Data Quality Assessments

Context
A major international family planning programme relies on six core monitoring tools to track programme delivery across countries and hubs globally. A baseline Data Quality Assessment identified systemic issues: inconsistent practices across reporting hubs, significant missing data, no standardised templates, and unclear treatment of missing versus zero values.

The Challenge
Recommendations from a baseline assessment are only useful if an organisation can actually act on them, and a second assessment two years later needed to establish, credibly, whether that had happened, not just repeat the same diagnosis.

What I Did
I led the comprehensive and systematic baseline and endline Data Quality Assessments independently, evaluating progress against every baseline recommendation before producing a fresh set for the programme's next phase. This meant scoring each of the six monitoring tools across multiple quality dimensions, tracing which baseline recommendations had actually been implemented and what measurable difference they'd made, and identifying where the next round of investment should go, from short-term fixes (automated dashboards, protected template formatting) to longer-term structural change (a centralised M&E system, hub-level error ownership).

Outcome
The programme had genuinely acted on the baseline findings: mandatory standardised templates, a formal two-tier data cleaning process, and regular hub-level support were all in place by midline, reflected in an overall data quality score of 3.9 out of 5, with perfect scores for uniqueness and strong validity. The client was pleased enough with the demonstrated improvement to move straight into planning automation and further standardisation based on the new recommendations.