How should claims in EI be supported if data is missing?

• A. Provide qualitative evidence, describe plans to collect data in the future, and provide transparent explanations.
• B. Ignore the missing data and proceed.
• C. Fabricate data to fill gaps.
• D. Use only qualitative evidence, with plans to collect data in the future.

Answer: (D)

When data is missing, the strongest way to support claims is to rely on qualitative evidence that describes the context, process, and perceived outcomes, paired with a clear plan to collect the missing data in the future. Qualitative evidence—such as stakeholder feedback, user observations, case descriptions, and narrative outcomes—can illustrate impact and feasibility without overstating measurable results. Stating a concrete plan to gather data later shows a commitment to evidence-based evaluation and continuous improvement. Avoiding data fabrication and not leaving claims unsupported is essential, and focusing on qualitative descriptions now while outlining how quantitative data will be obtained later keeps the claims honest and credible.