Monetizing car data

Cars generate data about how they are used, where they are, and who is behind the wheel. With greater proliferation of shared mobility, progress in powertrain electrification, car autonomy, and vehicle connectivity, the amount of data from vehicles will grow exponentially, raising a key question: How might industry players in the evolving automotive ecosystem turn car-generated data into valuable products and services?

Through a comprehensive course of research – comprised of surveys, interviews, and observations – McKinsey analyzed consumer perspectives on the prospect of accessing car-generated data, identifying and assessing the value and requirements of possible car data-enabled use cases.

The overall revenue pool from car data monetization at a global scale might add up to USD 450 - 750 billion by 2030. The opportunity for industry players hinges on their ability to 1) quickly build and test car data-driven products and services focused on appealing customer propositions and 2) develop new business models built on technological innovation, advanced capabilities, and partnerships that push the current boundaries of the automotive industry. Customer value proposition.

The car data monetization opportunity begins with an environment in which customers believe that there is something of value in it for them and that the cost is worth the benefit. The survey revealed that, in general, customers are interested in data-enabled features that make mobility safer or more convenient and save them time or money. Across geographies, nearly two-thirds of consumers saw the various car data use cases as personally relevant, and more than three-fourths deemed them useful. Certain use cases rely on driving-related or systems data (route, vehicle usage, etc.), while others require users to share more personal data, such as the content of personal communications.

Customers are more reluctant to share the latter type of data, but 60 percent of them are willing to do so when the feature is safety or convenience related. Younger customers appear to be significantly more open to the adoption of data-enabled features and services in cars than customers over 50 years of age, and frequent travelers (those spending more than 20 hours per week in the car) are almost twice as likely to adopt them than occasional drivers. Use cases and business models.

Through roundtables, interviews, customer clinics, and problem solving with industry leaders, we identified more than 30 separate use cases that could generate value for end customers and industry players, ranging from predictive maintenance to over-the-air software add-ons and from vehicle usage scoring to usagebased insurance. Each use case has the potential to create value in one of three main ways: revenue generation, cost reduction, or safety and security enhancement. Multiple direct monetization options exist; features and services can be charged to end customers – by rolling their cost into the vehicle price, selling them as a one-time purchase after initial vehicle sale, or offering them via subscription or rechargeable credit – or provided free of charge when customers agree to receiving advertising as part of the deal.

Customer willingness to pay for features – as opposed to a preference for free, ad-supported features – varies across use cases and geographies. For example, 73 percent of consumers globally are willing to pay for predictive maintenance services, but the spread ranges from 78 percent in China to 71 percent of consumers in the USA. When it comes to connected navigation services, the global average for customer willingness to pay drops to 43 percent, mainly driven by the availability of credible, free alternatives already established on the market. As a consequence, industry players must pragmatically develop and tailor their offerings to each specific use case and to the local preferences. In this landscape, it is critical for industry players to clearly define their strategic stance vis-à-vis a set of control points, i.e., critical technologies to capture value from the use cases. Across a number of existing control points, accessing the car data gateway, shaping the human-machine interface (HMI), and matching customer ID with data strings will be of central importance for industry players.

Enablers

The monetization of car data requires a set of enablers across three broad categories: in-car technology enablers include sensors, high-performance computing, in-car HMI, car OS, connectivity, data storage, and location/navigation hardware. Infrastructural technologies outside of the vehicle to enable car data monetization include 4G/5G data towers, big data analytics, cloud computing, software platforms, high-definition maps/highresolution positioning, smart-road infrastructure, and V2X communications. Back-end processes facilitate the analysis and sharing of car data and ensure the functioning and security of the whole ecosystem. Among others, these enabling players are regulators, infrastructure operators, content providers, cybersecurity players, and data center operators.

Capabilities and partnerships

For incumbents like auto OEMs or tier-1 suppliers, building and operating service businesses is a new and significant challenge, requiring the development of specific capabilities either internally (e.g., hiring, developing, and retaining digital talent) or externally, partnering or acquiring digital-native players. From a capabilities angle, the starting point for incumbents to enter the car data monetization arena is to step up their data management capabilities in terms of:
ƒ Data preparation collection, cleansing and formatting from a multitude of relevant sources (e.g., the car, OEM Web site, social media, dealer management system)
ƒ Data analysis that applies “big data/advanced analytics” techniques to extract valuable insights from this wide and complex data landscape
ƒ Data usage and value delivery, deploying features, products, services, and recommendations to final customers and/or to business partners in order to capture the opportunity and continuously refine their offerings. Pushing beyond the basics, making services, R&D, factories, and channels “digital ready” – especially for traditional automotive organizations – is likely to require a fundamental shift from current ways of working that may be less conducive to the digital innovation required to succeed in car data monetization.

Industry executives concur that organizational complexity and lack of specific digital skills fundamentally hinder OEMs’ ability to innovate at the rate of nimbler high-tech players and start-ups. Digital innovation for large OEMs might entail the establishment of a “digital accelerator” unit that is
1) independent enough to inspire creativity,
2) agile enough to quickly develop (or kill) innovations as a “venture capitalist” would, and
3) linked closely enough to the business to ensure that innovation translates into value for the broader company at scale.

Looking outside of the organization, technology, market, and regulatory trends will make strategic collaboration increasingly necessary.

Players in the car data monetization space will be naturally forced to partner with multiple entities (e.g., high-tech suppliers, their own customers, public institutions) to access specific capabilities and to reduce development costs. Openness and agility in creating partnerships on R&D and sales channels development will be required to succeed. Looking ahead. High-tech companies, start-ups, alternative mobility operators, data management services, insurers, roadside assistance providers, and infrastructure operators will all be players in the car data monetization landscape. It is the most traditional of automotive players, however, who may find staking a claim most challenging. OEMs and suppliers are accustomed to seven-year product cycles, full control over a stable value chain, consolidated monetization models, and few interactions with end customers. They are also used to delivering products and services with limited digital capabilities.

Car data monetization will challenge all of these current realities and compel incumbents to quickly make pragmatic changes to their approaches. In order to succeed, industry players can start making their way now with some practical early steps:
ƒ Fix an initial car data monetization “ambition target” at CEO level and set the organization towards truly transformational change!
ƒ Prioritize the use case offerings most suited to the organization, and define a realistic estimate of the overall value pool and timing for market development!
ƒ Begin pragmatic piloting on a limited number of use cases and quickly collect customer feedback to adjust the course!
ƒ Lay robust IT foundations for the future, but do not be afraid to leverage IT work-arounds to test the use cases today!
ƒ Note the spaces where long-term capabilities need to be developed or integrated, and build an ecosystem of partners to deliver on the use cases!
ƒ Cultivate a cross-functional, cooperative dynamic that fosters innovation, and identify the best organizational setup to act as “technological accelerator” for the company going forward!

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