Embedded OEM Telematics: The new landscape of connected fleet data

Remember when adding GPS trackers to every vehicle was the only way to manage your fleet? Those days are rapidly fading into the rearview mirror. Today's vehicles are rolling off assembly lines already equipped with sophisticated OEM telematics systems, creating both exciting opportunities and unexpected headaches for fleet managers everywhere.

As a fleet operator or telematics service provider, you're likely wondering: What exactly can I do with this built-in technology? How reliable is the data? And perhaps most importantly – does this mean I can finally say goodbye to aftermarket hardware installations? These aren't simple questions, especially when you're juggling vehicles from multiple manufacturers, each speaking their own digital language.

In this deep dive, we'll decode how OEM telematics actually works, explore what data you can expect to receive (from gasoline to electric vehicles), and tackle the very real challenges of turning this manufacturer-provided information into actionable insights for your business. We'll also spotlight how Navixy is bridging the gaps with solutions tailored for this new connected reality.

From OnStar to everywhere: OEM telematics goes global

A few decades ago, connected car tech like GM’s OnStar was a luxury add-on; today embedded telematics is powering fleets worldwide. In fact, three out of four cars sold in 2023 came equipped with an OEM-installed telematics system. This built-in hardware (typically a telematics control unit with a cellular modem and GPS) allows vehicles to transmit data directly to the manufacturer’s cloud. What was once novel is now mainstream: virtually all major automakers have some connected vehicle platform, and adoption is sky-high in key markets.

The surge isn’t limited to cars. Commercial fleets and off-road equipment are increasingly “born connected.” All major truck manufacturers in Europe, for example, now offer OEM telematics solutions as part of their product portfolio. In China, domestic OEMs like BYD, NIO, Geely, and SAIC bundle advanced telematics and even in-car app ecosystems into their vehicles, driven by a tech-savvy customer base and government initiatives for data sharing. The result is a connected vehicle boom: today’s fleets might include sedans reporting their fuel level to the cloud, semi-trucks uploading engine health stats in real time, and excavators pinging their hours of operation to an equipment management portal.

Why this explosive growth? Automakers recognize that data is gold – for them and their customers. Fleets can make profitable, data-driven decisions and streamline operations when they have direct insight into vehicle performance. OEMs see a chance to differentiate their product (a car that comes “fleet-ready” off the lot) and tap into new revenue by offering telematics services. In short, the connected car has evolved from a differentiator to a must-have feature, with both commercial and regulatory forces propelling it forward. As one industry analysis summarized the trend in OEM telematics data: “more!” – more vehicles connected, more data collected, more applications enabled.

What exactly is embedded telematics? (And how it differs from aftermarket)

Let’s clarify definitions. Embedded OEM telematics refers to the telematics hardware and software built into a vehicle at the factory. Think of a hidden “black box” or modem in your car that automatically logs data and connects to the internet. This contrasts with aftermarket telematics devices – those add-on GPS trackers or OBD-II dongles that fleets can install in any vehicle. Both serve a similar purpose (collecting vehicle data and sending it to a server), but their origin and integration differ greatly.

OEM embedded systems are native to the vehicle’s design. The automaker installs the module and integrates it with the vehicle’s CAN bus and sensors. This tight integration means access to deeper, vehicle-specific data that third-party devices might miss. It also means no installation required after purchase – a new fleet vehicle can be activated remotely in hours rather than spending days wiring aftermarket units into dozens of trucks. As a result, OEM telematics eliminates hardware installation downtime and comes online “out-of-the-box” for instant fleet visibility.

However, aftermarket telematics has its own strengths. Independent providers’ devices are brand-agnostic – a single platform can connect mixed fleets of Fords, Toyotas, Freightliners, you name it. By contrast, OEM solutions historically were siloed by brand (Ford’s data in Ford’s portal, GM’s in GM’s portal, etc.), which is impractical for mixed fleets that have multiple makes. A trucking company with five different truck brands would need five different OEM telematics dashboards – a non-starter for efficient operations. Aftermarket systems unify all vehicles under one roof. They’re also free of any conflict of interest – an independent TSP will gladly tell you to trim your fleet for efficiency, whereas an OEM might not rush to inform you that you could downsize your fleet (they’d rather sell more trucks!).

Today, these lines are blurring. Many OEMs now realize they must play nice in mixed fleets, and some are partnering with independent platforms or offering cross-brand support. For example, Ford’s telematics program even allows installing their device in other-make vehicles to unify fleet data on Ford’s platform. Likewise, telematics platforms like Navixy are building connectors and adopting standards (like the Navixy Generic Protocol, NGP) to ingest OEM data alongside aftermarket devices seamlessly. The end-game is a unified ecosystem where it won’t matter whether data comes from an embedded module or a plugin device – it all speaks the same “language” on the platform. Navixy’s NGP, for instance, acts as a universal translator, normalizing hundreds of proprietary device protocols into one format. This way a telematics solution provider simplifies integration and ensures that whether a data packet comes from a built-in BMW modem or a third-party tracker, it’s handled uniformly.

Telematics protocols: do all these vehicles speak the same language?

One of the technical hurdles in telematics is the Babel of protocols. Each OEM historically developed its own way of encoding and transmitting data – essentially, each speaks a different dialect. Telematics protocols encompass both the in-vehicle data communication (how signals from the engine, brakes, battery, etc. are packaged) and the server communication (how the device sends data over cellular networks to the cloud).

Inside the vehicle, data is often gathered via the CAN bus (Controller Area Network) – a vehicle’s internal network carrying signals from dozens of Electronic Control Units (ECUs). The OEM telematics unit listens for relevant parameters (speed, fuel level, fault codes, etc.) on the CAN bus. But which parameters get sent, and how often, is up to each OEM’s logic. For transmission, many embedded devices use standard cellular data links and common protocols like HTTPS or MQTT to push data to the cloud. However, the data schema – the structure and naming of the data – varies widely. For instance, one OEM’s API might label an odometer as “Odo” in kilometers, another as “Mileage” in miles; one sends a simple boolean for door lock status, another sends an enum code. The lack of standardization is a headache for TSPs: integrating five OEM APIs can feel like building five separate systems.

There are efforts to standardize. In the past, consortia tried to create common telematics frameworks (one example is NGTP – Next-Generation Telematics Protocol – initiated by European OEMs). More recently, industry groups like COVESA (Connected Vehicle Systems Alliance) have proposed standard data models (e.g. Vehicle Signal Specification). But adoption is slow – OEMs tend to prioritize their own ecosystems first. As a result, aggregators and platforms are filling the gap by translating these different “languages”. Navixy’s approach with NGP is one such solution: instead of feeding raw, disparate protocols upstream, devices (or IoT gateways) convert everything to the NGP schema, which the platform then uniformly processes. This drastically reduces the integration burden and ensures consistent data definitions (so “engine_speed” means the same thing whether it came from a Toyota or a Tesla).

