Data issues become hard to resolve when intake notes, severity, impacted reports, source owners, fix status and retest outcomes sit in separate places.
KPIs, Definitions & Data Quality
Data Issue Triage Register
A data quality triage register that keeps issue intake, impacted report, owner route, fix state and retest result together before reporting.
Data issue triage registerOpen image
Rendered from the included Excel triage workbook after publication-blocker, retest and owner counts were verified.
Data issue triage
Issue severity, report impact and retest state kept together.
Data issues can be prioritised and followed up without turning review meetings into a search for ownership and retest status.
Useful forReporting analystsData ownersOperations leadsFinance teams
Which issue blocks a report, who owns the source fix, what has been retested and what limitation needs to be carried into review?
A data issue triage register that records issue intake, severity, impacted report, source owner, fix status, retest route and publication decision.
How the work fits together
Each issue is followed from first report through fix and retest.
The register records severity, the affected report, the source owner, the proposed fix and the evidence used to close the retest.
01Source
What the work starts with
- Eight-row issue register
- Six-stage owner and retest route
- Validation and reporting-output records
02Prepare
How it is prepared
- Completed Excel triage workbook
- Reporting-impact and severity logic
- Fix status separated from retest state
03Check
Checks applied
- Two publication blockers
- Five open retests
- Seven named source owners and two ready items
04Output
What the review receives
- Issue register
- Publication-hold and partial-output decisions
- Owner and retest route
05Handover
Notes for the next update
- Limitation notes stay with impacted reports
- Open retests retain owners and next actions
- Build assertions and workbook retained
- Excel
- CSV issue register
- Validation checks
- Review-route records
- Data issue triage
- Reporting impact assessment
- Owner routing
- Retest management
Data issues can be prioritised and followed up without turning review meetings into a search for ownership and retest status.
Built from a non-client example dataset. No protected data is used.
From issue to retest
A data problem has an owner, an affected report and a clear route back to use.
Set the severity, affected reports, source ownership, fix states and evidence needed to close each retest.
- 01
Issue intake is grouped by severity, impacted report and source owner so urgent fixes are easier to route.
- 02
Fix and retest status are checked before the affected report is cleared for use.
- 03
Reports that remain blocked and any accepted limitations are recorded for the review.
Issue status
Which problems are urgent, what they affect and what remains to be retested.
Each issue keeps source, report impact, owner route and decision state in one register.
Two report sections remain on hold until ownership or evidence state is confirmed.
Fix status is kept separate from retest result before outputs are cleared.
Register contents
The issue records, ownership fields and limits included in this example.
What is included
- Data issue intake
- Severity
- Impacted report
- Source owner
- Fix status
- Retest route
- Readiness decision
What it can start from
- Issue register
- Impacted report list
- Source owner register
- Validation output
- Retest queue
What this example does not claim
- The register covers eight selected reporting issues rather than a live issue management process.
- Severity, publication holds and retest rules would require agreement with source owners.
Definitions pack overview
KPI Dictionary and Reporting Definitions Pack
- What is difficult now
- Reports lose trust when a shared KPI name hides different calculations, unclear source fields, assumptions or ownership.
- What the work helps decide
- Which KPI definitions are agreed, which need review and which downstream reports move when source fields or calculation rules change?
- KPI dictionary
- Reporting definitions
- Source mapping
Data quality review overview
Data Quality Checks
- What is difficult now
- Reports become unreliable when missing owners, duplicates, stale files, invalid periods and unmatched references surface during review.
- What the work helps decide
- Can this data be used in the report, what failed, how severe is it, who owns the fix and which output is affected?
- Quality check
- Failed record review
- Source confidence
Metric reconciliation workbook
Metric Reconciliation Pack
- What is difficult now
- Review time is lost when the same measure uses different formulas, grains or source fields across recurring reports.
- What the work helps decide
- Which version of the metric should be used, why do reports differ, what sits outside tolerance and who signs off the agreed definition?
- Metric reconciliation
- Formula comparison
- Source confidence
Next step
Route data issues through ownership and retest.
Start with the measures people dispute or the failed checks that need clearer ownership before reporting.