The evolution of customer experiences is coming into focus thanks to real-time data. The value of information has never been lost on organisations. In fact, research suggests that the brands that place a greater premium on data-driven approaches are six times more profitable year to year than those that do not – and 92% of marketers see first-party data collection as critical to keeping pace with customer interest and demand and scaling up those potential earnings.
The emergence of next-generation (that is, software-defined, connected and autonomous) vehicles shines an even brighter spotlight on how real-time information is influencing the landscape of driver experiences. But having an eye on data is just the start – nurturing and applying it properly is another task entirely.
Data is a game-changer along every link of the automotive supply chain, from OEM to dealer and every stakeholder in between. Building a frictionless, customer-friendly driver experience requires a comprehensive in-house data strategy (aka data factory) that empowers drivers and brands to work in tandem to develop a standout connected driving experience.
Defining next-generation automotive experiences
All next-generation car experiences are not created equal. While all leverage technology and data to varying degrees, they’re each subtly different in their composition – and understanding these distinctions is paramount to understanding the role data plays and how to properly craft that in-house data strategy.
Let’s explore each vehicle type in more depth:
Software-defined vehicles
Where traditional cars are powered by a finely tuned collection of physical parts and pieces, software-defined vehicles (SDVs) run atop software-exclusive architectures. From propulsion to steering to braking to information, the software foundation drives it all.
Key SDV features include:
- Electronic control units
- Centralised computing platforms
- Modular software architecture
- Over-the-air updates
- Advanced driver assistance systems
- Connected services
- Data analytics and telematics
SDVs function due to finely calibrated software ecosystems working in conjunction with one another. As information becomes readily available (like oil change needs, low gas and tyre pressure), the software monitoring those needs updates the system and the driver or dealer.
Autonomous vehicles
Autonomous vehicles (AVs) leverage sensors, radar, GPS and lidar to operate free of human input. These elements collaborate with the vehicle’s internal technology, surveying the environment and using that data to manoeuvre the car.
Key AV features include:
- Sensing and perception capabilities
- Mapping and localisation
- Decision-making algorithms
- Control and communication systems
Connected vehicles
Connected vehicles (CVs) boost internet connectivity and vehicle-to-vehicle and vehicle-to-infrastructure communication technology so they can talk to other cars. Housed with onboard computers and sensors akin to SDVs and AVs, CVs can collect information and use it to deploy real-time safety and efficiency upgrades.
Key CV features include:
- Telematics
- Mobile app and remote services
- Infotainment and connectivity
- Cybersecurity and privacy safeguards
Each variant requires unimpeachable, continuous data flows to run. Putting an equally reliable data strategy in place is a must, but recognising potential barriers is just as vital.
Challenges to data-driven automotive strategies
Clean, transparent data is valuable to any next-generation vehicle’s viability. Compromised data can cast just as large a cloud of doubt over the car, its functionality, the brand and the overall driver experience.
When trying to solidify an automotive data strategy, these variables can introduce issues into the processing and operational workflow.
Data volume
With information being pulled from several repositories, the sheer amount of data powering SDVs, CVs and AVs warrants mention. Experts estimate as much as 4 gigabytes per minute flow through these vehicles, information that OEMs and dealers must monitor. Putting a system in place capable of ingesting and allocating that information needs to remain top of mind to next-generation car manufacturers that want to create vehicles that can adjust and run as needed.
Data transference
Next-generation vehicles are, in essence, on-the-go data containers. Where it’s easy to see information flowing through stationary receptacles like a laptop or mobile phone, there’s no guarantee a signal or connection will be available to help vehicles operate in more remote areas. It’s incumbent upon OEMs and car creators to infuse their data systems with functionality that can ingest and process information, and then piece it together and make it actionable when the end user needs it.
Stakeholder investment
Ironing out the technological barriers is imperative to any data system. But will the engagement and investment in maintaining it always be there? As the automotive industry continues to evolve, the kind and amount of data needed to move it forward will mature – and the money needed to grow or maintain that system will begin to rise. Being willing to grow those systems so they can continue to serve drivers needs to be an ongoing discussion for car companies and their stakeholders.
As these barriers get regularly tended to, automotive brands can begin to prioritise the necessary elements that every data factory must exhibit to generate that ideal driver experience.
Key elements of a dynamic automotive data factory
A data platform that yields a data-driven, customisable driver experience needs structure to support the stream of information. These are the traits to keep in mind:
Compliance
Data sharing and housing regulation are always evolving. As customers swap their personal data for more informed and customised experiences, it’s imperative for the companies that leverage that data to protect it and use it as advertised.
For car companies that sell both commercial and private vehicles across the globe, it’s necessary to stay familiar with local data laws. Be it in the US, UK or Europe, ensure your data factory is compliant so customers feel peace of mind that their information is being appropriately applied.
Health
Inaccurate data pushes processes down ineffective paths, and it can lead to massive overspending by companies trying to rectify the situation. Automotive companies must do diligence to get a read on the accuracy of their information.
Auditing the health of your data streams needs to be a regular task, one overseen by a team or outsourced to a third-party vendor. No matter the manager, make sure they prioritise the accuracy and credibility of that information so as not to compromise the product and brand’s integrity.
Security
Inaccurate data is a money-waster, but so is unsafe data. With several well-known examples of expensive data breaches, automakers surely understand the value of protecting drivers’ information – for brand awareness and customer safety reasons, among many others.
Treat health and security audits as one and the same and designate a specialist to monitor both on a regular or annual basis. And in the case of both, reassure your customers of the work you’re doing to verify with them that the security of their information is paramount to you and your company.
Customer experiences and the data that drives them are changing by the day. A data platform that can support these next-generation vehicle solutions can help the industry evolve with the times without sacrificing the tenets that should define in-car experiences: safety, reliability and efficiency.
Endava’s experts are well-versed and experienced in helping OEMs and car industry decision-makers craft solid, scalable, data-driven automotive technology. Learn more about what the future of these next-generation vehicles holds by downloading our connected vehicle whitepaper now!