Big Data Market in the Automotive Industry - Growth, Trends, and Forecasts (2020 - 2025)

Big Data Market in the Automotive Industry - Growth, Trends, and Forecasts (2020 - 2025)

The big data market in the automotive industry is expected to grow at 14.4% CAGR during the forecast period of 20202025. The automotive industry is the one that faces significant competition and thrives for innovations in every aspect. The players operating in the market need to upgrade themselves to have a competitive edge over others. Big data and data analytics provide them with the opportunity to be a step ahead of competitors. Moreover, most of the automotive manufacturers are primarily driven by increased competition and data explosion. Complexity and scalability of disparate data pose a challenge for the traditional analytics and database technologies. Realtime processing of big data, using the cloud as an enabler, has become the norm. Disruptive technologies that underpin SMAC (social, mobile, analytics, and cloud) drive new business scenarios, making the best use of data.

According to an Accenture Plc’s recent study, 79% of business executives agree that companies that do not embrace big data will lose their competitive edge and face extinction. Furthermore, 83% have pursued big data projects to seize a competitive advantage.
For automotive manufacturers, actionable data represents an opportunity in terms of fast repair times, improved diagnostics, and easy service processes. A vendor can leverage knowledge gained from AI and machine learning to schedule preventive maintenance with conditionbased, hyperspecific maintenance. As a result, maintenance and repairs can be prepared based on the fuel utilization of the specific vehicles.
In a recent study conducted with the Volvo Group, enhanced processes were achieved by integrating predictive maintenance strategies. In the beginning, Volvo Group had plenty of data collected from vibration, pressure, and temperature sensors, as well as voltage and flow meters. But a lot of data does not make a cohesive plan, so the organization required actionable insights. By integrating the sensor collected data with the IBM SPSS modeler, Volvo Group was able to recognize patterns from the past and get insights for the future.
Increasing government initiatives for smart manufacturing is also creating opportunities for the big data market in the automotive industry. For instance, As per the 13th FiveYear Plan of Smart Manufacturing, China aims to establish its intelligent manufacturing system and complete the key industries’ transformation by 2025. As China’s manufacturing sector becomes more enhanced, big data can also support increased customization and niche manufacturing.
At this time of the COVID19 pandemic, the automotive sector is facing a significant downturn due to a disrupted supply chain. According to a recent study conducted by Accenture Plc, the car sales drop in February 2020 of more than 80% compared to January is a strong indicator of the direction the global automotive market is heading, and the impact is already visible. The forecasts for global lightvehicle sales in major regions predict that the market will observe a decrease by around 12% in 2020. Sales forecasts for the United States estimate a decline of 9% annually that customers are not buying new vehicles due to the pandemic.
AutoHome, an online car marketplace for Chinese automotive consumers, has been using big data solutions to analyze changes in customer behavior during the COVID19 pandemic to understand their requirements better. Also, through the creation of smart showrooms and virtual stores, AutoHome provides major functions of online car purchasing. This type of significant use case will drive market growth in the coming years.

Key Market Trends

Product Development, Supply Chain and Manufacturing Segment is Expected to Grow at a Significant Rate Over the Forecast Period

Big data allows the automotive manufacturing industry to collect data from the ERP systems to combine information from multiple functional units of the business and the supply chain members. With the emergence of industrial IoT, a networked system, M2M communication, the automotive industry is positioning itself towards industry 4.0 ready. Sensors, RFIDs, barcode readers, robots are now standard in the industry’s manufacturing floor. These devices have increased the data generation points exponentially.
For many developed countries like the UK, the implications with its automotive manufacturing base and significance as a major sales market for manufacturers are clear; connectedness to the clients and their cars can directly impact the supply chain. With more direct demand signs coming from the users, and the automobile themselves, agile market participants will increasingly be in a position to use big data to shape, build, and produce and become more proactive in managing customer expectations in the aftermarket.
Automotive manufacturer Daimler is digitally transforming its business, from vehicle design to core business systems, using the advanced data solutions through the cloud. In a recent project, Daimler replaced its procurement system, which is used to manage 400,000 global suppliers, with a data analytics solution running in Microsoft Azure. The new system, which involves the SAP Supplier Relationship Management on HANA, Icertis Contract Management platform, and the SAP S/4HANA database, was operational in just three months. The records can be updated daily to have a transparent view into the supply chain management, and costs incurred were 50% less than the previous system.

