September 2017 The 2017 Strategy& Digital Auto Report Fast and furious: Why making money in the roboconomy is getting harder www.strategyand.pwc.com
The 2017 Strategy& Digital Auto Report: Insights for an industry in turmoil Key facts and main contents Main contents Key facts Sixth annual Digital Auto Report, developed by Strategy& Global study, with a focus on the U.S., the E.U., China Quantitative market forecasts based on detailed research Interviews with key industry executives at OEMs and suppliers, leading academics, and industry analysts Digitization of the car: When can we expect the true ramp-up of connected, autonomous, and electric vehicles? What does it mean for the business? Impact from mobility: What are the latest dynamics in the fast-growing new mobility market? What is the market potential? Who will win or make money? Industry profit shifts: A perspective on the large-scale changes impacting the industry participants, including OEMs, suppliers, new alliances, new players OEM success factors: What does it take to reshape the business to weather the upcoming changes? Who will be successful? 2
2017 has confirmed that technology drives a sustained shift in automotive: autonomous/electric/connected and mobility services as #1 priority Revolution of the automotive industry Revolutionary phase: Disruptive change Digital products and services Cars becoming autonomous, electric, and connected Large-scale emergence of mobility and digital services Primary focus of this report Digital customer experience Omnichannel, digital commerce, and personalization Customer insight/data analytics, predictive services Marketplaces Always-on service relationship Digital enterprise IT transformation ID, cybersecurity, payments Industry 4.0 horizontal and vertical integration between suppliers and partners 3
Yes, mobility is a $2.2 trillion opportunity, but it will halve today s players share of profits Yes, the future of mobility is a US$2.2 trillion opportunity but... The digital auto revolution toward a shared/autonomous scenario is sparking intense competition, a margin squeeze, and high capital expenditure Competition, technology, and scale will drive down the average cost-per-kilometer for using shared transport to <50% of today s levels That will reduce by 10% the amount that consumers spend on mobility by 2030 In the growing shared/autonomous/fleet-based segment of the market, OEMs, suppliers, and dealers in the U.S. and E.U. will see their share of industry profits cut in half from 85% in today s owner/driver/retail model Automotive markets in the U.S. and E.U. will contract as a result, forcing consolidation of OEMs and suppliers All this will be propelled by unstoppable trends By 2030, up to 37% of kilometers traveled will be done by shared and autonomous (and sometimes pooled) vehicles Households buying premium vehicles in mature transport markets will spend ~$3,800 per annum on shared mobility The full shared mobility market shared fleets, vehicle pooling will be worth about the same as today s global e-commerce market In 2030, shared mobility will be hypercompetitive and regional/local, involving OEMs, digital tech firms, city councils, utilities, transport authorities, logistics, and e-commerce fleets 4
Playing in this space requires a reconfiguration of OEMs strategies OEMs need to fix their strategies and align with shareholders Shared mobility is barely profitable today, and full autonomy will come by 2027 at the earliest Large amounts of high-risk capital are required to fund growth of autonomous fleets and customer acquisition OEM boards need to choose between: (1) leaving the field to emerging carriers fleet operators, mobility platform players and becoming thin specialists/design shops and (2) making a big commitment to penetrating the mobility market, finding new investors, and running a new diversification strategy Whichever is chosen, OEMs will face a talent squeeze as software and Internet firms expand research and development by 15% year-on-year 5
Agenda 01 Autonomous & electric & connected: By when? 02 Scale and impact of mobility and growth of the roboconomy 03 Industry profits reshaped by the roboconomy 04 Imperatives for the OEM organizing for success in services 05 Outlook: Flying cars and tunnels on the horizon The 2017 PwC's Strategy& Digital Auto Report 6
