STEP 5
Justify Conclusions

Justifying conclusions based on evaluation evidence includes analyzing data, synthesizing data into findings, interpreting and making judgments, and making actionable recommendations.

Analyze the Data

Data analysis is the process of organizing and classifying the information you have collected, tabulating it, summarizing it, comparing the results with other appropriate information, and presenting the results in an easily understandable manner. There are a wide variety of techniques for data analysis and many free resources to learn more about data analysis.

In addition to applying the appropriate data analysis techniques to your data, consider how you want to make comparisons and how you want to examine the data to better understand what is happening in your program. This is an important consideration when we want to understand what works for whom and how. Looking at trends over time can be useful to show what is influencing changes or how strategies work together in a bigger picture.

Synthesize the Data

During data synthesis, you examine patterns in the results to:

Enhance understanding

Provide different perspectives

Provide a more complete story

Offset weaknesses of one method or limited data source

Corroborate and strengthen the evidence with multiple data sources

Address discrepancies

There are multiple ways to organize and display all findings to help you make sense of the data. You might choose to organize data by your logic model, evaluation questions, program components, or emerging themes.

Interpreting the Data

Data interpretation is the process of identifying what your findings mean. Findings are interpreted within the context of the program and are dependent on stakeholders’ perspectives and standards. Involving stakeholders in the interpretation leads to deeper understanding and facilitates use of the data.

Consider the following as you plan for the interpretation process:

Who will be involved in making interpretations and judgments? What process will be employed?

Against what standards will you compare your interpretations in forming your judgments?

How will you deal with conflicting interpretations and judgments?

For more information about data analysis, synthesis and interpretation, download the Data Analysis, Synthesis and Interpretation tip sheet.

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Considerations when Justifying Conclusions

In relation to the Evaluation Framework Standards, ask yourself the following questions:

Utility

Are different perspectives and approaches considered to interpret findings to account for methods limitations and alternate explanations?

Feasibility

Is the approach to analysis and interpretation appropriate given the situations, time periods, persons, contexts, and purposes for which the findings are applicable?

Propriety

Are the perspectives and values of those most affected by the program being considered?

Accuracy

Will the findings be misinterpreted or have conflicting interpretations?

Engaging Stakeholders at Step 5

Engage stakeholders in data interpretation using participatory techniques (e.g., data parties, data placements). This can help frame and contextualize your findings so that the conclusions are sound, reasonable, and relevant.