Economies of Scope: Additive Manufacturing’s Trajectory Toward Bigness

Additive manufacturing (AM) enables new options in part geometry, including internal complex passages and topology-optimized forms. We’ve covered this. We have also covered the way AM is making possible new options in materials.

Now, it is time to begin considering how AM will change the shape of manufacturing organizations, a theme of our recent coverage. Articles we’ve posted describe a regional association, supplier collaboration and a new business model all built around AM. In each of these cases, people are organizing themselves in a new or different way to better advance or leverage additive.

Could it be that these various groups and companies are all onto something?

Dartmouth College business professor Richard D’Aveni, in his new book, The Pan-Industrial Revolution, takes a long view on additive manufacturing to speculate on the very different type of manufacturing company likely to result from the maturing of this technology. His central insight: Additive manufacturing wants to be big. That is, AM’s use will favor bigger and bigger manufacturers—albeit big in a way we have not seen before. Whereas manufacturers in the past thrived on economies of scale (redundant parts, high volumes) additive manufacturers will thrive on something different: economies of scope. By using their AM resources to serve an ever-broader mix of industries, additive manufacturers will become big by means of this breadth. In fact, D’Aveni argues they’ll become huge.

Why does additive favor bigness, and bigness by breadth? Here are some of the reasons I find most compelling:

1. Lack of dedicated resources. Traditional manufacturers tend to serve certain industry sectors because they have equipment or knowledge suited to that sector—types of machinery, expertise or tooling acquired for the work in that field. AM is not characterized by this kind of dedication. Two sets of parts for two very different industries can be made on the same machine and maybe even in the same build.

2. Consolidation of operations. Another obstacle to serving various industries is that the supply chains tend to be different. But because of the way AM generates a nearly complete, complex part that might consolidate what used to require different organizations for casting, machining and assembly, the length and impact of supply chains is significantly reduced. As a result, with additive, there is far less bureaucracy cost for serving many sectors.

3. Material savings. An AM operation able to get dramatically bigger would get more cost-effective as a result, because of the advantage it could command in material pricing. For this reason, D’Aveni sees manufacturers coming to specialize by material rather than by industry. Imagine a company with a dispersed array of plants full of additive machines that all run the same metal alloy. For work requiring this specific metal, this firm’s buying power could give it a raw material cost lower than that of any competitor.

4. Machine learning. Another powerful effect: Big scope equals big data. We have covered the way AM is distinctively poised to benefit from the application of machine learning. In a company marshaling more additive machines to serve more industries, machine learning algorithms aimed at making processes more efficient will have more data to work with and therefore will be more effective at improving efficiency. Bigness will produce better artificial intelligence for directing the company’s processes.

D’Aveni’s book goes farther than this, speculating on the nature of a world where production is dominated by massive pan-industrial additive manufacturing titans. We are still far from that world. But I am struck by the tiny trajectory already noticeable in the articles in this issue. While the stories are different, the solution in each case is roughly the same: The way to advance AM is to gather together.