01 Autonomous & electric & connected: By when? The 2017 PwC's Strategy& Digital Auto Report 7
Electric to grow strongly beginning in 2025, autonomous level 4/5 to become mainstream after 2028, niches such as robotaxis to proliferate sooner New car sales global forecast New car sales: Autonomous (U.S./E.U./China; in millions) 100 80 60 63 68 ~0 4 5 75 5 0 13 82 12 28 New car sales: Electric (U.S./E.U./China; in millions) 100 80 60 63 68 75 31 82 4 34 New car sales: Connected (U.S./E.U./China; in millions) 100 80 60 63 68 75 82 40 20 0 49 14 2017 52 7 2020 33 23 2025 11 30 1 2030 40 20 0 61 1 2 2 59 8 2017 2020 29 14 2025 44 2030 40 20 0 56 2017 65 75 82 2020 2025 2030 Level 5 Level 3 Level 1 Combustion Electric Connected Not connected Level 4 Level 2 Level 0 Hybrid Tech will allow level 4/5 adoption from 2028 on Pull from launch of robotaxi models from 2025 on Note: Totals may not equal sums shown due to rounding. Source: PwC Autofacts; Strategy& analysis Strong legislative push from 2020 on Price tipping point and sufficient charging infrastructure ~2025 Potential prohibitions for combustion engines from 2030 on Legal and customer pull for connected cars means 100% of new cars in U.S./E.U./China will be connected beginning ~2022 8
We forecast a population of ~470 million connected cars in the U.S., the E.U., and China by 2025, and ~80 million level 4/5 autonomous cars by 2030 Installed vehicle base and key assumptions (in millions; autonomous = levels 4 and 5) 2017 2020 2025 2030 Autonomous Electric Connected Autonomous Electric Connected Autonomous Electric Connected Autonomous Electric Connected U.S. - 0.5 31.3-2.2 67.3 2.1 11.3 116.3 20.8 45.0 146.0 E.U. - 0.8 32.6-1.5 71.3 2.7 9.5 123.5 27.1 45.4 147.7 China - 1.2 27.8-4.0 99.2 2.4 20.5 230.9 33.1 73.7 299.0 Total - 2.5 91.7-7.6 237.7 7.3 41.2 470.7 81.0 164.0 592.7 Move to shared/autonomous after policy and technology breakthroughs Growth of overall distance driven and relative share of vehicle-based mobility (China in particular) Increased vehicle utilization and turnover due to sharing/pooling Declining vehicle base due to sharing/pooling Temporarily increasing overall new car sales Note: Totals may not equal sums shown due to rounding. Source: PwC Autofacts; Strategy& analysis 9
Deep-dive autonomous driving: Mainstream ramp-up of level 5 autonomous driving is expected no earlier than 2027 28 Forecast time line for level 5 autonomous driving based on main elements 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Autonomous driving Vehicle technology E-mobility Level 5 technology Infrastructure technology Operating models Level 5 infrastructure technology 5G technology Legal (laws and regulations) Laws and regulations Mobility services Robotaxis E-hailing/car sharing Battery electric vehicle price tipping point Pilot projects L5 Source: Strategy& analysis Pilot applications/exceptions Ramp-up/adaptation to national laws Series application/laws and regulations mandatory 10
L5 autonomous driving will be difficult to achieve with current tech, confirming need for infrastructure and significant tech innovation Key algorithmic means to achieve L5 autonomous driving Driving modes All other (e.g., country roads, natural disasters/very low visibility) Inner-city driving Predetermined city routes Predetermined highway routes Predetermined closed campus or suburban Highway cruising Traffic jam Rules engine Convolutional neural Convolutional networks (CNN) Long short-term memory neural neural networks (LSTM) Reinforcement learning networks Pooling of results of mapping and neural network training Societal acceptance of technology risks/opportunities Next-generation AI algorithms general purpose intelligence/increased context awareness In-car AI training and/or Sufficient tolerance level for accident frequency Driving limitations outside designated areas (effectively L4) Visible, consistent road infrastructure High-resolution maps V2X (DSRC, 5G) communications with sufficient participants Central traffic information None of the preceding Source: Strategy& analysis Infrastructure availability 11
