Manufacturing is changing, and so is productivity

Two excellent articles on increasing productivity, and why this will not result in many new jobs:

Davison describes the new kind of manufacturing, where everything is done by multi-step, highly complex machines, producing small series, requiring very high-skilled workers with rather sophisticated education. But they also need unskilled workers doing simple things, like moving parts between machines. The problem is, the pay scale for the second type is very low, and the difference in training to get to the skilled level so high, that no company will provide it:

For Maddie to achieve her dreams—to own her own home, to take her family on vacation to the coast, to have enough saved up so her children can go to college—she’d need to become one of the advanced Level 2s. A decade ago, a smart, hard-working Level 1 might have persuaded management to provide on-the-job training in Level-2 skills. But these days, the gap between a Level 1 and a 2 is so wide that it doesn’t make financial sense for Standard to spend years training someone who might not be able to pick up the skills or might take that training to a competing factory.

It feels cruel to point out all the Level-2 concepts Maddie doesn’t know, although Maddie is quite open about these shortcomings. She doesn’t know the computer-programming language that runs the machines she operates; in fact, she was surprised to learn they are run by a specialized computer language. She doesn’t know trigonometry or calculus, and she’s never studied the properties of cutting tools or metals. She doesn’t know how to maintain a tolerance of 0.25 microns, or what tolerance means in this context, or what a micron is.

The reason Maddie – hardworking and dedicated – has a job is simply one of distance: Shipping fragile parts to China for the unskilled operations is too risky and expensive. So Maddie has a job, but not career prospects. And the company’s management is facing very hard competition – their customers see them as a distributor – and is constantly scanning for things that can be outsourced or bought from another vendor.

Mandel describes the differences in productivity increases from improving productivity in domestic production – doing things smarter – and lowering cost by bargaining and optimizing the supply chain before it reaches the domestic organization. Both show up as productivity improvements, but have vastly different effects on domestic jobs:

But here’s the rub: both of these corporate strategies— domestic productivity improvements and global supply chain management—show up as productivity gains in U.S. economic records. When federal statisticians calculate the nation’s economic output, what they are actually measuring is domestic “value added”—the dollar value of all sales minus the dollar value of all imports. “Productivity” is then calculated by dividing the quantity of value added by the number of American workers. American workers, however, often have little to do with the gains in productivity attributed to them. For instance, if Company A saves $250,000 simply by switching from a Japanese sprocket supplier to a much cheaper Chinese sprocket supplier, that change shows up as an increase in American productivity—just as if the company had saved $250,000 by making its warehouse operation in Chicago more efficient.

This is known as import bias, and may be a problem, as it overestimates domestic productivity increases. Mandel goes on to show that this bias affect both left and right, and the difference in views is largely one about how to effectuate a change: Stimulus or tax relief.

Both authors advocate better data and better education as a way out, but quick fixes they aren’t. This is a real puzzler.

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