The thesis of my recent piece on the comparative advantages of open / closed ecosystems was as follows. Closed, centralized systems offer greater potential efficiencies, but open systems tend to lower error costs. This suggests that a closed system has greater potential, but that open systems are a safer choice in an environment of high uncertainty.
John Gruber’s recent critique of this piece fails to address the error-cost theory just advanced. Instead, he chooses to contest the idea that the choice of an open or closed ecosystem is relevant to determining the success of a product ecosystem. He advances a rival hypothesis: “better and earlier tend to beat worse and later,” which comes close to being a truism.
Gruber is right about this: no one factor can ever completely determine the success of a given product. A million decisions go into product design, and reducing everything to one or two big factors is hazardous. A badly built open product will never beat a good closed product, and vice-versa. But the interesting question is what happens when both are well-executed.
To deny the importance of a designer’s choice between a more open or closed system goes too far; saying that everything depends on timing and execution is to mistake tactics for strategy. Perhaps we can best interpret Gruber as asserting that the relative importance of the choice can be exaggerated, and that execution — avoiding errors — matters as well (which puts him in agreement with my original piece). He surely cannot be saying that the choice between open and closed doesn’t matter at all: that’s denialism.
The study of centralized and decentralized decision structures in an economic system is hardly my invention. It goes back to classic economic debates between Oskar R. Lange and Fredrick Hayek in the 1940s. Lange was an advocate of centralized planning and argued that closed / state-run economies would be more efficient than open / decentralized market economies. Hayek, responding in 1945, argued that the advantage of an open system was largely informational. A theoretically perfect central planner would, Hayek conceded, outperform an open system, but in a reality of imperfect information, the open market system could usually be expected to perform better. There’s been much economic thought on the issue since that time, but I’ll skip it: the bottom line is simply that open and closed systems perform differently under different conditions and have differently strengths and weaknesses. I should add that this kind of analysis is relevant for any system and any product ecosystem, not just tech — it is really the study of institutional design.
Fast forward to our present time and you can see the same open/closed dynamics that characterized the difference between planned and market economies reflected in tech markets. iOS resembles a partially-planned economy. It is a controlled ecosystem, which gives it certain advantages, but also greater rigidity and higher error costs. In contrast, Android has some central planning as well, but exercises less total control. Consequently Android is messier, but has certain advantages, like the ability to work on more devices. Execution matters as well, and Apple’s products may be executed better, but both firms and the underlying device makers are all competent. Android is ultimately “worse and later” in Gruber’s terminology, yet, in defiance of his rule, successful nonetheless. (Of course the final chapter on iOS v. Android isn’t written: Android has more market share, but Apple makes much more profit).
While I’m an iPhone user, I actually don’t care so much whether Google and Apple wins; Gruber appears to have a more personal stake. But the bottom line is that, as Michael Arrington points out, you really can’t pretend to understand what has happened over the last twenty years without some understanding of the relative advantages of open and closed systems (or if you prefer, decentralized and centralized decision hierarchies.) To maintain otherwise is an exercise in willful ignorance.