Deep-dive electrification: Between 2025 and 2030, the cost of battery electric vehicles will fall below the cost of combustion engines Mobility costs for reference vehicles ICE = Internal combustion engine MHEV = Mild hybrid electric vehicle PHEV = Plug-in hybrid electric vehicle BEV = Battery electric vehicle FCEV = Fuel cell electric vehicle Content Fuel cost Depreciation TCO/mobility cost in /100km Usability 2017 2030 Range (km) Refuel time (min) Access to ZEZ* Other (tax, maintenance, insurance, and bonus) Assuming full tank Full reload Zero local emission and low noise Diesel/ gasoline ICE/MHEV 10.4 33.4 12.1 55.9 7.7 34.8 12.1 54.5 700 5 PHEV 9.0 35.4 7.9 52.2 7.2 35.8 11.9 54.8 700 5 o Electrical energy BEV 6.8 39.5 3.5 49.9 6.5 35.4 8.9 50.7 400 30 360** Hydrogen FCEV 9.0 41.2 5.3 55.5 8.7 36.9 10.7 56.2 600 5 Synfuel ICE/MHEV 23.8 33.4 12.1 69.3 Note: Totals may not equal sums shown due to rounding. Bonus of 5,000 (BEV/FCEV) and 3,000 (PHEV) included for 2017 Source: Strategy& analysis. 17.5 34.8 12.1 64.4 700 Good performance Medium performance Weak performance 5 *ZEZ: zero-emission zone **Largely depending on charging power o 12
02 Scale and impact of mobility and growth of the roboconomy The 2017 PwC's Strategy& Digital Auto Report 13
Mobility choices for consumers continue to expand and multiply fast Overview of mobility landscape Description Active mobility Nonmotorized Using own muscular strength to move Personal car Possession and usage of car Driver n/a Vehicle possessor Owner Private person Private person or company Customer interface Examples Rental Renting a car for a day or longer; picked up and returned at fixed stations Renting or authorized person Rental company n/a n/a Website/app or rental stations Walking or bicycling Private car or company car Supporting services Car sharing Passive mobility Ride hailing Station-based Free-floating Corporate P2P Taxi Private hire P2P Short-term ride; vehicles picked up and returned to specified parking spots Registered customers Car-sharing company Website/app carsharing company One-way rides; vehicles picked up and parked in area of operations Registered customers Car-sharing company Website/app carsharing company Hertz, Sixt Flinkster, TeilAuto DriveNow, Car2go Company carpools accessible to employees of one or more companies Employees of companies Car-sharing company Administrator Sharing of personal cars with others Peers (private persons) Official taxi brokered to customer Licensed taxi driver Licensed limousines or vans Licensed driver Private person Taxi company Private hire company Website/app service provider Website/app service provider Website/app private hire company AlphaCity Croove Mytaxi Blacklane, mydriver Integrated mobility Parking E-mobility Offering rides according to customer demand Usually selfemployed unlicensed drivers Private persons (usually driver) Website/app service provider Ride sharing Person offering seats in his car to others on a personal trip Private person Private person Website/app service provider Public transportation Local network of buses, rail, etc. Professional employees Cities, municipalities Shops, website, apps, ticket machines Uber, Lyft, Ola BlaBlaCar, MiFaZ MVG, BVG, Metro On-demand pooling (multiple persons per ride) Examples FromAtoB, Mobility Map, Moovel, Citymapper ParkNow, Parkmobile, EasyPark, PayByPhone Chargepartner, ChargeNow, PlugSurfing UberPool BlaBlaCar Hailed shared taxi or call-a-bus services Source: Strategy& analysis 14
In the future, key areas of mobility services (fleet, operations, regulation, infrastructure) will be local; global plays are unlikely to remain Mobility services will be mostly regional/local Element Max. scale/level Example Customer interface Regulation Fleet operations Fleet ownership Mobility infrastructure Infrastructure Website App Legal standards Safety standards Competition laws Vehicle cleaning/ maintenance Drivers Cars Vans Parking Charging Municipalities Administrations Global National Local Superregional Local Local Apps from Car2go, DriveNow, Lyft, Uber P2P ride-hailing restrictions in Germany Acquisition/hiring of drivers Large fleet owners such as rentals, OEMs, captives Parking allowance for car sharing Streets, smart infrastructure Attempts at global plays will face challenges 1. Strong regulatory moves on national and/or city level 2. Various regulatory restrictions (e.g., for ride hailing) 3. Continued innovation of mobility services from multiple players (e.g., car sharing, ride sharing) 4. Strong competition among regional players for expansion to get customer access and gain market share 5. Multiple types of players: public transportation, utilities, logistics, municipalities, OEMs, digital tech players, etc. 6. Traffic reduction initiatives in cities and municipalities 7. Development of on-demand public transport services 8. Development of new mobility modes such as high-speed tunnels or air solutions 9. Convergence of mobility services due to spreading of autonomous driving 10. Battle of industries for the downstream value-add Source: Strategy& analysis 15
