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Strategic Analysis of the Impact of Big Data on the European and North American Automotive Industry

  • February 2014
  • 70 pages
  • Frost & Sullivan
Report ID: 2039414

Summary

Table of Contents

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 xx% of OEMs to establish their Big Data strategies and offerings 1 within the next xxyears.
- By 2020, approximately xx 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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