Bad data leads to bad decisions. A program that reports 80% adoption based on poorly collected survey data is worse off than one that honestly reports "we don't know yet." This hub covers the five dimensions of data quality (validity, reliability, timeliness, precision, integrity), practical assessment tools, the difference between cleaning and re-collecting, and the common quality problems that plague M&E systems. The DQA Scorecard and Review Studio tools help you assess quality systematically.
Side-by-side comparisons, decision trees, and practical guidance for common M&E decisions.