Sprint Trends — Team University

Finalized-registry view of predictability, throughput, misses, and quality signals

University trend points are generated from persisted sprint issue facts and centralized formulas. The dashboard is designed to show miss patterns and execution quality, not just output volume. Every persisted point was rebuilt from the current validated revision in the finalized sprint registry.

Overview

University now has 7 source-backed checkpoint(s) in the persisted trend store.

These cards bias toward leadership questions: can we trust the promise set, what diluted it, and what actually came out of the sprint system.

Committed completion

55.0%

Improved by 18.6 pts vs prior checkpoint

Planning quality

30.0%

6.4 pts down vs prior checkpoint

Added load

25.0%

Improved by 12.5 pts vs prior checkpoint

Workflow mismatch

Worse by 1 vs prior checkpoint

Bug share

60.0%

Worse by 10.0 pts vs prior checkpoint

Product stories

1 down vs prior checkpoint

Trend explorer

Choose a consecutive week window to inspect how the delivery system changed over time for this scope.

Start week End week

Select a consecutive window to reslice the same persisted trend facts.

Delivery predictability

Committed completion, finish predictability, and planning quality should move together if the sprint system is healthy.

Committed completionFinish predictabilityPlanning quality

Percentage scale, higher is better.

Scope pressure

Carryover, added load, and bug share show how much execution was displaced by noise or late scope motion.

Committed carryoverAdded loadBug share

Percentage scale, lower is better.

Delivered mix

Stories, tasks, and bugs should stay legible enough that leaders can see where capacity actually landed.

StoriesTasksBugs

Stacked counts by checkpoint.

Miss pattern

Partial completion, dependency delay, and not-started misses help distinguish breakdown, coordination, and focus failure.

PartialDependencyNot started

Stacked miss counts by checkpoint.

Execution truth

Workflow mismatches, not-started committed items, and delivered product stories show whether the sprint closed cleanly and usefully.

Workflow mismatchNot-started committedProduct stories

Grouped counts by checkpoint.

Predictability

Metric	W30	W31	W32	W33	W34	W35	W36
Committed completion	38.9%	41.7%	50.0%	36.4%	0.0%	36.4%	55.0%
Finish predictability	53.8%	55.6%	63.6%	57.1%	0.0%	60.0%	76.9%
Planning quality	22.2%	50.0%	50.0%	36.4%	25.0%	36.4%	30.0%
Committed carryover	61.1%	58.3%	50.0%	63.6%	100.0%	63.6%	45.0%
Added load	23.8%	21.4%	13.3%	0.0%	14.3%	37.5%	25.0%
Bug share	90.0%	57.1%	75.0%	50.0%	0.0%	50.0%	60.0%

Delivery and misses

Metric	W30	W31	W32	W33	W34	W35	W36
Stories	1	3	2	1	0	3	2
Tasks	0	0	0	0	0	1	3
Bugs	9	4	6	2	0	4	9
Partial	6	5	6	2	6	4	4
Dependency	3	0	1	4	4	0	0
Not started	1	2	0	1	1	2	3
Workflow mismatch	0	0	0	0	0	0	1
Not-started committed	1	2	0	1	1	2	3
Product stories	1	3	2	1	0	3	2