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How to Run School Inspections That Produce Donor-Grade Data — Not Narrative Estimates

Who This Is For

You manage an education program inspecting and supporting schools across multiple counties. Field inspectors visit schools, submit Word document reports days later, and you're supposed to aggregate data across 200+ schools from narrative text. Infrastructure grant disbursements are tied to inspection outcomes. A mid-term review is coming and the donor wants to see the data — not the reports, the data.

The Problem

Inspection reports written as narrative Word documents, sometimes two or three days after the field visit, aren't data — they're reconstructions. They capture what the inspector remembered, filtered through their own framing, written to satisfy a reporting requirement. You can't aggregate them, you can't cross-reference them across schools without manual analysis, and you can't confidently use them to trigger grant disbursements without a quiet concern about accuracy. The grant disbursement gate problem is the most consequential part. If you're releasing infrastructure grants based on inspection sign-offs, and those sign-offs have no photo evidence that the previous grant's items were actually installed and functional, your inspection is a formality rather than a control. A mid-term donor review that discovers this won't necessarily distinguish between honest program slippage and something that looks a lot worse.

What You Can Achieve

  • Every inspection follows the same structured checklist, completed at the school on the day of the visit — not reconstructed from an inspector's notes the following week
  • Grant disbursement gates are enforced: photo evidence of previous grant items must be uploaded and confirmed before the next tranche can be approved
  • Photo evidence and structured responses replace subjective narrative — data from 200 schools is actually aggregatable because it's in the same format
  • Program leadership sees real-time inspection status for every school in the portfolio, by county — without waiting for reports to land in an inbox
  • Donor reporting is built on structured data rather than narrative estimates, which is a meaningful difference during a mid-term review
  • Every inspection is timestamped and attributed to the specific inspector who ran it — accountability is built in, not enforced through supervision alone

The Hakiki Workflow

  1. 1
    School Name Text

    Enter exact school name as registered — links the inspection to the school record in the portfolio

  2. 2
    County Single Select

    Select county from the program area list — enables county-level aggregation in reports

  3. 3
    Classrooms Count & Condition Text

    Enter number of classrooms inspected and overall condition assessment (Good/Fair/Poor)

  4. 4
    Latrines Functional Boolean

    Confirm that latrines are functional, clean, and meet gender-separation requirements

  5. 5
    Water Point Available Boolean

    Confirm that a functional water point is available and accessible to students

  6. 6
    School Photos File Upload

    Photos of school exterior, classrooms, and key infrastructure — minimum 3 photos

  7. 7
    Prior Grant Items Installed Boolean

    Confirm that items funded by the previous infrastructure grant are present and functional

  8. 8
    Prior Grant Installation Evidence File Upload

    Photo of previously funded items in place — REQUIRED before any new grant disbursement is authorized

  9. 9
    Teacher Attendance Rate Text

    Enter percentage of enrolled teachers present on the day of inspection

  10. 10
    Attendance Register Photo File Upload

    Photo of the current attendance register — cross-references the attendance rate entry

  11. 11
    Inspector Recommendations Text

    Free-form text for inspection observations, concerns, and specific recommendations

HAKIKI Features Used

Structured text and boolean stepsPhoto evidence enforcementConditional grant gatesSingle select countyAggregate reporting via audit logMulti-county department structure

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