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Test the one question that matters
Strategy in fast markets
In a settled market like payments, grand strategy pays off, because the pieces can be understood and the next moves predicted from first principles. A market that is emergent, fast-changing, and tied to research rewards the prolific and empirical over the academic and theoretical. A long reasoning doc, almost a PhD thesis on the plan for the next stretch of time, gives way to something users can try.
The eigen question
What remains is the core hypothesis, the eigen question: the one most important thing to test. Any other grand strategy is irrelevant. That has always been the job of product management: find the question that decides whether the product works, test it, read the results, and feed them back into a sharper hypothesis built from users, the market, and the technology.
Everyone tests now
Now engineering managers, engineers, data scientists, and designers have all moved their effort to this loop of defining the problem and testing it, while many of the other trappings of the job have fallen away.
Why does strategy fail in fast markets?
Helmuth von Moltke, the nineteenth-century Prussian army chief of staff, is paraphrased as saying no plan survives first contact with the enemy. Eric Ries made a version of this argument for startups in his 2011 book The Lean Startup. He proposed a build, measure, learn loop in which each release exists to test one assumption about customers. The approach drew on lean manufacturing at Toyota.
Why does a testable hypothesis speed up learning?
Philosopher Karl Popper argued in his 1934 book The Logic of Scientific Discovery that a claim is only useful if some observation could prove it wrong. A narrow, falsifiable question tells a team exactly which result would change its plan. A broad strategy can absorb almost any result without changing. Popper first published the book in German under the title Logik der Forschung.
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