For a fleet manager or TSP, the takeaway is that while vehicles might not natively speak the same language, modern telematics platforms serve as real-time translators. The days of juggling multiple protocol parsers and custom data mappings are fading. With tools like Navixy’s IoT Logic and Data Stream Analyzer, one can define data transformations and verify data flows easily, ensuring that a “Vehicle Ignition On” event from any source triggers the same downstream alert. This is crucial for scalability – it’s hard to manage thousands of vehicles if every subset speaks a different dialect. A standardized protocol layer turns a cacophony of data into a coherent symphony.

From fuel gauges to battery health: data attributes across vehicle types

One big promise of OEM telematics is rich, vehicle-specific data. So what exactly can we get from these embedded systems? It turns out, a lot – but it depends on the vehicle type (gasoline, hybrid, electric) and the manufacturer’s offerings. Let’s break it down:

• Common core data (all vehicles). Almost every OEM telematics unit provides a basic set of data that includes the vehicle’s GPS location (latitude/longitude), speed, and heading; ignition status (on/off); and often the odometer reading. You’ll also usually get fuel level for combustion vehicles or state-of-charge (% battery) for EVs. Altitude, time stamps, and VIN (vehicle ID) are typically in the mix too. This core data alone is hugely useful – fleets can track where vehicles are, how far they’ve gone, and their fuel/energy reserves, all without any aftermarket hardware.

• Gasoline/Diesel vehicle data. In addition to location and fuel, ICE (internal combustion engine) vehicles can report engine data like RPM, coolant temperature, oil life remaining, and diagnostic trouble codes (DTC) from the engine control unit. OEM APIs often expose some of these diagnostics so you know if the check-engine light is on and why. Fuel consumption rate or average MPG, throttle position, and even odometer readings direct from the vehicle (which are more reliable for maintenance scheduling) may be accessible. Some OEMs provide maintenance alerts – e.g., GM’s OnStar can report oil life and tire pressures; certain European models can even tell if brake pads or fluid need service. These data points let fleet managers proactively schedule upkeep.

• Hybrid vehicle data. Hybrids offer both worlds – fuel and battery data. Telematics can report not only fuel tank level but also battery charge, whether the vehicle is in EV mode, and hybrid system warnings. For example, a Toyota hybrid might tell you the battery’s state of charge and if the engine is currently running or auto-stopped. This can help in measuring fuel vs electric usage in hybrids and understanding their performance. Most underlying data (like DTCs or maintenance info) are similar to combustion vehicles, with some additional fields for the electric drive components.

• Electric vehicle (EV) data. EVs tend to broadcast a wealth of information through telematics – critical because fleets need to manage range and charging. Key EV-specific attributes include battery State of Charge (SoC) (%), charging status (charging, not charging, plugged in or not), charge rate, and estimated range (miles or km remaining). Many EVs will also report battery health metrics (like total kWh available, or if any battery cells are weak) and charging history. Some OEM APIs for EVs even include charging session details – start/end times, energy added – which are great for tracking electric fuel costs. Temperature of the battery and whether thermal management is active might be available on certain models. In short, EV telematics goes beyond location to give an almost real-time fuel gauge and refueling (charging) log for electric fleets. A fleet manager can remotely check if an EV van has enough charge for the next shift or if it’s currently plugged in and how soon it will be full.

• Advanced and niche data. Beyond the basics, OEMs are continually adding new data points to their APIs – though not always consistently. Some high-end European cars offer telemetry like driving behavior (e.g., whether stability control was engaged, harsh braking events, etc.), environmental data (outside temperature, wiper status which could imply rain, etc.), and even cabin info (is AC on? what’s the interior temp?). Maintenance-related data can include detailed service reminders (brake pad wear, oil change due dates, etc.). Electric trucks or specialty vehicles might provide data on auxiliary systems (for instance, a refrigerated truck’s telematics could give reefer unit status via the OEM if integrated). Industrial machine telematics (from OEM systems on bulldozers or tractors) often include engine hours, hydraulic pressure, payload weights, and more – tailored to equipment use-cases.

It’s worth noting that data availability varies widely by OEM and model. One brand might expose tire pressure data, another might not; one might allow retrieval of seatbelt status (for safety tracking), others keep that private. Therefore, fleets should identify which data points they truly need and check OEM support before buying vehicles. If an OEM lacks a critical data point (say, you really want real-time tire pressures for safety), you might need to install an aftermarket sensor or telematics device to get it.

Finally, there’s a class of data that’s notably not (usually) available via OEM telematics: remote controls and high-frequency sensor data. For security and safety, most automakers are cautious about allowing remote commands like unlocking doors or starting the engine through their public APIs. Only a few (Tesla, some Stellantis brands) have begun to permit such actions for fleet use. Similarly, data when the vehicle is off or out of cellular coverage is a blind spot – many OEM units don’t buffer and upload later, so if a car is shut down, you may lose location tracking until it’s turned on again. Dedicated aftermarket telematics units often have internal memory to store data during outages and then forward it when back online, which is something OEM systems currently lack. We’ll discuss these gaps more in the challenges section, but it’s an important caveat when considering OEM data completeness.

When and how often do vehicles “phone home”?

Having lots of data is great – but how frequently do we actually receive it from OEM systems? Reporting frequency (or data latency) is a critical factor, especially for use-cases like real-time tracking or driver behavior monitoring. Here, embedded telematics sometimes shows its conservative, consumer-oriented roots: OEMs often prioritize minimizing data usage and battery drain, so they may send data less frequently than hardcore fleet telematics devices would.

A typical OEM telematics system might update the vehicle’s status once every minute or two when the ignition is on. In some cases, it could be even less frequent (e.g., one update every 5 minutes) or event-based (send when ignition on/off, send when fuel level changes by X, etc.). By contrast, many aftermarket fleet trackers can be configured for 10-30 second intervals or even higher frequency with continuous streaming for things like accident reconstruction.

Why the gap? OEM systems were historically designed for use cases like emergency response (which doesn’t need high frequency), remote diagnostics, or stolen vehicle tracking – scenarios where minute-by-minute is usually fine. Additionally, cellular data costs money; an automaker providing free connected services for say 5 years per car will try to avoid a data-hungry configuration. Thus, they often dial down the frequency to balance cost and usefulness.

That said, the situation is improving. Some OEMs now offer “high frequency” data options delivering updates as fast as every 30 seconds, especially under premium fleet API packages. For example, BMW’s fleet telematics API can provide location updates every 30 seconds when the car is moving, which is sufficient for many tracking needs. Tesla, known for being a tech-forward brand, effectively streams data almost continuously when their vehicles are in motion (which is how third-party apps for Tesla can show nearly real-time location).

It’s also common that the ignition state dictates reporting frequency: when the vehicle is off, many OEM systems fall back to a very sparse schedule (or no reporting at all). Some might ping once every few hours just for status, or only on change (like if a door opens while parked, it might send an alert). When the vehicle is on, they ramp up to the active rate (e.g., every minute). If an OEM system detects an incident (airbag deployment, crash), it will typically send an immediate emergency notification regardless of the interval.

For EVs, frequency can depend on whether plugged in. During charging sessions, some will send frequent updates (to update charge percentage); others might just report start and end of charge.

