Are you a fleet manager or a data scientist? Why data has become the heart of fleet operations.

If you've ever found yourself deep in spreadsheets, analyzing maintenance trends, or tracking driver behavior metrics instead of simply managing vehicles, you're not alone. Today's fleet managers are increasingly wondering: Am I managing a fleet, or am I managing data? The answer, it turns out, is both—and understanding this evolution is critical to your fleet's success.

The growing burden on fleet managers

Perhaps the question of whether you're a data scientist isn't so far-fetched when you consider the expanding responsibilities of modern fleet managers. They handle purchasing vehicles, keeping up with paperwork and fleet maintenance, staying connected to drivers, and managing inventory—not to mention seemingly hundreds of tasks in between that make fleet management a complicated, nonstop occupation. On top of the operational demands, fleet managers are now expected to leverage data analytics to predict their fleet's future.

Yet as Nathan Niese, Regional Vice President of Client Partnerships at Mike Albert, points out: "Digging into your data takes resources. You need an experienced analyst to look at your data, compare it against similar businesses, and pinpoint the actionable insights that are the most valuable for your fleet."

Why data matters more than ever

Data reveals facts about your fleet that you otherwise wouldn't (or couldn't) know about efficiency gains and safety improvements. Consider what comprehensive fleet data can help you achieve:

• Cost reduction: When you track data properly to support maintenance, safety, and vehicle cycling, you optimize your total cost of ownership (TCO). The savings from data-driven decisions mean more capital to invest in business improvements. Fleet managers who utilize comprehensive telematics programs, maintenance management systems, and analytics platforms consistently report that their TCO decreases significantly.
• Driver compliance, safety and performance: Monitoring driver behavior through data—tracking metrics such as speeding, harsh braking, and seat belt use—helps you improve the safety of drivers, passengers, and others on the road. Remember, accidents not only raise insurance premiums but also potentially expose your company to high-cost litigation.
• Preventive maintenance and action: Being proactive based on data insights helps you avoid major, costly repairs, minimize driver downtime due to breakdowns, and prevent missed customer appointments that could damage your reputation.
• Asset utilization: Data can help ensure that you’re making the best of your assets. For example, data can identify the opportune time to cycle a vehicle out of your fleet. Another example: If your fleet is dispersed across a region or the entire country, data can distinguish those vehicles that perform best in a particular geography, given its climate and topography.

The challenge: Data fragmentation

Here's a scenario that likely sounds familiar: Your maintenance logs and expenses live in a spreadsheet owned by your finance manager. Your COO has vehicle acquisition contracts filed in her office. Fuel receipts and reimbursement records are only available in hard copy. Then there are GPS systems, fuel cards, telematics, and compliance reports—to name a few. This fragmentation makes it nearly impossible to see the complete picture of your fleet's performance.

On top of all your other responsibilities, you probably don't have time to dig into your fleet data—much less gather it. And difficulty gathering data is likely a top reason why fleet managers don't monitor it as closely as they should. Fragmented data means managers spend time manually pulling reports from different platforms. This slows down decisions, increases the risk of errors and makes it hard to identify trends.

The power of predictive analytics

Today's most sophisticated fleet operations go beyond simply collecting historical data—they use predictive analytics to anticipate future challenges. Predictive analytics can look back through time, examine current driving patterns, and then extrapolate what the picture will likely look like moving forward. This capability enables fleet managers to predict when a vehicle will reach its retirement criteria, identify high-risk drivers before accidents occur, and significantly reduce major issues that send vehicles to the side of the road.

By tapping into past data and projecting forward, modern analytics can paint a pretty accurate picture of your future costs. For example, advanced systems can fine-tune the data to reflect an anticipated increase in driver mileage, certain vehicle parts, and fuel. Fleet managers have found this tremendously helpful when sharing—and defending—a budget forecast. The savings potential is substantial. Depending on the fleet size and the extent to which fleet analytics are already in place, the savings can easily reach six figures—and sometimes multiple times over—and that's after factoring in the cost of predictive analytics services.

Turning data into stories

Fleet data almost always tells a story, but it takes extra effort and time to pinpoint the narratives that make the data more relevant, meaningful, and most importantly, actionable. As Brent Pietroski, Director of Client Partnerships at Mike Albert, explains, "My goal for all the data that I share with my clients is to make it actionable."

To find the best stories in your data, begin with what you believe is the key question you need answered. Then follow the data closely to see where it leads you—that's when the most impactful stories take shape.

