Many organizations collect large amounts of information intake forms, encounter notes, referral logs, survey data but the systems are fragmented, and it can be hard to see the full picture. Ensightics helps turn this patchwork into a more coherent data environment that supports routine tracking, equity-focused analysis, and clear communication.

This includes both behind-the-scenes data work and front-end visualizations, as well as emerging AI-supported tools that can streamline routine evaluation tasks.

How Ensightics can help

• Clean and manage survey, administrative, and program data, including coding, recoding, and documentation
• Support quantitative and qualitative analysis including descriptive, bivariate, and multivariate analyses matched to real-world data quality and sample sizes
• Integrate multiple datasets, when feasible, to tell a more complete story of client reach, services, and outcomes
• Design pragmatic data systems and workflows that specify who collects what, when, and how, and how data are checked and stored
• Build simple dashboards and visual summaries so staff, leaders, and funders can track implementation, outcomes, and equity indicators at a glance
• Create one-page data snapshots or scorecards for boards, advisory groups, and community partners
• Provide “rescue analytics” when data are messy, incomplete, or stuck salvaging what is useful and being transparent about limitations
• Develop or refine online data collection tools (e.g., Qualtrics, REDCap, or similar platforms), along with codebooks and data dictionaries
• (Optional / future) Integrate the Ensightics AI Evaluation Assistant, a guided online tool that helps generate draft logic models, indicator tables, and simple summaries based on program descriptions