Distilling market noise into market sense

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Self-driving cars are about platforms, not about cars

There is growing consensus that fully autonomous cars will become a reality by 2020. Google self-driving cars have driven over 1.2 million miles. Elon Musk, Tesla CEO, predicted in September 2015 that Tesla cars will have fully autonomous capability in 3 years. Zvi Aviram, CEO of MobileEye, a supplier of self-driving systems to many car makers, expects their technology will support fully autonomous driving by 2019.

Most traditional car makers still see autonomous driving as a feature of the car, rather than a market shift that will open the path to the creation of a completely new winner-takes-all industry. It’s just like PC makers focusing on adding connectivity to their products and missing the transition to the Internet platforms (Google Search, Amazon, Facebook). Or telecom operators focusing on adding always-on fast data connectivity to their networks and missing the transition to the mobile platforms (Google Android, Apple iOS).

Is the same about to happen in the car industry? Are car makers about to miss the transition to transportation platforms in the same way as PC makers missed the transition to Internet platforms and telecom operators missed the transition to mobile platforms?

The future transportation value stack will be very different from the existing automotive industry. It quite remarkable that only two companies, Google and Uber, are present in all layers of the stack that are necessary for creating a dominant transportation-as-a-service platform.

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The car hardware (the body, the power train, the wheels) increasingly becomes a commodity. Modern cars are good-enough for typical everyday use offering little opportunity for differentiation. Car commoditisation will only accelerate with the transition to electric vehicles. Electric vehicles are much simpler mechanically and easier to make, which opens the gates for new players, including such electronics and Internet services players like Apple, Google, LeTV and even Acer. It’s also notable that Tesla ‘open-sourced” their electric vehicle patents in 2014 pledging not initiate patent lawsuits against anyone who, in good faith, uses Tesla’s technology.

Autonomous driving is about guiding the car along the road, following the rules while avoiding obstacles and crashes. It involves lots of sensors, computing power and sophisticated software, but the most important part here is the ‘data’. Self-driving systems are machine learning systems that are trained to evaluate the environment and make fast decisions on how to react.

The ‘data’ represents all the collective experience learned by multiple cars driving in test and real-world conditions. The more cars you have on the road and the more miles these cars have driven in all possible conditions, the more experienced, safe and precise the self-driving system becomes. Google is undisputed leader here having its fleet of test cars driven over 1 million miles. Tesla’s Autopilot feature introduced in October 2015 on Model S cars will allow Tesla to start training its self-driving system in real-life conditions on tens of thousands of cars.

Uber seem to be behind in terms of putting real self-driving cars on the roads. The company poached 40 researchers and engineers from the Carnegie Mellon’s robotics lab in March 2015 and partnered with University of Arizona on optics research for self-driving cars.

Navigation is about figuring out which roads and streets the car should drive on in order to get from point A to point B. Google is again is a clear leader here with Google Maps and Waze. A consortium of German carmakers (Audi, BMW and Daimler) is trying to uphold an alternative acquiring the Here Maps business from Nokia in August 2015 for $3.1 Billion. Uber also works to create a proprietary mapping platform winning independence from Google and Here Maps. The company acquired San Jose-based deCarta in March 2015, absorbed part of Microsoft Bing mapping assets in June 2015 and has partnered with TomTom in November 2015 to use its mapping and traffic data. (Is Microsoft about to miss the huge opportunity in the future automotive and transportation markets?)

Fleet routing this is where it gets much more interesting. Self-driving cars combined with Uber-style on-demand services make individual car ownership less and less attractive. Some people even claim that hardware-as-a-service is the end game for Tesla. The shared usage models will turn car market into something that looks like a public transport platform, where operators will match in real-time the demand for transportation with the location and the capacity of self-driving vehicles. In other words, fleet guidance is about deciding in real-time where every car needs to go. Which car needs go to a specific pick up point? Shall the car drive to where the demand is expected in the coming 15 minutes? What is the optimal time to recharge or refuel? When and where to go to do the service and maintenance? Where to park, and more.

This is a very complex computational problem to solve at the scale required to support fleets of thousands of self-driving cars. Bill Gurley, one of Uber’s early investors, gives a glimpse into how difficult it is in his blog explaining why UberPool is the new Uber’s “Big Hairy Audacious Goal.” (BHAG). UberPool helps the company to build capabilities that will be directly relevant for the optimal routing of large autonomous fleets.