Consequently, we expect a complex local competitive setup in each city, eventually converging in the autonomous future and driving down margins Long-term development of mobility services Rentals (e.g., car-sharing fleets) Cities (e.g., on-demand public transport) OEMs (e.g., mobility services) Utilities (e.g., own EV fleets) Tech players (e.g., forcing autonomous driving) Captives (e.g., corporate car sharing) Short to medium term Personal car (self-driven) Future Personal car (autonomous) Car sharing Station-based Free-floating Corporate Peer-2-peer Shared autonomous Ride hailing Taxi Private hire vehicles Peer-2-peer Ride sharing Public transportation 1. Individual 2. Pooled Public transportation Source: Strategy& analysis 16
Shared autonomous will account for 25 37% of total person km driven in 2030; personally owned autonomous highest in Europe Distribution of mobility types (in % of total person km road driven) 100% Main driver: urban pooled/shared level 4 or 5 robotaxis 90% 80% 26% 25% 37% 70% 60% 50% 15% 10% 11% 9% 10% 9% 40% 30% 20% 49% 55% 44% 10% 0% 201718 19 20 21 22 23 24 25 26 27 28 29 30 201718 19 20 21 22 23 24 25 26 27 28 29 30 201718 19 20 21 22 23 24 25 26 27 28 29 30 Personally owned driver-driven Shared driver-driven Personally owned autonomous Shared autonomous Source: PwC Autofacts; Strategy& analysis 17
Hence, the vehicle base may decline by 25% in the E.U./U.S. and flatten out in China until 2030; new car sales will accelerate to create robotaxi fleets Global mobility development + Vehicle-based passenger travel (in km trillions) 11.7 12 600 10.2 10 9.5 9.7 3.0 500 8 6 4 2 0 10 8 6 4 2 0 Personally owned driver-driven 1.6 1.1 6.1 400 300 200 100 2017 2020 2025 2030 350 8.6 300 3.2 250 5.5 200 3.9 0.9 3.1 0.7 150 100 3.8 50 2017 2020 2025 2030 Note: Totals may not equal sums shown due to rounding. Source: PwC Autofacts; Strategy& analysis 0 0 556 2017 185 2017 Shared driver-driven Vehicle base (in millions) 560 531 2020 231 2020 2025 306 2025 416 29 356 2030 276 17 235 2030 19 11 16 8 50 40 30 20 10 Personally owned autonomous 0 40 30 20 10 0 New car registrations (in millions) 36.0 2017 27.5 2017 45.9 36.6 39.0 10.6 2020 31.6 2020 2025 35.6 2025 11.4 2.9 20.9 2030 35.7 11.1 6.8 2.6 15.3 2030 Shared autonomous Comments Increase in distance driven due to rising population and growth of shared mobility services Decline of vehicle population due to higher utilization of shared and autonomous vehicles Car ownership is still important, so personally owned autonomous vehicles represent a large proportion Driven distances in China will pass individual levels of E.U. and U.S. around 2025 Decline of vehicle population will happen later, as distance driven and motorization rate increase strongly Due to strong increase in shared mobility, vehicle sales may drop during the transformation, before higher turnover rates push sales 18
The value of shared mobility ( MaaS ) will reach ~US$1,500 billion in the U.S./E.U./China in 2030, growing at combined 24% p.a. from 2017 to 2030 Estimated MaaS market size development, U.S. (in US$ billions) 47 2017 292 2025 Estimated MaaS market size development, E.U. (in US$ billions) 25 2017 214 2025 Estimated MaaS market size development, China (in US$ billions) 458 2030 467 2030 564 CAGR 2017 30 +19% +25% Comments Global vehicle-based passenger travel as key underlying driver Total (shared/traditional) price per distance traveled derivation based on historical household spending Price for shared mobility significantly decreasing due to reduced vehicle-related costs (efficiency, maintenance) autonomous driving intensification of sharing/pooling 15 97 +32% 2017 2025 2030 Source: Expert interviews; PwC Autofacts; Strategy& analysis 19
