Mega Trends And Their Impact On Future Of Mobility
Mega Trends and Their Impact onFuture of MobilityKey NotePresentation by:Sarwant SinghSenior Partner
Today’s AgendaIntroduction:- Transformational Shifts Reshaping the Future of Mobility New Mobility Business Models Mobility Integration Convergence of Corporate Mobility The City as a Customer Women and the Automotive Industry Focus on Health Wellness and Wellbeing in the Automotive Industry Connected and Automated Mobility Growth in high Speed Rail and Public transport spending Autonomous Cars New Business Models Conclusions, Q&A2
Top Transformational Shifts Expected to Shape the Future of MobilityNew Business ModelsMobility integrationConvergence incorporate mobilityCity as a customerWomenEmpowermentHealth Wellness andWell-beingConnected andAutomated MobilityGrowth in high SpeedRail and Publictransport spending3
Transformational Shift No. 1: New Business Models - Growth of CarSharing Over 543,000 vehicles to be shared in Europe by 20202020Traditional49,3682.5 millionTraditional236,14514.9 millionP2P81,3801 millionP2P222,2103.3 millionCorporate2,896250 0Members P2P50014000MembersTraditionalVehicles 01220142020CarpoolingMembers (Millions)20000Vehicles (Thousands)Members 2201420204
Transformational Shift No. 1: New Business Models cont. - Growth ofRide Sharing Business ModelsComparative Market Positioning of Ridesharing business modelsHigher Price per KMPublic Transport“Taxi” & LimosineServicesPlanned –Long DistanceInstant –Short ateCarpooling?“On Demand” Carpooling“Fixed” CarpoolingLower Price per KMSource: Frost & Sullivan5
Transformational Shift No. 1: New Business Models cont. - Within 3years ehailing taxis control close to 20% of the global taxi marketeHailing is dramatically revolutionizing the taxi industry business model. By 2020 the global taximarket is expected to reach 5 million vehicles growing at a CAGR of inaS.KoreaSpainIndiaKakaoTaxi6
Transformational Shift No. 1: New Business Models Cont. - The rise ofUber and more is yet to comeLogistics /CourrierPrivate Hire / LimoRidesharingTaxiGroceries (UberEssentials)As of Jan 2015Food (UberFresh, UberEats)Retail delivery 47,417,139Parcels & Logistics (UberCargo)7
The Arrival of Uber for Trucking Signifies a DynamicChange in the Trucking LandscapeMobile Based Freight Brokerage Market:Revenue Scenario Analysis, North America,2015 and 2025 300.0CAGR : 39.3%Revenues (Billions) 250.0 19.2 200.0 0.5 150.0 220.0 100.0 160.0 50.0 0.020142025Year3rd Party LogisticsMobile Based8
Transformational Shift No. 2 : Integrated MobilityTechnology enabled, any device delivery of real-time, door-to-door, multi-modal travel encompassing pre-trip,in-trip and post-trip services bringing Convenience, Time & Cost Savings to the Mobility UserCar Rental &LeasingCar Sharing andPoolingDemandResponsiveTransport(Taxi, BRT)DynamicParkingIntercity PublicTransportIntracity PublicTransportConnected Living(Including Car)Car mobilitySolutionsEnergyManagementApps, JourneyPlanning, BigDataConciergeServices9
Transformational Shift No. 2 : Convergence of Vehicle Rental Business2020 14.5 million14 236,145 12.2 million102014 49,3688About 30.0–35.0% of theglobal shareis held byZipcar,Car2Go andDrive Now 5.3 million 75.0–78.06 45.0–50.0% shareby Enterprise, Hertz,Avis, Europcar4Others includeD’Ieteren, Sixt AGand so onOthers include VWLeasing, Arval, SumitomoMitsui, Alphabet, RCIBanque, Lex Autolease,Athlon and so on. 4.5 million2012Units (Millions)12ALDORIXARIGE Capital2 18,745,0up to 24 hrsup to 2 weeksCar SharingCar Rentalsup to 36 monthsCar LeasingNote: All figures are rounded; the base year is 2014. Sources: LMC Automotive, Frost & Sullivan.10
Transformational Shift No. 2 : Mobility Landscape – Many Actors, NewPartnerships, New Models, New CompetitorsOEMsCar FleetManagementProviders11