I’m sure Google is not standing still here as well. Being a machine learning company, it has the scale and the technical depth to become the leader in this space. Add to that real-time bidding capabilities with extremely complex optimisations that Google has mastered for its online ad business. One can even argue that building such transportation platform is the reason for Google’s interest in self-driving cars.

It’s very difficult to see how traditional car makers will be able to compete with software-centric companies in this space.

Finally, the transportation platform is the most intriguing part of the value stack. Moving people around Uber-style is not the only use for self-driving cars. What else can we do with the fully autonomous fleet of robotic vehicles, given that they don’t not have to look as Uber or Google cars of today? These robotic vehicles can be specialized delivery vehicles (see this Domino’s Pizza car as a hint for how they may look like), small delivery drones like Transwheel or StarShip or even autonomous motorbikes, like Motobot by Yamaha.

The number of possibilities and applications for autonomous transportation is mind boggling. No single company, even as nimble and well-funded as Google or Uber, will be able to address all possible needs and use cases by themselves. The recipe for addressing these yet to be known needs and use cases is in plain sight. It is a platform connecting vehicle manufacturers, vehicle operators, service providers and application developers with users (much like Google did with Android).

The platform will harvest permissionless innovation by startups and developers to discover and deploy new services and applications we cannot even imagine today – in the same way that no one could predict Instagram, Snapchat or WeChat on smartphones. Uber already works with developers extending its service into a platform. Google also has a long history of relying on permissionless innovation by developers to win its competitive battles, from Google Maps to Android. It’s only natural that Google will use the same approach to dominate self-driving cars.

It’s still too early in the game to say which companies will dominate the future transportation market. One thing is a safe bet: The future transportation ecosystem will look very different from the existing automotive industry. It will resemble modern technology ecosystems with their platform business models, permissionless innovation by developers, and domination of software-centric companies.

— Michael

  • Hugh Quigley

    The urban world is on the cusp of experiencing the most fundamental shift in transportation since the introduction of the automobile with wide ranging impacts on the both the physical structure of the urban landscape and many traditional business models.

    It is likely that many of the incumbent vehicle manufacturers will find tech companies swiping their core market unless they can adapt from manufacturing vehicles to manufacturing transport solutions.

    Soon urban people will own cars in the same way that many people now own boats – to primarily provide pleasure with transport requirements secondary.

    • Michael V.

      Hugh, I think it is even more than car makers adapting from manufacturing vehicles to manufacturing transport solutions. The latter requires new business models that are often incompatible with the incumbent’s DNA.

      • Hugh Quigley

        Thanks for the reply, Michael. I agree with your point: it will be incredibly difficult for existing manufacturers to write off all their infrastructural investments in existing business models and convert to a new model. Several of them are making changes (e.g. BMW and even Ford) but they have a long way to go and probably underestimate the speed at which innovation is about to collapse the traditional model.

  • Apan

    I think this analysis greatly over-simplifies the market drivers in the automotive space. First, if we for a moment accept the idea that people in crowded cities are willing to give up ownership, this does not in any way imply that people in less densely populated areas are willing or even able to give up their cars. (Think the typical American 4×4 owner, or someone in the remote parts of Scandinavia…)

    Second, just because I give up my own car and utilize a car pool or a fleet of autonomous vehicles for my transportation needs I will still require a typical ride to be “pleasant” in terms of comfort and style. This means that the underlying hardware is still very much a normal car; and designing and building a car bottom-up with profit requires a skill set that is vastly different from building let’s say mobile phones.

    Third, as a consumer of semi-public transportation I don’t really care about who made the navigation system, who created and designed the autonomous driving capabilities etc, I only care about the _experience_ of being driven from point A to B and whom I can hold accountable if things fail. This does not imply that Google/Apple/Über etc does not have a place in the future transportation eco system, but I highly doubt that they will dominate it.

    Fourth, the fleet optimization problems involved are not really that hard. This is something that is already well researched and where there exist solutions from other industries that can scale with/in this new domain. And the thing is that the number of “data points” are really not that staggering. Consider a mega city with 15 million people. Such a city might have 1-3 million autonomous vehicles. Even if you need to track and compute thousands of parameters per vehicle (and most likely we’re rather talking “hundreds” or even “tens”), this is well within the reach even for a very modestly sized data warehouse.
    Even more so for more ordinarily sized cities. The only upside for Google, Amazon etc here is that they already have computing infrastructure in place.