Some OEMs may choose a broad diversification into mobility, while others may choose to refocus toward thin specialist/design shop Potential value chain integration plays Build and run infrastructure (e.g., charge, park, V2X) Build cars Design cars Retail cars (where B2C still relevant) Finance cars Operate local/ regional fleets Create and operate digital services Retail mobility and digital car services Today s OEMs Potential OEM ways to play Fully integrated OEM + mobility provider (comparable to aircraft + national airlines/carriers + operations ) Specialist ( ARM of cars ) OEM + wholesale operations (comparable to aircraft OEM + fleet operations ) Mobility service provider What other players may do Source: Strategy& analysis Cities Ride hailing Partial-own value chain Specialist or generalpurpose marketplaces Specialized lease/finance companies Full-own value chain Cities Local startups Retail/logistics/transport Utilities/energy companies Ride-hailing firms 20
Key question: Should OEMs go asset heavy or asset light in mobility? Value chain depths asset heavy vs. asset light Offering scope Asset heavy Car2go, DriveNow, ChargeNow, Tesla, Hertz, Amazon, DB End-to-end delivery of owned product/service Asset light Mytaxi, ParkNow, Uber, Alibaba, Airbnb, Facebook Brokering of on-demand service/user-generated content USP Availability, consistency, trust Choice, simplicity, price Control points Disruption risk Business model Investment approach Product; service delivery Loss of customer access to OTT providers Service fees, product sales Invest in R&D/asset buildup, optimize working capital à EBIT margins 5 15% Customer insights and access; supplier selection Direct buyer supplier interaction; special interest portals Commission-based brokering (OTT), marketplaces Invest in network/inventory growth, optimize user acquisition cost à EBIT margins 15 30% Comments Two types of mobility business models: broker (asset light) vs. infrastructure provider (asset heavy), each with potential competitive advantages (network synergies vs. entry barriers) Shareholders will demand a clear investment story that benchmarks against digital best practices Key question: Fleet financing own exposure vs. partners vs. P2P? Source: Expert interviews; PwC Autofacts; Strategy& analysis 21
03 Industry profits reshaped by the roboconomy The 2017 PwC's Strategy& Digital Auto Report 22
The roboconomy creates opportunity on three levels to earn money for OEMs by addressing major categories of typical household spend Roboconomy digital services opportunities 2017 Western premium household expenditures (in US$) $30,424 Housing, personal insurance, pensions Vehicle purchase, new Others Vehicle purchase, used Vehicle lease, finance, $6,830 $3,603 insurance, maintenance $2,996 $3,963 Gas $2,832 Public and other 2017 average Western premium household annual expenditures: US$80,644 $1,532 $5,245 $14,391 transportation Entertainment (excl. restaurants, hotels) Food, apparel $3,618 $5,211 Healthcare Furnishing and housekeeping supplies Note: Totals may not equal sums shown due to rounding. Source: Destatis; DIW; Eurostat; Trading Economics; U.S. Bureau of Labor Statistics; Strategy& analysis Digital services opportunity categories (Gross addressable expenditure per household in US$) Augmenting the car through services Crossmodal mobility services Fifth-screen ecosystem services 2017 ca. $6,600 ca. $14,900 ca. $23,300 2030 ca. $5,400 ca. $13,400 ca. $29,700 Add digital services directly associated with use of the car, incl. functionality as a service to increase loyalty, sell more cars, achieve higher customer lifetime value Comparables: Connected TV/fridge, smartphone Becoming mainstream, quickly commoditizing Often substituting legacy value pools Provide mobility (e.g., hailing, sharing, parking) Comparables: Digital category services Netflix (entertain), Amazon (shop), WhatsApp (message) New type of business, displacing or rebundling legacy mobility spend Accessible to new entrants and OEMs Move beyond individual categories and become a hub for services and commerce (fifth screen) Comparables: Amazon, Apple, Facebook New digitally enabled entertainment/commerce/comfort Puts new categories in reach of new entrants 23