Transformational Shift No. 2 : Mobility Integration Platform ExampleCase Study - Qixxit – Deutsche Bahn Launches Mobility Integration ServicesIntegratedbookingCurrentServicesReal-time informationof integrated means oftransportAlternativeroutingCross- & upsell-products(Hotel, luggage service )SocialtravellingCurrent partnersRentalcarTaxiLocal publictransportationBicycleCar SharingCarFlightLong-distancetransportCoachvia partners partners12
Transformational Shift No.3: Future of Corporate Mobility - From TCOto TCMTotal Cost of OWNERSHIP Running Core Fleet & Keeping CompanyDrivers InformedTotal Cost of USERSHIP Managing Overall Fleet & Educating AllCompany DriversTotal Cost of MOBILITY Delivering Integrated Services & EmpoweringAll Employees13
Transformational Shift No.3: The Business & Leisure Convergence “Bleisure”Business travellers60% take a82% Business“Bleisure” triptravellers explore the city30% added 254% Bleisurevacation daystravellers bring familyReason for interest:Business Travel is a 1 TrillionMarket and MovingTowards A SelfService ConceptBut Policy is Unclear.only 14% of employees areaware of a Business & Leisure travel policySource: Bridgestreet Hospitality Bleisure Report 2014.14
Transformational Shift No.3: Frost & Sullivan’s Vision for the Future ofCorporate MobilityIntegrated Multi ModalPlatforms (forbusiness)OEMs increaseCorporate MobilityfootprintGrowth of “sharing”reducing need to own /sole use (e.g. companycar)Mobility Auditing &Mobility BudgetsChanging workinglocations/patternschange mobilityrequirementsRise of InternetAggregators(smartphone enabled)15
Transformational Shift No.4: City as a customer Over 5 million vehicles in theglobal taxi fleet by 2020. Close to 500,000 taxis to be replaced every year globallyLondonLTI Blackcab andMercedes Vitoboth ( 35,000-40,000)DubaiToyota Camry(86,900AED)BeijingHyundai Elantra ( 90000)Sonata ( 120,000)Volkswagen Jetta ( 115,000)TokyoToyota Comfort ,Nissan Crew( 18,500-20,000)TorontoToyota Camry ( 24,900)Chevrolet Impala ( 30,395)Lincoln Town CarHong KongToyota Comfort,Prius(HK 420,000)New YorkFord Escape ( 21,215)Toyota Prius ( 26,650)Nissan NV200Sao PauloFiat Siena, Fiat Idea,Chevrolet SparkParisPeugeot 406 ( 12000)Mercedes C ( 35224)MumbaiTata Indigo, RenaultLogan, Toyota InnovaSingaporeHyundai SonataSource: Frost & Sullivan16
Transformational Shift No.5: More women drivers and customers infuture than men and women prefer leasing vehiclesWomenDriving licence parity data by countryMen5150474444414140372912Source: Frost and Sullivan Analysis17
Transformational Shift No.5: Case Study : Nissan’s 300 ‘Lady First’DealershipsSpaciouschildren’s playareaStylish interiors polished woodenfloorsFemale staff –sales andmechanicsLarger, pink paintedparking spaces forwomen**Seoul only currentlySource: Nissan website, image – YouTube, Frost & Sullivan18
Transformational Shift No.6: Health, Wellness and Wellbeing the NextBig Differentiation Factor for OEMsBuilt-in(Embedded)Brought-in(Peripheral Integration)Cloud-enabled(Broadcast)Source: Frost & Sullivan19
Transformational Shift No.6: HWW Focal Points - HWW features arefocused on the mind, body, and soulAutomotive HWW Technologies: Key Features List, Global, 2014–2025 Outside ambient air quality monitoring Driver drowsinessdetection Fatigue monitoring Stress level monitoring Heart rate monitoring Blood pressuremonitoring Breathing ratemonitoring Glucose levelmonitoring Muscle therapy Palm and facialtemperature monitoring Erratic driving patternrecognitionBodyMindSoul Pollen/allergen levelmonitoring Drunk-drivingprevention Comfort/ease ofaccess/egress In-car ambient temperature monitoring In-car ambient lighting monitor Driver workload estimationSource: Frost & Sullivan20
