Global INGO program ops
Illustrative scenario

Cut the Six-Week DATIM Sprint Down to a Continuous Quality Check

If you're leading M&E for a global health INGO with PEPFAR awards, you already know what the quarterly DATIM cycle looks like: six weeks of manual extraction, site-by-site reconciliation, and last-minute data quality fixes before submission. The DQA findings that follow are often the direct consequence of that compressed, reactive process — not a reflection of what's actually happening in the field.

Up and running in ~5 wkFor: Director of M&E or VP of Programs
Estimate your payback
~3 mo
Payback period
$300K
Est. savings / year
+$220K
Year-1 net

Rough estimate — change the numbers to match your business. We scope the real figures with you on a call.

Why Six Weeks of Manual Extraction Produces Inconsistent Data

Pulling PEPFAR indicator data from DHIS2 across 20 or more implementing sites is labor-intensive by design — different sites have different data entry discipline, different reporting cycles, and different interpretations of OGAC indicator definitions. When M&E staff compress this reconciliation into a quarterly sprint, inter-site inconsistencies don't surface until late in the cycle, leaving insufficient time for correction. The result is DATIM submissions that carry data quality findings — which then trigger DQA reviews that consume additional M&E capacity and strain implementing partner relationships with USAID.

Weekly Validation Instead of Quarterly Crisis

An AI Labor Company agent mines your historical DATIM submission data and DQA findings, then deploys a Gemini agent that pulls PEPFAR indicator data from each implementing site weekly throughout the quarter. The agent validates each submission against OGAC data quality rules and surfaces inconsistencies — missing denominators, implausible trend deviations, site-to-site definitional mismatches — at 30-day intervals rather than in a compressed end-of-quarter review. When the quarter closes, the submission package is assembled and routed to the Director of M&E for final review and DATIM upload. The six-week sprint becomes a final verification step rather than the entire process.

Fewer DQA Findings, More Credible Reporting

The business case is dual. On the efficiency side, a 65–85% reduction in manual data extraction and reconciliation time is a realistic illustrative outcome — freeing M&E staff for analysis and site support rather than data wrangling. The more strategic outcome is fewer DQA findings. PEPFAR implementing partners with clean data quality records maintain stronger relationships with USAID OUs and face less friction at award renewals. Systematic in-cycle validation is the mechanism. Teams implementing this workflow are typically live and running weekly validation cycles in about 5 weeks.

Works with
DHIS2DATIM (PEPFAR platform)Salesforce Nonprofit CloudMicrosoft 365KoBoToolboxTableau
Questions

Does the agent integrate directly with DATIM, or does M&E staff still upload the final package?

The agent assembles the complete submission package and routes it to the Director of M&E for review. The final DATIM upload remains a human action — the agent ensures the package is accurate and ready, not that it submits autonomously.

Some of our implementing sites use KoBoToolbox rather than DHIS2. Can the agent pull from both?

Yes. The agent is configured to pull from KoBoToolbox and DHIS2, reconciling data across both collection systems before validation. The integration map is built during onboarding based on your actual site configuration.

What happens when a site's weekly data looks anomalous but isn't necessarily wrong?

The agent flags anomalies for M&E staff review rather than automatically flagging them as errors. Staff can mark a flagged item as reviewed and explained — maintaining an audit trail that supports the DQA process.

Related use cases

Illustrative scenario for nonprofit & philanthropy. Figures are example ranges, not guarantees — we scope real numbers with you on a call.

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