Consider these real-world examples:

A 150-vehicle commercial refrigeration company noticed that despite adding newer model vehicles, their overall maintenance costs were increasing. This seemed counterintuitive. A deeper analysis revealed that while newer vehicles indeed had lower per-mile costs, older vehicles that were still in the fleet’s rotation were dramatically more expensive to maintain. Because they were holding onto these older vehicles too long, the overall costs kept rising. The solution? Implement a more aggressive replacement cycle based on data-driven thresholds.

A healthcare company with a 500-vehicle fleet saw its transmission expenses spike by 853% in one quarter. By examining the data at the vehicle level, they found that three specific models from two manufacturers accounted for virtually all the skyrocketing costs. As Pietroski noted, "By looking at their maintenance expenses from an individual category level, we were able to provide them with peace of mind by knowing which areas of maintenance were costing more and acting as outliers." The company used these insights to evaluate what vehicle adjustments to make in the short- and long-term.

Managing the data deluge

One common concern among fleet managers is feeling overwhelmed by the sheer volume of data available. The key is not drowning in data but instead focusing on the findings and trends that the analysis reveals.

To effectively manage data, today's fleet managers need centralized platforms that consolidate all key information in a single digital repository. Key features to look for include:

• Customizable dashboards that provide quick, clear overviews of current fleet data
• Real-time monitoring of vehicle health, driver behavior, and route statistics
• Automated alerts for maintenance schedules using a ticketing system with red alerts (requiring immediate attention) or yellow alerts (requiring attention soon)
• Comprehensive reporting capabilities that allow you to generate documentation for compliance purposes
• Integration with telematics to capture vital data from engine computers and GPS tracking systems
• Anomaly detection to identify drivers or vehicles that are out of compliance with established tolerances

These tools enable you to monitor and measure performance in areas such as idling, fuel consumption, and braking patterns. As one fleet manager using advanced analytics noted: "Our traditional telematics solution provided an overwhelming amount of data around potential issues within our fleet. With [modern analytics platforms], I can log into one portal and quickly see a prioritized list of issues my drivers and I need to address. This has been an amazing time saver and truly allowed us to gain better control over the health of our fleet." For example, analytics platforms can collect dozens of diagnostic trouble codes (DTCs) from each vehicle, interpret them, and cross-reference data across multiple vehicle systems, ideally under the oversight of a certified mechanic. Then, all necessary maintenance is prioritized by urgency. This alerts fleet managers and drivers to any issue that requires immediate attention before it becomes a costly problem for your company and inconveniences your customers.

Making data work for you: The strategic approach

The best approach to fleet data management involves a systematic partnership process:

1. Data collection: Establish a system to collect all key data fundamental to understanding your fleet's health and overall operations (e.g., fuel usage, driver behavior, maintenance costs, etc.).
2. Expert analysis: Work with experienced analysts who can collect, organize, and analyze the specific data required to see a 360-degree view of your fleet operations and pinpoint the most impactful, needle-moving insights.
3. Comparison to benchmarks: Compare your data to industry-specific benchmark data pulled together in a way that's easy to see where you might be overspending.
4. Actionable solutions: Figure out exactly which levers to pull to identify opportunities within the fleet that can impact overall company goals and objectives. For example, you may be able to swap a gas-guzzling SUV for a sedan, or you may be on the verge of a breakdown in a high-mileage cargo van.
5. Strategic partnership: Work with a dedicated strategic partner who proactively communicates with you, guides you through timing and solution implementation, and regularly provides insights on industry trends and analysis of your fleet data.

It's a brand new world

So, are you a fleet manager or a data scientist? In truth, modern fleet management demands both skill sets. You need to understand vehicles, drivers, logistics, and operations—but you also need to be comfortable analyzing trends, identifying patterns, and making decisions based on the numbers.

The transformation isn't about abandoning traditional fleet management expertise—it's about augmenting it with the power of data analytics. When you embrace this dual role and partner with organizations that prioritize data-driven decision making, you can ensure your fleet performs at its highest level at the lowest possible cost—keeping drivers safe, productive, and happy.

In today's competitive landscape, data isn't just a tool—it's the foundation of smart fleet management. Embrace your evolving role as both fleet manager and data interpreter, and you'll unlock the full potential of your fleet operations. After all, when data tells you the story of your fleet, you gain the actionable insights you need to reduce operating expenses and drive your business forward.