Good data is essential for making informed program decisions, demonstrating impact, and meeting reporting requirements. Yet, data quality issues often persist even when organisations invest in MEL tools, systems, and processes. This is because the quality of data is shaped not just by how it is collected or checked, but by how programs are designed and implemented.

This session explores how everyday program processes and ways of working influence the quality, usefulness, and timeliness of data. It helps NGOs identify where data problems originate, improve data quality at the source, and ensure that the data they collect supports both program decisions and reporting.

With this resource, you will be able to:

1. Understand where data quality begins: Explore how program design and implementation influence the quality of data generated.
2. Identify the root causes of data problems: Recognise where and why data quality issues emerge within existing program processes.
3. Focus on useful data: Distinguish between data that supports program decisions and data collected primarily for reporting.
4. Improve data quality: Learn practical ways to strengthen data quality as it is generated, without relying only on downstream checks.

This resource is recommended for MEL and program professionals in NGOs and development organisations who have a basic understanding of MEL and want to improve the quality, usefulness, and timeliness of the data generated through their programs.