Experts say Tesla has repeated car industry mistakes from the 1980s

Production had been halted for much of last week in Tesla's car factory in Fremont, California, and its battery factory near Clark, Nevada. In a Tuesday note to employees, CEO Elon Musk said that the pause was necessary to lay the groundwork for higher production levels in the coming weeks. Musk said he wants all parts of the company ready to prepare 6,000 Model 3 cars per week by the end of June, triple the rate Tesla has achieved in the recent weeks.

The announcement caps a nine-month period of turmoil that Musk has described as "production hell" as Tesla has struggled to ramp up production of the Model 3.

Tesla had high hopes for its Model 3 production efforts. In 2016, Musk hired Audi executive Peter Hochholdinger to plan the manufacturing process, and Business Insider described his plans in late 2016: "Hochholdinger's view is that robots could be a much bigger factor in auto production than they are currently, largely because many components are designed to be assembled by humans, not machines."

A year later, Musk himself was touting Tesla's advanced robotics expertise. "We are pushing robots to the limit in terms of the speed that they can operate at, and asking our suppliers to make robots go way faster, and they are shocked because nobody has ever asked them that question," Musk said on a conference call last November. "It’s like if you can see the robot move, it’s too slow.”

Musk now admits he was wrong about this. "Excessive automation at Tesla was a mistake," Musk tweeted recently. "To be precise, my mistake. Humans are underrated."

"We had this crazy, complex network of conveyor belts," Musk told CBS News. "And it was not working, so we got rid of that whole thing."

Musk is discovering that large-scale car manufacturing is really hard, and it's not easy to improve on the methods of conventional automakers. And while automation obviously plays an important role in car manufacturing, it's not the magic bullet Musk imagined a couple of years ago. Far from leapfrogging the techniques of conventional automakers, Tesla is now struggling just to match the efficiency of its more established rivals.

And most of the auto industry experts we talked to thought Musk still had a lot to learn.

"A lot of the mistakes we're hearing about are mistakes that were made in the rest of the industry in the 1980s and the 1990s," says Sam Abuelsamid, an industry analyst at Navigant Research. He points to the experience of General Motors, which wasted billions of dollars in a largely fruitless effort to automate car production in the 1980s.

At the same time, it's rarely a good idea to underestimate Musk. Musk has a long history of setting optimistic deadlines for his companies and then failing to meet them. But Musk is persistent and a quick learner. He has made a lot of mistakes so far, but he may still have time to learn from those mistakes and turn Tesla into a competitive carmaker.

The same mistake
Roger Smith, CEO of General Motors in the 1980s.
Enlarge / Roger Smith, CEO of General Motors in the 1980s.
Shepard Sherbell/CORBIS SABA/Corbis via Getty Images
In reporting this story, we talked to two different experts who drew the same parallel to GM's automation efforts in the 1980s. At the time, GM was being led by chairman and CEO Roger Smith and faced rising competition from Toyota and other foreign carmakers. Smith had a vision for a "lights out" car factory where robots would do the bulk of the work, allowing GM to produce cars more efficiently than anyone else.

In their 1994 book Comeback, Paul Ingrassia and Joseph White (Author) described the results of Smith's automation project at GM's plant in Hamtramck, Michigan:

As Hamtramck's assembly line tried to gain speed, the computer-guided dolly wandered off course. The spray-painting robots began spraying each other instead of the cars, causing GM to truck the cars across town to a fifty-seven-year-old Cadillac plant for repainting. When a massive computer-controlled 'robogate' welding machine smashed a car body, or a welding machine stopped dead, the entire Hamtramck line would stop. Workers could do nothing but stand around and wait while managers called in the robot contractor's technicians.

Over the course of the 1980s, GM spent billions of dollars on advanced robotics, but it never saw a return on that investment.

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"Instead of easing robots onto the line a few at a time, providing for inevitable debugging problems with redundant equipment, GM bet the entire Hamtramck production system on the proposition that leading-edge automation would work instantaneously."

Three decades later, robots are more sophisticated. But the same basic insight applies: automation works best when it's added incrementally to a production process that's already working smoothly. And Musk seems to have made the same mistake Smith did: bringing in way too many robots, way too quickly, leaving little time for testing and refining the process.

Robots are supposed to allow production of more cars with fewer workers, but one ironic consequence of over-automation is that it can actually require more workers. Ingrassia and White report that GM's Hamtramck plant had around 5,000 workers on its payroll in the mid-1980s, compared to 3,700 workers at a nearby Ford plant with many fewer robots. Yet the Ford plant was "outproducing Hamtramck by a wide margin."

Today, Tesla is having the same frustrating experience. Tesla is manufacturing its cars at a plant in Fremont, California, that was formerly a famous GM/Toyota joint factory called NUMMI. According to Automotive News, NUMMI had 2,470 employees in 1985, its first year in operation, and produced 64,764 cars. By 1997, it had 4,844 workers and produced 357,809 vehicles.

