Impact measurement requires regular and consistent implementation throughout your program cycle. This means collecting and analyzing data at different stages, such as baseline, midline, endline, and follow-up. Additionally, you must monitor and evaluate the quality, validity, and reliability of the data. To ensure success in this endeavor, it is essential to train and engage staff and stakeholders in the process. They should be made aware of the impact measurement goals and processes, with adequate training, guidance, and feedback provided. It is also important to collect and analyze data ethically and rigorously while respecting the privacy, confidentiality, and consent of data subjects. Additionally, best practices and standards of data methods and tools should be followed. Descriptive, inferential, or thematic analysis techniques should be used to analyze the data. Lastly, the impact measurement plan should be reviewed and adjusted periodically based on data findings and feedback. This includes checking if the impact goals, indicators, data sources, methods, and tools are still relevant, realistic, and reliable while addressing any challenges or opportunities in the impact measurement process.