Cross-modal mobility services/maas represents the single biggest opportunity for auto OEMs both top and bottom lines OEM digital service opportunity, 2030 Western premium household; in US$ Augmenting the car through services Cross-modal mobility services Fifth-screen ecosystem services 2030 addressable household spend (gross) $5,400 $13,400 $29,700 5 8% of new car value in digital services ~ 30% of spend shifted to shared mobility ~10% of spend occurring during mobility through digital channel Relevant household spend (gross) $300 $3,800 $3,000 Value retained by OEMs (gross margin) $30 60 10-20% $110 190 3-5% $30 90 1-3% Source: AAA; emarketer; expert interviews; Euromonitor; PwC Autofacts; Strategy& analysis 24
The resulting digital mobility services sector is a $2.2 trillion industry in 2030 dwarfing today s smartphone market, matching e-commerce market Digital mobility services industry Scale comparison digital economy vs. roboconomy (in US$ billions) ~2,200 158x 77x 5x 1x ~2,300 Comments The 2030 roboconomy is projected to be close to the size of today s e-commerce market Roboconomy outgrows today s smartphone market by a factor of 5, app store/on-demand media revenues by a factor of 75+ 65 14 29 437 Participants (including OEMs) need to create a new digital services business, which is in total 5x larger than current smartphone market Today s roboconomy 2030 roboconomy Today s Spotify, Netflix, Apple Music Today s Apple App Store GMV Today s smartphone market Today s e- commerce market Source: Bloomberg; company publications; emarketer; IDC; Strategy& analysis 25
In a pure shared autonomous mobility scenario, households spend 20% less on mobility and profits shift drastically toward front-end and fleet players Industry distribution of household mobility spend in shared autonomous scenario Distribution of Western premium household spend, 2030 (in US$) Industry value added Profit MaaS Today 2030 scenario Pure-play shared scenario 14,920 270 13,410 4,260 1,470 2,830 3,960 2,490 1,110 2,930 1,790 3,860 2,360 1,000 1,085 5 1,000 260 170 170 180 70 340 1073 310 220 170 90 100 Other (used vehicles, public transport) Gas 830 Lease, finance, insurance, maintenance 770 290 80 Suppliers 11,520 Source: Euromonitor; Eurostat; Frost & Sullivan; Gartner; HBR; HIS; National Automobile Dealers Association; NHTSA; OEM reports; Oxford Economics; PwC Autofacts; Technavio; Thomson Reuters; Strategy& analysis OEM 3,560 1,420 3,670 1,090 520 2,100 60 140 570 Comments In pure-play shared autonomous scenario, significant price decline overcompensates growth in household person-km In pure-play shared autonomous scenario, profit share of traditional manufacturing/retail of cars declines from 85% to <50% 2030 scenario assumes ~35% of total person km conducted in shared mobility Realized total profits are assumed to remain stable as a result of downward pressure from decreasing revenue, set off by new value from service value-add and reduced costs of development/production 26
The long-term control point in digital services will be AI-powered hubs connecting customers with personalized services Strategic control nodes in the roboconomy? Comments Likely future control point for the roboconomy: Artificial intelligence brain steering personalized and predictive use of digital services across multiple domains (e.g., mobility, home, health), supported by data insight Multiple global contenders to occupy control point can OEMs play here? Source: Strategy& analysis 27
04 Imperatives for the OEM organizing for success in services The 2017 PwC's Strategy& Digital Auto Report 28
OEMs need to provide tightly coupled hardware and services to fulfill customer expectations and play successfully in the roboconomy Customer perspective on mobility and services Comments Mobility experience = hardware + software + services in a seamless, integrated, intuitive environment Monetization primarily through integrated experience value (not through individual services) Requires symbiosis between device (car) and services Source: Strategy& analysis 29
Digital services will involve the buildup of hundreds and thousands of partners globally, including physical journeys and money flows Ecosystem environment in the digital services cloud Outlook Hundreds of types of physical touch points Exponential complexity for OEMs Today no OEM ready for future opportunities at scale Thousands of services in each market Dozens of monetization business models Tens of thousands of partners Source: Strategy& analysis 30
