Guest Column | March 21, 2022

It's A Great Time To Improve Your Fleet Management With Data Analytics

By Emily Newton, Revolutionized

Data Artificial Intelligence Algorithm iStock-1295900106

Fleet management can be a challenging job. However, data analytics platforms can make it easier. They help users uncover insights that they would have otherwise missed. Perhaps you’re at the point where you’re curious about how data analytics tools could enhance your efforts but unsure how to apply them. Keep reading to get details about what’s possible.

Get Real-Time Data From All Fleet Vehicles

Data analytics platforms can greatly streamline efforts to stay aware of all vehicles currently on the road. You can then notice potential issues faster and intervene before major problems occur.

A recent study about fleets that have adopted connected vehicle data services found that the implementation rates vary depending on fleet size. More specifically, 79% of companies managing at least 500 vehicles use such offerings now. Another 8% of businesses in that group are actively looking for products to buy.

However, only 7% of fleets with 1-5 vehicles use these products. The segment rises to 24% in cases where companies have 6-50 vehicles to oversee. If you’re still on the fence about whether to deploy data analytics for fleet management, think about parts of your job that are particularly time-consuming or prone to errors. If getting current data could help you excel in those areas, it’s a good time to at least strongly consider adding fleet analytics to your workflow.

Having that real-time data could also help you find instances of driving behaviors that are dangerous or could raise the vehicle’s fuel consumption. Then, after you identify a pattern of those actions, the compiled information gives you justification for scheduling an intervention with the associated team member.

Research also indicates it doesn’t take as long as some people might expect to see a return on investment from fleet management technology. The study showed that 86% of people who chose to purchase such products saw a return on investment in less than 12 months. Then, 44% of the respondents said it occurred in less than six months. If you hope to see similar results, it’s essential to have a clear idea of what you hope to achieve and create a path for reaching that point.

Simplify Report-Generation Duties

Getting fleet reports every month or more often can help decision makers uncover the positive and negative trends that shape the business. One appealing advantage of data analytics programs for fleets is that they often have built-in report-generation capabilities. Then, people can substantially cut down the time they spend gathering information and putting it into the right format.

Data analysis tools often let people do things like see side-by-side graphs for particular months or seasons. It’s then easier for users to make decisions based on hard data rather than guesswork.

People may also use supplementary tools to speed report generation even more. One example is an artificial intelligence-based product from Microsoft called Smart Narratives. It can automatically generate explanations of chart data for users. That capability could come in handy when someone who is fairly comfortable working with and interpreting data needs to prepare it for people who don’t have that background.

Kirk Hay is the chief information officer at Jack Cooper Transport, which specializes in hauling automobiles. He says his company uses artificial intelligence software to automatically write text-based reports and distribute them to different departments within the company. Hay said the main benefits of this approach were improved clarity and speed. Additionally, seeing the data in a text format often helped decision makers spot and respond to trends with more agility.

Keep Better Maintenance Records

It’s becoming more popular across many industries to use data analytics for predictive maintenance. In one case, that approach gave an automotive parts manufacturer an alert about a fan failure several days before it happened. Getting those warnings could help fleets stay more resilient, too.

Consider an example where data analysis shows that an alternator used on a specific group of trucks you own is highly likely to fail within a specific mileage range. You could take that information and use it to solidify your decision to replace that part sooner than planned on the affected vehicles. Some data analysis tools also can send automatic smartphone reminders about when to schedule certain types of maintenance.

Data analytics programs also can help users remember to check or upgrade any components associated with work vehicles owned by a company. For example, a truck may have an accompanying stainless-steel tank to carry fluids safely. There is no single governing body regulating tank use and recertification after these products get deemed ready for safe use after initial manufacture. However, when the entity using the tank ensures it remains in good condition, it’s easier to prevent costly and potentially toxic spills.

Improving the approach to maintenance records with data analytics is also advantageous for fleet managers who don’t have on-site maintenance records. Those people could review the associated fleet data to ensure that as many upkeep needs get handled as possible during each visit from off-site maintenance specialists.

Reduce The Truck Driver Shortage With Data Analytics

An October 2021 report estimated a lack of necessary truck drivers that reached 80,000 people or an all-time high. Analysts believed the figure could reach 160,000 by 2030. There’s no single strategy for addressing this issue. However, data analytics tools could help by removing the unpleasant surprises that could make trucking roles unappealing and frustrated.

Allison Parker is the vice president of marketing at Wise Systems, which uses data analytics to assist fleets. She explained some of the various benefits, saying, “...Organizations can better plan and continuously improve every last mile route and delivery. Drivers have an intuitive, easier experience managing their schedule directly from their mobile devices, while fleet managers have up-to-the-minute plan tracking for resource allocation and utilize.”

Parker continued, “Drivers appreciate having full visibility into all the data about every delivery stop, including the number of products they’re expected to deliver. All they need to do is swipe in and out when they arrive and leave. The system also can record proof of delivery. They also can leave notes for themselves or future drivers on our secure app, such as a passcode for a loading dock.”

Data analytics could help dispatchers, too. If they have reliable information, it’s easier to use it to plan the number of truck drivers needed per shift. Then, it’s less likely the team members will feel overwhelmed and ill-equipped to handle their workloads.

Improve Your Understanding Of When And Where To Take Action

Besides the specific scenarios mentioned here, data analytics for fleets can help you drill down into information and feel more confident about taking particular measures. Consider an example where a particular driver is late with deliveries 55% of the time. That initially seems like a worrisome metric, but it might not be as severe as you think.

Perhaps the person is only late by 1-3 minutes in 99% of those instances, and they deliver the goods within 10 minutes for the remaining 1%. In that scenario, the lateness is probably acceptable and may not need further action. However, you could continue tracking the driver and their times to see if the metrics worsen.

It’s also often possible to use data analytics products to narrow down the factors that likely made a driver run behind schedule. Maybe there was road construction occurring on their route or an accident that caused a major backup. Digging into the data to get these specifics makes it easier to avoid future scenarios characterized by similar problems.

There’s no universally guaranteed way to experience gains with fleet management software that has data analytics features. However, start by taking the time to think about current pain points and what you could learn from better and constant information access. Then, it’s easier to create a viable plan for making this technology worthwhile and set accurate expectations for everyone using it.

About The Author

Emily Newton is the Editor-in-Chief of Revolutionized. She regularly explores the impact technology has on the industrial sector.