The bottom line: OEM telematics usually isn’t as granular out-of-the-box as specialized fleet trackers. But if your use-case can tolerate, say, knowing a truck’s position within the last minute rather than the last 10 seconds, OEM data can work. If you need higher resolution (perhaps for driver behavior scoring like harsh braking events or for usage-based insurance calculations), you might need either to supplement with additional sensors or hope the OEM provides event-triggered data. Some OEM APIs do offer event flags – e.g., a “harsh braking event” alert with timestamp – even if they don’t provide second-by-second speed records. Those can be extremely useful: instead of sifting through high-frequency data, you get a distilled alert.

Navixy’s platform helps bridge any gaps here by allowing hybrid setups: you could use OEM data for 90% of needs, but also attach a low-cost aftermarket sensor for specific high-frequency metrics, all funneled into the same system. Moreover, features like Navixy’s IoT Logic can simulate higher frequency insights – for instance, if you get one location per minute, the platform can interpolate or snap to roads for smoother visualization. The Data Stream Analyzer tool can monitor if data isn’t coming in as often as it should (say an expected “heartbeat” every 60s – it will flag if, suddenly, nothing came for 5 minutes, indicating an outage or issue). In essence, as vehicles “phone home” sporadically, the telematics platform acts like a good receptionist: if the call doesn’t come on time, it notices and can take action (alerting or buffering data from alternate channels).

Data quality matters: accuracy, completeness, and timeliness

All that glitters is not gold, and all that data from OEM telematics isn’t perfect. Data quality issues – ranging from accuracy of the values to the completeness of the dataset – are common challenges that fleet managers encounter. Let’s unpack a few key concerns and how they manifest:

• Accuracy. This can refer to sensor accuracy or the correctness of the data reported. For example, fuel level readings are notoriously finicky – the float sensor in the tank might only estimate to the nearest 5% and can be affected by the vehicle’s tilt. Some OEM telematics will report fuel level as an integer (0-100%) which might jump in chunks, giving a coarse picture. GPS accuracy is another factor: if an OEM unit uses only GPS and not newer GNSS or augmentation, you might see position drift of several meters. Speed reported from GPS vs. from the vehicle’s wheel sensors can differ slightly. There are also units conversion mistakes occasionally – one OEM API might give you an odometer in miles, another in km, and if you don’t realize, you’ll think one car drove 60 “units” when it actually is 60 miles vs 60 km (a ~1.6x error). Ensuring consistency (and converting units) is vital. Navixy’s NGP helps here by standardizing units and formats across devices, so you always get, say, kilometers and liters unless otherwise specified. Additionally, diagnostic data accuracy (like engine temperature or tire pressure) depends on sensor calibration; usually OEM sensors are pretty good, but if data seems off (e.g., unrealistic engine RPM), it may be a parsing issue or sensor fault. As a TSP, you often need to build logic to sanity-check incoming data and flag anomalies.

• Completeness. We touched on this earlier – data gaps are a reality with many OEM setups. Imagine a fleet car goes into an underground parking garage (no cellular signal) and then drives 50 miles before coming out in coverage. If its OEM telematics doesn’t store data offline, that entire trip might be missing from your records. You’ll simply see the vehicle jump from point A to point B with no info in between. For fleets where route tracking or trip records are important, this is a headache. Similarly, if a vehicle is powered off, a lot of OEM systems report nothing; they essentially go to sleep. So if someone tows the vehicle or it’s stolen while off, you might lose track. Aftermarket devices often have internal backup batteries and wake on motion to report even if the car’s off – OEM ones often don’t, to avoid draining the vehicle battery. Timeliness is related: even if data is being collected, how quickly do you get it? If an OEM solution only sends data after accumulating it for a few minutes, you have a delay. Most are fairly real-time, but some might batch data to save on overhead. For instance, an OEM device might collect data every 15 seconds but only transmit to the cloud every 60 seconds as one packet of four points. Usually this is fine, but it means you wouldn’t get an accident alert immediately at the 0 second mark – it might come a minute later, which in safety terms can be critical.

• Latency and jitter. This refers to the delay from when something happens to when you know about it, and the consistency of that delay. If a driver turns on the ignition, does your platform reflect that in a few seconds, or only on the next minute update? Is the update interval consistent or sometimes 30 seconds, sometimes 2 minutes (jitter) due to network variability? Typically, OEM data might have a bit more latency than a direct device feeding into a platform because it goes vehicle -> OEM server -> (maybe aggregator) -> your platform. Each hop adds delay. Many OEM APIs are polling-based: your system might have to ask the OEM server for new data, say, every 60 seconds. If the data just missed the polling window, you wait another minute. Some newer integrations are event-driven or push-based, which improves latency. TSPs need to design with tolerance for a bit of lag. For example, Navixy’s platform can ingest both instantaneous device streams and slower API feeds; using its Data Stream Analyzer, one can measure how fresh each source’s data is and generate alerts if something is stale (e.g., “Vehicle hasn’t updated in 5 minutes”).

• Consistency and reliability. OEM telematics services can occasionally experience outages or quirks. Perhaps the automaker’s cloud has maintenance, or a new vehicle model’s data comes in a slightly different format than documented. These can cause dropped data or parsing errors. Another factor is completeness of fields – one day you might get a data point (say, battery voltage), next day that field is null for some reason on the API. This could be due to a vehicle firmware update or an API version change. A robust solution has to handle missing fields gracefully and perhaps try to fetch them again later. Raw data storage is a great practice here: Navixy’s Raw Data Datalake, for instance, keeps all the raw incoming messages in full detail. If something looks fishy in processed data, engineers can dig into the raw logs to see if, say, the vehicle stopped sending a particular parameter or if it was never there to begin with. This historical raw archive is a lifesaver when debugging data accuracy issues – it’s like having the black box flight recorder for your fleet data.

In summary, while OEM telematics provides valuable data firehose, it’s not always a perfectly clean stream. Smart fleet management means filtering and compensating: using platform logic to fill gaps (interpolate or assume last known good), cross-check (compare odometer vs GPS distance to catch odometer resets or errors), and alert on anomalies (like a fuel level drop from 50% to 0% in one minute could mean a sensor fault… or a fuel theft!). Embracing these data quality challenges is part of the journey – and with proper tools, one can turn raw OEM data into reliable, actionable insights.

Europe and China at the forefront: OEM telematics trends by region

Embedded telematics may be a global phenomenon, but regional trends and manufacturer strategies differ, especially in Europe and China. These two hubs have been leading the charge in connectivity, albeit for different reasons.

