Connected Vehicle Data Series 3 of 7:
By now, we know our vehicles collect data. Let’s explore how that data is put to use and who stands to benefit.
@wiley_19#7828 (DIMO Media Contributor)
So far, we’ve learned what your vehicle knows (data about itself, the environment, and you) and how it got that knowledge (sensors and ECUs). It’s time to move on from the “what” and the “how” into the “why.”
As ECUs replaced mechanical control systems, vehicles collected data because their components needed to know information about each other in order for the vehicle to function. While that still remains the case, the “why” for data collection has rapidly expanded. With many new vehicle models equipped with embedded modems, the data once stored only on your vehicle can now be shared with the outside world.
In fact, an estimated 30 million of these connected vehicles were added to our roads in 2020. By 2030, Mckinsey estimates that 95% of vehicles sold will be connected, creating $250-400 billion in annual incremental value for vehicle data stakeholders. Market sizing projections for a relatively new industry should always be taken with a grain of salt, but you can start to see why the automakers’ “why” for data collection is rapidly expanding.
So who is receiving this data? And why is it so valuable?
The primary recipient of your vehicle’s data (if it is a connected vehicle) is the automaker. They likely have agreements to share certain data points with their suppliers (a brake supplier could receive data points on stopping distances, for example), but for now, let’s focus on the automakers.
Once the automaker receives your data (and the data from their other thousands of vehicles on the road), they can then:
Improve or develop services or features
Since 2017, Tesla has used data from its vehicles to improve their self-driving software, AutoPilot. With data from 8 cameras and numerous ultrasonic and radar sensors on each vehicle, Tesla has been able to advance their software to the point of releasing a beta version of their “full self-driving” software earlier this year. The issues with Tesla’s “full self-driving” software have been well documented, but there is no doubt that the years of on road data have aided their software development.
Prevent or reduce severity of quality issues
Automakers spent an estimated $49 billion on warranty issues in 2019 including a 1.2 million vehicle recall by Nissan and Infiniti. Software issues allowed the backup camera view to be unavailable while the vehicle was in reverse—which violates federal mandates. With a greater quantity and quality of vehicle data, the automaker could have identified this issue earlier, fixed it primarily in the plant instead of the field, and reduced the customer’s exposure to this potentially dangerous scenario.
Reduce variant complexity
Picture a new vehicle that offers seven different drive modes such as "Sporty," "Comfort," and "Eco." After launching the vehicle and gathering a significant data set, the automaker sees the "Comfort" mode is rarely used by customers. It can now make a data-driven decision to eliminate the "Comfort" mode and unnecessary software development, calibration, and hardware capacity on current and future models.
Optimize design requirements
When vehicle systems, features, and parts are designed, they have to meet a set of requirements. These requirements may tell the engineer how close it can be to other parts, how much wear and tear it must handle, what materials it can be made by, what environments it must function in, how quickly it must complete a task, or what the user experience should be. These requirements could be derived from previous testing data, simulations, customer clinics or just old rules of thumb. With large vehicle data sets, they can be optimized to reduce costs while maintaining performance.
Sell data to marketplaces such as Wejo or Otonomo
Data is cleaned, normalized, and sold by the marketplace to third parties such as municipalities, retailers, and insurers. How might these stakeholders use the data created by your vehicle?
Today, cities such as Detroit and Memphis are using sensor data from municipal vehicles to map road hazards such as potholes. In 2019, the city of Memphis fixed 63,000 potholes with only 20% of them having been reported by the public showing the benefit of utilizing vehicle data. In the future, vehicle data can be used to identify traffic patterns, redesign intersections to improve safety and efficiency, and identify optimal parking strategies.
Currently, insurers such as Allstate and Progressive provide usage based insurance (UBI) via smartphone data or dongles. However, OEMs such as GM, Ford, Nissan, and Kia are now partnering with data exchanges such as LexisNexis to allow users to opt in to UBI by sharing their vehicle data directly with the insurers. This allows the insurer to more accurately price risk through increased access to data and improved understanding of the vehicle’s safety and ADAS features.
A retailer’s location can make or break the business. With large vehicle data sets, the retailer can identify locations with sufficient traffic to increase their chances of success. They can also identify unmet needs by analyzing trip patterns to see if customers are traveling long distances to their store or a competitor’s. Once they have their location, they can use similar traffic data to develop their parking and entrance strategy. Finally, retailers and other advertisers will surely use this data for location based advertising both inside and outside the vehicles. Be ready for in-vehicle advertising to take off as autonomous vehicle technology matures.
Other potential data consumers include mobility services, fleet operators, electric vehicle infrastructure developers, and app developers.
It should be noted that there is some uncertainty in the exact data points being transmitted back to automaker and eventually sold. However, technological advances in vehicles and communications infrastructure (5G) as well as the margins of data products in an industry hovering around 10% profit margins will surely lead to increases in the quantity and variety of data sent back to the automaker. Later in the series, we’ll take a look at how regulations or user agreements affect automakers' usage of our data.
In the next post, we’ll explore how connected vehicles are expanding beyond just sending data back to the automaker and how these changes will affect our driving and vehicle ownership experiences.
Drive on to the next post:
This post is from a DIMO community member, and opinions are their own. Digital Infrastructure Inc. does not necessarily endorse any of the views herein.