Goodhart's Law: How Wells Fargo's Best Metric Went Wrong

October 3, 2026 Updated: October 20, 2026 · By Taylor Yang · #mental models #decision-making

Wells Fargo hit its cross-selling goal with millions of accounts customers may never have authorized. Here is how Goodhart's law works, and how to avoid it.

A three-step flow: set a target, optimize the measure, then check the outcome.

By 2016, Wells Fargo was famous for cross-selling. Its customers held about six of the bank’s products, roughly double the average at other large banks, and the internal goal was eight per household: “Eight is great” (Nova SBE case study).

On September 8, 2016, regulators revealed what had been feeding the number. Employees had opened roughly 1.5 million deposit accounts and applied for about 565,000 credit cards that customers may never have authorized (CFPB, 2016).

Goodhart’s law says that when a measure becomes a target, it stops being a good measure. Once people are rewarded for moving a number, they find ways to move it that leave the underlying goal behind. The number keeps improving while the thing it was meant to track gets worse.

Wells Fargo paid $185 million in penalties, and about 5,300 employees were fired over several years for these practices. The metric had looked healthy the entire time.

The cross-sell number rose while customer value fell

Products per household was a reasonable signal at first. Customers who use several of a bank’s products tend to be more engaged. Then the bank attached sales goals and incentive pay to it, and the signal broke.

What the cross-sell number showedWhat was actually happening
Products per householdClimbing toward eightMany accounts unwanted, or unknown to the customer
Branch performanceTeams hitting sales goalsEmployees moving customers’ money to fund new accounts
Customer relationshipDeeper and more profitableSome customers charged overdraft and insufficient-funds fees

The regulator’s description is blunt. The practice “gave the employees credit for opening the new accounts, allowing them to earn additional compensation and to meet the bank’s sales goals.”

The idea is older than the scandal. In 1975 the economist Charles Goodhart, writing about British monetary policy, observed that “any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes” (Goodhart’s law). The shorter version most people quote came later, from the anthropologist Marilyn Strathern.

Fraud is the dramatic version. Most Goodhart failures are quieter.

Gaming is only one way a target breaks a measure

People can damage a measure while working honestly. Here are the common routes:

Ask who gains from each way of moving the number. Following the incentives usually reveals which route people will take.

Goodhart’s law and the cobra effect answer different questions

The two ideas overlap, and they often appear in the same story.

QuestionGoodhart’s lawCobra effect
Main concernA targeted measure stops telling the truthAn incentive makes the original problem worse
In the Wells Fargo caseProducts per household stopped reflecting real relationshipsSales pressure created new harm: unwanted accounts and fees
What needs checkingHow the proxy relates to the goal under pressureThe chain from incentive to behavior to harm

Not every broken proxy creates a cobra effect. A number can drift away from the goal while the goal stays where it was. The cobra effect guide covers incentives that backfire. A well-known field study, A Fine Is a Price, shows how a new penalty at Israeli daycare centers changed behavior in a direction nobody intended.

So how do you set a target without breaking the measure?

Six questions to ask before you attach a reward to a number

  1. State the goal separately from the number. Wells Fargo’s goal was presumably customers who benefit from more products. Products per household was only a stand-in.
  2. Explain why the number is informative. Write down the assumed link: engaged customers use more products.
  3. List ways to move the number without moving the goal. Unrequested accounts, products customers never use, and accounts opened and closed quickly.
  4. Choose an independent outcome check. Accounts the customer actually funded and used, complaints, and customers who stay.
  5. Define a review trigger. For example, a jump in unfunded new accounts launches an investigation before bonuses are paid.
  6. Review the measurement burden. Each extra metric costs time to collect, and people can learn to game it too.
Goodhart's Law: Metric design diagram
Goodhart's Law: Metric design diagram

Question 3 does the most work. If you cannot think of a way to game your own metric, ask the people who will be measured by it. They usually know within a minute. Second-order thinking helps trace what they will do next.

When Goodhart’s law is taken too far

Questions people ask about Goodhart’s law

Who said “when a measure becomes a target, it ceases to be a good measure”?

The popular wording is usually credited to anthropologist Marilyn Strathern, summarizing Charles Goodhart’s 1975 point about monetary statistics.

Should I stop setting targets?

No. Targets help people coordinate. Pair each one with an outcome check that the target itself does not reward.

How can you tell real improvement from gaming?

Look for a second signal that should move with the first. At Wells Fargo, product counts rose while many new accounts sat unfunded. When the two diverge, investigate.

Test your next target for five minutes

Before you set a target for a team, or for yourself, fill in this card:

The goal behind this number: ___
Fastest way to hit the number without the goal: ___
Who would be tempted to do that, and why: ___
A second signal that would catch it: ___

Personal metrics break the same way. If you track a habit with the Sweat habit tool, write the real goal next to the streak, so a two-minute version that keeps the chain alive does not quietly replace the habit you wanted.