EUROPE: European automakers were early adopters of connected tech for safety and service differentiation. The EU’s eCall regulation, which took effect in 2018, mandated that all new cars must have the capability to automatically call emergency services in a crash. This essentially meant every new car needed a cellular-connected telematics unit (even if a very basic one). That pushed Europe’s new car telematics attach rate to about 90% by 2023 – on par with North America’s 91%. European OEMs like BMW, Mercedes-Benz, Audi/VW, and Volvo have offered connected car services (remote door unlock, vehicle status apps, concierge, etc.) for many years. They also rolled out fleet-specific programs: e.g., Mercedes has Daimler Fleetboard (for trucks) and Mercedes PRO for vans, BMW aunched a CarData platform and fleet APIs for corporate customers, and Volkswagen introduced We Connect Fleet. A notable European concept is the “Extended Vehicle” model, where the OEM acts as a gatekeeper to vehicle data, providing it to third parties via cloud APIs (as opposed to allowing direct OBD-II access). This approach, championed by organizations like ACEA, was meant to address cybersecurity by funneling all access through the OEM’s backend. The result is that independent service providers must interface with each OEM’s cloud to get data – which can be cumbersome but is exactly why aggregators emerged in Europe to simplify that.

European fleets also face strict data protection laws (GDPR), meaning driver consent and privacy are paramount. In many European countries, even if a company owns the vehicle, the driver must consent to sharing data from it. OEMs therefore have built consent management into their workflows. For example, a fleet may have to upload a driver-signed consent form to the OEM before data flows – an extra step not as common in the U.S. In practice, this has slowed some B2B data services rollouts in Europe, but it’s being streamlined.

On the technology side, Europe is seeing a lot of standardization in backend. Many European OEMs have partnered with platforms like High Mobility, Targa Telematics, or Munich Re’s Car Data platform, to offer one-stop-shop APIs for multiple brands. This signals a trend: rather than every OEM reinventing the wheel, they might use common interfaces for third parties. Also, Europe’s focus on sustainability and efficiency means telematics data is leveraged to reduce emissions and improve logistics (e.g., using data to optimize routes and cut idle times). We also see Android Automotive OS making headway in European cars (e.g. Volvo, Renault adopting Google’s platform), which could eventually blur lines between infotainment and telematics data – though that primarily impacts user-facing features for now.

CHINA: If Europe’s push was regulatory and premium-service driven, China’s connected vehicle surge is driven by a mix of consumer tech enthusiasm and government direction. Chinese OEMs have been very aggressive in adding connectivity to cars – as of 2023, 78% of new cars in China have embedded telematics, and rising fast (up from ~65% the year before ). One driver is that Chinese consumers are extremely mobile-app centric; they expect their car to integrate with their digital life (navigation, music, remote control via phone apps, etc.). Brands like NIO, Xpeng, BYD, Li Auto distinguish themselves not just by the car’s hardware, but by the software experience – over-the-air updates, smartphone control apps, and even in-car “app stores” are selling points. Indeed, Chinese automakers were among the first to integrate features like in-car e-commerce and video streaming. By 2023, Chinese brands were equipping vehicles with app ecosystems on the infotainment units, something foreign brands are now starting to emulate.

On the government side, China has a unique regulation for NEV (New Energy Vehicles – i.e., EVs and plug-in hybrids): manufacturers are required to send EV battery and location data to a national monitoring platform for safety and research purposes. This means every EV in China has connectivity by mandate, effectively. While that data is for government use, it ensured the hardware is there and likely spilled over into consumer features. China’s regulators also actively shape data security via the IoV (Internet of Vehicles) standards – recent guidelines (in 2021-2022) mandate secure handling of car data and restrict exporting vehicle data out of China. So international TSPs working with Chinese OEM data must often use local servers and abide by data localization rules.

In terms of services, Chinese OEM telematics often offer more “lifestyle” features: AI voice assistants in the car, remote air-conditioning start (to pre-cool the car in summer, for example), and deep phone integration (some cars integrate with WeChat for messages). For fleets, this might not seem directly relevant, but it showcases how embedded telematics is non-negotiable in China – it’s the conduit for all these features. For commercial fleets, local companies like Alibaba, Tencent, and Baidu have partnered with OEMs to provide telematics and AI solutions (like AliOS automotive operating system, Baidu’s Apollo platform for telematics and autonomous data). The Chinese market also leans towards all-in-one platforms – a fleet management app might incorporate OEM data, dashcam video, and even driver behavior scoring powered by AI, all tied into ubiquitous super-app ecosystems.

NORTH AMERICA: While the question emphasizes Europe and China, a quick note – the U.S. and Canada have also reached high connectivity (91% of new cars ). There, it was more market-driven: GM’s OnStar (since 2000s), followed by Ford, Chrysler, etc., all added telematics to add value (remote start, roadside assistance) and later to enable subscription services (Wi-Fi hotspot in car, etc.). By mid-2010s, every major automaker in NA had some offering. The ELD mandate for trucks (Electronic Logging Device) in the U.S. indirectly boosted telematics in commercial trucking, though many opted for aftermarket ELD devices, some truck OEMs integrated ELD features into their telematics platforms for sale. The net effect is that whether it’s a luxury sedan in Los Angeles or a semi-truck hauling freight cross-country, chances are it’s connected – or will be next time it’s replaced.

OTHER REGIONS (Latin America, Africa, SE Asia) are catching up, though cost and infrastructure are factors. In 2023, outside the big markets, less than 40% of new vehicles had telematics, but that will rise as affordable connectivity and regulations (like Brazil’s stolen vehicle tracking requirement or India’s AIS-140 standard for GPS in public transport) proliferate.

To summarize the regional landscape: Europe and China are trailblazers – Europe from a regulatory and premium OEM stance, China from a consumer-tech and policy mix. Both have near-saturated new car connectivity and are exploring next frontiers (like vehicle data monetization platforms and V2X infrastructure). For TSPs, this means in Europe you’ll navigate stringent consent and multiple OEM portals (unless you use an integrator), and in China you’ll work within a framework of heavy connectivity but also heavy data governance (and maybe interface with Chinese platforms). In both cases, a platform like Navixy that can handle multi-country, multi-OEM data with compliance in mind is invaluable. For example, Navixy’s compliance tools can help ensure GDPR requirements (like ability to delete personal data or record consent) are met when using EU vehicle data, and its flexible deployment (cloud or on-prem) can accommodate data localization needs for markets like China.

Beyond passenger cars: telemetry in trucks and heavy equipment

It’s not just sedans and SUVs getting all the telematics love. Commercial vehicles and industrial machines have their own telematics ecosystems, which are crucial for professional fleet managers to understand. These sectors often pioneered telematics before it was cool – long-haul trucks and construction equipment have leveraged remote monitoring for maintenance and logistics for many years. Let’s take a tour:

• Trucking and commercial fleets. All major truck OEMs (Freightliner and Navistar in the US, Daimler Trucks, Volvo Trucks, Scania, MAN in Europe, FAW and Dongfeng in China, etc.) offer factory telematics for their vehicles. For example, Daimler’s Fleetboard, Volvo’s Dynafleet, Scania Fleet Management, Paccar’s TruckTech+, and so on. These systems provide data similar to cars (GPS, fuel, speed) but with truck-specific additions: engine hours, diesel exhaust fluid (DEF) level, brake wear, axle weights (if sensors), and advanced engine diagnostics. They also often tie into fleet management services for trucking, like remote download of tachograph data (in Europe) or driver log integration.

