August 25, 2026·
post
When a metric communicates the truth but tells a lie.
When a metric communicates the truth but tells a lie.
Not because they are wrong.
Because they are technically correct but in a way that consistently and predictably creates the wrong impression.
Take “Settlement Ratio” in insurance, for example.
An ad says:
“99% Claim Settlement Ratio”
What does most consumers hear?
“99% of claims were paid in full.”
But a claim can be considered settled without communicating:
- How much was actually paid
- What percentage of the claimed amount was actually paid
- How many claims were settled in favour of the consumer after disputes or escalations
A better consumer-facing metric would be:
“Percentage of claimed amount paid”
Or, show the full picture:
- Claims received: 100
- Claims paid in full: 82
- Claims partially paid: 12
- Claims rejected: 6
- Average payout as % of amount claimed: 91%
If companies find upside in displaying a higher settlement ratio, they have an incentive to optimise for the metric.
Consumers, meanwhile decide using what *they think* the metric means.
If consumers consistently interpret a metric differently from what it actually measures, the problem isn’t just consumer literacy. The metric itself is broken and should be regulated.
The most dangerous metrics aren’t necessarily false.
They are the ones that become a signal, not because of what it communicates, but because of whom it is communicated to and what they infer from it.
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