Service guides / AI automation
Human review points · AI automationSpreadsheet consolidation: human review points
Give reviewers specific decisions to make. Start with sample workbooks and column definitions and plan a merged dataset with a validation report.
Available remotely for local and international enquiries. Platform choice and final scope depend on your requirements.
The project in view
- Start with
- sample workbooks and column definitions.
- Proposed result
- a merged dataset with a validation report.
- A decision to resolve
- conflicting identifiers and inconsistent units.
This is a planning example. It does not describe a completed client engagement.
Human review points for this project
- Assign a reviewer who understands sample workbooks and column definitions.
- Present a merged dataset with a validation report beside its source so corrections can be checked.
- Require an explicit decision on conflicting identifiers and inconsistent units; keep the decision in the review record.
Questions to answer together
- Which result must be approved before it is used?
- What source evidence should the reviewer see?
- How is a rejected result corrected and checked again?
What to have at the end
A review matrix with decision owners, evidence and a correction route.
Record the decision on conflicting identifiers and inconsistent units alongside the source material. If it is still unresolved, identify who can answer it and what work depends on the answer.
Prepare your enquiry
Use this as a starting point. Add your current process, available examples and constraints before sharing.
Send your completed brief to hello@iansamonte.com or visit the main page to discuss your project.