Therefore, digital services are a radical departure from designing and selling cars leading to tensions in OEMs planning to do both Characteristics of traditional vs. digital services business Vehicle business Digital services business Outlook Customers Frequency of interaction with customers Dealers/workshops, few end customers in B2B Monthly to yearly (sales, service, maintenance, accident) End customers (direct interaction) Real time to weekly (sales, activation, usage, billing, etc.) Digital services business is fundamentally different from vehicle business Need for a dedicated end-toend operating model Customer feedback Only via dealers, modification with new release/face-lift Direct from end customer, instant reaction and modification Customer problems Infrequent; defects in product; solved at the dealer Frequent; bugs in services, access, etc.; solved in customer operations center Channel mix Dominant: dealer/service partner Dominant: digital Portfolio Portfolio changes Single category, 10 to 20 variants, numerous options Low frequency (2 or 3 per year) Long lead times (3 to 5 years) Many categories, need to be simple High frequency (<monthly) Short lead times (months) Source: Strategy& analysis 31
The implied change for OEMs requires (1) a different way of doing R&D, (2) the buildup of a services business, (3) external innovation, and (4) talent Capability implications for OEMs Key requirements to support aspirations Capability implications Incubate new mobility business(es) Create digital services innovation/ delivery/scale-up capability Rearchitect internal innovation/r&d Build ability to run end-to-end services business Significantly expand strategic partnerships Build direct-to-consumer relationship Accelerate external innovation Access relevant talent Source: Strategy& analysis 32
Example R&D: Continue to outspend most other industries globally OEMs R&D spending Top 20 global R&D spenders 2016 rank 2015 rank Company Geography Industry R&D spend (in US$ billion) 1 1 Volkswagen Germany Automotive 13.2 2 2 Samsung South Korea Computing and electronics 12.7 3 7 Amazon U.S. Software and Internet 12.5 4 6 Alphabet U.S. Software and Internet 12.3 5 3 Intel U.S. Computing and electronics 12.1 6 4 Microsoft U.S. Software and Internet 12 7 5 Roche Switzerland Healthcare 10 8 9 Novartis Switzerland Healthcare 9.5 9 10 Johnson & Johnson U.S. Healthcare 9 10 8 Toyota Japan Automotive 8.8 11 18 Apple U.S. Computing and electronics 8.1 12 11 Pfizer U.S. Healthcare 7.7 13 13 General Motors U.S. Automotive 7.5 14 14 Merck U.S. Healthcare 6.7 15 15 Ford U.S. Automotive 6.7 16 12 Daimler Germany Automotive 6.6 17 17 Cisco U.S. Computing and electronics 6.2 18 20 AstraZeneca Britain Healthcare 6 19 32 Bristol-Myers Squibb U.S. Healthcare 5.9 20 22 Oracle U.S. Software and Internet 5.8 Remarks Increasing importance of innovative technologies drives increasing R&D spending Top OEMs have been among largest R&D spenders consistently for many years Source: Bloomberg data; Capital IQ data; Strategy& 2016 Global Innovation 1000 study OEM 33
This model is challenged: There will be a run on critical skills as software and Internet industries heavily increase R&D investments War for talent strong R&D among tech firms Change in R&D spending by industry 2015 2016 Remarks 20% 15% 10% 5% 0% 15.4 3.6 0.7 Significant increase in R&D spend in software and Internet businesses many of them cited among most innovative companies and active in automotive As a result, large share of young R&D talent joining new tech firms Auto companies reducing R&D spend -5% -1.8-2.0-2.8-3.3-4.0-10% -15% Software and Internet Healthcare Consumer Computing and electronics Other Industrials Aerospace and defense Auto -11.5 Chemicals and energy -12.2 Telecom Source: Strategy& 2016 Global Innovation 1000 study 34
