EP-05
Business Value vs Effort Ratio — Low ROI Items
Estimation Precision
Default severity: medium
EstimationQualityBusiness ValueEffort
What it detects
Items with high story point or time investment are delivering low business value — the ROI distribution is skewed toward effort-heavy, low-value work. Identifies the worst value-for-effort items in the backlog and delivered set.
Detection formula
IF bv_field = config.workflow.bv_field // only if BV field configured FOR each_issue I WHERE story_points > 0 AND bv > 0: roi(I) = bv(I) / story_points(I) // BV per SP ROI_distribution = \[roi(I) FOR all I\] bottom_quartile_cutoff = PERCENTILE(ROI_distribution, 25) FOR each_issue I WHERE roi(I) \< bottom_quartile_cutoff AND story_points(I) > config.ep.large_item_sp // default: 5 THEN FLAG as low_roi_large_item Report: ranked list of items by roi ascendingExamples in practice
- A team shows items with high story point or time investment are delivering low business value while bv field is set to Configured per workspace.
- Example signal: Items with high story point or time investment are delivering low business value — the ROI distribution is skewed toward effort-heavy, low-value work.
Suggested response
Recalibrate estimation precision—check size classes, drift, and BV vs effort trade-offs.
Coaching playbook
Symptom
Items with high story point or time investment are delivering low business value — the ROI distribution is skewed toward effort-heavy, low-value work. Identifies the worst value-for-effort items in the backlog and delivered set.
Why it matters
When "Business Value vs Effort Ratio — Low ROI Items" 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
Recalibrate estimation precision—check size classes, drift, and BV vs effort trade-offs.
Facilitation questions
- What system change would stop "Business Value vs Effort Ratio — Low ROI Items" 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.