Your Telematics Platform Knows Where Your Vehicles Went. It Has No Idea What It Cost. If you run a fleet of 50 to 500 vehicles, there's a very high probability that you're using Geotab, Samsara, Verizon Connect, Motive, or one of their competitors. Telematics has become the connective tissue of modern fleet operations. Every modern vehicle is, in some sense, a telematics device with wheels attached. The data these platforms produce — vehicle location, driver behavior, idle time, fault codes, mileage, state of charge — has transformed how fleets are operated. But if you've ever sat in a finance meeting where the CFO asked a simple question — are our EVs actually saving us money? — and watched the fleet director, with full access to a market-leading telematics platform, struggle to give a clean answer, you've encountered the limit of what these platforms can tell you. The problem isn't that telematics platforms are bad. The problem is that they were built to answer operational questions, and what your CFO is asking is a financial question. The data they produce is necessary but not sufficient to answer it. This article walks through what telematics platforms do well, where the gaps are, and what it would take to close them. None of it is a criticism of Geotab, Samsara, or any specific vendor. The gap is structural. It exists because the data needed to answer financial questions about a mixed-fuel fleet doesn't live in any single system — and a telematics platform, by design, isn't structured to bring it together.

What your telematics platform actually knows Let's start with the inventory. A modern telematics platform — using Geotab as the example, but the same is broadly true of Samsara and others — knows the following about every vehicle in your fleet, in something close to real time:

The vehicle's identity and a unique device ID The driver currently assigned to it Its precise location, updated every few seconds Its speed, acceleration, braking patterns, and idle time Its odometer reading Its fault codes and engine health indicators For EVs specifically: state of charge, charging events (start, stop, location), battery state of health (where the OEM exposes it via API), and energy consumption per mile Driver behavior scoring across whatever metrics the platform tracks

That's a substantial dataset. With it, you can answer most operational questions a fleet manager would have. Where are my vehicles right now? Which drivers brake hardest? Which routes generate the most idle time? Which vehicles are due for service? These are the questions telematics platforms were built to answer, and they answer them well. For mixed-fuel fleets specifically, telematics platforms have evolved to handle some EV-specific concerns. You can usually see when a vehicle was charged, where it was charged, and how its battery state of charge changed over time. Some platforms expose battery state of health through OEM API integration, though the quality and freshness of this data varies considerably by manufacturer. This is genuinely useful operational visibility. It's not the same as financial visibility.

What your telematics platform doesn't know Here's where the gap appears. Take a single charging event — a fleet vehicle plugged into a public DC fast charger somewhere in your service territory. Your telematics platform sees this event happening. It records the location, the start and end times, and the change in state of charge from beginning to end. From that data, it can estimate roughly how many kWh were delivered (state of charge change × battery capacity × an efficiency assumption). What it does not see, and cannot see, is everything else that matters about that transaction. Specifically:

What it cost. The dollar amount of the charging session is paid by the fleet card, not the vehicle. The transaction ends up on a WEX statement, a Coast statement, or a similar fleet card record. The telematics platform never sees this number. The actual kWh delivered, as measured at the meter. Telematics-derived kWh estimates are based on state-of-charge change and battery capacity assumptions. Real kWh — the number the charging network meter recorded, the number the fleet was billed for — comes from the charging network's session record, not the vehicle. The price per kWh paid. This is on the network's session record and the fleet card transaction, not in telematics. Whether this was the cheapest option available. The driver may have been parked next to two chargers — one at $0.32/kWh, one at $0.43/kWh — and chosen the more expensive one. Telematics knows where the vehicle charged. It doesn't know what it didn't charge at. Whether the cost is being attributed correctly. If this is a personal vehicle being charged on a fleet card, telematics doesn't know. If this is a fleet vehicle being charged on a personal card and reimbursed, telematics doesn't know. The relationship between the vehicle and the payment record lives in a separate system. What this charging behavior is doing to the battery's long-term value. Frequent DC fast charging accelerates battery degradation. So does prolonged dwelling at high state of charge, especially in heat. Telematics can record the charging events, but linking them to a financial impact — this charging pattern is reducing this vehicle's projected resale value by a documentable amount — requires correlating telematics data with charger session data, charger type information, and resale value modeling that doesn't exist in the telematics platform.

This is the structural gap. Your telematics platform is observing the operational layer. The financial layer is in a different set of systems. They were never designed to talk to each other, and in most fleets, they don't.

The questions this gap makes hard To make this concrete, here are questions a finance leader at a mixed-fuel fleet would reasonably want to answer in any given month. For each, consider how much of it your telematics platform can give you. Question 1: What is our actual cost per mile, by vehicle, for the EV portion of the fleet — and how does it compare to diesel? Telematics gives you the miles. It does not give you the cost numerator. Without correlating telematics mileage to fleet card transactions and charging session records, you have a denominator without a numerator. A precise fraction with a missing top half. Question 2: Which drivers are choosing more expensive charging when cheaper options were available, and what is that costing us per month? Telematics knows where each driver charged. It does not know what other charging options were available to them at that location, or what those options would have cost. Answering this question requires layering charging network pricing data, location-aware availability data, and the actual transactions, and then comparing chosen-cost to optimal-cost per driver. None of those layers exist in telematics. Question 3: Which vehicles caused last month's depot demand charge spike, and what would it cost to prevent it? Demand charges show up as a single line on the utility bill. Telematics knows when each vehicle arrived at the depot and started charging. The depot's charging management system knows the simultaneous load profile. The utility bill shows the charge. Putting these three together — vehicle X, charger Y, time Z, contributing kW W to the spike that triggered charge $C — requires correlating three datasets that none of the participating systems own. Question 4: Is one of our EVs degrading faster than the fleet average, and what's the projected residual value impact? Telematics can tell you battery state of health, where the OEM exposes it. It cannot tell you why one vehicle is degrading faster than another, because the explanatory variables (DC fast charging frequency, time spent above 80% state of charge, thermal exposure during charging) require charger session data correlated with the telematics-side battery readings. The recent Geotab study of 22,700 vehicles found 2.3% average annual degradation across the dataset — with what the study's authors described as "enormous variance" that telematics data alone couldn't fully explain. Question 5: Is anyone using a fleet card for charging that our vehicles didn't actually do? Fleet card statements show the transaction. Telematics shows the vehicle's location at the time. Putting these two together — and flagging mismatches, where the card was used somewhere the vehicle wasn't — requires correlation that neither system performs by default. These are the questions finance leaders ask. None of them are answerable with telematics alone, no matter how good the telematics platform is. They require the telematics data to be one layer in a stack that also includes charging network session data, fleet card transactions, depot energy data, and a model that holds them together.

