Data Reconciliation
Reconciliation checks that two systems or reporting views agree on the business facts that are supposed to match.
Also called: data reconciliation, reconcile
Definition
Reconciliation compares an implemented output with an agreed source or control total and identifies differences that require explanation or correction.
Why it matters to the business
A dashboard or integration can run successfully while still carrying the wrong totals, missing records or inconsistent states. Reconciliation provides an explicit trust check.
How it works
The implementation defines the fields or totals that should match, chooses the authoritative source, compares them at an agreed cadence and makes mismatches visible.
Where it appears in real systems
Examples include CRM-to-accounting record counts, report totals against source exports, transaction backfills and integration exception queues.
Common failure modes
- The comparison uses two equally untrusted sources.
- Different refresh times create false mismatches.
- Exceptions are detected but nobody owns resolution.
- A backfill changes historical totals without an audit trail.
Implementation considerations
- Name the source of truth.
- Account for refresh timing.
- Define acceptable tolerances where appropriate.
- Assign exception ownership.
When it is appropriate
Use reconciliation where missing, duplicate or inconsistent records would change an operational or management decision.
When it is not appropriate
Do not create heavy reconciliation machinery for low-value data where an occasional manual check is sufficient.
Relationship to BYFORCE
Reporting implementations define reconciliation where important KPI totals need a control source; Integration Sprint includes failure visibility and reconciliation behavior where required.
Source basis
- docs/commercial/BYFORCE_PACKAGE_BIBLE.md
- docs/website/BYFORCE_SELF_SERVICE_INTAKE_SPEC_2026-09-23.json