Research, Evaluation & Data
This work focuses on making data useful. Research and evaluation are not about reports that sit on a shelf or metrics collected for compliance. They are tools for understanding what is actually happening, what is working, and where adjustments are needed to improve outcomes.
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We work with organizations that need clear insight, credible findings, and practical recommendations they can act on. This includes program evaluation, applied research, needs assessments, and data-informed decision-making that supports accountability, learning, and performance.
Program Evaluation & Assessment
Designing and conducting evaluations that measure effectiveness, relevance, and impact. This includes formative and summative evaluation, outcome tracking, and process analysis.
Applied Research and Data Collection
Qualitative and quantitative research to understand experiences, needs, gaps, and trends. Methods may include interviews, focus groups, surveys, document review, and data analysis.
Logic Models and Theory of Change
Clarifying how programs are intended to work, what assumptions are being made, and where breakdowns or misalignment may exist.
Performance Measurement & Indicators
Developing meaningful metrics that align with goals and funder or regulatory requirements without overburdening staff.
Reporting & Data Translation
Turning findings into clear, usable reports, dashboards, and presentations that support decision-making and communication with stakeholders.
Continuous Improvement Support
Using data to inform adjustments, strengthen implementation, and improve results over time rather than treating evaluation as a one-time activity.
Our Approach
This work is grounded in a strengths-based, participatory approach. We engage leadership, staff, and stakeholders as contributors to the evaluation process, not just subjects of it. Existing strengths, effective practices, and on-the-ground expertise are identified and built upon alongside areas for improvement.
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In practice, this includes collaborative planning sessions, shared sense-making of findings, and facilitated discussions that help teams interpret data in context. The result is greater buy-in, more accurate insights, and findings that feel relevant and usable rather than imposed.
Data becomes a tool for learning and improvement, not judgment or compliance.