    (Btw. Stating that an electric vehicle is so much easier to build is just plain wrong, it’s just shifting complexity from one point to another in the design and manufacturing phases…)

    • Michael V.

      Apan, so you say that the industry will remain as it is today irrespective of self-driving cars. This could be pretty risky assumption. It is tech companies who drives creation of new value (“innovation”) in the transportation value-chain, much like in telecom, healthcare, education, banking, aviation and entertainment. Therefore tech companies will drive the agenda. Car makers are not going away anytime soon, but they will have rather different role and market power in the new value-chain.

      • Apan

        Thanks for the reply!
        Nope, that’s not what I’m saying. I’m saying that the assumptions made by people outside the automotive space are overly simplified. I would say that it’s a rather risky assumption to write off the traditional OEMs and their suppliers as “non-tech”. Essentially everything that adds value in a premium car today is already governed by software.

        Given that autonomous driving, viewed in a system setting, is “soon” a commodity – how is Google/Apple/someone else supposed to add value in a way that the traditional OEMs cannot?
        Granted, self -driving cars will definitely be disruptive in how we *use* cars, but the technology in itself is far from the disruptive technology its made out to be.
        More than one OEM already have the technology for autonomous driving and their advantage is that they are already 100% immersed in the regulatory environment governing the automotive space. (And their technology is on par with Google and Tesla, but they deliberately downplay their achievements…) They also have production capacity that cannot be matched without huge investments.
        Further, OEM’s and their re-sellers are already experimenting with new business models for usage, like private leasing and cooperating with car pools, so there’s really no surprise in store for them on that front either; they’re definitely picking up the trends.
        So I would say that betting on Google/Apple to monetize autonomous vehicles is a very risky bet.

        • Michael V.

          Hi Apan, interesting discussion. Your arguments are almost exact replica of telco reasoning 5 years ago. Car industry will benefit a lot from learning what happened in telecom. Telco don’t go away anytime soon. Eberybody needs them. But guess what? Their business suddenly became much much less attractive (profitable) than it used to be. Financial markers don’t like that, which is a problem for a capital intensive business to say the least. This happened because value creation moved to other parts of the value chain leaving incumbents with a) a commodity business and b) little ability to influence the course of events. There are examples of specific telco mistakes that are a direct parallel to your arguments, but this is longer discussion than we can have here. Drop me a note if you’d like to hear more.

          • Apan

            Hi Michael, I definitely see what you mean, but I still disagree with (most of) your conclusions… 🙂
            From my perspective it’s quite sobering to sit down and look at the different use cases enabled (or that we think will be enabled) by for example self-driving and/or fully autonomous vehicles some time in the future.
            It’s quite easy to list a bunch of exiting use cases, but what’s more interesting is to break down these cases into a set of actions/issues/bullets that needs to be addressed by someone who looks to profit from them. And I’m not really talking about software or platforms, even though that will be important pieces.

            Further, I think you might have missed the fact that the OEM tier in automotive is already a really-low-profit-margin business for a majority of the players, so it’s not like they’re enjoying the cosy oligo/duo/monpoly national markets the telcos did in the 90’s. Rather, the’re actively looking for new ways to add value. If they will succeed? No idea, but I wouldn’t count them out…

    • Remedy Ailment

      poor analysis in my opinion on your first point, i don’t think that the article implies a binary switch over from existing usage to modern, Look at internet access for how things are likely to develop, large commercial centres with dense populations will be serviced first for many ($$$) reasons gradually as networks and technology, cost and availability increase so will accessibility for everyone. There will still be those who hold onto the legacy and thats fine but i think this misses the point – being that its going to happen whether some people like it or not. Second point the point was already made about modern cars already becoming a commodity, base levels of comfort are already attained and differentiation is splitting hairs in this already commoditised market. Third most people will care about getting from A to B not some abstract *experience* if i can leave my home at a specific pre-defined time that guarantees i get to work or some other destination at a specific time, that will matter much more than any experience other than simply being transported from A to B reliably – transportation becomes a passive activity allowing me more of my valuable time to do something else, not directing my vehicle along roads. Fourth this seems to be a bit naive of the real problem, check out the computing power required to automate operation of the hong kong underground system. The key here is real time as well, real-time is not a domain that data warehousing really caters for at all, this is a huge technical challenge even for todays compute capability. Electric cars are easier to build, this has been explained many times by Elon Musk its ALL about the power source

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