  The adoption in heavy trucks is quite high for large operators – it’s reported by Penske that over 50% of large fleets use telematics on their trucks, whereas small fleets lag (only about a third of small fleets use it). This indicates a divide: big logistics companies instrument everything (sometimes using the OEM’s solution, other times removing it and using a third-party), while a local 5-truck company might still be in early stages of adoption due to cost. In North America, the ELD mandate essentially forced even small fleets to adopt at least a minimal telematics device (for hours-of-service logging), boosting penetration.

  One challenge with OEM truck telematics is that mixed fleets are very common – a company might have Freightliners and Volvos, etc. Using each OEM’s portal separately is inefficient, so many turn to aftermarket fleet platforms that can aggregate data. Interestingly, OEMs themselves sometimes partner with those platforms: e.g., Volvo’s Mack brand allows data piping into third-party systems, and major fleet telematics providers have data integration programs with OEMs like Ford, GM, Volvo Trucks, and others, effectively acting as an aggregator. Navixy similarly can ingest OEM data for trucks if the API is available, or you can always fallback on a hardware device that Navixy supports (with its library of virtually all modern device integrations).

  Another note on trucks: trailers and assets towed by trucks also have telematics (tracking trailers, containers, etc.), but those are usually always aftermarket add-ons since a trailer isn’t tied to one truck OEM. Still, modern trucking telematics solutions combine both truck (tractor) data and trailer data for a full picture. OEM tractor data can tell you when a trailer is connected or if the trailer ABS threw an error (some trucks can read trailer diagnostics via the ISO 11992 connection). So it’s a rich field where OEM and non-OEM data blend.

• Light commercial vehicles (vans & pickups). These often fall under passenger car divisions for OEMs (e.g., Ford Transit vans use Ford’s telematics tech just like Ford cars). So availability is high, especially in Europe where vans are common for delivery fleets. Many vans now come with optional connectivity modules (Ford, Peugeot, Mercedes Sprinter, etc. all have solutions). Fleets that run delivery vans (like logistics, service companies) might use those OEM solutions or add their own devices if they need features like driver ID, etc. Pickup trucks in North America (think Ford F-series, Chevy Silverado) have high connectivity rates because they’re also consumer vehicles and OEMs include those features across their lineup. So the data from a fleet of pickups can be pulled via OEM APIs similarly. The use-cases: routing, delivery verification, fuel usage, etc., don’t differ much from cars, but one interesting aspect is job-specific equipment on these vehicles. For instance, a utility company’s pickup might have a boom lift; OEM telematics probably won’t cover that accessory’s status. That’s where aftermarket sensors still play a role (and where Navixy’s IoT Logic can merge those sensor inputs with OEM vehicle data for a holistic view).

• Buses and public transport. City buses and coaches often have telematics for operations and passenger info (like tracking arrival times). Some bus manufacturers provide this (e.g., Volvo and Mercedes make buses with telematics). Also, regulations in some places require GPS tracking on public transport for safety. While not a focus of this article, it’s worth acknowledging that OEM telematics isn’t just about personal or freight vehicles – it extends to mass transit too.

• Industrial, construction, and specialty equipment. This is a fascinating domain. Heavy machinery OEMs have been extremely forward with telematics – largely to support maintenance contracts and maximize uptime for customers. Caterpillar, for instance, has its Cat Product Link telematics on excavators, bulldozers, generators, you name it, and they have over 1.4 million connected assets globally using it! Companies like John Deere (JDLink), Komatsu (Komtrax), and others each have hundreds of thousands of machines connected. These systems report data like engine hours, fuel burn, idle vs work time, error codes, and location. They help schedule preventative maintenance (dealers often monitor machines and contact owners when service is due) and assist in machine utilization analysis on job sites. For fleet managers dealing with construction or agricultural equipment, tapping into OEM data can yield big benefits – e.g., automatically logging operating hours for each machine to allocate costs per project, or geofencing machines to prevent unauthorized use.

  Industrial telematics often has to contend with harsh environments and sometimes no cellular coverage (mining sites in remote areas). OEM solutions might use satellite uplinks or require local data logging. Some third-party providers offer dual-mode telematics hardware that works in those conditions. So integration here can be complex. Navixy’s platform, with its flexible device integration, can combine data from OEM feeds and any aftermarket rugged trackers (including satellite and LPWAN devices) to ensure even off-grid assets are accounted for.

Table: OEM telematics adoption across vehicle categories

For a quick overview, here’s how embedded telematics availability and usage vary by segment:

As we see, OEM telematics now spans almost every vehicle category, but usage patterns differ. Fleet managers often end up with a hodgepodge of data sources – a few vehicles natively connected, some older ones outfitted with aftermarket devices, maybe an equipment OEM portal or two – which brings us to the question of how to aggregate and actually use all this data efficiently.

Getting the data: OEM APIs, aggregators, and third-party platforms

So your vehicles are broadcasting all this great data to the manufacturer’s cloud – how do you, as a fleet manager or TSP, tap into it? There are typically two routes: direct from the OEM or through an aggregator/third-party platform. Each has pros and cons, and often a combination is used.

Direct OEM APIs

Many automakers provide API platforms or data services for customers (especially fleets) to retrieve telematics data from their vehicles. These are essentially web services where, once you’re authenticated and permissioned, you can query vehicle data (or subscribe to updates). Examples include GM’s OnStar Business Solutions API, Ford Data Services (accessible via their Ford Pro platform), Toyota’s MSPF, Mercedes-Benz Fleet API, Volkswagen’s Car-Net/We Connect APIs, and so on.

To use these, typically four steps are needed :

1. Subscribe to the OEM’s service and API. Often you need to purchase a telematics service plan for each vehicle (sometimes included for a period when you buy the vehicle). For fleets, OEMs usually have a B2B API program separate from the consumer app. These B2B APIs often come with fees or service contracts but allow bulk access to data (consumer ones might limit to one vehicle per account). For instance, BMW has a “BMW CarData / BMW Fleet API” for companies, and GM has a fleet telematics plan independent of the consumer OnStar account.

2. Authenticate and connect. You’ll register your application (or use a partner platform) and get API keys or OAuth credentials. Then you set up connections to the OEM’s endpoints. This is a non-trivial development effort, as each OEM API is different. One might use REST JSON calls, another uses SOAP XML, each with its own data schema. There’s also maintenance – if the OEM changes something, you adapt. Few OEMs unify across brands (an exception is Stellantis, which now encompasses FCA and PSA brands; they’re working on one platform for all). So if you have five makes in your fleet, you may be coding to five APIs. This is where many throw up their hands and consider aggregators, which have done this work already,

3. Provide vehicle credentials/proof. OEMs need to ensure only authorized parties access a vehicle’s data. So fleets usually must prove ownership or permission. This can be uploading documents like registration or purchase info for each VIN, or sometimes a bulk letter. Mercedes, for one, has required something like 15% of VINs to be proven with docs as a spot-check, Others may ask for a signed declaration that you indeed own those vehicles, or verification of the current odometer reading from the user as a consent mechanism. It can be bureaucratic, but it’s a one-time onboarding step per vehicle or fleet.

