CC-01

Sustained Rolling Avg Uptrend

Control Chart

Default severity: critical
ProcessMetricsOutputRisk

What it detects

Rolling average has been rising for the configured number of consecutive time windows — process is actively deteriorating. slope = linear_regression(rolling_avg_series, last N windows)

Detection formula

N = config.cc.trend_window_count // default: 3 IF slope > 0 AND r_squared > config.cc.trend_r_squared_min // default: 0.7 THEN FLAG Severity scales with slope steepness relative to avg

Examples in practice

  • 2–4 weeks
  • Rolling averages, control limits, or band width diverge from expected statistical bounds.
  • Recent control-chart windows show drift, clusters, or missing limit configuration.

Suggested response

Treat the metric as a control signal: confirm limits, windows, and cross-team spread before acting.

Coaching playbook

Symptom

Rolling average has been rising for the configured number of consecutive time windows — process is actively deteriorating. slope = linear_regression(rolling_avg_series, last N windows)

Why it matters

When "Sustained Rolling Avg Uptrend" 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

Treat the metric as a control signal: confirm limits, windows, and cross-team spread before acting.

Facilitation questions

  • What system change would stop "Sustained Rolling Avg Uptrend" 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.

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CC-01: Sustained Rolling Avg Uptrend — FlowAnalyzer