CA-10
Throughput Variance Too High
CFD Advanced
Default severity: medium
PrioritizationProcessMetricsOutputRisk
What it detects
Daily or weekly throughput variance exceeds the configured coefficient of variation — throughput is too erratic to support reliable forecasting even if the average looks acceptable. throughput_series = \[done_per_period for each period in config.ca.throughput_variance_window\] throughput_cv = stddev(throughput_series) / mean(throughput_series)
Detection formula
IF throughput_cv > config.ca.max_throughput_cv // default: 0.5 THEN FLAG erratic_throughput IF throughput_cv > config.ca.critical_throughput_cv // default: 0.8 THEN CRITICAL — forecasting unreliableExamples in practice
- A team shows daily or weekly throughput variance exceeds the configured coefficient of variation while max throughput cv is set to 0.5.
- Example signal: Daily or weekly throughput variance exceeds the configured coefficient of variation — throughput is too erratic to support reliable forecasting even if the average looks acceptable.
Suggested response
Use planning-event context when interpreting advanced CFD bottlenecks, spikes, and ageing WIP.
Coaching playbook
Symptom
Daily or weekly throughput variance exceeds the configured coefficient of variation — throughput is too erratic to support reliable forecasting even if the average looks acceptable. throughput_series = \[done_per_period for each period in config.ca.throughput_variance_window\] throughput_cv = stddev(throughput_series) / mean(throughput_series)
Why it matters
When "Throughput Variance Too High" 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
Use planning-event context when interpreting advanced CFD bottlenecks, spikes, and ageing WIP.
Facilitation questions
- What system change would stop "Throughput Variance Too High" 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.