4. Driver/owner consent. Particularly in Europe (and increasingly elsewhere), you may have to obtain explicit consent from the vehicle’s primary driver or owner to access data. If your company owns the vehicle and employs the driver, this might be a form the driver signs acknowledging tracking. These consent forms might be stored in case of audits. Some OEMs integrate a digital consent – e.g., the driver might get an email to click approve, or in the vehicle’s infotainment, they accept a prompt. It varies. But it’s a step to be mindful of (and not to skip, for legal compliance).

Once set up, the data flow begins! You will likely receive JSON or XML messages with the vehicle data at intervals or upon request. Some APIs are push (they send you data to a callback URL or MQTT topic), others are pull (your system must poll for each vehicle’s latest status). If it’s pulled, you’ll schedule periodic calls to get updates.

Aggregators and data marketplaces

If doing all the above for every OEM sounds daunting, you’re not alone. This need gave rise to vehicle data aggregators – companies that do the heavy lifting of integrating with dozens of OEM APIs and offer a single unified API to customers. Examples include Otonomo, Wejo, High Mobility, Smartcar, MotoLauncher (formerly Abright), and others. Their pitch: “One contract, one API, access to many brands.”

For instance, High Mobility’s platform lets you connect vehicles from BMW, Mercedes, Audi, Ford, etc., and they provide a normalized data model so you don’t have to parse each differently. Navixy’s platform can integrate with such services or customers might use them to feed data into Navixy via webhooks.

Pricing structures for these services typically involve per-vehicle subscription fees or per-data-call fees. High Mobility advertises prices starting from €0.99 per vehicle per month for basic data packages, with tiered plans above that. That would be for something simple like odometer or fuel level infrequently. More comprehensive data or higher frequency can cost a few euros per vehicle monthly. Otonomo historically had pricing in the few dollars per car per month range for basic fleet data, sometimes with volume discounts. They may also charge setup or API usage fees (e.g., some charge per API call if you exceed a certain quota).

For fleets, this cost might still be lower than installing hardware (which could be $100+ device cost plus $5-$10/month service each). But at scale, paying, say, $3 per vehicle to the aggregator plus the OEM’s subscription if any, can add up. Some OEMs don’t charge directly and just allow aggregators who then charge you; others require you to have an active OEM plan as well as paying the aggregator.

Another flavor of aggregator is the vertical-specific platform. Navixy similarly to be a one-stop where whether you use hardware trackers or OEM feeds, the platform handles it. In effect, the telematics platform itself can serve as your aggregator if they’ve built those connections.

Availability of data via aggregators is generally good for major brands, but can be hit-or-miss for smaller or region-specific OEMs. European, American, and some Asian brands are commonly integrated. Chinese OEM APIs might not be as readily available to foreign aggregators for regulatory reasons. So if you operate a fleet of, say, Chinese domestic brand cars outside China, you might find less support. In such cases, direct dealing with the OEM’s local entity might be needed.

One also must consider that not all data is equal – some OEMs have tiers of data (basic vs premium package). Aggregators usually support multiple data packages, and you choose what you need (and pay accordingly). E.g., basic might include location and mileage; advanced might add fuel and tire pressure and DTCs.

Typical process using an aggregator: You sign up with aggregator X, provide proof of vehicle ownership/consent similarly (they often handle it in a streamlined way, you give them VINs and docs, they do the legwork with OEMs or have pre-approvals). Then they give you an interface to activate each vehicle’s data feed. Once activated, you start getting data in a unified format. It’s more convenient, but you’ve introduced a middleman (cost and another point of dependency).

Third-party telematics platforms and integration

The third route is leveraging a telematics service provider platform like Navixy that has built-in support for OEM data. The advantage here is you also get the application layer – i.e., a ready-to-use fleet management interface, analytics, alerts, etc., on top of the data, whereas raw aggregator API just gives data and you’d still have to build an app or integrate into one.

With Navixy, for example, you can connect OEM data in two ways:

• Use device simulators/connectors if Navixy has integrated a particular OEM (Navixy’s library of devices could include virtual “devices” representing OEM API data streams).

• Use Navixy’s API/SDK to push data from an aggregator or OEM API into Navixy (the Data Bridge feature can help funnel external API data into the platform, translating it if needed via NGP).

The heavy lifting of harmonizing data is handled by Navixy’s system so that it appears just like any other tracking device in the interface. This means a fleet manager can see their OEM-connected vehicles on the same map and reports as those with aftermarket trackers. They can set alerts (geofence, overspeed, etc.) and run analytics (fuel consumption reports, driver behavior) across the whole fleet uniformly.

A note on pricing: Some OEMs have started offering direct fleet platforms themselves – e.g., GM has OnStar Vehicle Insights (a fleet web portal for GM vehicles data, subscription-based). These can be decent for single-make fleets but don’t solve multi-make. Their pricing can range from $10 to $20 per vehicle per month typically (since they bundle software and data). In contrast, aggregators might be cheaper but require an existing platform to use the data. TSP platforms like Navixy are hardware-agnostic – whether you pay the OEM or an aggregator for data, you’d pay Navixy for the software service as usual (which is often per vehicle or device as well, but you might not need a physical device).

In summary, accessing OEM telematics data has gotten much easier with these new channels. You no longer need to negotiate separately with every car manufacturer if you use an intermediary that did that already. However, each layer adds cost and potential latency. Large fleets sometimes go direct to OEM to cut out fees (especially if they have dev teams to integrate APIs). Mid-size fleets might use an aggregator to save dev time. Small fleets might bypass OEM data entirely and just stick an aftermarket GPS tracker in for simplicity’s sake (even if the car is connected, because dealing with OEM setup was historically complex – though that’s changing).

For a TSP launching services around OEM data, a wise approach is often a hybrid: integrate a few top OEM APIs directly for core brands, and use an aggregator for the long tail of less common ones, all funneled into your platform’s unified model. Navixy’s flexible API and NGP make it straightforward to funnel in data from various sources: one partner might feed from OEM A, another from aggregator B – once in Navixy, it’s normalized and clients can leverage features like IoT Logic (to trigger automated workflows on certain data conditions) regardless of source. And if something isn’t available via OEM (say an older vehicle without telematics), you can always fall back on installing a supported aftermarket tracker. Ultimately, TSPs must be data-source-agnostic problem solvers – the fleet customer just wants their info, it’s our job to stitch it together behind the scenes.

Hurdles for TSPs: authentication, coverage gaps, cost, and latency

Even with all this progress, telemetry from OEM systems isn’t plug-and-play bliss. TSPs and fleet managers face practical challenges when working with OEM data. Let’s highlight the main pain points:

• Authentication and integration complexity. Connecting to OEM APIs means navigating different authentication schemes (OAuth tokens, API keys, certificates) for each. Keeping tokens refreshed and secure is non-trivial. A TSP might need to maintain dozens of API integrations, each with its own quirks. If one OEM changes their API version or requires re-auth (perhaps the fleet’s subscription expired and renewed), the TSP has to handle that smoothly. This overhead is why TSPs value solutions like Navixy’s NGP and integration toolkit – they abstract a lot of these differences. It’s akin to juggling many keys for many doors versus having a master key. TSPs essentially have to become experts in each OEM’s developer portal (assuming one exists and is in a language they understand – some Chinese OEM docs might not be in English, for example). This is a resource challenge: not all telematics companies have the developer bandwidth to do 10 different API projects in parallel, plus continuous maintenance. That’s often a justification to use aggregators or middleware.

