What are the best practices for ensuring unbiased program evaluations?

2 Choose appropriate and diverse methods and sources

The second step to avoid bias is to choose appropriate and diverse methods and sources of data collection and analysis. Methods and sources should be selected based on their suitability, validity, reliability, and ethical considerations for the evaluation questions and the program context. Methods and sources should also be diverse, meaning that they should use a mix of quantitative and qualitative approaches, and triangulate data from different perspectives, such as beneficiaries, staff, partners, or experts. Diversifying methods and sources can help to reduce the risk of bias by cross-checking and corroborating the evidence.

3 Involve stakeholders and ensure transparency

The third step to avoid bias is to involve stakeholders and ensure transparency throughout the evaluation process. Stakeholders are the people who have an interest or a stake in the program or the evaluation, such as funders, implementers, beneficiaries, or policymakers. Involving stakeholders can help to avoid bias by ensuring that the evaluation is relevant, responsive, and inclusive of different views and experiences. Transparency means that the evaluation process, methods, assumptions, limitations, and findings are clearly documented and communicated to the stakeholders and the public. Transparency can help to avoid bias by enhancing the accountability, credibility, and usability of the evaluation.

4 Address and mitigate potential sources of bias

The fourth step to avoid bias is to address and mitigate potential sources of bias that might affect the evaluation design, implementation, or reporting. Common sources of bias include selection bias, measurement bias, confirmation bias, and reporting bias. To address these sources of bias, the evaluator or stakeholder should use appropriate sampling techniques and criteria to ensure representativeness and diversity of the sample or participants. Additionally, data collection tools or instruments should be tested and validated to ensure accuracy, consistency, and sensitivity of the measurements. Alternative or opposing evidence or viewpoints should be sought and considered to challenge assumptions and expectations about the program. Lastly, data and findings should be reported in a balanced, comprehensive, and honest way while acknowledging the strengths, weaknesses, and limitations of the evaluation.

5 Seek external feedback and verification

The fifth step to avoid bias is to seek external feedback and verification from independent and qualified experts or peers. External feedback and verification can help to avoid bias by providing an objective and critical assessment of the evaluation process, methods, findings, and recommendations. External feedback and verification can also help to improve the quality, validity, and reliability of the evaluation, and to identify and address any gaps, errors, or inconsistencies. External feedback and verification can be sought at different stages of the evaluation, such as the design, implementation, or reporting stage, and can take different forms, such as peer review, quality assurance, or audit.

6 Reflect and learn from the evaluation experience

The sixth and final step to avoid bias is to reflect and learn from the evaluation experience. Reflection and learning can help to avoid bias by encouraging the evaluator and the stakeholder to examine their own values, assumptions, and behaviors that might have influenced the evaluation, and to identify and apply the lessons learned for future evaluations. Reflection and learning can also help to enhance the utility and sustainability of the evaluation, and to foster a culture of learning and improvement within the program and the organization. Reflection and learning can be done individually or collectively, formally or informally, and can involve different tools or techniques, such as self-assessment, feedback, debriefing, or action planning.