The vehicle analytics market was valued at USD 1.74 billion in 2019 and is expected to reach a value of USD 6.34 billion by 2025 at a CAGR of 24.3 %, over the forecast period (2020 - 2025). Automobile sector and its stakeholders are being impacted and are evolving with transformed business ecosystem getting enabled by technologies, applications, and services through the adoption of various electronic items, such as sensors, artificial intelligence, and big data analysis.
- With vehicles nowadays generating volumes of data in moments, the opportunity to deliver exceptional customer experiences and business processes is becoming more significant than ever. For instance, Nissan has entered into a partnership with Tata Consultancy Services(TCS) in a move in which TCS would help Nissan with Vehicle Analytics System.
- owing to the rising adoption of predictive analytics, which has been a logical upgrade for the end users, who have adopted some means of automation and data collection solutions, the market is expected to grow.
- Innovative business models can be generated by blending vehicle telematics data and analytic insights with customer and business data. For instance, Goodyear Tire & Rubber Company, in March 2019, announced a new pilot program with Envoy Technologies, which is aimed at minimizing operational downtime for vehicle fleets.
- Envoy technologies, under this arrangement, is using Goodyear’s predictive tire servicing solution for its connected vehicle fleets to forecast and automatically schedule needed tire maintenance and replacement. With other complementing technologies, such as gesture recognition, Computer vision, AI, ML, and NLP being used in the automotive industry and its ecosystem has further snowballed the vehicle analytics opportunities. These have made driver performance analysis almost possible to use in real-time and take a decision based on the derived data insights.
- The rising demand for vehicle telematics is expected to drive the market for the forecast period. for instance, IBM's Watson IoT Platform Cloud Analytics can be used for Vehicle analytics. Watson IoT Platform Cloud Analytics helps in performing analytics on the real-time vehicle's data that is generated from IoT devices and gain diagnostics control.
Scope of the Report
Vehicle Analytics is a technology that allows the user or the manufacturer to gather real-time information about the current state of the vehicle, driving methods of the driver, etc. It also helps in vehicle counting, tracking, brand detection, speed detection, road condition inspection, and incorrect direction detection.
Key Market Trends
Predictive maintenance is Expected to Notice a Major Market Share in the Forecast Period
- As automakers are constantly assessing the performance of the vehicle part in real time through sensors, this unlocks the opportunity toward a predictive maintenance approach. For instance, on August 15, 2017, Trimble transportation introduced predictive maintenance analytics that helped them reduce fleet repair costs and increase vehicle uptime
- Using predictive maintenance, data can be pulled out from a majority of the vehicles of a given year and model, and that information can be compared with warranty repair trends. These trending issues are carefully observed and addressed, which limits the fallout from large-scale recalls, minimizing unnecessary wrench time, and potentially saving lives in the process.
- For instance, Foray Motor Group's TRACKER platform would provide information regarding time and distance traveled and fuel consumption, insurance renewals and servicing reminders and CO2 emission rates of the vehicle. It is also compatible with Google Maps which provide directions to all the nearby amenities.
- Goodyear built on its commercial solution based on the success tested in the predictive analytics test program with a city-to-city mobility service named Tesloop, which exclusively used Tesla electric vehicles for the study. The commercialization of Goodyear’s Proactive Solutions used for truck fleets tires maintenance and management make use of advanced telematics and predictive analytics technology. By maintaining optimum tire pressure, it helps the fleet operators to optimize fuel efficiency and precisely identify and resolve tire-related issues before they happen.
Asia-Pacific is Expected to Register Highest Market Growth in the Forecast Period
- The region is witnessing a growing dominance of connected and autonomous vehicles. Also, increasing penetration of new technology companies making ways into the automotive industry is expected to lead to a new era of automotive analytics. For instance, TPL Trakker on September 27, 2018, introduced Pakistan's first ever in-app vehicle analytics that provides data regarding fleet safety and productivity.
- China’s ambition to have at least 30 million autonomous vehicles within a decade (2018-2028) is expected to drive the demand for automobile analytics. The government has been very active in technology adoption to help policy implementation. It is expected that the country will emerge as the major user of Artificial Intelligence for surveillance over the next decade.
- Technology adoption and digital revolution in the region has made the market highly attractive for the vendors as the business volume has been rising. Apart from this, the government is expecting to build a manufacturing industry for parts, such as sensors and embedded chips with a production value exceeding CNY 100 billion, by 2020.
- However, Indian Transport Minister, in 2017, announced that the country would not allow driverless cars on its roads, owing to employment issues in the country. This is expected to act as a major challenge for the autonomous car market in the region and is expected to affect the sensors and equipment used for generating data for analytics in autonomous cars.
Owing to the presence of major players in the market, the competitive rivalry in the market is high. Some of the key players in the market are SAP SE, IBM Corporation, Microsoft Corporation, Harman International Industries, Inc. Inseego corporation and many more. Their ability to constantly innovate the products by investing heavily in R&D has allowed them to gain a competitive advantage over their competitors which has enabled them to gain major market share over others.
- July 2018 - SAP has launched Data Analytics Application For Connected Vehicles. It is based on the SAP HANA Cloud Platform. The application will collect, store, map and analyze real-time sensor data from vehicles and equipment.
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1.1 Scope of the Study
1.2 Study Deliverables
1.3 Study Assumptions
2 RESEARCH METHODOLOGY
2.1 Analysis Methodology
2.2 Research Phases
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Industry Attractiveness - Porter's Five Force 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 Introduction to Market Drivers and Restraints
4.4 Market Drivers
4.4.1 Growing Adoption Of Vehicle Telematics
4.4.2 Advancements in Technology like Artificial Intelligence and Predictive Analytics
4.5 Market Restraints
4.5.1 High Cost of Solutions to be Deployed
5 MARKET SEGMENTATION
5.1 By Deployment
5.2 By Application
5.2.1 Predictive Maintenence
5.2.2 Safety and security management
5.2.3 Driver Performance Analysis
5.2.4 Other Applications
5.3 By End-user Industry
5.3.1 Fleet Owners
5.3.3 OEMs and Service Providers
5.3.4 Other End-user Industries
5.4.1 North America
5.4.3 Asia Pacific
5.4.4 Latin America America
5.4.5 Middle East and Africa
6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 SAP SE
6.1.2 IBM Corporation
6.1.3 Microsoft Corporation
6.1.4 Samsung Electronics Co. Ltd. (HARMAN International)
6.1.6 Inquiron√ä Ltd
6.1.7 Intelligent Mechatronic Systems Inc.
6.1.8 Teletrac Navman US Ltd
6.1.9 Inseego Corporation
7 Investment Analysis
8 MARKET OPPORTUNITIES AND FUTURE TRENDS
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.
The market engineering phase involves analyzing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.
The market engineered data is verified and validated by a number of experts, both in-house and external.
REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.