I worked for Tesla for 5 years, joining with a cohort a few months before Model S launch in 2012 and departing recently to take a rest. My role involved architecting, developing, and helping support many software systems focused in the financial domain. These systems process all of the downstream events arising from sales, procurement, production, and other activities of the company with financial effect.
Many often wonder why large software system projects are difficult. Many often wonder why running large organizations such as governments is difficult. In this topic some wonder why large scale vehicle manufacturing processes are difficult. These fundamentally share properties.
One key challenge is that system, organization, and process complexity do not grow in a linear manner. If you have ever tried to estimate software development time for larger projects you understand how wildly inaccurate it can be. The number of interaction points multiply with growth. Progress feels extremely fast at the beginning. As the system surface area grows it becomes increasing difficult to push incremental improvements forward. A single person or small team comprehensively understanding the entire system and keeping enough of it in working memory becomes a challenge. There are design and management strategies to combat the challenge but in my opinion only time and iteration can truly overcome.
The single most important long-term factor here is whether quality and continuing improvement is part of the culture or not. I believe they are, as suggested by the production target miss. A process of prioritizing and then fixing sub-optimal system and process interaction points, both internally and externally, will drive the company to high output while maintaining quality over time. TPS [0] concepts are well known but one doesn't simply download and install it in an afternoon. It can take decades to optimize.
The single worst decision the company could make is to pump out vehicles to meet a production target metric while sacrificing quality. That has been tried before in this country (and at the same factory several decades ago no less [1]) and did not work out well.
For perspective: Competitive threats are just not a very big deal. Globally, 72 million cars were produced last year [2]. If Tesla captures just 1% of that market it is still a huge achievement - 720k cars per year. Even if we assume they sell only the lowest price Model 3 at $35k and ignore all other vehicle and energy products that would equate to over $25 billion in revenue - 10 times the 2016 annual figure. The market will also grow as the global economy does. There is plenty of room.
Many often wonder why large software system projects are difficult. Many often wonder why running large organizations such as governments is difficult. In this topic some wonder why large scale vehicle manufacturing processes are difficult. These fundamentally share properties.
One key challenge is that system, organization, and process complexity do not grow in a linear manner. If you have ever tried to estimate software development time for larger projects you understand how wildly inaccurate it can be. The number of interaction points multiply with growth. Progress feels extremely fast at the beginning. As the system surface area grows it becomes increasing difficult to push incremental improvements forward. A single person or small team comprehensively understanding the entire system and keeping enough of it in working memory becomes a challenge. There are design and management strategies to combat the challenge but in my opinion only time and iteration can truly overcome.
The single most important long-term factor here is whether quality and continuing improvement is part of the culture or not. I believe they are, as suggested by the production target miss. A process of prioritizing and then fixing sub-optimal system and process interaction points, both internally and externally, will drive the company to high output while maintaining quality over time. TPS [0] concepts are well known but one doesn't simply download and install it in an afternoon. It can take decades to optimize.
The single worst decision the company could make is to pump out vehicles to meet a production target metric while sacrificing quality. That has been tried before in this country (and at the same factory several decades ago no less [1]) and did not work out well.
For perspective: Competitive threats are just not a very big deal. Globally, 72 million cars were produced last year [2]. If Tesla captures just 1% of that market it is still a huge achievement - 720k cars per year. Even if we assume they sell only the lowest price Model 3 at $35k and ignore all other vehicle and energy products that would equate to over $25 billion in revenue - 10 times the 2016 annual figure. The market will also grow as the global economy does. There is plenty of room.
[0] https://en.wikipedia.org/wiki/Toyota_Production_System [1] https://en.wikipedia.org/wiki/NUMMI#Background [2] https://www.statista.com/statistics/262747/worldwide-automob...