When More is Not Better, the new book by Roger L. Martin, will be published on September 29th by Harvard Business Review Press (Pre-order). Roger is professor emeritus at the Rotman School of Management at the University of Toronto and was formally the school’s Dean. In 2017 he was also named the world’s leading management thinker by Thinkers50. He has written 11 previous books and is a strategy advisor to the CEOs of Procter & Gamble, Lego, and Ford.
Overcoming an Obsession with Economic Efficiency
The new book is focused on “overcoming America’s Obsession with Economic Efficiency”. He notes, “our obsession with economic efficiency has featured too much pressure, too much connectedness , and too much pursuit of perfection, all of which has produced a dangerously unbalanced economy lacking resilience”. He points to the fact, “our dominant model of the economy is that of a machine” and suggests the blame for that can be directed to economics generally, and to Professor Wassily Leontief, a former Nobel Prize for Economics winner, and a former professor of economics at Harvard Business School from 1931–75.
Leontief left his mark on Harvard, where Martin himself started studying economics just two months after Leontief’s departure. Martin says he graduated in 1979 thinking he knew how the US economy worked, but soon learned that he had been taught only one model of economics and it was wrong. He admits he was “naïve to the power of models to shape action and the power of metaphors to drive the adoption of models”. He believed the models he was taught were descriptions of how the economy actually works, not how they might work. His professors “oversold the veracity of their model”, and that still irks him to this day.
All Models Are Wrong
Martin notes that he later learned about the “foibles of models” from John Sterman, MIT professor in systems-dynamics who pointed out “all models are wrong” in an article with that title. But Martin also notes we cannot operate without models, whether we realise it or not, and most of the time we do not. Models simplify the complexity of the real world to help us make decisions and take actions.
Martin goes on to note that we use analogies and metaphors to help us make sense of the new. “We select our metaphors, and afterwards, our metaphors shape us”. They do so because different metaphor drive adoption of different models that produce very different outcomes, says Martin.
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