Transformational Shift No. 7: Connected Cars Accelerating Big DataOpportunitiesConnected and Non-Connected Cars, North America and Europe, 2013 and 2020 34.0–34.5million35.030.0 8.5–9.0millionUnits ed Car201620172018Non Connected Cars20192020Note: All figures are rounded. The base year is 2013. Source: Frost & Sullivan analysis.21
Transformational Shift No. 7: Impact of Connected Cars: Big DataDigital LeadsInternet AggregatorsWarranty CostsReduction, PredictiveMaintenanceProduct PerformanceAnalysis, Productionand Supply ChainUser & DealerSatisfactionAdvanced Mobilityservices, DynamicNavigation and ParkingImages and logos are only for representation Source: Frost & Sullivan analysis.22
Transformational Shift No. 7 : From Hands Free to Mind Free : FutureWill See Fully-automated VehiclesDrive and Let Drive ConceptPredetermined A-to-BPersonal Mobility with Route InputsCan be manually driven or selfdriven by the vehicleIdeally suitable for Personal RapidTransit (PRT)Ideally suitable for urban commutersand people with special mobility needsAutonomous Adaptive Mobility VehiclesFully-automated vehicles hold the potential for fundamental rethinking of vehicle designs.For instance, partially collapsible vehicles also save parking space when not in motionSource: Frost & Sullivan23
Transformational Shift No. 8: Driverless Technology Not Just a Trendfor Cars, Rail has a Better Business CaseAutomatic Train Protection(ATP)ATP is the first step towardsautomation. All primary safetyfunctions are automated.Automatic Train Operation(ATO)Driving functions of the train canbe automated through the ATO(basic driving to zero staff).Automatic Train Supervision(ATS)Real time automation of trainmanagement and operationsregulation through ATS.Empty Driving cab conceptHigher speeds of operationHigh speed end to end connectivityCan be manually driven or selfdriven by the vehicleMaximum wait time of 60seconds onthe platform for the next trainRapid dissemination of data andinformation to all parties involved24
Transformational Shift No. 8: 200 Year old rail Will Still be a Mega Trendin 21st Century Over 10,000km of HSR planned in Europe by 2030Length of High-speed Rail Infrastructure by Region, 2013 and 2020Total 83,960 km16,72615,85810,7926,2582,56551,3768,321Total In 362Asia-PacificOperational Length*Includes both Eastern and Western Europe777Europe*511North America Latin AmericaUnder Construction2020PlannedNote: Center chart depicts length of high-speed infrastructure by region for 2013. Source: UIC, Frost & Sullivan25
Autonomous Cars New Business Models26
Autonomous Cars New Business Models Four key areas impacted by Fully-AutonomousMobilityOpportunities from Fully-Autonomous Mobility, Global, 2015Fully-AutonomousMobility OpportunitiesVehicleondemandFirst & LastmileCommutingMobilityas autilityPeer-topeersharingSource: Frost & Sullivan27
Autonomous Vehicles to revolutionize the e-Hailing Business Model –Case Study – New York Yellow TaxiAutomated Driving Business Models: Case Study – New York Yellow Taxi, NA, 2015Current Taxi MarketParameterFuture Taxi Market36Average number of daily Trips per taxi 50200Average Daily Miles Covered by a Taxi 3507.1%Taxi User Base (% of Population)15-20%22.39Number of Taxis per 1000 Daily commuters 18 540 (2013)Driver cost per day 050,000Number of Drivers0 6.31 (2013)Average Fare per mile 4 29,700 (2014 Nissan NV200)Taxi Price 40000Note: Taxi user base in New York City was 600,000 passengers per day in 2014Source: NYC Taxi And Limousine Commission, Frost & Sullivan28
