SG-04
Worklog Signal — Zero Effort Issue
Signal Chart
Default severity: medium
ProcessMetricsQualityEffort
What it detects
An issue was resolved with zero or near-zero total worklog time — it was marked Done without any recorded work. This is either a data quality problem (work happened but was not logged) or a phantom closure (issue closed without being genuinely worked on).
Detection formula
IF issue.status IN config.workflow.done_statuses: total_logged = SUM(worklog.time_spent, issue=I) IF total_logged = 0 THEN FLAG zero_effort_done IF total_logged \< config.sg.min_effort_hours // default: 0.5h (30 min) THEN FLAG near_zero_effort Report: issue, resolution_date, total_logged, story_points — flag if SP > 0 AND logged = 0 (CRITICAL: SP claimed with no work evidence)Examples in practice
- A team shows an issue was resolved with zero or near-zero total worklog time while done statuses is set to Configured per workspace.
- Example signal: An issue was resolved with zero or near-zero total worklog time — it was marked Done without any recorded work.
Suggested response
Use worklog shape (gaps, bursts, handoffs) to coach sustainable pacing and clarity.
Coaching playbook
Symptom
An issue was resolved with zero or near-zero total worklog time — it was marked Done without any recorded work. This is either a data quality problem (work happened but was not logged) or a phantom closure (issue closed without being genuinely worked on).
Why it matters
When "Worklog Signal — Zero Effort Issue" 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 worklog shape (gaps, bursts, handoffs) to coach sustainable pacing and clarity.
Facilitation questions
- What system change would stop "Worklog Signal — Zero Effort Issue" 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.