How do you ensure your program monitoring and evaluation data is valid?

1 Define clear indicators

One of the first steps to ensure data validity is to define clear and relevant indicators that measure the specific objectives and results of your program. Indicators are quantitative or qualitative variables that show the changes or achievements of your program over time. They should be SMART: specific, measurable, achievable, relevant, and time-bound. By having clear indicators, you can avoid collecting irrelevant or ambiguous data that may not reflect the true situation of your program.

3 Establish data quality standards

A third tip to ensure data validity is to establish data quality standards that guide your data collection and analysis process. Data quality standards are the criteria or principles that define how good or reliable your data is. They may include aspects such as accuracy, completeness, consistency, timeliness, relevance, and security. By setting data quality standards, you can ensure that your data meets the minimum requirements for validity and reliability. You can also monitor and evaluate your data quality regularly and identify any gaps or issues that need to be addressed.

4 Validate your data with stakeholders

A fourth tip to ensure data validity is to validate your data with stakeholders who are involved or affected by your program. This means that you should share your data findings and interpretations with them and seek their feedback and input. By validating your data with stakeholders, you can increase the credibility and transparency of your data and ensure that it reflects their views and experiences. You can also use this opportunity to verify your data accuracy, identify any discrepancies or errors, and resolve any conflicts or misunderstandings.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?