Analysis Guide

Generally, what are the characteristics of the people who live in my organization’s service area and have income below my organization’s poverty limit?

Generally, what are the characteristics of the people who request assistance from my organization (those for whom we conduct prescreens and/or intakes)?

Generally, what are the characteristics of the people my organization serves and those it rejects?

Generally, what are the characteristics of the people who receive limited service and/or extended service, who achieve positive outcomes or not, and/or are served by staff or pro bono volunteers?

Generally, how many hours does my organization work on different tasks for different people with different legal needs?

Definition: Snapshot analysis measures counts or percentages for a specific period, typically the most recently completed year, quarter, or month. It provides a snapshot of the current state of your data.
Purpose: Establishes a baseline or identifies unexpected results requiring further analysis.
Examples:

• Total number of cases handled in the last year.
• Percentage of clients served by demographic category (e.g., age, gender).

Key Insight: If any counts or percentages are unexpected, follow up with comparison, trend, or spatial analyses to explore possible reasons.

Definition: Comparison analysis examines relationships between two or more variables to uncover insights about client conditions or data linkages.
Purpose: Highlights disparities, disproportionalities, differences, relationships, or conditions requiring further investigation.
Examples:

• Comparing service rates by gender or ethnicity.
• Analyzing links between poverty levels and case types.

Key Insight: When unexpected differences arise by demographics or legal problem, investigate to understand the data relationships and determine whether advocacy or services targeting multiple conditions are needed.

Definition: Trend analysis examines changes over time to identify patterns, spikes, or dips in client conditions or service needs.
Purpose: Tracks improving and/or worsening conditions, progress or regress, and emerging issues.
Examples:

• Monitoring increases in housing-related cases over five years.
• Tracking the seasonal variation of client intakes.

Key Insight: Analyze trends over a five-year period (or longer when possible). Unexpected changes, such as spikes or dips, may confirm expectations or raise new questions about whether proactive steps are necessary.

Definition: Geographic concentration analysis compares high or low concentrations of multiple variables to understand how location impacts client conditions. It often uses location quotients (LQs) to quantify concentrations.
Purpose: Highlights areas where services could be ramped up to better meet client need, and pinpoints "hotspots" or regions with specific emerging needs or resources.
Examples:

• Identifying neighborhoods with higher-than-expected concentrations of eviction cases.
• Comparing service levels with poverty concentrations across regions.

Key Insight: Concentration analysis reveals the interplay between variables and locations, helping you understand how geographic factors influence service needs or outcomes.

Definition: Geographic distribution analysis examines how people, problems, or resources are distributed across a service area. Dividing the area into smaller subregions reveals spatial patterns.
Purpose: Identifies spatial dimensions of your organization’s reach and client needs.
Examples:

• Mapping cases by zip code.
• Showing distribution of foreclosure cases across counties.

Key Insight: Spatial patterns provide opportunities to learn about the geographic dimensions of your services and client needs, highlighting where interventions may be needed.