by James Bessen The New Goliaths is one of my books of the year so far (with a trendy chatterbox subtitle). Indeed, I was waiting for it impatiently because I liked its previous one, Learning by doing, so many. Based on his impressive research into technology for several years and his previous experience as the founder of a successful digital start-up, the heart of the argument is that a small number of (usually) large companies have builds computer systems that can handle the immense complexity of their operations. Sophisticated software and massive streams of data allow them to coordinate in ways previously unimaginable, delegating decisions to where the information can go. Complexity – say of a new car model loaded with software or a large retailer’s logistics system – increases the cost of entry for potential competitors. The Goliaths are not only found in “Big Tech”, but in many sectors of the economy.
What’s more, “the investment in software is only part of the total investment in these systems. All of the technology investment companies make in these proprietary systems goes well beyond software code to include data, workforce skills, and investments in alternative organizational structures. An example used throughout the book is Walmart – which McKinsey says accounted for a substantial part of the productivity increase of the 1990s in the United States. Somewhat counterintuitively, at least to those who view Big Tech as the main competitive issue, Bessen sees Walmart as the unassailable incumbent in US retail, while Amazon is the only entry example. successful and provides a platform for other retailers.
This dynamic of superstar companies in many sectors, from retail to automotive to finance, with a growing productivity advantage, has consequences for income inequality: workers in these companies are better paid because they gain invaluable experience simply by working in superstar companies, so salaries are dispersed within sectors. Skills are rare because you have to work for a large complex and sophisticated company to acquire the skills, which are therefore rare. This has led to less momentum – fewer entries and exits in many markets. Small companies simply cannot match the R&D expenditures of large companies: one example given is speech recognition software, where pioneer Nuance was a huge commercial success, but still could not match the expenditures of large companies: Amazon has (still) over 10,000 engineers working on Alexa products, more than ten times the number Nuance had at its peak. “Proprietary information technologies exacerbate economic and social visions. It widens the gaps between the wages of workers in different companies. This leads to greater segregation of skill groups between companies and cities.
The dynamics of complexity also have implications for competition policy – which becomes difficult, because after all superstars generally offer excellent services – and regulation more broadly – because the information asymmetry between the firm and the regulator keeps growing.
So what to do? The book advocates for mandating open standards, more compulsory licensing and for reform of intellectual property law to incentivize large companies to unbundle their services more voluntarily, cracking down on workers’ non-competition agreements to distribute skills. All excellent policies, and ultimately inevitable, because inequalities are socially and politically unsustainable. But there’s a lot of devil in the details, and there will be massive lobbying against change. It is therefore a political struggle rather than a technocratic one.
But that’s wandering into the future. I highly recommend The New Goliaths. It synthesizes a growing body of research on how companies use technology, how it interacts with organizational structures and markets, and what the consequences are. It is also very well written, with many examples and a thorough understanding of the realities and limitations of technology policy.
