Uber and Tesla: What telcos should do

Introduction

This report analyses the market position and strategies of Tesla and Uber, two of four Internet-based disruptors that might be able to break into the top tier of consumer Internet players, which is made up of Amazon, Apple, Facebook or Google. The other two challengers – Spotify and Netflix – were the subject of the recent STL Partners report: Can Netflix and Spotify make the leap to the top tier?

Tesla, Uber, Spotify and Netflix are defined by three key factors, which set them aside from their fellow challengers:

  • Rapid rise: They have become major mainstream players in a short space of time, building world-leading brands that rival those of much older and more established companies.
  • New thinking: Each of the four have challenged the conventions of the industries in which they operate, driving disruption and forcing incumbents to re-evaluate their business models.
  • Potential to challenge the dominance of Amazon, Apple, Facebook or Google: This rapid success has allowed the companies to gain dominant positions in their relative sectors, which they could use as a springboard to diversify their business models into parallel verticals. By pursuing these economies of scope, they are treading the path taken by the big four Internet companies.


This report explores how improvements in digital technologies and consumer electronics are changing the automotive market, enabling Tesla and Uber to rethink personal transport almost from the bottom up. In particular, it considers how self-driving vehicles could become a key platform within the digital economy, offering a range of commerce services linked to transportation and logistics. The report also explores how the high level of regulation in transportation, as in telecoms, is complicating Uber’s efforts to build economies of scale and scope.

The final section provides a high-level overview of the opportunities for telcos as the automobile becomes a major computing and connectivity platform, including partnership strategies, and the implications for telcos if Uber or Tesla were able to make the jump to become a tier one player.

The report builds on the analysis in two previous STL Partners’ executive briefings that explore how artificial intelligence is changing the automotive sector:

Self-driving disruption

Uber, the world’s leading ride-hailing app, and Tesla, the world’s leading producer of all-electric vehicles, could evolve to become tier one players in the digital economy, as the car could eventually become a major control point in the digital value chain. Both companies could use the disruption caused by the arrival of self-driving cars to become a broad digital commerce platform akin to that of Amazon or Google.  As well as matching individuals with journeys, Uber is gearing up to use self-driving vehicles to connect people with shops, restaurants, bars and many other merchants and service providers.  With a strong brand, Tesla could potentially play a similar role in the premium end of the market as Apple has done in the PC, tablet and smartphone sectors.

However, Uber and Tesla are just two of the scores of technology and automotive companies jostling for a preeminent position in a future in which the car is a major computing and connectivity platform. As well as investing heavily in the development of self-driving technologies, many of these companies are splurging on M&A to get the skills and competences they will need in the personal transportation market of the future.  For example, Intel bought Mobileye, a maker of autonomous-driving systems, for US$15.3 billion in March 2017. Delphi, a big auto parts maker, bought nuTonomy, an autonomous vehicle start-up, for US$450 million, and has since reinvented itself as an autonomous vehicle company called Aptiv.

Self-driving vehicles will change the world and the way people live in a myriad of different ways, just as cars themselves transformed society during the 20th century. Some shops, hotels and restaurants could become mobile, while car parks, garages and even traffic lights could eventually become obsolete, potentially heralding new business opportunities for many kinds of companies, including telcos. But the most important change for Uber and Tesla will be a widespread shift from owning cars to sharing cars.

Contents:

  • Executive Summary
  • How Uber and Tesla are creating new opportunities for telcos
  • Uber’s and Tesla’s future prospects
  • Lessons for telcos
  • Introduction
  • Self-driving disruption
  • Making car ownership obsolete
  • From here to autonomy
  • The convergence of car rental, taxi-hailing and car making
  • Business models beyond transport
  • Opportunities for telcos
  • Uber: At the bleeding edge
  • Uber’s chequered history
  • Uber looks beyond the car
  • Uber’s strengths and weaknesses: From fame to notoriety
  • Tesla: All electric dreams
  • Tesla’s strengths and weaknesses: Beautiful but small
  • Conclusions and lessons for telcos
  • The future of Uber and Tesla
  • The future of connected cars
  • Lessons from Uber and Tesla

Figures:

  • Figure 1: Self-driving vehicles will become commonplace by 2030
  • Figure 2: The two different routes to self-driving vehicles
  • Figure 3: The first self-driving cars could appear within two years
  • Figure 4: Money is pouring into ride hailing and self-driving companies
  • Figure 5: Waymo is way ahead with respect to self-driving disengagements
  • Figure 6: Uber’s vision of a “vertiport” serving a highway intersection
  • Figure 7: Uber believes VTOL can be much cheaper than helicopters
  • Figure 8: Uber’s strengths, weaknesses, opportunities and threats (SWOT) analysis
  • Figure 9: Growth in Tesla’s automotive revenues has been subdued
  • Figure 10: Tesla’s strengths, weaknesses, opportunities and threats
  • Figure 11: Tesla loses money most quarters
  • Figure 12: Tesla is having to cut back on capex

Autonomous cars: Where’s the money for telcos?