Digital companies organize R&D quite differently faster, cheaper Scale-up by design by digital players Business model focus on digital principles...... and creation of agile organizational structures Amazon Uber Lyft Google Didi Apple Ola Small and autonomous teams with startup spirit/atmosphere Interdisciplinary teams with clear product instead of functional focus Fast go-live with minimum viable products Think it, build it, ship it, tweak it End-to-end responsibility of teams from planning to development to operations Extreme customer focus, internal as well as external Deliberate, fast decision making different for reversible and irreversible decisions TL Chapter Chapter Spotify model Tribe PO PO PO PO Squad Squad Squad Squad Principles Split of applications in microservices which leverage standardized platforms Systematic use of a cloud architecture to ensure scalability by design Strong in-house capabilities (product owner, technical owner) and small, agile, and integrated teams with clear responsibility for their own releases Note: TL = tribe leader, PO = product owner; guild works across tribes Source: Strategy& analysis Tribe (e.g., back-end infrastructure) Squad (e.g., radio experience) Chapter (e.g., developers) Guild (e.g., testing) 35
Rather than doing only R&D, scaling up new businesses becomes key Lessons learned from scaling of innovations Typical stall Ideation and sourcing Best startups = no lemons Internal ideas with real potential Selection criteria no CEO pet projects Talent innovator employer brand Team commitment no return ticket Acceleration Focused working environment, no distraction by corporates Linking of founders with internal organization Right level of supervision investor, not corporate, mind-set No overfunding in early phases $50,000 instead of $2 million Support for follow-up funding also externally, particularly round A Scale up Aligned incentive structure for founder/team and corporate Willingness for high payout Balance independence and synergy potential for parent company No restriction of the startup even in case of cannibalization Minimization of consolidation requirements Deliberate choice of exit strategy and time Source: Strategy& analysis 36
05 Outlook: Flying cars and tunnels on the horizon The 2017 PwC's Strategy& Digital Auto Report 37
The future may yet be very different as mobility takes new forms Potential alternative future mobility options Tunnels/tubes The Boring Company Vision to shift traffic underground either by moving vehicles as fast as 200km/h on electric slides or by supporting Hyperloop (pneumatic high-speed tube) development Founded in 2016 by Elon Musk Objective to improve tunnel boring technology to increase speed of tunneling and reduce cost by >10 times Boring machine, tunnel, and car elevator tested at SpaceX headquarters in Hawthorne, California Interest from multiple cities in U.S. announced (e.g., Los Angeles, Chicago) Drones Volocopter Want to provide all people with the opportunity to fly and improve urban mobility Founded in Germany in 2010, and prototyped VC1 as global first manned flight with an electric helicopter in October 2011 Objective to develop an electric, five-seat flying taxi Funding partners include Daimler or Federal Ministry of Economics Test flight of first autonomous flying taxi in Dubai in 2017 Flying cars PAL-V Drive to offer people the most flexible form of mobility and the highest sense of freedom imaginable Strive to offer the best of both worlds flydriving Started in 2001, with the first flight of the proofof-concept prototype in 2012 Delivery of PAL-V Liberty as the first serial production flying car starting end of 2018 Requires driver and pilot licenses Source: Strategy& analysis 38
Get in touch! Core team: 2017 Digital Car Report Further contributors Richard Viereckl Senior Partner, PwC Strategy& Germany Lead EMEA Auto Consulting Industry Steffen Hoppe Principal, PwC Strategy& Germany Mobility and Industry Trends Felix Kuhnert Partner, PwC Germany Global Auto Consulting Industry Lead Dr. Jörn Neuhausen Principal, PwC Strategy& Germany E-mobility Alex Koster Partner, PwC Strategy& Switzerland, Lead Author Lead EMEA Digital Automotive Anne Pohlmann Manager, PwC Strategy& Switzerland Mobility and Industry Trends Marcus Gloger Partner, PwC Strategy& Germany Autonomous Driving Christoph Stürmer Global Lead Analyst, PwC Germany Autofacts Industry Insights and Trends Dietmar Ahlemann Partner, PwC Germany Mobility and Digital Operating Model Thilo Bühnen Senior Associate, PwC Strategy& Switzerland Mobility and Industry Trends Hartmut Güthner Principal, PwC Strategy& Germany Autonomous Driving Michael Kofler Consultant, PwC Germany Autofacts Industry Insights and Trends Jonas Seyfferth Principal, PwC Strategy& Germany Mobility and New Business Models 39
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