Definition
Goodhart's law is an economics principle: the moment a measurement becomes a "target" for management or evaluation, people change their behavior, and the measure loses the very value it was meant to track. British economist Charles Goodhart put forward the idea in 1975 while analyzing monetary policy. The short version people quote today ("When a measure becomes a target, it ceases to be a good measure") was polished in 1997 by anthropologist Marilyn Strathern.
The strange thing that happens in a call center
Say a company wants its customer service reps to be friendlier and more efficient. It makes "cut average call time to under 3 minutes" the key goal. The original idea was to reduce customers' pointless waiting and raise satisfaction.
But the plan backfired. When a complicated, hard question came in, reps stopped explaining kindly and started hanging up fast. The call-time statistic looked dazzling, yet customer complaints actually exploded. The real goal, customer satisfaction, vanished, and all that was left was hitting the number that was being measured.
This is how people work. When a number is tied to reviews and rewards, they change their behavior to hit it in the easiest way possible. Along the way, the true purpose behind it falls apart.
A bit more precisely: the dilemma of economic policy
The idea began with Charles Goodhart, an adviser at the Bank of England, who pointed out the limits of monetary policy. At the time, British monetary authorities wanted to keep prices stable. So they made the total amount of money in circulation (a money supply measure) their management target.
When the authorities pushed down a particular money supply measure, financial markets came up with new products and ways of trading to get around the rules. The number they were watching looked under control. But it no longer showed what was happening in the economy the way it used to. Once the measure became a control target, the old statistical link between the measure and reality broke.
People aren't fools. When the rules of a policy change, they react in their own interest. That's why policy targets built only on past data are easy to miss.
Why does fixating on numbers cause side effects?
To manage a complicated reality, we often pick simple numbers as measures. We gauge a student's learning by test scores, and a researcher's ability by the number of papers published. Watching things through numbers is not a problem in itself.
Trouble starts the moment rewards like promotions, bonuses, or punishments get attached to the number. If researchers are judged by paper count, some will stop digging deep into one excellent study. Instead, they'll slice their work into many small papers. Only the packaging grows, not the substance. This is a flip between means and ends.
So to beat Goodhart's law, don't cling to a single measure. Look at the real value hidden behind the numbers too, and keep your way of evaluating flexible.
Common misconceptions
Goodhart's law means that measures and statistics are useless.
Measures themselves aren't bad. The problem comes when a measure becomes the "target of evaluation and control" and rewards are tied to it, so people twist their behavior. Plain statistics used to observe what's going on are still very useful.
Where you meet it
If firefighters are judged only on how fast they get out the door, they might leave without checking their safety gear, which makes the scene more dangerous.
If a software developer is judged by "lines of code written," they may end up writing code that is needlessly long and complicated.
In one sentence
When a measure becomes the target for rewards and control, people's shortcuts and strategic behavior make it lose its original value.