Importance Of Data In The Automotive Industry

Importance Of Data In The Automotive Industry

Technology June 2020 Importance Data Automotive Industry

Clichéd as it may sound, data is the new oil and new currency, since the variety of information gained can be utilised in improving various aspects of the automotive sector, and driving mobility experience to new heights.


Terms like Big Data and Data Analytics are commonplace during present times when a large amount of information can be collected, examined, reviewed and processed for enhanced results. When a product is under development, various teams work on its different aspects. The data generated from the design or engineering team could potentially be of high value for decisions being made by the other during the product development phase. The exchange of such information during early stages of development could enable the identification of flaws and errors, thereby enabling them to take corrective actions. The earlier an error is detected, the quicker product development takes place along with lower cost incurred.

Data is not only helpful during the product development stage, but also provides the manufacturing section with much-needed details on the optimum requirements for lean and efficient production. Data regarding the design of the component or product being manufactured along with the structural and physical requirements can provide intricate details about the tools or dyes to be used, as well as the manufacturing process to be adopted during production. Data that helps improve production efficiency is becoming more and more substantial in manufacturing as a whole, especially in automotive, due to the highly cost-conscious nature of these businesses.


In addition to data on components, products and vehicles, data is equally critical during the entire vehicle life, when it is plying on the road. Seat settings, steering & mirrors adjustments, riding or driving style, usage of accelerator, brakes, clutch and other parts can describe the type of driver – whether timid or aggressive. Such information, in turn, can be used to determine the wear & tear of components and the expected remaining life.

This information on the life of the components is subsequently received by OEM’s service centre, which can be used to alert the driver of the potential servicing requirement for their vehicle. This advanced information also helps the service centre to keep a component ready, or order for it if it is not in stock, consequently ensuring a seamless product replacement process, when the vehicle comes in for its repair or scheduled servicing.

In addition, repeated actions by the driver and occupants help the vehicle use this as behavioural traits to enable similar offerings automatically. For example, data in driving mode most preferred by the driver, which is different from the options offered by the car as standard can be stored under the individual’s own mode, which offers inputs to the engine, transmission, steering and suspension accordingly.

All the above uses of data lead to its ultimate responsibility, which is in collecting information about the vehicle’s surroundings and environment, so as to be able to address requirements of active safety. Advanced driver assistance systems (ADAS) collect data through various sensors in the vehicle using cameras, radar and Lidar, and enable the vehicle to automatically respond to the environment in order to avoid any incidents with other vehicles, pedestrians and infrastructure. These active safety systems along with vehicle connectivity are enabling lower levels of vehicle autonomy (L1-L3), which will eventually lead to fully-autonomous, self-driving vehicles for on-road and off-road applications.


There is a high level of potential in various companies to monetise data that is available from vehicles, once on the road. According to McKinsey, the overall global source of revenue from monetisation of car data may reach $ 450-750 bn by 2030. There is an opportunity for industry players to quickly build and test car data-driven products and services focussed on appealing customer propositions as well as to develop new business models built on technological innovations, advanced capabilities, and partnerships.

The process of generating revenues through vehicle data can be categorised into three areas – (i) direct monetisation by selling products, features, or services to the customer; (ii) tailored advertising, where car data can be used to push individual offerings to customers; and (iii) selling data, wherein Big Data is collected, analysed and resold to third parties. While the third category is self-explanatory, use cases under the first two categories include over-the-air software updates, usage-based tolling, tracking/theft protection, fleet management, remote car performance configuration, connected navigation and predictive maintenance.

Insurance providers could use and monetise data to provide Usage-Based Insurance (UBI), and roadside assistance providers could collect & process distress calls in real-time from vehicle sensors and automated alerts. This can enable them to optimise the dispatching of rescue vehicles. The IT and engineering service providers also stand to earn heavily from vehicle data, since they provide solutions for data analysis, in addition to developing front-end applications. These high-tech giants offer OEMs and component suppliers with solutions that can process collected data into useful information for end-customers. Retailers and vehicle dealerships can use analytics to optimise their sales network and get out messages about services & offerings directly to vehicle owners.


Vehicle data has its own set of offerings, and plays out as a lucrative segment of the automotive industry. But who owns the data? This question on ownership of data as well as the liabilities arising out of ownership of different kinds of data, is probably as old as data collection and analysis itself.

There is no single answer to this question that provides ultimate clarity on the ownership of various types and levels of data. A number of functional safety technology developers as well as standards-setting bodies are trying to categorise data into varying levels of criticality, and then designating probable ownership for the same. However, it is largely understood that data ownership cannot be held completely by OEMs, but will have to trickle down to component manufacturers, their suppliers as well to engineering service providers that assisted with design and development of the final vehicle.

Regulators and government bodies are setting standards regarding the collection and sharing of car data. These agencies are also fixing mandates for vehicle data-enabled services that support overall user benefits like e-call, while regulating controversial topics including technical certification of connected vehicles, data ownership and intellectual property rights over shared technologies.


Data, in any form is a method of understanding a product or component better, and can be used for improving any vehicle or related service. However, securing such data also becomes a matter of priority since this same data can be utilised to perform criminal activities that could result in incidents that could eventually cause causalities on the road. Therefore, adequate protection of data that can be used for improving products or services as well as to monetise from will ensure it maintains its status as the ‘new oil.’

(Inputs from McKinsey, Deutsche Telekom, Archer Soft Consulting)

TEXT: Naveen Arul