In June 2015, as part of the core Future Agenda programme, we ran a dedicated workshop in Munich on the future of the connected vehicle, the stimulus for which can be found on our slideshare site (http://www.slideshare.net/futureagenda2/the-future-of-the-connected-vehicle-29-july-2015) while the outputs are on Flickr (https://www.flickr.com/photos/131046472@N07/albums/72157650615072522). With the connected car vision fast growing in impact and reach, many are highlighting what new data sources may be available in the future and how these may provide benefit to drivers, manufacturers and support services. As such we are now taking a deeper look at this, what is possible, what is probable and where value may be created, delivered and shared. Building on last year’s views and additional recent discussions, we created a new initial view that brought together a number of different perspectives on the potential future of automotive data, the varied sources potential shifts within the sector as well as adjacent trends on data and connectivity. Over the past couple of months we gained feedback and opinion from around the world on which of these shifts are most likely to occur, where greatest value lies and what may be missing from this view. As many organisations are rushing to grab as much data as possible, many hoping to extract value from the associated insights, we hope that this discussion will help clarify the reality from the hype, prioritise the propositions that will truly have benefit and so enable more focused activities. This is an area where collaboration, data sharing and competitor cooperation is clearly critical and as a lead arena for digital transformation we hope that the associated insights that emerge will be of interest to many. This is an update of the initial view that includes comments from multiple experts around the world with whom we have talked. Some are from within the automotive sector and others from adjacent fields - potential partners and disrupters. We have grouped the updated insights into clusters around potential pots of value as seen by these experts - and separated them into level of value (high / medium / low etc) and level of sharing of data - from proprietary to shared to open. As the final stage of this project we are now opening this up for wider comment to build a more broadly informed point of view. We welcome your views

1. The Future of Automo-ve Data
An Updated Perspec.ve for Final Feedback
25 July 2016 The world’s leading open foresight program

2. Context - The Connected Vehicle
In June 2015 we ran a dedicated workshop in Munich on the future of the
connected vehicle, the output of which can be found on our slideshare and
Flickr site. This new document builds on the previous discussions.

3. Context – Automo-ve Data
With the connected car vision growing in impact and reach, many are
highligh.ng what new data sources may be available in the future and how
these may provide benefit to drivers, manufacturers and support services.

4. The Ini-al View
An ini.al view has been shared that brought together different perspec.ves
on the poten.al future of automo.ve data, the varied sources poten.al shiLs
within the sector as well as adjacent trends on data and connec.vity.
Data
Sources
Sector
ShiLs
Adjacent
Trends

5. Feedback and Addi-ons
Over the past couple of months we gained feedback and opinion
from around the world on which of these shiLs are most likely to occur,
where greatest value lies and what may be missing from this view.

6. Poten-al Sources of Informa-on

7. Vehicle Data
There is a vast array of informa.on becoming available from vehicles
themselves. With the inclusion of mul.ple sensors and onboard control units,
the ability to have near total vehicle real-.me analysis is becoming a reality.
Tyre Pressure
Vehicle Weight
Brake Pads
Tyre Wear
Steering
Airbags
Driver Assistance
Lights
Emissions
Suspension
Tilt Angle
Key Access

8. Engine Bay Data
Within the engine bay, integrated sensors are enabling car
manufacturers, dealers, workshops and drivers to have far greater
insight on engine condi.on, performance and need for aWen.on.
Oil Level
Oil Quality
Engine Wear
Fuel Quality
BaWery Life
Temperature

9. Environmental Data
As a vehicle moves down the road, there is also a host of ambient
informa.on that can be collected and shared about the environment
within which the vehicle is passing and interac.ng.
Lane
Air Quality
End Des.na.on
Route
Road Condi.on
Weather
Speed
Loca.on
Pedestrians
UV Levels
Road Type

10. Driver Data
Within the car, sensors can increasingly track mul.ple sources of
informa.on about the driver, his / her alertness and driving behaviour
as well as connec.vity and media consump.on.
Iden.ty
Fa.gue
Media Use
Driving Time # Passengers
Behaviour
Safety
Level of Autonomy
Mobile Network

11. Value and Access
ALer discussing the future poten.al with a wide range of organisa.ons from
within and outside the automo.ve sector, we have now grouped around 50
opportuni.es into clusters by value and level of access for wider sharing.
High Medium No / Low
Proprietary Shared Open
DATA ACCESS
VALUE
15 24
18
12
11
13
14
16 17
19
20
21 22
23 25
26 27
28
29
10
31
30
1 2
3 4 5
6 7
8 9
32
33
34
35
36
37
38
39
40
41
42
43 44
45
46
47 48
49
50
51
52
53

12. Proprietary Data – High Value
There are a few areas where organisa.ons believe that they can create
significant value for themselves by having beWer customer informa.on or
providing dedicated product support and personalised services.
High Medium No / Low
Proprietary Shared Open
DATA ACCESS
VALUE

13. Access to Mobility
Vehicle manufacturers shiL from selling products to focusing on fleet,
asset and lifecycle management within a wider ecosystem – with value
produced from services across the lifecycle of the customer rela.onship.

