1、M ONETIZ IN G V E H ICLE DATA How to fulfill the promise A C A P G E M I N I I N V E N T P O I N T O F V I E W How has the market evolved? Predictions of the global revenue for vehicle data monetization by 2030 range between $80bn to $800bn, highlighting the enormous potential for both automotive OE

2、Ms and service providers using data for service innovation. However, despite heavy investments in IT platform infrastructure, in-vehicle technology, and service innovation by OEMs, achievements are falling short of projections. Volumes of connected vehicles started to rise later than expected and da

3、ta signals are often restricted to a limited set of basics. Factors such as these mean market growth is slower than many experts have predicted. Capgemini has undertaken extensive research into this area, including a survey of 3,000+ end customers in the EU and industry expert interviews. This resea

4、rch explores the main obstacles and investigates how automotive OEMs and service providers can better exploit the potential. Major obstacles identified for OEMs and service providers: Low end customers willingness to share vehicle data due to trust and transparency issues High complexity of setting

5、up a suitable data collector and platform infrastructure Lack of service innovation culture to successfully manage novel data-based business models from ideation to implementation Service providers are given limited access to vehicle data. How Capgemini can help Short-term business success with vehi

6、cle data has been overrated in the past. However, be patient. Keep on investing and testing, as it will be a major revenue pool in the future. To fulfill the monetization promise and add a central in-vehicle data collector, both supply and demand must be built up starting with simple but value-creat

7、ing services. At the end of the report, Capgemini presents its evaluation of the most prominent services based on personalized vehicle data. The segmentation of the results can help OEMs and service providers determine which services they should prioritize. E XECU T I V E SUMM A RY To overcome these

8、 obstacles, Capgemini recommends the following actions: DATA TRUST: Build end customers willingness to share data by increasing transparency in data use and incentives to increase consumer trust and adoption. CUSTOMER CENTRICITY: Establish customer co-creation in a collaborative setting with automot

9、ive OEMs and service providers to design service experiences that customers enjoy. DATA ENRICHMENT: Enrich vehicle data with other data sources (e.g. customer data, third-party data) to build more valuable data-driven services. DATA COLLECTOR STRATEGY: Develop a universal data collector box in all v

10、ehicle models to increase the volume of data signals for greater service innovation. ORGANIZATIONAL SETUP: Embed service innovation within a new organizational setup and collaborate with partners to speed up prototyping and scaling. SERVICE PRIORITIZATION: Prioritize investments carefully, systemati

11、cally evaluating data monetization opportunities to form a manageable set of promising services. 2Monetizing Vehicle Data: How to fulfill the promise TA BL E OF CONTENT S 0 4 H O W FA R H A S V E H I C L E DATA M O N E T I Z AT I O N P R O G R E S S E D? 07 W H AT O B S TAC L E S H A M P E R M O N E

12、 T I Z AT I O N ? 12 H O W C A N W E R E A L I Z E DATA S F U L L P OT E N T I A L ? 15 H O W S H O U L D V E H I C L E DATA- B A S E D B U S I N E S S O P P O R T U N I T I E S B E P R I O R I T I Z E D A N D E VA LUAT E D? 18 H OW C A P G E M I N I A P P R OAC H E S V E H I C L E DATA M O N E T I

13、Z AT I O N 3 HOW FA R H A S V EHICL E DATA MONE T IZ AT ION PROGRE S SED? 4Monetizing Vehicle Data: How to fulfill the promise VEHICLE DATA THE BIG PROMISE Overall, the monetization of data has become one of the most promising profit pools across industries. Among other data sources, organizations r

14、ely especially on the utilization of vehicle data, be it for internal processing, product optimization, or generating new revenue streams through service innovation. Capgeminis 2020 Connected Vehicle Trend Radar confirmed that vehicle data monetization is the connected vehicle ecosystems most promis

15、ing value driver for automotive OEMs. In fact, Capgeminis experts have identified estimates suggesting that in 2030 the global vehicle data market will be worth $80800bn. Automotive OEMs and service providers have been swift to invest in vehicle data monetization, aiming to achieve early mover advan

16、tage and new revenue streams. Worldwide, there are more than 150 established startups in the connected vehicle platforms sector. The volume of investments made in these startups amounts to more than 500m. Meanwhile, vehicle data platforms have been launched, external platform players integrated, pri

