The EV Data Problem Fleets Aren’t Talking About

At Geotab Connect 2026, one of the more revealing conversations wasn’t about range, charging infrastructure or incentives. It was about data — specifically, the quality and accessibility of EV data once vehicles enter fleet operations.

According to Mike Branch, VP Data and Analytics at Geotab, the industry may be underestimating a structural issue that could slow the next phase of fleet electrification.

EVs can be harder to read than ICE vehicles

There is an assumption that because electric vehicles are “software-defined”, they must be data-rich and easy to integrate into fleet systems. Branch suggests that isn’t always the case.

While internal combustion vehicles have benefited from decades of standardised diagnostic frameworks, EV data availability can vary significantly by manufacturer. Access to state of charge (SOC), state of health (SOH), battery temperature data and degradation indicators is not always consistent — and in some cases is restricted.

For Fleet Managers, that creates risk. If you cannot reliably access battery health metrics, it becomes harder to:

• Forecast residual values
• Model lifecycle costs
• Plan replacement timing
• Detect early degradation issues
• Build confidence with finance teams

In short, EVs may be mechanically simpler — but operational visibility is not guaranteed.

Sampling frequency matters more than AI

Another issue raised at Connect 2026 was the importance of sampling quality. AI tools can identify patterns, but only if the underlying data is sufficiently granular. If battery or electrical data is sampled too infrequently, predictive models lose accuracy. That can undermine efforts to detect abnormal degradation or emerging faults early.

Branch emphasised that fleets should not assume AI can “fill in the gaps” where telemetry is incomplete. Poor sampling creates blind spots that no algorithm can fully compensate for. For fleets transitioning to electric, that distinction is critical.

Data access should be part of procurement

As more EV models enter the Australian market — across passenger, light commercial and bus segments — procurement criteria are evolving. Range and charging speed are now standard considerations. But data accessibility may need to sit alongside them.

Fleet buyers should be asking:

• What battery health metrics are available?
• How frequently is the data sampled?
• Is access standardised across models?
• Are APIs open and supported?
• Can telematics platforms access raw data directly?

If not, the fleet risks operating with partial visibility — which affects whole-of-life cost modelling and executive reporting.

The finance and governance implications

For many organisations, EV transition is now tied to emissions reporting, sustainability commitments and board-level KPIs. Without consistent, high-quality operational data, reporting becomes approximate rather than precise. That may be acceptable in early adoption phases, but as EV penetration grows, scrutiny will increase.

Accurate battery health data affects:

• Asset valuation
• Insurance risk modelling
• Carbon accounting accuracy
• Replacement cycle forecasting

This shifts the conversation from technical integration to governance.

Standards will determine scalability

The long-term solution likely lies in harmonised data standards across manufacturers. Without standardisation, each OEM effectively becomes its own ecosystem. That increases integration cost and reduces comparability across mixed fleets.

For large corporate fleets and government operators — particularly those running mixed ICE and EV assets — this creates complexity that doesn’t exist in traditional fleets.

Standardisation won’t make headlines like a new model launch, but it may prove more important to scalable electrification.

A quiet risk in an accelerating transition

Australia’s EV uptake continues to grow, supported by policy, incentives and increasing model choice. However, the next stage of transition is less about vehicle availability and more about operational intelligence.

The EV data problem isn’t visible on a showroom floor. It appears months later, when Fleet Managers try to reconcile utilisation, charging behaviour, degradation trends and financial forecasts.

Electrification promises simplicity in drivetrain mechanics. But without reliable, standardised, high-resolution data, operational management can become more complex — not less.

As fleets move from pilot programs to scale deployment, data access may become one of the most important — and least discussed — procurement criteria of the decade.

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