14. Tyre Wear Monitoring
Tyre wear is deduced via accelera.on and braking styles, road surface,
tyre pressure and temperature. Tyres are self tracking as workshops
automa.cally match and balance tyres to vehicles and driver behaviour.

15. Brake Pad Wear Tracking
Brake pad wear is deduced via accelera.on, braking styles and usage
profiles. Workshops and parts suppliers proac.vely target likely
replacements and vehicles are maintained at a safer opera.on level.

16. Forensic Accident Data
In the event of a collision, the black box records key data such as impact speed,
direc.on, secondary impacts and brake ac.va.on. It provides proof for insurers
of what happened just before and during an accident and prevents fraud.

17. Enhanced Entertainment
Personalised content from tailored media plagorms, enhanced digital
storage, high bandwidth and the ability to access mul.ple media libraries
provide a full digital experience in the vehicle - as good as in the home.

18. Proprietary Data – Medium Value
Equally there are a couple of opportuni.es for some organisa.ons
to provide incremental, and most likley short term, value by
avoiding problems and offering targeted retail promo.ons.
High Medium No / Low
Proprietary Shared Open
DATA ACCESS
VALUE

19. BaJery Drain
Tracking baWery drain when the engine is off predicts probable dead baWeries.
As this is the most common reason for roadside call-outs for commercial
vehicles, reducing lost .me improves overall fleet efficiency.

20. Chassis Fault and Wear Detec-on
Iden.fica.on of faults before excessive wear is enabled via connec.vity to
chassis faults currently not measured - including tracking, shock absorbers,
brake disc warpage and damaged and out of balance wheels.

21. Fuel Brand Loyalty
Analysis of vehicle loca.on, rou.ng and fuel consump.on allows
fuel brands to provide targeted discounts. Driver loyalty grows and
results in increased foogall and higher spend on retail product offers.

22. Iden-fying Driver Risk
Iden.fying the drivers that are least likely to have an accident is achieved
by matching historical data with actual driver behavior such as speed,
accelera.on and braking. Companies pay to recruit the safest drivers.

23. Proprietary Data - LiJle or No Value
However, for the majority of organisa.ons looking to use only their own data
with customers and suppliers, the general view is that there maybe internal
efficincies to be gained but these will generate liWle extra value.
High Medium No / Low
Proprietary Shared Open
DATA ACCESS
VALUE

24. Full Rental Vehicle Condi-on
Details of of how and where a vehicle has been driven is provided
alongside visual checks to give hire car users the same confidence in
a rental car or van as they have in their own vehicle.

25. Data Islands
Some economies seek to maintain closed or parallel networks, independent of
global systems. Different approaches from the standard are developed for
major popula.on centres and, in .me, could have global reach.

26. Oil Reuse
Improved collec.on, recondi.oning and reuse of oil, and the ability
to make the owner aware of their ‘life.me’ oil footprint and CO2 impacts,
are made possible via monitoring of oil condi.on and any top ups.

27. Oil as an SKU
Plagorms such as the Nexcel oil and filter unit turns a consumable into
a hard part. Workshops, auto parts retailers and distributors
all gain the benefits of SKU shipping and inventory management.

28. Fuel Upgrade
Understanding which drivers are in the vicinity, their route and
driving style allows fuel retailers to incen.vise premium grades that
deliver beWer consump.on and performance for the right customers.

29. Downhill Coas-ng
Cheaper driving and longer service intervals come from vehicle .lt
sensors that highlight downhill travel – automa.cally causing the car
to coast with engine on .ck-over and so op.mising fuel consump.on.

30. Shared Data – High Value
For new proposi.ons based on organisa.ons sharing data, many believe
that there are a number of clear opportuni.es for significant new value
crea.on through intelligent connec.ons between par.es.
High Medium No / Low
Proprietary Shared Open
DATA ACCESS
VALUE

31. Re-establish Rela-onships
Vehicle iden.ty and usage - engine performance, tyre and oil - is tracked
beyond ini.al new service term or lease. Car brands re-establish rela.onships
via approved parts, inclusive service contracts and trade-in valua.ons.

32. Fleet U-lisa-on
Fleet managers achieve beWer vehicle op.misa.on via real-.me analysis
of engine use and performance, oil condi.on, usage, idle .mes, load,
rou.ng criteria, area traffic inputs and historic vehicle performance.