17、vacy-compliant consent management solutions established and data has started flowing. Early services offered include pay-as-you-drive, vehicle status, e-mobility charging, and service maintenance. EARLY ACHIEVEMENTS LAG BEHIND EXPECTATIONS Despite this progress, connected vehicle sales, available da

18、ta, services offered, and market penetration all fall short of projections. Of the data monetization use cases that automotive OEMs intended to launch, fewer than 20% have actually been offered to end customers. According to Capgemini research and in-field project experience, many remain at the proo

19、f-of-concept stage. In 2020, however, automotive OEMs and service providers are not yet seeing significant revenue streams from this source. Less data is available than earlier projections suggest. In 2017, experts predicted that modern vehicles would be able to provide more than 400 data points, ge

20、nerated from at least 200 different sensors. Currently, however, on average 100 data points are available, whether via automotive OEMs own data platforms or those of service providers. Moreover, todays data transmission techniques are unable to send even this volume of vehicle data to OEMs servers i

21、n real time. In future, however, Capgemini experts expect that the next generation of vehicles will soon be able to provide up to 10,000 data points. 10,000+ data points will be available on vehicles in the future HOW FA R H A S V EHICL E DATA MONE T IZ AT ION PROGRE S SED? 5 THE R ANGE OF POT ENT I

22、AL DATA SIGNAL S I N CONNEC TED V EH ICLES (EXCERPT ) F IGURE 1 G E NER AL Instrument display unit, outside temperature, date and time in the vehicle, availability of teleservices, orientation of vehicle, vehicle position N A VI GAT I ON GPS speed, navigation destination, position of the vehicle lat

23、itude & longitude, time and distance to navigation destination, alignment of the vehicle, state of motion of the vehicle, maximum number of POIs stored in the navigation device, free POI spots D OORS & W IN D O W S Status of convertible roof: sunroof, doors, windows, hood & trunk, spoilers, service

24、fl ap WAR NI NG S Y S T EM S ABS/ESP events, DTC, ADAS events, automatic teleservice call, teleservice battery guard, number of CBS messages, sensors (parking, distance, speed) L IGH T S Condition of lights, condition of turn signals ELEC TRI C V E H ICL E Battery health and voltage, charging profi

25、le, charging status, electrically driven part of the route, consumption of electrical energy, mode of the last trip, recovered energy S M AR T P H ONE Mobile phone pairing, use pattern of applications L IQU I DS Coolant and oil temperature, coolant and oil level, brake fl uid D RI VER Driver identit

26、y, preferred settings F U EL Range of tank capacity, remaining range, tank capacity D RI VI N G Mileage, acceleration/deceleration, remaining range, activation time of ECO or SPORT mode, average distance, driving style evaluation, average fuel consumption, intensity of braking operations, gearing be

27、havior S EC U R I T Y Belt status, passenger airbag S ER VI C E Date of next inspection, trip details (distance, time, events, positions), date of next service, date of brake fl uid change, distance to the next service, time threshold for main and exhaust emission test, check control messages, low-v

28、oltage battery, remote service result, remote service type, time threshold for service information D RI VER CO N D IT IO N Heart rate, stress level, diabetes level BREA KD O W N Crash severity, crash location EN GI N E Ignition, engine temperature WH EEL S Status of tire pressure, tire warning indic

29、ator status, status of brakes, status of parking brake 6Monetizing vehicle data: How to fulfill the promise WH AT OBS TACL E S H A MPER MONE T IZ AT ION ? 7 To understand why vehicle data monetization is not gaining traction as fast as expected, we reviewed the situation from the perspectives of end

30、 customers, automotive OEMs, and service providers. END CUSTOMERS PERSPECTIVE We conducted research with an EU sample comprising 3,000+ participants from Germany (37%), France (33%), and the UK (30%). To understand the perspectives of automotive OEMs and service providers, we conducted several exper

31、t interviews. Many end customers are unwilling to share data Sharing vehicle data still raises mixed feelings with participants and only around one-third are willing to share data. Interestingly, when considering the German sample more closely, participants exhibit a higher willingness to share vehi

32、cle data compared to the other two countries. Looking more deeply into the group who are generally willing to share their vehicle data, a clear trend emerges: end customers are particularly concerned about personalized, as opposed to anonymized data sharing, with only about one-third willing to shar

33、e this type of data (two-third for anonymized data). Not enough awareness about the purpose of data sharing Uncertainty is a major issue when participants were asked about data sharing. While more than 80% are not even aware of the data their vehicle transmits, pointing out the benefits and use case

