The Corner

A U.S. Manufacturing Strategy, Part 2

This continues from the prior post, which argued that the U.S. government ought to care a whole lot about absolute and relative American productivity growth.

Proposition 2: Not all kinds of productivity growth are created equal

I’ll illustrate two different kinds of productivity growth with practical examples from my experience in the manufacturing industry. I once invented a new production planning algorithm (essentially, the decision rules for which products to make when, and in what sequence) that improved the output of a specific factory by about 5 percent. This is pure gravy: the same people show up at the same factory and work the same number of hours, the same raw materials are purchased and so on, but the world just gets 5 per cent more widgets out of the other end. This is normally the kind of thing most people picture when they use the term “productivity growth” in normal speech. On another occasion, I figured out the financing that made it profitable to shut down an entire factory, and sell the land to a property developer. This is normally the kind of thing that most people mean in normal speech by “the locusts of private equity.” I’ll call the first example an improvement in “operational efficiency” and the second example an improvement in “allocative efficiency.” In fact, both are necessary for ongoing improvements in productivity and wealth for an advanced economy.

Let me describe the decisions around these kinds of changes from the point of view of a business owner or executive. In somewhat simplified terms, if I’m doing stuff that earns returns below my cost of capital, or if I can get someone else to do it for me at lower cost than I’m doing it, it makes sense to cut out the activity. These cut activities will tend to be those with lower productivity. Cutting activities for shareholder value reasons will therefore strongly tend to cut low-productivity activities, and increase my firm’s average productivity through pure “high-grading.” But this ignores at least a couple of important questions. First, did I fail to uncover economically achievable improvements in operational efficiency that would have allowed me to conduct these activities at higher returns and cheaper than alternatives? Second, are the cut activities linked in some non-obvious way, and potentially only over time, to the other more profitable activities, such that I have fooled myself into putting the profitable parts of the business at risk?

A business culture that ignores these questions can tend to get into a death spiral of endless high-grading against an ever-rising tide of competition that eats the business one bite at a time. The fear of many critics of American business (or “Anglo-Saxon financial capitalism”) has for a long time been that this is what is happening to the American economy on a grand scale.

And further, at the level of the entire society, while a firm can get more productive by high-grading, if the alternative employment for the people who used to work at the closed factory is collecting unemployment checks, can’t this become a society with an ever-shrinking base of people with high-paying jobs? This is the nightmare scenario of an ever shrinking number wealthy financiers, who are increasingly detached from a broader society all around them living off a combination of table scraps and handouts.

There is something to this fear. But on the other hand, the failure to allocate capital and labor from kinds of activities where there are inherent limitations to how productive they can be to those where they have greater inherent productivity will also hurt productivity growth in the long run.

The key word in that sentence is “inherent.” The more we can take what is currently viewed as inherent productivity by analysts, economists and others, and improve it by unanticipated innovations, the more we can have allocative efficiency without giving up as many manufacturing jobs.

Think of operational efficiency as getting better at playing a given game, and allocative efficiency as deciding what games to play. We need both. We want to have an economic regime such that the people working a specific line in a given plant work as hard and as smart as possible to get that line to be as productive as possible; such that the management of that plant is allocating resources among the production lines, and thinking hard about the overall production process such that they make that plant as productive as possible; such that the company is doing the same thing at a yet-higher level for its collection of factories, warehouses and sales offices; and such that the economy as a whole is allocating resources across firms intelligently.

In fact, when we move from the level of the individual firm to the economy as a whole, the nature of the process of resource allocation should change. If, following Coase, we very crudely define the boundaries of the firm as the maximum extent of activity for which central planning can work effectively, then we need to use markets to allocate resources across firms. The unique virtue of markets is not so much in their allocative efficiency, as in what Douglas North termed their “adaptive efficiency”: basically, discovering entirely new ways of organizing resources. If allocative efficiency is deciding what game to play, adaptive efficiency is inventing entirely new games. Adaptive efficiency is not nearly as important for an economy in catch-up mode, but for an advanced economy, it is essential for productivity growth.

We can think of a hierarchy of kinds of productivity growth, with operational efficiency at the foundation, then allocative efficiency next, and finally adaptive efficiency as the master-allocator of resources. We then need to think about manufacturing strategy in the context of the need for the combination of operational efficiency, allocative efficiency and adaptive efficiency that will create rapid, continuing productivity growth in the economy as a whole. In effect, adaptive efficiency – which, all else equal, is likely to continue to squeeze out manufacturing jobs – needs to be the evolutionary principle by which the economy creates productivity growth, but efforts to improve operational efficiency within manufacturing will change the set of “givens” (for example., the relative profitability of in-sourcing versus outsourcing) that this evolutionary process will confront.

The next post in this series will try to sketch out some ideas for what I think is most likely to help do this.

Jim Manzi is CEO of Applied Predictive Technologies (APT), an applied artificial intelligence software company.


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