• Coverage gaps and mixed fleets. No matter how new or high-tech a fleet is, there tend to be coverage gaps in OEM data. Maybe 80% of the fleet are new connected models, but 20% are older or off-brand that don’t have OEM systems. During a transitional period (like now), fleets will be hybrid – some vehicles feed via OEM, others via installed devices. This can create data silos if not unified. Moreover, as noted, even connected vehicles can have gaps when out of network or powered down. For TSPs, this means you need to handle incomplete datasets. You might have to tell clients, “We can get X data when the vehicle is on, but if it’s off we can’t, unless we install a backup device.” Some advanced setups include a backup battery on the OEM unit, but that’s rare. One creative solution some car-sharing companies did was install a secondary telematics unit purely to cover remote unlock and offline logging, even if the car had OEM telematics – because the OEM wouldn’t do those needed functions. For a typical fleet, redundancy might not be cost-effective, so they live with the gaps. TSP platforms can mitigate this by at least clearly indicating last known data time (so you don’t assume current info if it’s 3 hours old). Navixy’s platform, for instance, shows the last update timestamp prominently, and one can set up alerts like “no contact for 30 minutes” to catch when a vehicle has effectively gone dark.

• Data consistency and standardization. Each OEM provides data in a different structure, which can lead to inconsistencies unless normalized. For a TSP, mapping these to a common data model is a continuous task. It’s not just naming – even the meaning might differ (one OEM’s “idle” status might mean engine on but vehicle not moving for 5 minutes, another might not even send an idle flag at all). Ensuring a consistent experience (so that a “stop” event or “trip distance” is calculated uniformly across all vehicles) may require translating or even deriving data. For example, if OEM A doesn’t give a direct odometer but gives GPS, you might accumulate distance manually, whereas OEM B gives odometer reading – to provide a report to the fleet manager, you need to combine these seamlessly. This is where IoT Logic on Navixy can help: one can write rules or formulas to derive missing values (like calculate distance from GPS when odometer is missing) so that end reports don’t show blanks. But it’s a challenge behind the scenes.

• Costs and ROI considerations. As discussed, getting OEM data might involve additional costs – either paying OEM subscription fees or aggregator fees. TSPs integrating OEM data must factor this into their pricing. It can be a tough sell to customers: “Your new cars have OEM telematics – we can connect to them but it will cost $X per month per car for data access.” Some customers assume if the hardware is built-in it’s “free” to use – not always the case. TSPs might choose to absorb some cost to stay competitive, or highlight that even with a fee, it’s cheaper than installing new hardware. There’s also a cost in the time to integrate – which is an engineering cost. For smaller TSPs, pursuing OEM data might not yet be worth it if their clients’ fleets are mostly older vehicles. But as the balance shifts (with ~75% of new vehicles having it, eventually a majority of fleets will have some OEM data capability), ignoring it isn’t viable long-term.

• Latency & real-time limitations. OEM pipelines can introduce latency (as covered earlier). For a TSP promising real-time visibility, it’s a bit awkward if OEM-fed vehicles show a slight delay or slower refresh compared to those with aftermarket devices. TSPs must communicate expectations (“updates every 60 seconds” vs “every 10 seconds”) clearly to clients. There is also the issue of command latency – if you send a command (like remote door unlock for a car), how fast does it execute via the OEM system? Some OEMs might take 5-10 seconds to wake the car and do it, others might be near instant. And as mentioned, not many OEMs even allow remote commands via API yet, which can be a limitation for services like car rental or sharing. This means TSPs catering to those use cases still need aftermarket hardware to perform certain actions (immobilizers, horn honks, etc.).

• Support and service dependencies. When a TSP uses OEM data, they become partly dependent on the OEM or aggregator’s service reliability. If the OEM’s cloud goes down or data is delayed, the TSP gets blamed by the fleet for any outage. However, the TSP might have little control in that scenario beyond raising a support ticket with the OEM. This loss of some control is uncomfortable for many providers accustomed to managing their own devices end-to-end. It underscores the importance of SLAs (Service Level Agreements). Many OEMs, when selling fleet API access, will provide some SLA or uptime guarantee, but it may not be as strong as what TSPs provide to their customers. Some OEMs still consider their APIs “beta” or best-effort. Aggregators might offer better consolidated SLAs. Regardless, TSPs should monitor OEM feeds and have alerts if data stops, so they can proactively inform clients (“Looks like manufacturer X’s data feed is temporarily down, we’re on it…”). Having a backup plan – even if it’s deploying a temporary device – can be a lifesaver for critical cases.

• Privacy and cybersecurity. Accessing OEM data brings responsibility to handle it per privacy laws and to secure the data. Fleets and TSPs must ensure that any personal data (like driver behavior patterns or location trails) are stored and used in compliance with regulations and the consent given. Cybersecurity is also key; OEM APIs if compromised could lead to unauthorized access. TSPs have to implement strong authentication and not expose those API keys. Navixy’s compliance tools can assist in managing data retention and permission controls – for instance, automatically purging personal trip data after a set time if required, or restricting who in an organization can view certain OEM-derived data (maybe only managers see driver score, not the drivers themselves, depending on policy).

Considering these challenges, TSPs are evolving their role. They are not just GPS tracking providers anymore but data integrators and analysts. Platforms like Navixy are gearing up by building the scaffolding needed: unified data protocols, edge processing (IoT Logic) to catch and fix anomalies on the fly, robust APIs to allow mixing multiple data sources, and comprehensive analytics that work whether the input is from a Teltonika tracker or a Tesla API. The competitive edge for TSPs in the OEM data era will be the ability to seamlessly blend all this into a coherent service for the fleet user. Those who can will thrive; those who can’t may find themselves outmaneuvered by new players (including the OEMs themselves, who might offer more direct services).

Navixy’s take: navigating the OEM data revolution

Throughout this article, we highlighted how Navixy’s capabilities align with these evolving industry demands – but let’s explicitly connect the dots. As OEM telematics becomes dominant, Navixy has positioned itself to empower TSPs and fleets in this new world:

• Raw Data Datalake: Given the concerns about data accuracy and completeness, Navixy’s Raw Data Datalake ensures that every piece of incoming data (from OEM APIs or devices) is stored in its original form. This transparent archive means nothing is lost, and if you need to audit or troubleshoot (e.g., “Did we miss a location update or did the vehicle never send one?”), you have the evidence, It’s a safety net that’s increasingly important when you rely on third-party data sources.

