Authored by Joe Bender and DIMO Co-Founder Andy Chatham
The next 10 years of the automotive industry are shaping up to be a bloodbath. As competition heats up the knives are starting to come out, and gaps are opening up for new product categories and business models.
Consider how much is at stake:
The public markets have priced in a very high chance that some of the legacy players like GM, Ford, Mercedes Benz, Stellantis, etc., will go bankrupt in the next 5-7 years. VW has said their core brand is no longer competitive and they’re years behind on shipping next generation software for vehicles.
If you went back in time and showed Henry Ford any car from the 20th century, he would be able to wrap his head around it. There would be an internal combustion engine, a highway map jammed in the glovebox, and an immediate trip to the mechanic when anything isn’t working.
Fast forward to today and imagine Henry hopping in a Tesla Cybertruck. Unless someone showed him how to use the Tesla app, he might not even be able to unlock it and start driving. The idea that computers thousands of miles away could send an update to the drive-by-wire system or autopilot would seem like witchcraft.
The Cybertruck is the most tangible proof that three of the biggest transformations in 100 years are going up the S-curve at the same time: EVs, Autonomy (AI), and Connectivity.
We’ll demystify these trends here and introduce some of the opportunities that are emerging for both automakers and completely new business models and applications.
Electric Vehicles
Most automakers started taking EVs seriously after the Tesla Model S launched in 2012, and since those companies operate on 10-year product cycles, their first real efforts came to market this year.
Except for Toyota (they primarily stuck with hybrids), the transition is not going great for any of the legacy automakers.
Tesla has a 60% (and climbing) EV market share in the US, and Chinese OEMs like BYD Company are eating their lunch in international markets. Things don’t seem to be looking up as they're walking back expectations for Gen2/3 vehicle sales and delaying spending.
Autonomy (AI)
This is the biggest unknown, as it's primarily driven by software improvements vs. hardware.
Most legacy OEMs (Original Equipment Manufacturers) have given up on their own "Full Stack" AV Plans and are relying on tech from Mobileye.
If (BIG IF) Waymo can get to a profitable/scalable robotaxi deployment that people don't hate in San Francisco or Phoenix, then there is likely a path towards automating 2-3% of the total trips.
Connectivity
Connected cars are unlocking novel use cases (and new attack surfaces).
To get a sense of the possibilities, watch this Tesla club set a new record by assembling 687 vehicles in the Finnish countryside to perform a coordinated holiday light show.
This also opened a digital Pandora’s Box when it comes to privacy. With such rich data being collected from vehicles, the attack surface broadens, and vulnerabilities are unfortunately commonplace.
In recent years, there has been a nonstop stream of disclosures from legacy automakers about customer data being compromised. In 2021, Volkswagen announced that an unauthorized third party obtained limited personal information about 3.3 million customers. In 2022, Mercedes-Benz disclosed a data leak affecting 1.6 million prospective and actual customers, including names, street addresses, email addresses, and phone numbers. Only this year, Toyota reported that they were victims of a decade-long data leak that exposed the data of 2.15 million customers.
The capability gap between legacy auto and new “Software Native” players is huge here:
Legacy OEMs need to differentiate vs. trying to copy Tesla.
Toyota has done this by sticking with Hybrids and partnering (Aurora Innovation & May Mobility) instead of buying AV companies.
Ford is doubling down on commercial vehicles with Ford Pro.
Many OEMs are building their own “walled garden” developer platforms. GM has shared some access to theirs, and Tesla is migrating an emerging ecosystem of 3rd party apps to a new protocol that will allow developers to access data directly from vehicles rather than having to rely on their servers.
The problem with this approach is that it’s hard to command developer attention when the biggest OEM (Toyota) only has 15% of the vehicles on the road, and the vast majority of them are unaddressable because they still aren’t connected to the internet.
This brings us to the open and permissionless approach - after all, when you buy the car, shouldn’t you own the data from it and use whatever apps you want?
There are some new approaches to create a more resilient system where drivers and fleets are in control of their data - DIMO has built an open, connected vehicle network that puts car owners in the digital driver’s seat, giving data back to drivers and helping them earn rewards.
Like Roku for TVs, DIMO goes “over the top” of OEMs to allow any car to connect: Using a hardware device that plugs right into a car’s OBD2 port or, more simply, by linking with the native connected car service like the Tesla app or FordPass, drivers can collect and store their own car data directly.
Today, this gives users comprehensive monitoring of all reported vehicle systems right in a mobile app or on the web for fleets.
Everything from odometer, battery health, location, fuel level, and VIN number, to useful utilities like reading confusing error codes, estimating the car’s valuation, or estimating battery capacity. Demystifying valuable vehicle metrics and putting them in the hands of the user is the first step to a more transparent automotive industry.
However, leveling up insights into your vehicle is only half of DIMO’s approach to car ownership. With such sensitive data on user driving habits, adopting the legacy strategy of storing this information on centralized corporate servers feels dangerous and antiquated.
That’s why DIMO chose to build an open network and anchor vehicle identity to a blockchain. This gives users with ownership of the network transparency into how their vehicle data is used and, most importantly, the ability to share it with any application they want.
DIMO users are rewarded for the longevity of their connection with the network and not necessarily the amount of time or miles driven. This incentivizes maintaining good-faith participation in the network and discourages reward farming. By having a car connected to the DIMO Network, users earn a weekly baseline issuance in $DIMO tokens. There are also opportunities for earning additional rewards by transacting with DIMO apps and services - like an airline reward point for your automotive spending.
The DIMO Marketplace is a collection of service providers that offer automotive solutions for drivers in the DIMO Network. By browsing the DIMO Marketplace in the mobile app, users can see partners that have offered tools and services valuable to car owners. For example, Marble is a digital insurance broker. DIMO users can leverage Marble to check for potential insurance savings and receive $DIMO tokens for utilizing the service. This sort of mutually beneficial ecosystem has never existed in the auto industry before today.
Typically, drivers are at the whim of big businesses that view consumers as the product. Additionally, the data that is maintained in the DIMO application can be invaluable when leveraging these services. In the past when visiting the mechanic, problems with the vehicle could be a total mystery. Now, with a quick glance at the car’s health in the DIMO app, a repair shop could easily assess that low battery voltage is causing ignition issues or suboptimal tire pressure is resulting in fuel inefficiency.
In the same way that there was a monumental shift in perspective when the internet was popularized, or smartphones were widely adopted, it is time to rethink the way we approach car ownership. It has been observed time and time again that open networks benefit the end user. DIMO envisions a future where driving doesn’t have to be so lonely because each car is sharing data and being rewarded for its contributions. If cars are closer to supercomputers than a vintage Model T, then why shouldn’t we be as conscientious about data privacy, transparency, and analytics as we are with our phones or laptops?