Group Rapid Transit to Replace Public Transport Buses To reduce congestionand reduce queuing in the event of demand spikePeak Hour RoutingScenario 1510BA72CD During peak hours, group rapid transit(GRT) will act as a point-to-point service,picking passengers en route. Frequency is increased to meet thedemand. No of GRT Required to transportpassenger: 3Scenario 213BA13D During off-peak hours, group rapid transit(GRT) will picks more passengers to makeoptimal utilization of capacity. No of GRT Required to transportpassenger: 1CGRT is assumed to have a capacity to transport 8 passengers.Source: Frost & Sullivan29
Case Study – Public Transport in LondonAutomated Driving Business Models: Case Study – Public Transport in London, Europe, 2015-2050Current PublicTransportationParameterFuture Rapid Transportation1,073Fleet size per million Population 300056 - 87Seating Capacity per Vehicle8 - 564.86Average Waiting Time for a Bus AlongFrequently Availed Route (Minutes)2-3Government appointed bodyOwnershipCould be owned byhousing societyPredefined/Supply DrivenRouteDemand DrivenDesignated along main roadBoarding and Alighting PointFlexible to accommodate originand destination of journeydesired by user groupCommuter waits for thevehicleBasis of boardingCharted GRT awaitsdesignated commuterNote: Current and Future transportation includes only road based vehicles such as busesSource: TfL, Frost & Sullivan30
With Increasing Autonomy, Insurance Liability Likely to Shift to OEMsPresent-day Motor Insurance Model in driver centricDriver centric evaluationFuture Motor Insurance ModelCrash Prevention, CrashWorthiness, Algorithm.ManufacturersProduct Liability3. System centricevaluation2. Product centricevaluation1. Brand centricevaluationOrPods, personal vehicles,group rapid transit vehicles 80%*Vehicle owner pays premium to cover some excesses such as stray incidents like theft, fire and vandalismOrIncreased Comfort, Option ToTake Manual Control. 20%Users share ofliabilitySource: Frost & Sullivan31
At Present, Driving Behaviour & Incident History Key to CalculatingPremiumVehicle-relatedDriver-related Age/Driving Experience Brand, Vehicle age & Value Claim Frequency Model features (safety technology) Occupation Performance Driving intervals and duration Type of cover (Comprehensive vsthird party) Driving record and no-claimsbonus Vehicle Size and UsageInsurancePremium Modifications Annual Mileage Desirability (vulnerability to theft)RiskSocial Trends Residential Locality Average number of occupantsCalculatingFactorsStray causes Damage to public property Damage through natural calamity Coverage Gaps Damage due theft, fire and vandalism Accident history of locality (route) Other Excesses Where the car is parked (secured,covered space, curb side, garage) Frequently used routesThe above is not an exhaustive list and it contains some of the key parameters.Source: Frost & Sullivan32
Parameters Considered for Motor Insurance Premium CalculationsNew-to-bracket parameters relevant tomainly Level 4 Automated VehiclesParameters with continuedrelevance for Level 4Automated VehiclesBrandDriving AlgorithmPeer TrafficCyber-security vulnerabilityVehicle Size and UsageControl logic robustnessFrequently Used RoutesType of CoverDesirability, Vehicle age & ValueOccupationAge/Driving ExperienceAccess securityrobustnessRecall History Of Vehicle ModelTime & Duration Of JourneyPrivacyAverage Daily Miles DrivenDriving RecordVehicle DensityResidential & Parking LocalityDriver BehaviourDamage due theft, fire and vandalismDriver Alert / Warning SystemsClaim FrequencyAverage number of occupantsParameters not relevant to Level 4Automated VehiclesHigh ImportanceMedium ImportanceLow Importance Source: Frost & Sullivan33