North America Geographic Segment is Expected to Hold a Significant Share Throughout the Forecast Period

The major driver for the North America geographic segment’s growth is the significant presence of technology providers. These players focus on entering into partnerships, mergeracquisitions, and innovative solutions offerings to stay in the regional and globally competitive landscape.
FleetPride, North America’s one of the significant distributors of trailer and truck parts in the heavyduty aftermarket channel, is transforming its supply chain management with the help of IBM Decision Optimization solutions. The solution helps FleetPride to work out optimal warehouse locations, minimize delivery time across its distribution network. This results in reduced labor costs and higher ROI.
Car selling platforms are also using big databased solutions to stay competitive in the global landscape. For example, New Yorkbased online car selling platform Vroom ingests millions of data points from significant corners of the automotive industry every day. It uses the data to analyze market dynamics at scale. The company can also use the insights for making decisions on selling cars, or on vehicle acquisitions. Vroom has also used its collected data to create an automated pricing tool, with which it offers realtime insights to consumers on its app and website.

Competitive Landscape

The big data market in the automotive industry is moderately competitive and consists of a significant number of global and regional players. These players account for a considerable share in the market and focus on expanding their customer base. These vendors focus on the research and development activities, strategic partnerships, and other organic & inorganic growth strategies to earn a competitive edge over the forecast period.

In March 2020, GAC R&D center and ThunderSoft, a Chinese OS technology provider, announced the launch of an innovation center focusing on intelligent vehicle data and software technologies. GAC has its incar smart ecosystem at the core, designed to build platforms of autonomous driving, cloud platforms, and big data. The newly built innovation center will boost the speed of datadriven automotive solution innovations in the future.
In February 2020, IBM Corporation and, an enterprise AI software provider, announced a global strategic partnership to drive the growth of artificial intelligencebased data solutions across all potential industries globally. already has the automotive giant 3M as its client, and with the help of this alliance with IBM, the company will have the chance to avail more customers from the automotive industry.

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1.1 Study Assumptions
1.2 Scope of the Study
4.1 Market Overview
4.2 Industry Attractiveness - Porter's Five Forces Analysis
4.2.1 Threat of New Entrants
4.2.2 Bargaining Power of Buyers/Consumers
4.2.3 Bargaining Power of Suppliers
4.2.4 Threat of Substitute Products
4.2.5 Intensity of Competitive Rivalry
4.3 Major Categories of Data that Represent Most Value
4.3.1 Diagnostics
4.3.2 Location
4.3.3 User Experience
4.3.4 Advanced Driver Assistance System (ADAS) & Other Data for Autonomy of the Vehicle
5.1 Market Drivers
5.1.1 Increasing Efforts from Various Stakeholders in Utilizing the Vehicle Generated Data
5.1.2 Growing Installed-base of Connected Cars
5.2 Market Challenges
5.2.1 Privacy Issues and Regulations on Vehicle Data Protection
6.1 Application
6.1.1 Product Development, Supply Chain and Manufacturing
6.1.2 OEM Warranty & Aftersales/Dealers
6.1.3 Connected Vehicle & Intelligent Transportation
6.1.4 Sales, Marketing and Others
6.2 Geography
6.2.1 North America
6.2.2 Europe
6.2.3 Asia Pacific
6.2.4 Rest of The World
7.1 Key Vendor Profiles*
7.1.1 N-iX LTD
7.1.2 Future Processing Sp.z.o.o.
7.1.3 Reply S.p.A (Data Reply)
7.1.4 Phocas Ltd
7.1.5 iSoftStone
7.1.6 Mayato GmbH
7.1.7 Qburst Technologies Private Limited
7.1.8 Monixo
7.1.9 Traffilog Ltd.
7.1.10 Driver Design Studio Limited
7.1.11 Sight Machine Inc.
7.1.12 SAS Institute Inc.
7.1.13 IBM Corporation
7.1.14 SAP SE
7.1.15 Microsoft Corporation
7.1.16 Amazon Web Services Inc.
7.1.17 Teradata Corporation

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