33. Vehicle As Payment Card
Using a combina.on of mobile loca.on and biometric data, driver iden.ty
is authen.cated and linked to the vehicle, which becomes the payment card –
for road tolls, conges.on charge, gas sta.ons, parking and drive thru services.

34. Health Analysis
Drivers’ health is monitored on a daily basis by sensors within the vehicle.
This becomes a credible plagorm for diagnosis and tracking of key
indicators of interest to both insurers and wider healthcare providers.
34

35. AQersales Upselling
Consumers are becoming more inclined to make separate purchases of the in-
car func.ons that they want most via aLer-sales rela.onships. Some will pay
15% extra for safety systems, remote services and parking assist technology.

36. Shared Data – Medium Value
Most significantly however, many see a host of new opportuni.es
emerging to realise addi.onal value by crea.ng and knilng together
a number of medium value shared data plagorms.
High Medium No / Low
Proprietary Shared Open
DATA ACCESS
VALUE

37. Virtual Fleets
Linking together vehicles and drivers with common needs enables individuals
to share the benefits of a large group. From collec.ve purchasing of
consumables to peer-to-peer self insurance, more efficient models emerge.

38. Fixed Price Motoring
Car and truck opera.ng costs are bundled like mobile phone tariffs.
Fuel, insurance, servicing and cleaning are all included in,
for example, 500, 1000, 1500 mile per month fixed bands.

39. Window on Driver
Analysis of driving behaviour, style, routes and loca.ons builds a
detailed view of the life of the driver. More personalised, targeted
marke.ng beWer matches products and services to the driver profile.

40. Detailed Data Integra-on
AWen.on focuses on control of the permissions of data at a granular level
and aWribute it with things like cost, trace routes of accountability, sharing
permissions. You need to be able to slice and dice the data dynamically.

41. Data Curators
Personal Informa.on Managers grow in number and seek to manage
and protect both ‘free’ individual data sets and aggregated data:
“If you are not paying for a product, you are the product.”

42. Advanced Parking
No more searching for spaces as automated access to car park informa.on,
shared parking bays and route planning allow drivers to rest easy – knowing
that an available parking spot is booked and automa.cally paid for.

43. Open Electronic Log Book
Some of the electronic log book is made more open and extended. It is
made accessible to owners and garages and includes details of how and
where the vehicle has been driven as well as the full service history.

44. Reduced Warranty Costs
Tailored warranty cover, with reduced prices or longer terms, derives from
monitoring engine, tyre and brake use and relaying this to key par.es.
Repairs are proac.vely managed and cost savings are shared.

45. Deferred Repair
Improved monitoring of oil and engine condi.on by car manufacturers and
workshops enable vehicle services to be scheduled when needed, not just
when mileage triggers are hit. Cost savings benefit owners.

46. Vehicle Value
The current value of a vehicle is regularly updated using mileage,
wear, servicing and environmental data. This is shared to owners and
marketplaces to provide greater transparency and less uncertainty.

47. Enhanced Journey
Brands provide targeted, personalised offers via a mix of route informa.on,
driver / passengers’ digital footprints and opt-in preference selngs.
This leads to increased sales and improved journey experience for all.

48. Work Produc-vity
The vehicle is a secure, high-speed, fully connected extension of the
workplace. Home, office and mobile data is ubiquitous and, as autonomy
develops, the car becomes a fully func.oning work space.
48

49. Automated Spare Parts Provision
Integrated analysis of vehicle performance and wear provides proac.ve
iden.fica.on and sourcing of approved spare parts aligned to driver
loca.on which ensures minimum disrup.on and op.mizes supply.
49

50. Shared Data – LiJle or No Value
There are also a host of new proposi.ons being developed on the back of
shared informa.on that will help improve system efficiency and enhance
compliance and insight but with liWle new tangible value crea.on.
High Medium No / Low
Proprietary Shared Open
DATA ACCESS
VALUE

51. Ac-va-ng Idle Vehicles
Unused and parked vehicles are iden.fied and matched to customers keen to
rent access. Idle cars are put to good use, improving overall fleet efficiency,
reducing the number of vehicles needed and proving extra income for owners.

52. Agreement on Use Not Collec-on
The best approach to future proof access to big data is to ensure there is
agreement around its use, not its collec.on. We need a core reference dataset
to iden.fy the data that is most effec.ve in driving social and economic gain.

53. Overloaded Commercial Vehicles
The ability to accurately track total vehicle weight in real-.me enables
fleet owners and highways agencies to monitor gross weight within and beyond
legal limits - and so beWer schedule maintenance and apply road taxes.

54. Driver Training
Driver behaviour, ‘hours’ logged and local traffic informa.on help
drivers to improve their skills. Accompanying assessments match
skills to the driver and also help bridge the gap to driverless cars.

