In 1975, British economist Charles Goodhart wrote a paper on monetary policy titled, Problems of Monetary Management: the U.K. experience. In said paper, he wrote,
"Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes."
Put more simply, Goodhart's law states that once a measure becomes a target, it ceases to be a good measure.
In March of last year, I started uploading weekly to YouTube. My only goal at the time was to upload one video/week on any topic, with any depth, at any length– that was my target. Other measures in doing this were subscriber count, click-through rates, average watch time, and other infinite amounts of statistics Youtuber's can drown themselves in.
If I apply Goodhart's law to this situation, subscriber count is a good measure to track. It shows my videos resonate with people, and they want to watch more of what I have to say. But as soon as my target becomes a subscriber count, that ceases to be a good measure because I'll do anything I can to increase that number. In the words of UCLA professor of Law and Communication, Mario Biagioli,
All metrics of scientific evaluation are bound to be abused. Goodhart's law [...] states that when a feature of the economy is picked as an indicator of the economy, then it inexorably ceases to function as that indicator because people start to game it.
Data is always going to be an important part of making decisions. However, you have to be careful about what data you use as measurements and what you use as pure insights.
Anything can be presented in a way that looks better than it actually is.