Research Strategy and Study Design

Transform an important question into a clear, feasible research or evaluation plan.

A defensible study begins before data collection. The question, population, measures, methods, operating conditions, and intended decision must fit together. When they do not, even technically competent research can produce an answer that is difficult to interpret or use.

Aster & Axiom works with clients to clarify what they need to learn, what evidence could reasonably answer the question, and what design is feasible within the available time, population, data, budget, and organizational setting.

This work is useful when:

• A broad topic needs to become a specific, answerable research question
• A team has selected a method before fully defining the decision or problem
• Several possible designs are available, but their tradeoffs are unclear
• Recruitment, measurement, data access, or implementation constraints may affect feasibility
• A program needs an evaluation plan tied to its actual objectives
• Existing data require careful interpretation and responsible translation
• A proposed conclusion is stronger than the available design can support

Support may include:

• Research question development: Clarify the decision the research must inform, define the population and setting, specify the relevant constructs or outcomes, and identify assumptions that should be tested rather than accepted.
• Qualitative, quantitative, and mixed-methods design: Select methods that fit the question and explain the tradeoffs involving depth, measurement, sampling, inference, timing, and feasibility.
• Survey and interview development: Develop questionnaires, interview guides, focus-group protocols, response structures, and administration plans aligned with the intended analysis and use.
• Feasibility and implementation planning: Examine recruitment, participation burden, workflow, staffing, data availability, timing, governance, and other operating conditions that may affect execution.
• Program evaluation: Develop evaluation questions, logic models, measures, data-collection plans, and interpretation frameworks that connect program activity with meaningful outcomes.
• Data interpretation and research translation: Assess what the findings support, where uncertainty remains, which conclusions are reasonable, and how results should inform decisions, communication, or further study.

Representative deliverables

• Research or evaluation design brief
• Refined research questions and objectives
• Logic model or theory of change
• Study framework or protocol outline
• Sampling and recruitment plan
• Survey, interview, or focus-group instruments
• Measurement and analysis framework
• Feasibility assessment
• Evaluation plan
• Evidence or interpretation brief
• Research translation materials

The finish line

You have a research or evaluation plan that is methodologically coherent, operationally realistic, and explicit about its assumptions and limitations. The team understands what the work can answer, what it cannot answer, and what decision the resulting evidence is intended to support.