Data Analysis and Interpretation in Monitoring and Evaluation
Author: Dr. Anna Neya Kazanskaia
Publisher: NEYA Global Publishing
Journal: NEYA Global Journal of Non-Profit Studies (ERDO)
Year: 2025
DOI: https://doi.org/10.64357/neya-gjnps-me-analysis-2025
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About the Article
Data analysis and interpretation are central to Monitoring and Evaluation (M&E), transforming raw data into actionable insights that guide program design, decision-making, and accountability. This article explores quantitative and qualitative approaches, examining methods such as descriptive and inferential statistics, coding, thematic analysis, and narrative inquiry. Triangulation is emphasized as a critical strategy to enhance validity by integrating diverse data sources, methods, and perspectives.
The discussion also highlights interpretation practices, including contextualization, data disaggregation, and effective communication with stakeholders. Special attention is given to low-resource settings, where organizations must rely on affordable tools, streamlined indicators, and local capacity building to maintain rigor. By combining methodological precision, ethical responsibility, and contextual sensitivity, the article shows how data analysis and interpretation strengthen program learning, equity, and long-term impact in international development.
Key Topics
- Role of data analysis in M&E systems
- Quantitative methods: descriptive and inferential statistics
- Qualitative methods: coding, thematic and narrative analysis
- Software tools for analysis (SPSS, R, NVivo, Atlas.ti)
- Triangulation for credibility and validity
- Interpretation practices and data disaggregation
- Ethical principles in analysis and reporting
- Strategies for low-resource contexts
Academic Value
This article bridges methodological theory and applied practice in M&E by presenting a comparative review of analytical approaches. It highlights the complementary value of quantitative and qualitative traditions and underscores the importance of triangulation for credibility. For academics, it contributes to debates on adaptive and mixed-method evaluation strategies. For practitioners, it provides practical guidance for applying rigorous yet cost-effective analysis in diverse development settings. By framing interpretation as both analytical and ethical, the article positions data analysis as a cornerstone of sustainable and accountable development practice.
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