Risk slicing and risk-sharing models are to evolve, with manufacturer’sproduct liability and other stakeholders’ limited liability offsetting therisk borne by the insuredRiskMotor Insurance for Automated Driving: Risk Split Between Entities, Global, 2015 - 2050-20%Active SafetyManufacturer’s product liability-15%Potential impact on premiumSemi-automated ModeInsured’s liability-15%Highly-automated Mode-20%Fully-automated ModeOther Stakeholders’ liabilitySource: Frost & Sullivan34
With decline in average premium per vehicle, the EU motor insurancemarket is expected to reduce by a CAGR of 3.88% over the next 35 yearsIn 2013, Motor Insurance accounted for 29% of the total non-life insurance premiums in Europe. 130 BillionCoverage Split (2013)-0.5% Y-o-Y 103 Billion4.8% Y-o-Y40%Total Motor Premium(2013)Own Damage60%Third PartyTotal Motor Claims(2013)Average premium per vehicle is 4702050Scenario 1Scenario 2Assuming vehicle in use to reduceby10%30%Vehicle in Use (Million)249.3193.9Total motor insurance market size 70.30 Billion 54.67BillionAssuming average premium per vehicle for motor insurance to decrease by 50%Source: Frost & Sullivan35
Future to evolve to bundling of motor insurance with other servicesADAS & Semi Automated DrivingTraditionalMotorInsuranceModelEvolved InsuranceModel with NewSet of PremiumCalculation CriteriaFully-automated Driving Traffic1Motor insurance built intoextended warranty2Motor insurance bundledalong with property insuranceInsurance risk split betweenmanufacturer and other3stakeholders4Motor insurance offered byVehicle ManufacturersSource: Frost & Sullivan36
Conclusions and Recommendations37
Impact of Mobility Business Models on OEMs impacting Design, Sizeand ShapeFuture growth from newmobility business modelsSub compact1 series2 seriesPrivateOwnershipSedan3 series5 seriesSUV7 seriesX1X5X7Trifecta effect?Merging of 3segments SUV Sedan Minivan orHatchbackSedan (Sports) Minivan SUVHatchback Sedan SUVTesla Model XVolvo S60 Cross Country38
Key Takeaways on Future of Mobility123Transformational shift totech enabled platforms –driving customerexpectationsNew mobility businessmodels changing theautomotive landscape –vehicle sharing businessmodels estimated toreach 10bn by 2020Door to door is the wayforward – driven bypublic and privateintegration456Competition, cooperationand collaborationbetween stakeholders inthe fieldCorporate mobility to bea key focus area with themerger of fleet, traveland expensemanagementFuture mobility solutionsneed to be tailored tocustomer groups, e.g.women, gen Y , corp.Source: Frost & Sullivan39
Learn More About “New Mega Trends”Published Book:New Mega TrendsImplications for our Future LivesBy Sarwant SinghPublisher: Palgrave px?pid 577423Join Our Mobility and MegaTrend Groups On LinkedInMega Trends: Strategic Planningand Innovation Based on Frost &Sullivan ResearchFollow Sarwant’s serieson Mega Trends gh/40
A Distinguished Panel . . .Shai Agassi,Newergy(Founder & CEO,)Jay Nagley, UKTrade & Investment(Senior SpecialistAutomotive)Steve Yianni,Transport SystemsCatapult(CEO)Dr.GeorgeGillespie, MIRA(OBE, CEO)AndreyBerdichevskiy (WorldEconomic Forum)Senior ManagerAutomotive Community41
2 Introduction: - Transformational Shifts Reshaping the Future of Mobility New Mobility Business Models Mobility Integration Convergence of Corporate Mobility The City as a Customer Women and the Automotive Industry Focus on Health Wellness and Wellbeing in the Automotive Industry Connected and Automated Mobility Growth in high Speed Rail and Public transport .
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The Mega Trend Matrix Understanding Implications of Key Mega Trends on Global Economy Note: The size of the bubble represents the scale of opportunity within each Mega Trend. These Mega Trends have been plotted based on quantitative and qualitative reasoning. Source: Frost & Sullivan Analysis Low Degree of Certainty Low High High Urbanization
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