When you reward a metric, people optimize the metric, not the goal it stood for — so the number rises while the real thing drifts. Goodhart's law: a measure that becomes a target stops being a good measure.
Goodhart's law: when a measure becomes a target, it stops being a good measure — people optimize the number instead of the thing it was meant to track.
A metric is a proxy — a stand-in for something you actually care about but can't measure directly. Test scores stand in for learning; call-handling time stands in for good support; lines of code stand in for productivity. The moment you reward the proxy, people optimize the proxy, and the proxy and the real goal quietly come apart.
Economist Charles Goodhart noticed this in monetary policy; the crisp version is 'when a measure becomes a target, it ceases to be a good measure.' Teach to the test and scores rise while learning doesn't. Reward call centers for short calls and agents hang up on people. Pay developers per line of code and you get bloated, padded code. The number goes up; the thing you wanted goes down — and people aren't cheating, they're doing exactly what you rewarded.
The fix isn't to stop measuring — you need metrics to navigate. It's to hold them loosely: use several so no single one can be gamed, pair every quantity with a quality check, watch for the goal and the proxy diverging, and remember the number was always a map, never the territory. The most dangerous metric is the one nobody questions because 'it's gone up.'
Almost every incentive, KPI, and goal you set is a proxy — and if you forget that, you'll get the number you asked for and lose the thing you actually wanted.
It's misread as 'metrics are useless, stop measuring.' Wrong — you can't steer blind. The point is that a metric is a proxy that decays the moment it becomes the goal, so you hold it loosely and use several, rather than worshipping one number.
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