What type of data does ADB prioritize for success measurement?

The Asian Development Bank (ADB) emphasizes the importance of quantitative data that reflects project outcomes for measuring success. This type of data is critical because it provides objective, measurable results that can be analyzed statistically. Quantitative data allows ADB to assess the effectiveness of its projects, track progress against established indicators, and evaluate their impact on the target populations and sectors.

Using numerical data can reveal trends, identify areas for improvement, and support evidence-based decision-making. By prioritizing quantitative outcomes, ADB ensures that stakeholders can have a clear understanding of project effectiveness and how resources are being utilized to achieve desired results.

While personal testimonials, historical data, and expert opinions can be valuable in their own right, they often lack the rigorous structure and reliability of quantitative measures. Personal testimonials can be subjective and vary widely, historical data may not always reflect current project contexts, and expert opinions might introduce bias. Hence, the focus on quantitative data within ADB's methodologies underpins a commitment to transparency, accountability, and continuous learning in development efforts.