Why this gap exists It's worth dwelling briefly on why this gap exists, because it isn't an accident, and it isn't going to close on its own. Telematics platforms make their money by being deeply integrated with vehicle operations. Their natural product expansion is into more granular operational data — better driver scoring, more accurate predictive maintenance, deeper safety telematics, better video integrations. Expanding outward into financial integration is a different kind of work. It requires partnerships with fleet card issuers, charging network operators, accounting systems, and utilities — all of whom have their own product strategies. It also requires a different buyer. Telematics platforms sell into the fleet operations team. The fleet operations team's question is "is the platform helping us run the fleet better?" The financial integration question — "is this giving our finance team the data they need?" — usually doesn't surface in operational evaluations. So even when telematics platforms have done some financial integration work, it tends to be a feature added late, not the design center of the product. Fleet card companies are in the same shape, looking from the other direction. They were built around fuel transactions, where the fleet card carries enough information (gallons, price per gallon, vehicle, driver, odometer, location) to be self-sufficient. EV charging broke that model. The fleet card transaction now carries one useful field — the dollar amount — and someone, somewhere, has to enrich it with the missing detail. That someone is rarely the fleet card company; the integration work isn't worth it for them at the per-vehicle margins they operate on. Charging network operators, similarly, are focused on their own product surface — the charging experience, network expansion, rate competitiveness. Their session data is rich, but exposing it in a way that integrates cleanly with fleet card and telematics data isn't their core priority. The result is a gap that nobody operating in the existing fleet software market is structurally incentivized to close. Each system is good at its own thing. The cross-system layer is where the financial questions live, and it isn't anyone's home territory.

What closing the gap actually requires Closing this gap — building an answer to the questions in the section above — requires four datasets to be brought together in one place:

Vehicle data from telematics: identity, location, driver, mileage, state of charge, battery state of health where available Charger session data from charging networks (public sessions) and depot OCPP feeds (private sessions): kWh, duration, price, charger type, network identity Fleet card transaction data from the card issuer: dollar amount, merchant, timestamp, card number Energy cost data from utility bills (for depot charging) and home utility rates (for driver home charging)

Bringing these together is, technically, not exotic. The data sources have APIs or exportable records. The matching logic — linking a fleet card EV transaction to the charging session that generated it, attributing the session to a vehicle via telematics location and timing — is solvable engineering work. Once the data is unified, the questions in the previous section become tractable. What it requires is a system that's structurally focused on this cross-system integration as its primary purpose, rather than as a feature appended to a telematics platform, a fleet card portal, or a charging network dashboard. The work is not glamorous. It's matching, normalization, exception handling, audit trail construction, and reporting. It's accountancy work with software in front of it.

The implication for fleet managers If you're a fleet manager today — running operations, talking to your CFO, being asked questions you can't fully answer with the tools at your disposal — there are two practical takeaways. First, recognize what you have and what you don't. Your telematics platform is doing what it was built to do. Its limits aren't a failure of the vendor; they're a feature of the category. Asking your telematics platform to give you cost-per-mile-by-vehicle reporting that includes EV charging is asking it to do something it wasn't designed for. Your CFO doesn't need to hear "Geotab can't do that." Your CFO needs to hear "the financial reporting is in a different layer of the stack, and here's what we'd need to build it." Second, the layer that closes this gap is becoming a recognizable category. A few years ago, the answer to "where do I get cross-system financial reporting for my mixed-fuel fleet" was "you build it yourself in spreadsheets, or you don't get it." That's changing. There are now products specifically designed to sit in the financial intelligence layer between vehicle data, charger data, and payment data. None of them are perfect yet — the category is young — but the alternative ("we'll just keep doing it in spreadsheets") is becoming a worse answer every month. The 2.3% average annual battery degradation finding from Geotab's recent 22,700-vehicle study is a useful data point in this argument. The variance the study identified — vehicles degrading at meaningfully different rates from the fleet average, for reasons telematics data alone couldn't fully explain — is exactly the kind of question that requires correlated data across multiple systems. The fact that one of the largest telematics studies ever conducted ran into the limit of what telematics alone could explain is not a negative reflection on Geotab. It's a positive demonstration of where the next layer of fleet software has to live.

Closing thought Telematics platforms are necessary infrastructure for any modern fleet. They are also, on their own, insufficient to answer the financial questions that mixed-fuel fleets generate. Recognizing that distinction is the first step to building a fleet data architecture that gives both the operations team and the finance team what they need. If your fleet manager and your CFO are asking different questions, and only one of them is being answered well, the gap is structural, not personal. It's a gap worth closing — for the operational confidence it gives the fleet team, and for the financial clarity it gives the finance team. The data exists. The technology to bring it together exists. What's needed is the recognition that this is a category of software in its own right, not a feature missing from your telematics platform.