Reporting Visibility Assessment

Does this report answer the specific question its users are actually asked?

Why this matters: A technically correct report still fails if it does not support the decision in front of the user.

Do users keep a separate spreadsheet alongside this report?

Why this matters: Parallel files expose requirements, definitions or confidence gaps in the shared report.

Can a new user understand what each figure means without asking someone?

Why this matters: Shared definitions prevent interpretation from depending on personal knowledge.

Does the report change when the underlying decision or target changes?

Why this matters: A report that lags business changes can look current while answering an old question.

Would users notice and escalate within a day if this report stopped?

Why this matters: Active reliance is stronger evidence of value than circulation or page views.

Can users check this report before they need to act, rather than afterwards?

Why this matters: Information only creates value when it arrives inside the decision window.

How current is the data when a user opens the report?

Why this matters: Users need to know whether the position shown is current enough to act on safely.

When a refresh fails, do users know before they rely on the numbers?

Why this matters: Silent failures can cause decisions to be made on stale data.

Is the refresh schedule matched to how often the underlying activity changes?

Why this matters: Refresh effort should be driven by the decision window, not habit.

Do users trust the timestamp, or double-check the data elsewhere?

Why this matters: Independent checking adds effort and signals unresolved confidence problems.

Is there a visible benefit to users for keeping their own data accurate?

Why this matters: People maintain data more consistently when they can see how it improves their own work.

Do users correct or contribute data without being asked to?

Why this matters: Voluntary correction is a practical signal that users trust the report and its response process.

When a user reports a data problem, do they hear what was done?

Why this matters: Closing the loop shows users that raising issues improves the shared result.

Are known data quality issues visible in the report?

Why this matters: Visible limitations let users judge risk rather than discover defects after acting.

Is someone accountable for fixing the source of recurring data problems?

Why this matters: Corrections at report level do not stop the source from producing the same defect.