Big Data Strategies Expected to Lead to Explicit Annual Savings up to $800 per VehicleKey FindingsThe shift toward Big Data strategies is taking place because of the need to reduce spiraling warranty costs and to create a data sharing network between the dealer, customer, and OEMs.- Frost & Sullivan expects'% of OEMs to establish their Big Data strategies and offerings 1 within the next 'years. - By 2020, approximately ' million vehicles in North America and Europe will make relevant data sets available for OEMs to assimilate and convert them into actionable insights. - Big Data will bring about differentiation based on varied metrics, such as brand awareness, digital engagement of customers, response time, and vehicle configurability satisfaction. - Post-2015/2016, the industry will witness the foray of integrated service providers with expertise in providing end-to-end services across the automotive value chain, i.e., from consulting to implementation. Key Societal, Technological, and Other Challenges for Big Data Implementation - Big Data: Relevant and prioritized information Which data you process and which data you do not process - Shortage of skill sets for data analytics and data governance : Data scientists- Data privacy issues on the types of data being shared : Government limitations and driver concerns - Understanding the customer from the Web (car versus lifestyle preferences) : Customer analytics and CRM - The need for improved data quality : High data transfer cost per vehicle for downloading information- Who is benefitting from the ecosystem' Monetizing data and sharing value among ecosystem partners Savings Achieved Using Big DataSignificant savings expected across the entire value chain, from OEMs to end users' Reduction in warranty costs ' Reduction in product development costs ' Reduction in recall related expenses ' Increased aftersales revenues' High quality of LBS services ' Increase in subscription revenue ' Increase in connected services uptake rate' Reduction in infrastructure development cost ' Smart parking and other public use cases ' Reduction in congestion using Big Data

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Strategic Analysis of the Impact of Big Data on the European and
North American Automotive Industry
Published on February 2014
Report Summary
Big Data Strategies Expected to Lead to Explicit Annual Savings up to $800 per Vehicle
Key Findings
The shift toward Big Data strategies is taking place because of the need to reduce spiraling warranty costs and to create a data
sharing network between the dealer, customer, and OEMs.
- Frost & Sullivan expects'% of OEMs to establish their Big Data strategies and offerings 1 within the next 'years.
- By 2020, approximately ' million vehicles in North America and Europe will make relevant data sets available for OEMs to assimilate
and convert them into actionable insights.
- Big Data will bring about differentiation based on varied metrics, such as brand awareness, digital engagement of customers,
response time, and vehicle configurability satisfaction.
- Post-2015/2016, the industry will witness the foray of integrated service providers with expertise in providing end-to-end services
across the automotive value chain, i.e., from consulting to implementation.
Key Societal, Technological, and Other Challenges for Big Data Implementation
- Big Data: Relevant and prioritized information Which data you process and which data you do not process
- Shortage of skill sets for data analytics and data governance : Data scientists
- Data privacy issues on the types of data being shared : Government limitations and driver concerns
- Understanding the customer from the Web (car versus lifestyle preferences) : Customer analytics and CRM
- The need for improved data quality : High data transfer cost per vehicle for downloading information
- Who is benefitting from the ecosystem' Monetizing data and sharing value among ecosystem partners
Savings Achieved Using Big Data
Significant savings expected across the entire value chain, from OEMs to end users
' Reduction in warranty costs
' Reduction in product development costs
' Reduction in recall related expenses
' Increased aftersales revenues
' High quality of LBS services
' Increase in subscription revenue
' Increase in connected services uptake rate
' Reduction in infrastructure development cost
' Smart parking and other public use cases
' Reduction in congestion using Big Data
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Table of Content
Executive Summary
Research Scope, Objectives, Background, and Methodology
An Overview of Big Data Basics'North America and Europe
Big Data for the Automotive Industry
Automotive Big Data Market Analysis
Key Opportunities in the Auto World Using Big Data and Related Case Studies
Additional Big Data Success Case Studies
Key Conclusions and Future Outlook
Appendix
The Hot Topics Covered and Upcoming
List of Studies'Past, In-progress, and Planned for 2014
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