Every reporting function gets a number wrong eventually. What separates a trusted function from a doubted one is not the absence of errors – it is the response. A controlled correction builds trust; a silent fix discovered later destroys it. This guide covers how to correct and disclose errors in reports so that the response strengthens, rather than undermines, credibility.
It is the companion to Data Quality for Reporting.
Errors are inevitable. Covering them up is a choice – and the wrong one.
Why the response matters more than the error
A reader can forgive a wrong number. What they cannot forgive is discovering that the number changed without explanation. The instinct to quietly fix a figure, hoping no one noticed, is exactly the instinct that damages trust most.
A controlled response does three things at once: it corrects the figure, it tells the people who relied on it, and it fixes the cause so it does not recur. That is what turns an error into evidence of a functioning process.
Assess the impact first
Before you correct anything, work out how far the error travelled.
- Which reports contained the wrong figure, and which versions.
- Which decisions relied on it, and whether they are affected.
- Which audiences received it – internal, client, investor, regulator.
- Whether it is material – does it change a conclusion or a number that matters?
The assessment determines the response: a minor internal figure may need only a note; a material published figure may need a reissue and a disclosure.
Correcting the report
Corrections follow the same discipline as the original report.
- Correct promptly, once the impact is understood.
- Version the correction, and mark the superseded version clearly.
- Reissue through the controlled distribution list, not ad hoc.
- Record the correction beside the original, with a note of what changed and why.
- Retain both versions, so the record is complete.
An uncontrolled correction – a new file emailed to half the audience – is how two “final” versions end up in circulation. See Data Refresh & Versioning.
Disclosing it proportionate to the impact
Disclosure should match the error’s reach.
- Internal, immaterial: note it in the next cycle, and fix the cause.
- Internal, material: correct and tell the readers who acted on it.
- External, client-facing: correct the client’s report and acknowledge the change.
- Regulated or published: follow the applicable disclosure requirements, with counsel where needed.
Under-disclosure is a risk; over-disclosure of immaterial errors erodes confidence in the numbers. The judgment is proportionality.
Fixing the cause
A correction that only fixes the figure is half a correction.
- Find the cause – a source, a definition, a process step.
- Fix the cause, not just the instance.
- Add a check so the same error is caught earlier next time.
- Feed it to the post-cycle review, where the process change is owned.
Without the cause fixed, the same error recurs, and the next correction is harder to excuse.
A worked correction
Suppose a client report contains a figure that is wrong by $40,000.
- Impact: the error is in a client-facing report, in a figure that affects a fee calculation.
- Assessment: material and external, so a correction is required.
- Response: correct the figure, version and reissue the report, acknowledge the change to the client, and record the correction.
- Cause: a source extract used the wrong period; the fix is a period check in the data-quality checklist.
The response took an hour and strengthened the relationship; a silent fix would have risked it.
Disclosure language
Disclosure should be plain and specific.
- State what changed – the figure and the correction.
- State why – the cause, once known.
- State the impact – whether any conclusion changes.
- State the action – what is being done to prevent recurrence.
Avoid vague phrasing like “minor corrections to the figures.” A reader who relied on the number deserves to know exactly what changed.
Preventing the next one
The correction process ends with prevention.
- Log the error in a register, with its cause and its fix.
- Add or tighten a check that would have caught it earlier.
- Review the register at the post-cycle review, and look for patterns.
- Fix the pattern, not just the instance, where the same cause recurs.
One correction is an incident; three of the same kind is a process gap. The register is how a reporting function learns.
A minimal correction routine
When a figure is wrong, work through six steps.
- Assess – how far the error travelled, and whether it is material.
- Correct – fix the figure promptly.
- Version – mark the superseded version, and record the correction.
- Disclose – proportionate to the impact, through the controlled list.
- Fix the cause – the source, definition or process step.
- Log it – and add a check so it is caught earlier next time.
Six steps, and an error handled this way leaves the reporting function stronger than it found it.
Common mistakes
- Silent fixes. The correction is made, no one is told, and trust erodes when it surfaces.
- Uncontrolled reissue. Two versions circulate, with no clear authority.
- Correcting the figure but not the cause. The error recurs.
- Under-disclosure. A material error reaches fewer people than it should.
- Over-disclosure. Immaterial errors are escalated, which erodes confidence in the numbers.
Frequently asked questions
What should you do when a report contains a wrong figure?
Assess the impact, correct promptly, version the correction, reissue through the controlled list, disclose proportionate to the impact, and fix the underlying cause.
Should you always disclose a correction?
Disclose proportionate to the impact. Immaterial internal errors may need only a note in the next cycle; material or external errors need a correction and an acknowledgement to those who relied on them.
How do you avoid two versions of a report circulating?
Version every correction, mark the superseded version clearly, and issue only through the controlled distribution list.
How do you stop the same error recurring?
Fix the cause, not just the figure – the source, definition or process step – and add a check so the error is caught earlier next time.
Is a corrected report as trustworthy as one with no errors?
It can be more trustworthy, if the correction was controlled and disclosed. A functioning correction process is evidence of a functioning reporting function.
What should a correction notice say?
What changed, why, whether any conclusion is affected, and what is being done to prevent recurrence. Plain and specific, not vague.
Who should be told about a correction?
Proportionate to the impact: the readers who acted on the figure, and – for regulated or published reports – whoever the applicable disclosure requirements specify.
Should errors be logged even when no one noticed?
Especially then. An error nobody noticed is still an error, and the log is how the same cause gets fixed before a reader finds it.
How do you handle an error in a report already filed or published?
Follow the applicable disclosure requirements, with counsel where needed: correct, disclose proportionate to the impact, and record the correction and its cause.
Who owns the correction?
The reporting owner owns the response; the metric or source owner owns the cause fix. Both are recorded, so neither is left as anyone’s assumption.
Should you apologise for an error in a report?
Acknowledge it plainly and move to the correction. Over-apologising draws attention away from the fix; under-acknowledging suggests the error did not matter.
How do you decide whether an error is material?
By whether it changes a decision, a published figure or an obligation. Materiality is a judgment, informed by the size of the error and who acted on it.
How do you handle an error a reader found before you did?
Thank them, correct and disclose, then log the cause. A reader who finds an error you missed is a signal that a check is missing, not a reason for defensiveness.
Next step
When a figure is wrong, respond in control: assess, correct, disclose proportionately, and fix the cause. See Data Refresh & Versioning for the correction mechanics and Data-Quality Checks for Report Production for the checks that catch errors earlier.
Sources
- Data-quality and reporting practice: controlled correction, disclosure and root-cause remediation as standard reporting controls.
- Harvard Business Review (Nagle, Redman and Sammon, 2017): the prevalence of errors in newly created data.
Good-practice claims are cited from their sources; no statistic in this article is invented. This article is not legal advice; confirm disclosure obligations with qualified counsel.