55. Independent Engine Analysis
Data on engine use and performance, oil condi.on and historic vehicle
usage is mined producing regular reports that give peace of mind
for owners and validated comparison data for workshops and insurers.

56. Vehicle Environment and Condi-on
Environmental sensors monitor ambient temperature, UV exposure,
sub-zero exposure and proximity to the sea to provide insight on likely
vehicle condi.on, corrosion and areas for poten.al repair.

57. Find My Stuff
Owner valued and RFID / NFC enabled objects within the vehicle
are automa.cally monitored and tracked, allowing drivers to
‘find their stuff’ when missing, if lost within or near the vehicle.

58. Open Data – High Value
In the arena of open data use, greatest value is seen to lie in systems
that provide greatest benefit to personal ease of use and marketplaces
that allow more data to be transparently accessed and traded.
High Medium No / Low
Proprietary Shared Open
DATA ACCESS
VALUE

59. Personal Mobility Accounts
Consumers have a single, digital mobility account that is accepted by all in
the eco-system. This gives them access to public and private transporta.on
op.ons and mobility data is made available to mul.ple service providers.

60. Integrated Mobility
Shared automo.ve data is just one piece of a patchwork of mobility
informa.on for the individual. This is well integrated and branded with easy to
use interfaces to enable consumers complete control of their mobility op.ons.

61. A Data Marketplace
Data is a currency, it has a value and a price, and therefore requires a
market place. An ecosystem for trading data is emerging and anything
that is informa.on is represented in a new data marketplace.

62. Open Data – Medium Value
There are a couple of areas where open data is seen as a key enabler to
major macro shiLs that will provide benefit to a wide community and
hence some incremental value to the leading informa.on integrators.
High Medium No / Low
Proprietary Shared Open
DATA ACCESS
VALUE

63. Autonomous Vehicles
The shiL to fully autonomous transport is an evolu.on via truck platoons on
highways and small urban delivery pods. Connected trucks create the network
and test the technologies for the eventual revolu.onary driverless experience.

64. Full Personalisa-on
Through accessing calendars, journey routes and individual preferences,
the vehicle responds to personal profiles and choices. Design configura.ons
and informa.on provision are automa.cally adapted to fit.
64

65. Open Data – LiJle or No Value
However, most agree that the big shiLs enabled by wider open data sharing
and access will help improve transport networks and associated environmental
impacts, but there will be liWle extra direct financial value crea.on.
High Medium No / Low
Proprietary Shared Open
DATA ACCESS
VALUE

66. V2V Communica-on
Vehicle to vehicle interac.on accelerates around safety, conges.on and
entertainment. Road hazards, ABS ac.va.on and slow traffic informa.on is
shared while gaming between passengers in different cars takes off.

67. Traffic Management
Police, road authori.es and app developers leverage vehicle loca.on
informa.on combined with historic use paWerns, predic.ve analy.cs and
surrounding traffic informa.on to enable improved flow management.

68. Faster Emergency Response
In the case of a crash, systems such as eCall automa.cally call the
nearest emergency centre. This cuts emergency services response .me.
It goes down by 50% in the countryside and 60% in built-up areas.

69. Car Sharing Repor-ng
Real-.me weight of vehicle, routes taken and driver iden.fica.on
collec.vely provide a record of vehicle sharing to the owner (and other
par.es) and so highlights any rebates / rewards that may be due.

70. Vehicle Tracking and Recovery
Tracking and recovery of stolen and broken down vehicles by the
police, emergency services and owners is enhanced via access to
mul.ple sources of independent vehicle loca.on and status data.

71. Higher Connec-vity Speeds
Vehicle connec.vity is upgraded to latest networks (4G / 5G) enabling
manufacturers, drivers, passengers and providers of telecoms, entertainment
and content to all take advantage of fastest available data speeds.

72. Emissions Data Sharing
Emissions data is broadcast for open use from vehicles and street sensors -
thus crea.ng a shared dataset. Planners, governments and app developers
use this to beWer manage traffic flows and highlight healthier urban zones.

73. Improving Air Quality
All vehicles measure and report local air pollu.on and their contribu.on
to it. Transparency leads to ac.on as claims are challenged and validated
while, as a global response, air pollu.on standards are .ghtened.

74. Five Further Ques-ons

75. Five Ques-ons
The ini.al in-depth discussions with experts on and around the future of
automo.ve data have created this emerging view. We now want to open this
up to a wider audience for comment and feedback via five main ques.ons.
1. What is s.ll missing from this view that you think will have significant impact?
2. Do you see more opportuni.es for new value crea.on that currently outlined?
3. Are there opportuni.es that are grouped in the wrong area and if so which?
4. Which of these shiLs are more likely to become mainstream earlier than others?
5. Which do you see as helping accelerate the overall rise in automo.ve data use?

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