The systematic analysis of grant data enables non-profit organizations to transform information into insight, strengthen accountability, and enhance program performance. This article examines qualitative, quantitative, and mixed-method approaches for interpreting data within diverse operational contexts. It highlights how techniques such as thematic analysis, content analysis, descriptive statistics, and inferential testing can help organizations assess outcomes, identify patterns, and make evidence-based improvements. Emphasis is placed on practical, low-cost solutions suitable for resource-constrained environments, including the use of tools such as Excel, Google Sheets, SPSS, and R. Ethical considerations and participatory validation processes are also explored, ensuring that findings are both credible and contextually grounded. By integrating analysis into program cycles, non-profits can move beyond compliance toward adaptive learning and strategic refinement, strengthening trust with both funders and communities.
Anna Neya Kazanskaia (Wed,) studied this question.