What Funders See When They Review Your Report
A program officer reviewing a grant report is asking three questions: Did you do what you said you'd do? Can I trust these numbers? Is this a well-run organization worth funding again?
Data quality answers the second and third questions. A grant report with internal inconsistencies, vague outcome metrics, or numbers that don't reconcile with prior reports signals organizational weakness — even if the programs were excellent.
The Most Common Grant Reporting Data Errors
Participant counts that don't match across sections The executive summary says you served 842 individuals. The program data table says 820. The budget narrative says "over 800." Which is right? A funder notices this immediately.
Outcome metrics without baseline or comparison "85% of participants reported improved skills" without knowing what they reported at baseline or what the comparison population showed is not a meaningful outcome. Funders increasingly require pre/post measurement and are skeptical of post-only self-reported outcomes.
Undocumented methodology How did you collect the data? Who administered the survey? What was the response rate? Without methodology documentation, outcome data is unverifiable — and funders are training to ask for it.
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Budget-to-actuals mismatches Grant budgets are projections. Actuals will differ. But a final report where actuals are dramatically different from the budget — especially for personnel — without a documented explanation signals weak financial oversight.
Prior report contradictions A mid-year report showing 400 participants and a final report showing 600 without explanation. A prior report citing one program model and the final report describing a different one. Funders read all your reports — contradictions raise questions.
Building Grant-Ready Data Systems
Start data collection at program launch, not near the grant deadline The data you need for a grant report must be captured throughout the program. A participant tracking spreadsheet built the first week of the program produces better data than one built the last week before the report is due.
Sohovi gives you a full quality report on any spreadsheet in seconds — upload your file and see exactly what needs fixing.
Define your metrics in the grant proposal, then stick to them If your proposal says "we will measure X using method Y," your report must show X measured using method Y. Changing metrics mid-grant because the data wasn't collected properly is a red flag.
Build a reconciliation step into your report production Before submitting: participant count in all sections must match. Budget actuals must reconcile to your accounting system. Outcome metrics must reconcile to your data collection source documents.
A two-hour reconciliation before submission is far less expensive than a follow-up call from a funder asking why your numbers don't add up.
Sohovi gives you the data quality picture you need to make the case for fixing it — and to track improvement over time.
