Perverse Incentive
What it is
A perverse incentive is a reward, rule, metric, pressure, or design choice that encourages people to do something that works against the system’s intended purpose.
The system may be trying to create improvement, efficiency, compliance, growth, safety, quality, or accountability.
But the incentive teaches a behavior that undermines the outcome.
The phrase is often used broadly rather than tied to one single origin story. It is closely related to unintended consequences, incentive design, and economic thinking about how people respond to rewards and constraints. Its value for MNKY Math is less in where the phrase came from and more in the pattern it names: systems can make the wrong behavior make sense.
Sometimes the behavior is obviously harmful. Other times, it looks rational, productive, or even successful from inside the system.
In plain language: a perverse incentive is when the system rewards the behavior that makes the real problem worse.
Why it matters to MNKY Math
Perverse Incentive is a deep neighbor to MNKY Math because it names one of the structural mechanisms beneath many system failures.
It shows how systems do not merely ask people to behave.
They teach people what behavior is worth repeating.
A perverse incentive can turn good intent into bad system behavior.
It can make people chase the signal instead of the outcome. It can make a visible number improve while the actual condition degrades. It can make harmful behavior feel rational because the system has made that behavior count, pay, protect, or win.
This is especially important because perverse incentives often do not feel perverse to the people inside the system.
They may feel practical.
They may feel necessary.
They may feel like “just how the work gets done.”
The danger is that the system can produce the wrong behavior while everyone inside it believes they are responding correctly.
Where we overlap
Perverse Incentives and MNKY Math overlap around incentives, behavior, measurement, adaptation, and unintended outcomes.
Both are interested in questions like:
- What did the system actually reward?
- What behavior became easier, safer, faster, or more defensible?
- What outcome was the system trying to produce?
- What outcome did the system actually make more likely?
- What did participants learn to repeat?
- Where did the real cost move?
Perverse incentives are especially useful when examining bonus structures, productivity targets, compliance systems, loyalty programs, performance dashboards, school testing regimes, healthcare throughput, customer-service metrics, and any environment where people are rewarded for producing a visible sign of success.
Where MNKY Math differs
Perverse incentive is usually used to describe a misaligned reward: the incentive creates behavior that undermines the intended goal.
MNKY Math agrees with that framing, but extends the lens.
The question is not only: Was the incentive badly designed?
MNKY Math also asks:
What did the system make rational?
What behavior became easier to defend?
What signal replaced the intended outcome?
Who absorbed the hidden cost?
What did the system begin teaching people to repeat?
What outcome became more likely because the incentive existed?
A perverse incentive helps name the misalignment.
MNKY Math asks how that misalignment becomes behavior, culture, and outcome over time.
How it shows up
How it shows up
Perverse incentives can appear anywhere a system rewards a proxy, behavior, or visible signal that is not the same as the intended outcome.
- A sales team may be rewarded for activity volume and begin producing more calls, emails, or meetings without improving customer fit, trust, or revenue quality.
- A customer-service team may be rewarded for shorter handling times and begin moving faster while leaving customers less understood, less helped, or less resolved.
- A school may reward test-score improvement and unintentionally narrow learning toward what is easiest to test.
- A workplace may reward issue closure and teach teams to close tickets instead of solving root causes.
- A healthcare system may reward throughput and create pressure to move patients quickly while shifting hidden burdens onto staff, patients, or downstream care.
- A company may reward cost reduction and unintentionally push costs onto customers, employees, future maintenance, or another part of the system.
- A platform may reward engagement and teach creators to produce outrage, repetition, simplification, or emotional escalation rather than meaning, accuracy, or care.
In each case, the incentive may appear to be working.
The visible signal may move.
But the system may be learning to produce the sign of progress instead of the substance of progress.
MNKY Math lens
Perverse incentives help name the moment when a system rewards behavior that works against its own stated purpose.
MNKY Math extends the lens by asking:
- What was the system trying to produce?
- What did it actually reward?
- What behavior became rational inside the system?
- What proxy replaced the intended outcome?
- What tradeoff became hidden?
- Who or what absorbed the displaced cost?
- What did the system begin producing more of?
This is where incentive design becomes behavior design.
A system does not have to ask people to create the wrong outcome.
It only has to make the wrong behavior easier, safer, more rewarding, or more defensible than the right one.
Relationship map
Closest twin: Cobra Effect Both describe incentives that produce unintended harm, but the Cobra Effect emphasizes the backfire pattern where the attempted fix makes the original problem worse.
Clarifying contrast: Goodhart’s Law Goodhart’s Law focuses on measures becoming targets; perverse incentive focuses on rewards or pressures that make the wrong behavior worth doing.
Mostly shaped by: Incentives Incentives shape systems and behavior. A perverse incentive is a type of incentive that occurs when the system rewards, protects, or pressures behavior that works against the intended outcome.
Helps explain: System-shaped Behavior It shows how behavior that looks irrational from outside the system can become rational from inside the incentive structure.