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Baker provides excellent background on formative theories in management, particularly the sexist and racist views and writings of some of modern management theory's progenitors. Unfortunately, most of the rest of this book consists nearly entirely of analysis by vibes - quantitative data is nonexistent, and most claims that are held up as untrue aren't refuted with any sort of analysis. According to Baker, it's bad management practice to insist that McDonald's franchisees work in a restaurant first (wut), and quality of life got worse for a large percentage of people after WW2 (nearly every shred of research says the exact opposite).

Beyond that, Baker conflates entrepreneurship - starting your own company - with work/management in large organizations. To be fair this is rife throughout the popular discourse, as Baker rightly points out. But as a consequence, this book never actually examines the kind of entrepreneurship involved in starting your own company, except for ones that eventually become extremely large. Restaurants? Other small businesses? Nowhere to be found.

This book ends up being a missed opportunity, and one that is hopefully followed up with a more thoroughly researched sequel.

Coyle absolutely knocks it out of the park in this expanded follow up to her can't miss book on the history of the GDP metric. Here she more fully interrogates how we currently measure GDP, its gaps, recent trends in constituent metrics, and how to improve societal welfare metrics more broadly. Starting with the concerning declining productivity growth trend since ~1980 in pretty much every developed economy, Coyle methodically works through different explanations of that trend from mismeasurement of new innovations, problems with measuring improvements in products, movement of production outside of firms, declining actual innovation, and more, with implications for how we measure GDP and regulate firms. Personally I think the contribution of the basket neoliberal policies is the flashing red light in all of this, and Coyle does somewhat consider this but partially dismisses it with less focus than I'd like. That, however, is a minor quibble in what is an essential book - there are even multiple sections on the inherent subjective nature of metrics and algorithmic bias, and the entire book contains copious citations! Highly recommend