Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Upcoming SlideShare
Driving digital transformation in Automotive industry
Next
Download to read offline and view in fullscreen.

2

Share

Download to read offline

Updated - The Future of Automotive Data 25 07 16

Download to read offline

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

Related Books

Free with a 30 day trial from Scribd

See all

Related Audiobooks

Free with a 30 day trial from Scribd

See all

Updated - The Future of Automotive Data 25 07 16

  1. 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. 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. 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. 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. 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. 6. Poten-al Sources of Informa-on
  7. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 74. Five Further Ques-ons
  75. 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?
  76. 76. Future Agenda 84 Brook Street London W1K 5EH +44 203 0088 141 futureagenda.org .m.jones@futureagenda.org The world’s leading open foresight program
  • LaurentE

    Jan. 3, 2018
  • charliecurson

    May. 20, 2016

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

Views

Total views

1,597

On Slideshare

0

From embeds

0

Number of embeds

21

Actions

Downloads

52

Shares

0

Comments

0

Likes

2

×