Why Information Grows: The Evolution of Order, from Atoms to Economies
Source: https://www.basicbooks.com/titles/cesar-hidalgo/why-information-grows/9780465048991/ ↗
Hidalgo, a physicist working at the MIT Media Lab, proposes that economic development is fundamentally the accumulation of information embodied in physical products and the networks of people who know how to make them.
He calls this "economic complexity" and measures it by analysing which countries export which products, revealing that the structure of an economy's knowledge network predicts its growth better than traditional macroeconomic indicators.
The argument connects thermodynamics (why information is rare in the universe), biology (how organisms accumulate information), and economics (why some countries are rich and others are not) into a single framework.
Hidalgo draws on the work of Schrödinger, Prigogine, and Romer but goes further by making the information-economy connection empirically measurable.
The book bridges the Brynjolfsson digital-economy axis and the Castells network-society axis in a genuinely new way, grounded in physics rather than sociology.
Central argument
Hidalgo argues that economic growth is driven not by capital or labor in the abstract, but by the accumulation of 'economic complexity' — information embedded in physical products and in the tacit knowledge networks of the people who produce them. Drawing on thermodynamics and information theory, he frames economies as systems that locally reverse entropy by encoding know-how into matter, and demonstrates empirically that a country's position in the global product-export network predicts its future growth more accurately than conventional macroeconomic indicators like GDP or institutional quality. The central finding is that wealth is crystallized knowledge, and the bottleneck to prosperity is the capacity of human networks — not individuals — to hold and recombine that knowledge.
Critique
The framework's empirical power rests on product export data, which captures embodied knowledge in manufactured goods reasonably well but struggles with services, software, and platform economies — precisely the sectors driving growth in the 21st century. A country or firm that exports algorithms, financial instruments, or digital platforms may be extraordinarily knowledge-dense yet invisible to Hidalgo's complexity metrics, which means the model may systematically misread where economic sophistication is actually accumulating today. This is not a flaw in the underlying theory, but it creates a significant gap between the book's explanatory ambition and its measurability when applied to dematerialized production.
Why it matters for product
Hidalgo's insight that productive knowledge is always distributed across networks of people — never fully held by any single person — has direct implications for how a CPO should think about team structure and organizational capability: the question is not whether you have talented individuals, but whether your organizational topology allows knowledge to combine and recombine across them. For product strategy, the complexity framework reframes the build-versus-buy decision: capabilities you build in-house are nodes in your knowledge network that compound over time, while outsourced capabilities remain economically thin no matter how efficient. It also offers a lens for discovery — the products and features a team can actually build with excellence are constrained by the adjacency space of what it already knows, which means capability audits are as strategically important as market opportunity assessments.