OL-02
Growing Outlier Density
Outliers
Default severity: medium
MetricsOutputQualityRisk
What it detects
Number of items above the configured outlier threshold is increasing over consecutive time windows — systemic deterioration signal.
Detection formula
outlier_threshold = config.outliers.density_multiplier * avg // default: 2x avg IF COUNT(outliers, window=t2) > COUNT(outliers, window=t1) * config.outliers.density_growth_rate // default: 1.3 THEN FLAGExamples in practice
- Individual items or windows fall outside statistically expected cycle time bounds.
- Outlier density increases compared with the prior analysis window.
- A team shows number of items above the configured outlier threshold is increasing over consecutive time windows while density multiplier is set to 2x avg.
Suggested response
Validate whether outliers reflect real incidents or data and process issues before changing targets.
Coaching playbook
Symptom
Number of items above the configured outlier threshold is increasing over consecutive time windows — systemic deterioration signal.
Why it matters
When "Growing Outlier Density" keeps appearing, the team is signalling a repeatable process gap. Left unexamined, the pattern hides where work really stalls and makes improvement metrics harder to trust.
What you can achieve
Validate whether outliers reflect real incidents or data and process issues before changing targets.
Facilitation questions
- What system change would stop "Growing Outlier Density" from firing again?
- What do the cited issues have in common — same root cause or same workaround?
- Who owns the two-week experiment and how will we verify on the next import?
Run this rule against your own tracker data with Flow Analyzer.