By contrast, Automotive news estimates that Tesla has somewhere between 6,000 and 10,000 workers in 2016 (the San Jose Mercury News said it was "about 10,000" last year) and manufactured just 83,922 vehicles. That means Tesla's plant in 2016 was less than half as productive, on a per-worker basis, as it was during the first year of GM management—and less than one fifth as productive as it was during NUMMI's heyday in the 1990s.

"The number of people Musk's got in there has a great deal to do with why he doesn't make money building vehicles," automotive manufacturing consultant Michael Tracy told Automotive News last year.

To be fair, Tesla is known for being more vertically integrated than competitors. So some of those extra workers may be doing work that would have been performed by suppliers in the NUMMI plant.

And Tesla says it's making progress. "The number of labor hours needed to complete a vehicle has decreased 33 percent since early 2016," Tesla's Laurie Shelby wrote in a February blog post.

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Applying Silicon Valley culture to carmaking didn't work
Tesla CEO Elon Musk in 2015.
Enlarge / Tesla CEO Elon Musk in 2015.
ODD ANDERSEN/AFP/Getty Images
Building cars at scale is one of the most complex and capital-intensive manufacturing tasks in the world. To cope with these challenges, carmakers tend to have a highly regimented process for designing and building cars.

Car designs are worked out years in advance, and companies do extensive testing—both of car prototypes and of manufacturing equipment—before launching the main assembly line for a new car model. Employees are expected to scrupulously follow policies and procedures to avoid disrupting the plans of their colleagues.

This runs directly counter to the ethos of Silicon Valley. Because software is so easy to modify and distribute to customers, the software industry tends to value creativity and rapid iteration. Musk, who earned his early millions in the software industry, naturally tried to bring this same agile approach to the car business.

"Everything about Tesla is supposed to be fast, the car, the development process, the launch process," said John Shook, an auto industry veteran who got his start at NUMMI, in a recent podcast. Shook summarized Tesla's approach as "let's start to build the thing before we've actually finished designing it. Because what we're building even for cash-paying customers is actually betas."

"The idea is we can go fast by leaving out steps, and we'll just iterate our way to something really good. But what we can see is that actually creates a lot of problems."

This kind of rapid iteration works well in the software industry because a programmer can change one line of code and then re-build the entire project with the click of a button. But physical manufacturing isn't like that. Car design decisions have to be translated into physical tooling that takes months to build and fine-tune.

And rapid iteration is a nightmare for suppliers, Shook added.

"I talked to a supplier and asked 'who's your worst customer'" Shook said. "The answer was Tesla. How can you be a good supplier when you don't know when you're supposed to deliver?"

"I was giving a talk at a tooling group," said David Cole, an analyst at the Center for Automotive Research. Veteran toolmakers there told Cole that most automakers do prototype tooling when they're designing a vehicle. "They make some vehicles so they can test them and find out if the tooling is good. They said that that was standard procedure at every auto company except for Tesla."

At Tesla, he said, "they take their prototype into production."

"I think what we're seeing is a lack of basic manufacturing experience," Cole added.

Don't count Tesla out yet
Tesla's Model X SUV.
Enlarge / Tesla's Model X SUV.
Of course, the obvious response to this is that if Musk had listened to the experts, he probably wouldn't have started Tesla in the first place. Conventional wisdom in the mid-2000s was not very bullish about the prospects for battery electric cars. And there was widespread skepticism that it was even possible to start a new, independent automaker. After all, no American company had managed to break into the car business in many decades.

Musk ignored the conventional wisdom, and he has gotten much further than anyone expected. He has sold hundreds of thousands of cars and has hundreds of thousands more people eager to buy the Model 3 as soon as it's available. Moreover, Tesla has had a huge influence on the broader car industry, forcing every major carmaker to take battery electric vehicles seriously.

It's clearly true that Tesla's frenetic pace of experimentation is not the most efficient way to produce cars in the short run. However, it might be the best way to learn the lessons Tesla needs to learn to produce cars more efficiently in the long run. Tesla hasn't produced very many Model 3 cars over the last nine months, but Musk and his team have learned a lot about how to produce cars efficiently—lessons they'll be able to carry with them in future manufacturing projects.

Musk likely could have spared himself a lot of short-term headaches if he had relied more heavily on auto industry veterans to warn him against repeating mistakes made by other car companies in previous decades. But if he had done that, he would also be less likely to discover ways to optimize the manufacturing process—particularly optimizations that work particularly well for a company specializing entirely in electric vehicles.

The big question, however, is whether Musk will be able to apply the lessons of the last nine months in a disciplined way in the future. Whatever the value of experimentation in the early months of Model 3 production, Tesla is going to have to run its manufacturing efforts more like a conventional automaker in the long run if it wants to produce cars with competitive prices and quality. That won't be easy.

At the same time, Tesla has unique strengths. It has unrivaled expertise in batteries and software. It has an intensely loyal fan base. And it has Musk himself, one of the world's most talented marketers. All of which means that—like Apple—Tesla may be insulated from the intense margin pressures most other carmakers face. A lot of people may be willing to pay a premium to say they drive a Tesla, which means that the company may be able to turn a profit even if its manufacturing process isn't quite as efficient as its more established rivals.

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