Data collection is the foundation of any research or M&E activity. Yet, many NGOs unknowingly make mistakes that compromise their data quality.
In this article, we highlight five common mistakes and provide practical solutions:
1. Poorly designed questionnaires
2. Inadequate enumerator training
3. Sampling bias
4. Ignoring data quality checks
5. Not piloting instruments
By addressing these issues, you can significantly improve the quality and reliability of your data.
In this article, we highlight five common mistakes and provide practical solutions:
1. Poorly designed questionnaires
2. Inadequate enumerator training
3. Sampling bias
4. Ignoring data quality checks
5. Not piloting instruments
By addressing these issues, you can significantly improve the quality and reliability of your data.
Tags
data collection
NGO
best practices
E
Written by
Emmanuel Kofi Mensah
Head of Training
