Electrification Without Data: The Costly Mistake Many Fleet Managers Make

Fleet electrification is no longer a question of if but when. With stricter emissions regulations, rising fuel prices, and sustainability targets, businesses are shifting to electric fleets. In the Netherlands, municipalities can introduce zero-emission zones for delivery vans starting 1 January 2025, accelerating this transition.

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However, without data-driven planning, electrification can be costly and inefficient. Many fleet managers overlook key factors like route feasibility, charging infrastructure, and total cost of ownership (TCO). According to Geotab, nearly 60% of fleets could save money by switching to EVs, yet poor planning often leads to unexpected costs and operational disruptions.

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Let’s explore where fleets go wrong and how data ensures a successful and cost-effective EV transition.

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The Most Common Pitfalls in Fleet Electrification

Despite increasing EV adoption, many fleet managers struggle with the transition. The most common and costly mistakes include:

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• Choosing the wrong vehicles: Not all EVs fit fleet needs. Poor range or payload capacity can cause missed deliveries, longer routes, and operational disruptions. In fact, 28% of fleet managers regret their initial EV choices due to operational mismatches.
• Ignoring charging infrastructure: A lack of charging stations leads to longer downtime, higher costs, and inefficiencies. Without a structured charging strategy, fleets risk operational delays.
• Overlooking real-world driving behaviour: Simply replacing ICE vehicles with EVs without analysing mileage patterns, idle times, and energy use can lead to unexpected costs and range limitations. Poor route planning alone can reduce EV efficiency by up to 20%.
• Underestimating Total Cost of Ownership (TCO): While EVs have lower running costs, businesses must factor in higher upfront prices, fluctuating electricity rates, and battery replacement expenses.
• Lack of telematics integration: Fleets that fail to use data-driven insights for charging optimisation, route planning, and battery health monitoring often experience higher costs and lower efficiency.

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How Data-Driven Decisions Make EV Fleets More Efficient

According to McKinsey, businesses that invest in data-driven charging and route optimisation can cut EV operational costs by up to 25%. By leveraging fleet telematics, AI-driven analytics, and predictive insights, companies can:

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✔️ Select the right EVs: Analysing mileage, energy consumption, and route patterns prevents costly vehicle mismatches.

✔️ Optimise charging schedules: Smart analytics help fleets charge during off-peak hours, reducing electricity costs.

✔️ Monitor battery health: Predictive maintenance reduces breakdowns by 30%, improving uptime and extending battery life.

✔️ Plan charging infrastructure: Data insights help install the right number of chargers at optimal locations, avoiding bottlenecks.

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Roadmap to Electrifying Your Fleet

A successful EV transition happens in three key stages:

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1. Preparing for EV adoption
2. Optimising EV operations
3. Scaling up with smart charging

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1. Going Electric: Making the Right Choices

One of the biggest challenges for fleet managers is determining which vehicles to replace with EVs. While EVs may look similar to ICE vehicles, they differ significantly in range, charging requirements, and operational efficiency. Selecting the wrong EVs can lead to unexpected costs and operational disruptions.

To support data-driven decision-making, Geotab developed the Electric Vehicle Suitability Assessment (EVSA). This advanced tool analyses real-world fleet data to identify which vehicles are best suited for electrification based on:

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• Daily mileage and route patterns: Ensuring an EV meets operational needs
• Charging availability and infrastructure: Identifying charging requirements
• Financial feasibility: Confirming EVs are more cost-effective than new ICE vehicles

The EVSA only recommends electrification when it makes both financial and operational sense, helping businesses build a solid business case for EV adoption. Find out how the EVSA can help your fleet.

2. Operating Electric: Maximising EV Performance

Once EVs are integrated, the focus shifts to efficiency and performance optimisation. While fleet managers may understand EV capabilities, drivers often require additional training and real-time insights to maximise vehicle range.

With fleet telematics, businesses can:

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• Coach drivers: Improving EV efficiency and extending battery life
• Monitor battery health: Preventing downtime and optimising charging cycles
• Analyse energy consumption: Adjusting charging schedules to reduce costs

3. Scaling Up: Smart Charging Integration

As fleets expand their EV adoption, charging infrastructure becomes a critical factor. Without an effective charging strategy, businesses may face higher costs, unnecessary downtime, and operational inefficiencies.

By integrating smart charging solutions, fleet operators can:

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• Receive real-time alerts: Preventing empty batteries by detecting charging issues early
• Optimise charging costs: Tracking energy consumption and scheduling off-peak charging
• Plan charging schedules: Using real-time battery data and GPS location for more efficient energy management

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Case Study: Hoppenbrouwers

Hoppenbrouwers Techniek, a leading Dutch technical services company, faced challenges as their fleet rapidly doubled in size. With over 1,200 light commercial vehicles (LCVs), the company struggled with tracking vehicle locations, fuel efficiency, and driver behaviour. By switching to Geotab’s OEM telematics solution, Hoppenbrouwers gained full fleet visibility, allowing them to:

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✔️ Identify underutilised vehicles: Reducing fleet size and cutting costs

✔️ Monitor fuel and energy consumption: Improving efficiency and sustainability

✔️ Enhance driver safety: Using data insights to optimise driver behaviour

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This data-driven approach led to greater operational efficiency with fewer vehicles, proving that smarter fleet management leads to real cost savings.

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‘Data is crucial for the electrification of our fleet ’

Fleet Manager Michiel Westdorp

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The Future of EV Fleets: AI & Predictive Analytics

AI and predictive analytics will drive the next phase of fleet electrification. According to McKinsey, AI-powered fleet management will help businesses optimise battery health, route planning, and energy consumption, resulting in greater efficiency and lower operational costs.

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AI will enable more precise route planning, ensuring that vehicles achieve maximum range per charge while avoiding unnecessary detours. Automated charging optimisation will help businesses align charging schedules with energy demand and pricing, reducing electricity costs. Additionally, predictive battery health monitoring will allow fleet managers to replace or service batteries before performance declines, preventing unexpected downtime.

How Data Powers a Successful Transition

Fleet electrification is a necessity, but without data, businesses face higher costs and operational risks. Telematics, predictive analytics, and AI-driven insights enable a smoother transition, minimising expenses, downtime, and inefficiencies.

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Are you ready to make the shift, the right way? Let’s talk.

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