Trend View

Sprint Trends — Team University

One-screen view of predictability, throughput, misses, and quality signals

University trend points come from persisted source-pair metrics and the published pulse archive. The dashboard is designed to show miss patterns and execution quality, not just output volume.

Overview

University now has 12 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
22.7%
12.3 pts down vs prior checkpoint
Planning quality
18.2%
Improved by 8.2 pts vs prior checkpoint
Added load
75.0%
Worse by 11.0 pts vs prior checkpoint
Workflow mismatch
0
Improved by 3 vs prior checkpoint
Bug share
50.0%
Worse by 5.6 pts vs prior checkpoint
Product stories
0
1 down vs prior checkpoint

Historical checkpoints were reconstructed from their published pulse metric tables; frozen source-pair rows remain authoritative whenever both are available.

Trend explorer

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

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
0%25%50%75%100%W11-12W14W18W19W20W21W22W23W24W25W26W27
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
0%25%50%75%100%W11-12W14W18W19W20W21W22W23W24W25W26W27
Percentage scale, lower is better.
Delivered mix
Stories, tasks, and bugs should stay legible enough that leaders can see where capacity actually landed.
StoriesTasksBugs
01234157101191171091196W11-12W14W18W19W20W21W22W23W24W25W26W27
Stacked counts by checkpoint.
Miss pattern
Partial completion, dependency delay, and not-started misses help distinguish breakdown, coordination, and focus failure.
PartialDependencyNot started
012344323345386813W11-12W14W18W19W20W21W22W23W24W25W26W27
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
01234W11-12W14W18W19W20W21W22W23W24W25W26W27
Grouped counts by checkpoint.

Predictability

MetricW11-12W14W18W19W20W21W22W23W24W25W26W27
Committed completion55.6%63.6%53.8%50.0%57.1%61.5%50.0%50.0%28.6%43.8%35.0%22.7%
Finish predictability71.4%63.6%54.5%50.0%66.7%80.0%62.5%60.0%33.3%46.2%42.9%25.0%
Planning quality100.0%0.0%38.5%27.8%42.9%53.8%50.0%21.4%21.4%12.5%10.0%18.2%
Committed carryover44.4%36.4%46.2%50.0%42.9%38.5%50.0%50.0%71.4%56.2%65.0%77.3%
Added load31.6%8.3%18.8%43.5%60.0%18.8%25.0%22.2%26.3%61.9%64.0%75.0%
Bug share40.0%57.1%70.0%45.5%55.6%54.5%28.6%70.0%66.7%72.7%44.4%50.0%

Delivery and misses

MetricW11-12W14W18W19W20W21W22W23W24W25W26W27
Stories501420222110
Tasks432225311243
Bugs647556276843
Partial221113335444
Dependency111011000134
Not started100210203115
Workflow mismatch202210210330
Not-started committed100210203115
Product stories501420222110