Turning Fleet Data into Strategic Insight

Fleet managers today can access more fleet data than ever – from vehicle health and driver behaviour to fuel usage, downtime, and emissions. However, having data isn’t the same as using it, and more data doesn’t automatically lead to better decisions.

Big Data vs Informed Decisions

Fleet data often exists in silos – across telematics platforms, fuel cards, maintenance systems, and back-office tools. Aggregating this data into a single view helps uncover relationships that aren’t visible when systems are disconnected.

For example, comparing telematics data on driving behaviour with maintenance trends might reveal that certain drivers are contributing to higher wear and tear. This can inform training, route planning, or even reassignment of vehicles.

Telematics might show a van is only used for a few hours a week. Yet maintenance records reveal it’s had multiple repairs in the last quarter. This could indicate it’s no longer cost-effective and could be better de-fleeted, relocated, or even replaced with a suitable EV to support sustainability goals.

This kind of aggregation allows fleets to move from reactive decisions to proactive planning.

As a data aggregator, Holman consolidates these sources into a single, coherent view. This “True View” gives fleet managers the context they need to make informed decisions, whether that’s reducing downtime, improving utilisation, or planning for future investment.

Turning Insight into Action

Once the fleet data is aggregated, the next challenge is interpretation. Dashboards are useful, but they don’t tell you what to do next.

That’s why our Business Analyst at Holman developed a machine learning-powered vehicle replacement model. Built in-house with our engineers, this tool analyses maintenance history, breakdowns, and vehicle characteristics to predict replacement probability, with 94.5% accuracy. It provides 12-month forecasts for SMR costs, downtime, and breakdown risk, and categorises vehicles into four actionable groups:

• Retain: Mechanically sound and cost-effective to keep.
• Replace: Showing signs of decline or costly repairs.
• Redeploy: Underused but in good condition; ideal for relocation.
• Retire: Low-use vehicles flagged for replacement that may not need replacing.

This predictive intelligence supports our Portfolio Management approach, treating each vehicle as a distinct asset with its own lifecycle. It allows for more tailored decisions based on individual performance and business needs, whether that’s flagging vehicles for timely replacement, improving asset utilisation, or aligning fleet decisions with your sustainability roadmap through targeted EV adoption.

Final Thoughts

The best place to start with your fleet data is ask better questions. Not “what’s the average fuel cost?” but “why is fuel cost rising in this region?” Not “how many vehicles are off-road?” but “what’s driving downtime in this part of the fleet?”

Data doesn’t make these decisions but informs them. And the more context and visibility you have, the more confident those decisions become.

With data from telematics, maintenance, fuel, and more in one place, Holman provides the clarity needed to act. Our account managers partner with you to turn insight into strategy – helping you make confident, data-driven decisions that move your fleet forward.