What 4,800 participants said about a regional leadership program
AI-assisted analysis of open-ended feedback in three languages to decide what to keep, fix and scale in the next cohort.
The challenge
After three cohorts of a leadership program for public officials, the team had close to 4,800 open-ended answers in English, Spanish and Portuguese. Nobody had read them all, and decisions about the next edition were being made on satisfaction scores alone.
Our approach
We used language models to group every answer into themes in its original language, then two evaluators reviewed each theme, merged overlaps and checked a sample of answers by hand.
We compared themes by country, cohort and role, and kept a set of representative quotes for each finding so the program team could hear participants in their own words.
Results
Twelve themes explained most of the feedback. The two most frequent, mentoring time and examples from participants' own countries, became the main changes for the next cohort.
The analysis took three weeks instead of the four months a manual review was estimated to need, and the report was shared with all participating institutions.
Project details
- Client
- Regional development bank
- Year
- 2025
- Location
- Latin America and the Caribbean
- Services
- Consulting Services
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