenge: the Internet and a proliferating number of sensors in everyday items are generating massive amounts of data that exceed our ability to extract actionable information. ML programs enable computers to sort through immense data streams at lightning speed and find meaningful patterns that they weren’t pre-programmed to recognize. In turn, ML programs can use those patterns to make predictions of future events.

Here’s how Josefin Rosén, an ML and AI expert, describes it:

Machine learning enables computers to find hidden insights without being explicitly programmed where to look. They can change their behavior and improve their algorithms by themselves, and every time an error is made and recognized, the algorithm corrects itself and begins another iteration of learning.

The first ML application was created in 1952 by a pioneer in AI and computer gaming at IBM named Arthur Samuel. But as an independent discipline, machine learning didn’t begin to flourish until the 1990s, when the field changed its goal from achieving artificial intelligence to creating computers than can independently solve problems of a practical nature.

Now, businesses are rushing into the field with billions of dollars being invested. A recent survey of 500 chief information officers across 11 countries found that 89 percent said their organizations are using, piloting or developing strategies to machine learning. And it’s no wonder: just as AI has been used to automate thousands of manual tasks, ML has the potential to automate far more sophisticated functions that rely on data analysis used by business, government, medicine and more. The benefit is expected to be counted in trillions of dollars of increased productivity, improved customer service, creation of new products and marketing strategies, and millions of lives saved and made more enjoyable.

Machine learning applications have already started to seep into our daily lives. We have smart appliances and smart homes, voice-interactive digital assistants that can operate other devices and look up information for us, like restaurants with food we like or where our kinds of movies are playing. More and more service companies are using “chatbots” to interact with customers online, ML-powered digital assistants that respond to keyboard messages.

Behind the scenes, Uber and Lyft rely on ML applications to match drivers and riders and support dynamic pricing, rates that change based on supply and demand for rides by location and time of day. Google and other search engines use ML to improve each user’s search results employing back-end algorithms that watch how far down in the results users click on search items.

ML is also making headway in two industries with which I’m familiar: insurance and fleet.

  • User-based insurance. Drivers shopping for car insurance with Progressive can opt to install a company-provided telematics device that measures how much risk for an accident they pose, based on how often they speed and engage in harsh braking (a sign of distraction or tailgating). Safe drivers are offered premium discounts of up to $150.
  • Real-time repair estimates. Many insurance carriers are experimenting with ML-based technologies to help drivers who’ve had an accident receive real-time repair estimates by taking photos of their vehicle damage with a smartphone camera. The app is being built based on thousands of images of damaged vehicles and their repair costs.
  • Accident reduction. Fleets are beginning to turn an ML-assisted way of identifying high-risk drivers called predictive or prescriptive analytics. These algorithms use records of driver behavior and various demographic and industry data to predict the probability that they’ll be involved in a collision over the following 12 months. Once those that pose the greatest risk are identified, fleets can remediate their poor driving behavior with additional training and coaching.
  • Predictive maintenance. Based on historical data, Programs have been developed that can predict when auto parts or systems are likely to fail, and recommend replacements before those failures occur.

There’s more coming, in every industry. It’s part of what historians are calling the Fourth Industrial Revolution, in which disruptive technologies and trends such as the Internet of Things, robotics, virtual reality and artificial intelligence are changing the way we live and work. As with the previous three revolutions, many jobs will become obsolete and disappear, but – and I’m confident of this – many more will be created, and mankind will be much better off.

Competition in the business world will depend more and more on the extent to which companies harness machine learning and the related digital tools of the Fourth Industrial Revolution. The survivors will be those who master them strategically and master them first.