• Navixy Generic Protocol (NGP): As we discussed, the Babel of telematics protocols can be overwhelming, NGP is Navixy’s answer – a standardized language that all devices and data sources can speak on the platform. By converting disparate OEM data formats into NGP, Navixy dramatically cuts down the integration effort and potential errors. It essentially bakes in the solution to the “different data definitions” problem by mapping OEM fields to a common ontology. This future-proofs your fleet data strategy – new devices or OEM feeds can be added with minimal fuss, as they’ll just be translated into NGP.

• IoT Logic and Data Stream Analyzer: These tools shine in a world of complex data flows. IoT Logic allows TSPs and even end-users to create custom rules and processing pipelines on incoming data in real-time. For instance, you could make a rule: “If OEM data reports fuel < 10% and vehicle not at depot, send alert” or “If no GPS data from OEM for >5 minutes, switch to last known cell tower location if available” – any conditional logic can be crafted. This is crucial for tailoring OEM data (which might be raw) into meaningful actions. Meanwhile, Data Stream Analyzer is like a diagnostician for your data feeds. It lets you monitor the health of those incoming streams – is a particular vehicle’s data arriving on schedule? Are there parsing errors? It provides visibility into potential issues (like an API integration glitch or a misbehaving device) so you can address them before they impact operations. When juggling multiple OEM and device sources, this kind of oversight is a godsend.

• OBD-II/CAN/EV data support: Navixy has deep roots in supporting data from hardware trackers that read OBD-II and CAN bus info. This expertise translates to handling OEM data because, fundamentally, it’s the same data points. Navixy’s platform knows how to interpret fuel level, engine RPM, DTC codes, EV battery stats, etc., whether they come from a physical OBD dongle or an OEM cloud feed. For EVs especially, Navixy already supports parameters like state-of-charge, charging status, range – aligning perfectly with what OEM APIs provide. If an OEM’s data is lacking something, one can augment it. For example, if an OEM API doesn’t give tire pressure but you can install a Bluetooth tire sensor with a gateway, Navixy can merge that data. The flexibility ensures no data blind spots – whatever the vehicle can sensibly provide, Navixy can record and use, one way or another.

• Compliance and reporting tools. As fleets use OEM data for operations, they’ll also need to use it for compliance (think hours of service, fuel tax reporting, safety compliance). Navixy provides modules and reports for various compliance needs – and they aren’t limited to device data. For instance, you can use Navixy’s platform to log driver hours or mileage for tax, regardless of source. If the law requires retaining certain data for X years, Navixy’s data management can help with that too. Additionally, Navixy’s focus on data security and privacy (with robust user access controls and the ability to anonymize or delete personal data on request) helps TSPs comply with regulations like GDPR while leveraging OEM data. If a driver revokes consent, you can quickly disable that vehicle’s data feed and demonstrate erasure if needed.

• Unified user experience: Perhaps Navixy’s biggest strength is providing a single pane of glass for all fleet data. Fleet managers shouldn’t have to care that Truck 123’s location came from OEM API while Truck 124’s came from a tracker – they just see both on the map and in reports. Navixy’s frontend and analytics treat them uniformly. This also extends to high-level insights: you can run a fleet-wide fuel efficiency report that covers both OEM-equipped cars and aftermarket-equipped ones together. Or set up a dashboard that shows KPIs like utilization or driving behavior scores across the whole mixed fleet. Navixy ensures that the increasing fragmentation at the data source level does not result in fragmentation at the user level.

In essence, Navixy is equipping its users to embrace the OEM telematics era rather than be disrupted by it. It’s about turning what could be a chaos of apps and portals into a streamlined data powerhouse. A bit of subtle irony: the OEMs, in trying to capture data value, have inadvertently created a new pain point (multiple data silos) – which platforms like Navixy are cleverly solving, thereby adding even more value on top of the OEM offerings.

Embracing a data-driven fleet future

Embedded OEM telematics systems are rapidly becoming the circulatory system of the modern fleet, pumping a constant stream of data that – if properly harnessed – can yield healthier operations, safer drives, and a stronger bottom line. We stand at a point where nearly every new vehicle is a connected vehicle, whether it’s a compact electric hatchback or a 40-ton diesel truck. The challenge for telematics service providers and fleet managers is to ride this wave without drowning in complexity.

The current landscape offers immense opportunities: richer data (from engine fault codes to EV battery health), less hardware to install, and new services to offer drivers and customers. But it also presents new puzzles in integration, data management, and cost control. OEM telematics isn’t a silver bullet; it’s more like a new ingredient in the recipe – one that needs skillful mixing with the existing ingredients (aftermarket devices, business systems, etc.) to bake the perfect fleet management solution.

Key trends to watch include further standardization attempts (we may see more collaboration among OEMs on data formats as pressure mounts from industry and regulators), the rise of universal data marketplaces (imagine if vehicle data becomes as accessible as smartphone data APIs – not far-fetched with players like Google or AWS eyeing the space), and the creep of OEMs into traditional TSP territory by offering their own fleet platforms. However, fleets are rarely homogenous enough for a single-OEM solution to win out, so third-party platforms will continue to play the vital role of data aggregator and innovator.

For fleet managers, a practical takeaway is: inventory your data sources. Know which of your vehicles can provide OEM data and what kind, and make a plan for integrating that. Don’t be afraid to demand data access when purchasing vehicles – many OEMs have fleet data programs ready, but you might have to ask and sign the dotted line to activate them. It’s an asset you paid for when buying the vehicle, after all. And for any gaps, choose reliable aftermarket solutions to fill them.

Telematics service providers should focus on flexibility and partnerships. Build systems that can ingest data from anywhere and forge alliances with OEMs or aggregators where possible – this can unlock new offerings like insurance telematics, maintenance forecasting, or sustainability metrics (e.g., using precise fuel consumption data to calculate carbon emissions more accurately). Also, invest in the analytics and human factors: with so much data available, the winners will be those who make it insightful and user-friendly. A fleet manager doesn’t need raw data – they need actionable intel, like “Which vehicles are due for maintenance next week?” or “Which drivers could improve their eco-driving?”. When OEM data is combined with smart algorithms, you get answers to questions you didn’t even think to ask.

In a subtly humorous way, one could say we’ve gone from an era of “no data, only trust your gut” to “big data, too much to gut”. The role of platforms like Navixy is to make sure it feels more like “right data, ready for action”. As telematics continues to mature, the ecosystem will likely balance out – perhaps in a decade, we won’t distinguish between OEM or aftermarket data at all; it’ll just be vehicle data, universally accessible (one can dream!). Until then, staying informed and adaptable is key.

Fleet telematics has always been about connecting the dots – connecting vehicles to the office, drivers to dispatchers, maintenance alerts to mechanics. Embedded OEM telematics has added millions more dots to connect, scattered across OEM clouds and APIs. It’s a complex picture, but with the right strategy and tools, it becomes a vibrant, insightful mosaic of your operations. The landscape is indeed changing, but as we’ve seen, it’s changing in ways that ultimately empower those ready to adapt. So here’s to embracing the connected future – one data packet at a time – and turning these streams of data into driving smarter business decisions on the road ahead.