You don’t make your measures your targets.

Example:

“Our customers hate us. We will make our employees get a 10 on their surveys for each customer or we’ll punish them” makes the measure a target.

“Our customers hate us, so we’re going to change our shitty policies to be more consumer friendly and see how our customers respond” keeps the measure as a measure.

Ok I'm going to answer my own question because I'm too curious to wait lol

Goodhart’s Law states that “when a measure becomes a target, it ceases to be a good measure.” In other words, when we use a measure to reward performance, we provide an incentive to manipulate the measure in order to receive the reward. This can sometimes result in actions that actually reduce the effectiveness of the measured system while paradoxically improving the measurement of system performance. ... The manipulation of measures resulting from Goodhart’s Law is pervasive because direct measures of effectiveness (MOEs), which are more difficult to manipulate, are also more difficult to measure, and sometimes simply impossible to define and quantify. As a result, analysts must often settle for measures of performance (MOPs) that correlate to the desired effect of the MOE. ... These negative effects can sometimes be avoided. When they cannot, they can be identified, mitigated, and even reversed.

• Use MOEs instead of MOPs whenever practicable and possible
• Use the scientific method to generate new measurement data, rather than harvesting existing and possibly compromised data
• Help customers establish authoritative and difficult-to-manipulate definitions for measures
• Identify and avoid the use of manipulated data and data prone to manipulation
• Use measurement data not generated by the organization being measured
• Collect data secretly or after a measurable activity has already occurred
• Measure all relevant system characteristics rather than just a representative few
• Randomize the measures used over time
• Wargame or red team potential measures

This report recommends that the organizations that employ analysts should do the following:

• Return to the roots of operational research to focus more on direct measurements in the field
• Answer the questions that should be answered, rather than the questions that can be answered simply because the required data are already available
• Train analysts on MOEs, MOPs, and Goodhart’s Law and how they are interrelated
• Make recognition of Goodhart’s Law part of the internal peer review process and part of all delivered analytical products
• Identify and share mitigation best practices

[Source]