Application of Data Analytics in Automobile Manufacturing-- Evidence from Existing Literature

Abstract

 The auto manufacturing industry is one of the most dynamic business industries and is extremely competitive. Since auto manufacturing is technology-intensive as well as competition-intensive, making data-based decisions has become an important part of the industry to make the right business strategies to achieve competitive advantage. Across the auto manufacturing process, human resources, function sales and marketing, product design, and support services use data analytics to extract useful insights from the immense amount of data on customers, employees, and market trends. However, the use of new technologies in the automotive industry is still not addressed in the automotive industry-based research works of literature. Analysis of the old and growing analytics techniques, this article proposes that applications of more advanced analytics, such as reinforced learning, deep learning, and cognitive learning, will play an important role in the future of the automotive industry to make driverless cars a reality.