Introduction

Connected cars have been around for about two decades. GM first launched its OnStar in-vehicle communications service in 1996. Although the vast majority of the 1.4 billion cars on the world’s roads still lack embedded cellular connectivity, there is growing demand from drivers for wireless safety and security features, and streamed entertainment and information services. Today, many people simply use their smartphones inside their cars to help them navigate, find local amenities and listen to music.

The falling cost of cellular connectivity and equipment is now making it increasingly cost-effective to equip vehicles with their own cellular modules and antenna to support emergency calls, navigation, vehicle diagnostics and pay-as-you-drive insurance. OnStar, which offers emergency, security, navigation, connections and vehicle manager services across GM’s various vehicle brands, says it now has more than 11 million customers in North America, Europe, China and South America. Moreover, as semi-autonomous cars begin to emerge from the labs, there is growing demand from vehicle manufacturers and technology companies for data on how people drive and the roads they are using. The recent STL Partners report, AI: How telcos can profit from deep learning, describes how companies can use real-world data to teach computers to perform everyday tasks, such as driving a car down a highway.

This report will explore the connected and autonomous vehicle market from telcos’ perspective, focusing on the role they can play in this sector and the business models they should adopt to make the most of the opportunity.

As STL Partners described in the report, The IoT ecosystem and four leading operators’ strategies, telcos are looking to provide more than just connectivity as they strive to monetise the Internet of Things. They are increasingly bundling connectivity with value-added services, such as security, authentication, billing, systems integration and data analytics. However, in the connected vehicle market, specialist technology companies, systems integrators and Internet players are also looking to provide many of the services being targeted by telcos.

Moreover, it is not yet clear to what extent the vehicles of the future will rely on cellular connectivity, rather than short-range wireless systems. Therefore, this report spends some time discussing different connectivity technologies that will enable connected and autonomous vehicles, before estimating the incremental revenues telcos may be able to earn and making some high-level recommendations on how to maximise this opportunity.

 

  • Executive Summary
  • The role of cellular connectivity
  • High level recommendations
  • Contents
  • Introduction
  • The evolution of connected cars
  • How to connect cars to cellular networks
  • What are the opportunities for telcos?
  • How much cellular connectivity do vehicles need?
  • Takeaways
  • The size of the opportunity
  • How much can telcos charge for in-vehicle connectivity?
  • How will vehicles use cellular connectivity?
  • Telco connected car case studies
  • Vodafone – far-sighted strategy
  • AT&T – building an enabling ecosystem
  • Orange – exploring new possibilities with network slicing
  • SoftBank – developing self-driving buses
  • Conclusions and Recommendations
  • High level recommendations
  • STL Partners and Telco 2.0: Change the Game 

 

  • Figure 1: Incremental annual revenue estimates by service
  • Figure 2: Autonomous vehicles will change how we use cars
  • Figure 3: Vehicles can harness connectivity in many different ways
  • Figure 4: V2X may require large numbers of simultaneous connections
  • Figure 5: Annual sales of connected vehicles are rising rapidly
  • Figure 6: Mobile connectivity in cars will grow quickly
  • Figure 7: Estimates of what telcos can charge for connected car services
  • Figure 8: Potential use cases for in-vehicle cellular connectivity
  • Figure 9: Connectivity complexity profile criteria
  • Figure 10: Infotainment connectivity complexity profile
  • Figure 11: In-vehicle infotainment services estimates
  • Figure 12: Real-time information connectivity complexity profile
  • Figure 13: Real-time information services estimates
  • Figure 14: The connectivity complexity profile for deep learning data
  • Figure 15: Collecting deep learning data services estimates
  • Figure 16: Insurance and rental services’ connectivity complexity profile
  • Figure 17: Pay-as-you-drive insurance and rental services estimates
  • Figure 18: Automated emergency calls’ connectivity complexity profile
  • Figure 19: Automated emergency calls estimates
  • Figure 20: Remote monitoring and control connectivity complexity profile
  • Figure 21: Remote monitoring and control of vehicle services estimates
  • Figure 22: Fleet management connectivity complexity profile
  • Figure 23: Fleet management services estimates
  • Figure 24: Vehicle diagnostics connectivity complexity profile
  • Figure 25: Vehicle diagnostics and maintenance services estimates
  • Figure 26: Inter-vehicle coordination connectivity complexity profile
  • Figure 27: Inter-vehicle coordination revenue estimates
  • Figure 28: Traffic management connectivity complexity profile
  • Figure 29: Traffic management revenue estimates
  • Figure 30: Vodafone Automotive is aiming to be global
  • Figure 31: Forecasts for incremental annual revenue increase by service