The automobile industry has been riding the wave of digitization along with many other sectors. Changing customer expectations and the evolution of data analytics in the automotive industry are causing disruption.
Over the last decade, the automotive sector has witnessed a sea change, disrupting the conventional ecosystem of automotive manufacturers. In the years since Karl Benz invented the first car in 1886, the industry has become obsessed with creating the 'car of imagination. In fact, the 'car of imagination' is slowly taking shape, and it will be smarter than any imagination ever has been. In the future, cars will be increasingly intelligent and connected like never before. In other words, automakers will use data analytics in order to allow cars to communicate, collaborate, and navigate without human intervention, resulting in vast amounts of data. Within the next few years, cars will produce 25GB of data an hour. Ultimately, this pool of data will power disruptive technologies, opening up multiple possibilities for the players along the value chain. Do you think the automotive industry is ready to capitalize on these opportunities?
Data analytics in the automotive industry: enabling disruptive technologies
Automobiles equipped with advanced technology are likely to become the poster child of the technological revolution. As a result of these developments, existing prototypes will be reinvented, the ecosystem will be altered, and customer satisfaction will improve. Through the transformation journey, profit pools will shift, and economic value will be permanently altered.
Connectivity and mobility
The automotive industry is now embracing connectivity, which was once considered science fiction. A car is equipped with sensors that can monitor everything including miles driven, location, routes, brake wear, and tire pressure. Availability of connectivity and mobility is enabling new applications that will provide the automotive industry with unrivaled value. In other words, connected cars have gone green.
Data analytics is igniting the connected vehicle era.
Connected vehicles also provide localized information on everything from petrol stations to retail stores. Automotive companies will eventually use regional data to create personalized offerings based on client preferences. Predictive and prescriptive analytics give relevant data that can be turned into next-best-action offers for a more tailored consumer experience. This type of strategy is assisting the sector in increasing client involvement and acceptability. Furthermore, the automotive sector must prioritize and rapidly resolve vehicle faults in order to ensure quality and reliability. Automobile manufacturers, for example, are using warranty analytics to identify impending faults, lowering warranty costs and preserving brand equity.
Smartest Moves in the Automotive Industry: Data Analytics
General Motors has created OnStar, a full-fledged connection mesh that is a marvel of vehicle data analytics. GM has over 12 million linked vehicles on the road right now. The company is gathering information in order to improve its vehicle infrastructure. For example, GM's Verizon telematics has assisted auto owners in tracking stolen vehicles and remotely unlocking their vehicles using their smartphones. However, based on our observations, the corporation will be able to generate new revenue streams by allowing independent developers to trade information in its database.
Autonomous driving
Every day, autonomous vehicles, with their enormous potential, make headlines in the automotive industry. The next generation of self-driving cars has the potential to dramatically alter the industry's dynamics. Consumers will no longer understand the significance of learning to drive. However, how does the industry intend to keep drivers and passengers entertained while they sit idle in a driverless car? In fact, all stakeholders in the automotive value chain will be busy analyzing data, while consumers will be content to sit back and enjoy the possibilities revealed by assistive technologies. Meanwhile, the industry is experimenting with data analytics techniques in order to provide consumers with an intuitive, unforgettable experience.
The stakeholders in the autonomous driving value chain may benefit from the following opportunities:
OEMs are expanding their primary businesses.
OEMs can better understand customers by studying data in addition to selling infotainment and navigation services. As a result, automakers will be able to predict and determine consumer maintenance preferences, closing the gap between service dealers and customers. OEMs might use advanced analytics to fuel real-time remote booking of car check-ups, for example. Automotive suppliers, on the other hand, can create platforms to collect and analyze consumer data in order to provide OEMs with effective product and service portfolio improvement recommendations.
Infrastructure companies are capitalizing on opportunities.
Providers of roadside help can better assess autonomous driving data and process crisis calls in order to deliver rescue personnel more quickly. Furthermore, these roadside assistance robots can evaluate auto breakdown data and provide OEMs with useful information. Infrastructure operators, such as toll operators, battery recharging dealers, and refueling stations, can use autonomous driving data to plan the geographic distribution of services and track consumer preferences to create variable-pricing structures. In order to profit on data with usage-based insurance contracts and occasion-related policies, insurers will partner with roadside assistance.
Creating a new ecosystem by expanding the value chain
Deep tech behemoths and OTT providers are also well positioned to work with OEMs and advertising to provide relevant content to essential autonomous driving data. To speed up the data creation process, tech titans may develop in-car platforms and operating systems. OEMs and suppliers may, for example, use voice-activated virtual assistants in their infotainment systems to encourage customers to submit larger chunks of data. Furthermore, VR and AR developers might create applications that include gesture-activated controls, allowing for novel revenue models. Retailers, on the other hand, might use consumer data to optimize their distribution network. If shops receive extensive data information, they may use drones to deliver merchandise to the precise position of self-driving automobiles. Based on customer choices, OTT apps might deliver highly personalized marketing to drivers' handheld devices and infotainment systems.
Smartest Moves in the Automotive Industry: Data Analytics
Daimler, the producer of Mercedes-Benz vehicles, has teamed with Uber to provide self-driving cars for ride-hailing services. General Motors is also working on self-driving cars, leveraging its in-house automotive manufacturing capabilities. Cruise Automation's expertise in robotics and artificial intelligence is being used to build and construct automobiles that can make rational judgments. "Today, new technologies and evolving consumer expectations are assisting us in transforming personal mobility and delivering new transportation solutions that are safer, more sustainable, and better than ever," said Mary Barra, Chairman, and CEO of General Motors.
"We believe one of the greatest ways to achieve these answers is through expanded access to self-driving electric vehicles deployed in sharing networks," she said at the Orion Assembly factory event. In addition, the business intends to roll out autonomous technology to clients in ridesharing fleets across the United States.
Conclusion
RFID, or radio-frequency identification tags, proximity, and heat sensors are used to track the products and machinery of modern vehicle manufacturers. Based on the examples above, it is clear that harnessing data from the automotive industry's supply chain is critical for unlocking benefits such as greater profits, reduced downtime risks, and a lean supply chain. Good automotive analytics technology can help you achieve a long-term competitive edge.