Cognitive BiasesPublic knowledge library

Practice Lab

Reviewing KPIs & proxy metrics

Learn to connect a practical check with the evidence-reviewed lens behind it. A real situation can involve several patterns, so each exercise asks for the best first lens among the listed options, not a diagnosis.

How to use this set

Read the check. Choose a lens. Then inspect the evidence.

Use these evidence-reviewed lenses when a team is using scores, dashboards, targets, benchmarks, or AI evaluations to represent a broader objective.

Read the full decision guide before or after the set.

Exercise 1 of 4

In reviewing kpis & proxy metrics, which lens does this check belong to: “Are we treating the measure as evidence about the objective, or have we started treating the measure as the objective itself?”

  1. Surrogation
  2. Anchoring Effect
  3. Confirmation Bias
Show the best first lens

Surrogation

Are we treating the measure as evidence about the objective, or have we started treating the measure as the objective itself?

Evidence note Surrogation is a domain-specific management-accounting construct: a measure that was designed to represent a strategic objective can start to be treated as though it were the objective itself. It is closely related to metric fixation and proxy problems, but those broader labels should not be treated as exact synonyms without checking the setting and mechanism.

Read the evidence review · Open the decision guide

Exercise 2 of 4

In reviewing kpis & proxy metrics, which lens does this check belong to: “Which target, benchmark, baseline, or first score is shaping later judgments before we build an independent estimate?”

  1. Confirmation Bias
  2. Outcome Bias
  3. Anchoring Effect
Show the best first lens

Anchoring Effect

Which target, benchmark, baseline, or first score is shaping later judgments before we build an independent estimate?

Evidence note Anchoring is a well-supported effect in which an initial numerical value can pull a later estimate toward it. A 2026 meta-analysis covering 2,601 effect sizes found a large overall effect, but also substantial variation across studies. The effect should not be treated as a rule that every number changes every judgment: incidental anchors, anchors from a different dimension, clearly random values, incentives, and some debiasing conditions were associated with smaller or null effects.

Read the evidence review · Open the decision guide

Exercise 3 of 4

In reviewing kpis & proxy metrics, which lens does this check belong to: “What evidence would show that this KPI is a poor proxy, and have we actively looked for it?”

  1. Surrogation
  2. Confirmation Bias
  3. Outcome Bias
Show the best first lens

Confirmation Bias

What evidence would show that this KPI is a poor proxy, and have we actively looked for it?

Evidence note Confirmation bias is an umbrella label for several ways existing beliefs or hypotheses can influence information search and interpretation. It should not be reduced to one behaviour such as reading only agreeable news, and a preference for confirming tests is not irrational in every task or environment.

Read the evidence review · Open the decision guide

Exercise 4 of 4

In reviewing kpis & proxy metrics, which lens does this check belong to: “Are we judging the quality of the metric and decision process mainly from whether the final result happened to be good or bad?”

  1. Outcome Bias
  2. Surrogation
  3. Anchoring Effect
Show the best first lens

Outcome Bias

Are we judging the quality of the metric and decision process mainly from whether the final result happened to be good or bad?

Evidence note Outcome bias occurs when knowledge of a result changes how people evaluate the quality of a decision even when the information available at the time of the decision is held constant. Outcomes can still be relevant for learning, so the error is not 'never look at results'; it is using luck or hindsight as if it had been available to the original decision-maker.

Read the evidence review · Open the decision guide