Abstract

The case discusses the automation strategy of Tesla, Inc (Tesla), the world’s largest Electric Vehicle (EV) maker. Tesla vigorously pursued automation solutions to develop high-performance environment-friendly cars that were not only sustainable, but also superior to fossil-fuel alternatives, delivering massive savings in energy costs, performance, efficiency, and reliability. In 2017, Elon Musk (Musk), CEO of Tesla, focused on hyper-automation, including a robotic assembly line, to increase manufacturing speed and drive down costs. Tesla’s Fremont manufacturing facility in California was heavily automated with hundreds of industrial robots being used for manufacturing, replacing many of the human workers employed there. However, the production ramp-up came with huge setbacks including massive cash burn, missed production targets, financial losses, and high employee turnover. Automation processes actually slowed down production as Tesla. Eventually, Musk admitted that his company had gone way overboard with automation and, ultimately, had to turn back to human assembly line workers to achieve the production targets of Model 3. Despite the setbacks, Musk stated in 2019 that automation would be key to the company’s future. Going forward, the biggest challenge for Musk would be how to reach an optimal level of automation in order to achieve efficiency in production processes and drive down costs.

Learning Objectives

The case is structured to achieve the following Learning Objectives:

• Understand the importance of automation in the auto industry as well as its benefits and limitations.
• Understand the link between business strategy and manufacturing strategy.
• Understand Tesla’s manufacturing strategy that relied on automation.
• Identify the problems Tesla faced due to hyper-automation and what solutions it came out with.
• Explore strategies that the company can adopt to employ an optimal level of automation in production processes.

Keywords

Automation; Hyper-automation; Robotic process automation; Artificial Intelligence; Machine learning; Manufacturing Strategy; Production Systems; Information Technology & Systems; Organizational Crisis; Strategic Change; Value Chain Analysis; Strategic capabilities; Collaborative Intelligence; electric vehicles