34、s raises willingness to share by 28%, suggesting that lack of understanding of the proposition is a barrier. Total transparency around how their vehicle data is used can mitigate concerns regarding data security and misuse. Vehicle data needs different incentives to share Outside the vehicle ecosyst

35、em, gamification and competition are usually key motivating factors for sharing data (especially personalized data). However, when it comes to vehicle data, only a small number of respondents said these incentives increase their willingness to share vehicle data. For data that they consider sensitiv

36、e, end customers prefer to have full control and discounts in return for using services. The proportion of participants willing to share personalized data increased to approximately 50%, when discounts were mentioned as an incentive. Automotive OEMs are trusted most with data Around 36% of participa

37、nts stated that they trust automotive OEMs when it comes to data sharing. Of these, heavy users (those driving their vehicle more than five days a week) were more open to releasing their data to automotive OEMs. Interestingly, data platform providers were the group that participants trusted least pr

38、esumably because they are seen as operating a “black box,” where end customers have no insight into how their data is being used. AUTOMOTIVE OEMS PERSPECTIVE A break with tradition is needed Most automotive OEMs have acknowledged that their history does not equip them to provide data services for th

39、eir end customers. Besides a cultural mismatch, there are practical difficulties, such as inadequate skill sets, resources, processes, and digital business sense for innovative pricing models (as there is no historical pricing information to build business cases). Often, automotive OEMs are confiden

40、t about designing new business models, but lack steering processes to manage their service portfolio roadmap. Hence, their service development funnel is too ambitious so that only a few services reach implementation status. “ W E D O N OT H AV E A DATA S E R V I C E D N A A N D A R E H AV I N G TO B

41、 U I L D U P T H E C U LT U R E A N D T H E CO U R AG E F O R D I G I TA L B U S I N E S S M O D E L I N N OVAT I O N F R O M S C R ATC H .” Thomas Geiger, Data Business Expert, AUDI AG There are similar concerns regarding the distribution of services directly to end customers. Until now, automotive

42、 OEMs core business has been selling vehicles through importers, with services outsourced to partners. Now, OEMs have to take a huge step, not only towards service innovation but also towards direct distribution of services to their end customers. Another roadblock is that data platform providers an

43、d service providers are perceived by automotive OEMs as competitors rather than enablers for fast service adoption. OEMs prefer to protect their own services (e.g. predictive maintenance) and exploit them fully themselves. They are afraid to let in other market players. “ I WA N T TO K N O W E X AC

44、T LY W H AT I A M S H A R I N G B E F O R E I AG R E E .” Capgemini study participant from Germany 8Monetizing Vehicle Data: How to fulfill the promise “ FO R H I S TO R I C A L R E A S O N S T H ER E I S A WI DE, COM PL E X VA R I E T Y O F I N -V EH I C L E COM P O N EN T S , WH I C H M A K E S I

45、T C H A L L EN G I N G FO R AU TOMOT I V E O E M S TO M A N AG E V EH I C L E DATA I N A S T RUC T U R ED A N D C US TOM ER - FR I EN DLY WAY.” “ BO O K I N G A N E W T EL E M AT I C I N SU R A N C E P O L I C Y H A S TO B E A S E A S Y A S PAY I N G V I A PAY PA L .” Thomas Geiger, Data Business Ex

46、pert, AUDI AG Lead Vehicle Operations Strategic Tasks, German Insurance Company Market uncertainty is inhibiting maturity and lack of technical standards is hampering progress Automotive managers told us in focus interviews that innovation around the vehicle data business model is inhibited at both

47、business and technical levels by uncertainty, since politicians and lobbyists have not yet managed to agree on a common industry standard. Lack of common data and platform standards is another major inhibitor. Most automotive OEMs have complied with the ExVe ISO standard, but are still implementing

48、platforms according to their own standards. Service providers, however, are primarily interested in purchasing data that is standardized across automotive OEMs. Setting up a user-friendly platform infrastructure is complex Managing vehicle data is a challenge, especially given the variety of compone

49、nts in a typical vehicle and considering the current, highly heterogeneous, system landscape. The challenge starts with the data catalogue: automotive OEMs do not always know what data they already have and where it is stored. On top of the component variety, OEMs lack a universal data collector technology, leading to a heterogenous set of data signals across vehicle models and a limited volume of connected vehicles with relevant data signals overall. This reduces the possibility for adva