Interpretation Layers

Interpretation Layers

Interpretation layers apply a configurable analysis lens on top of your report's raw aggregated data. Each type serves a different purpose.

None (Raw Data Only)

Presents numbers exactly as they are — averages, pass rates, score distributions — without any added analysis or labels.

Best for: Getting a clear, unbiased picture of the data before applying any judgment.

Threshold-Based (Strength/Weakness)

Compares each score against configurable thresholds:

• •Scores above the strength threshold (default: 80%) are tagged as Strengths
• •Scores below the weakness threshold (default: 50%) are tagged as Weaknesses
• •Scores in between are labeled Neutral

Best for: Compliance officers who need to quickly identify which areas are performing well and which need attention. Useful for executive summaries and board reporting.

Example: A domain scoring 85% gets a green "Strength" badge, while one scoring 42% gets a red "Weakness" badge.

Binary Gate (Any Fail = Audit Fails)

The strictest interpretation. Any element in the scope that has a failing verdict marks the entire group as "Fail." This is an all-or-nothing evaluation.

Best for: Strict audit environments where 100% compliance is required. Useful for regulatory audits where a single failure has consequences.

Example: If 46 out of 47 assessments pass but one fails, the entire report shows "Fail."

Quartile Analysis (Top/Bottom 25%)

Ranks all items by score and highlights the top and bottom quartiles:

• •Items in the top 25% are tagged "Top 25%"
• •Items in the bottom 25% are tagged "Bottom 25%"

Best for: Benchmarking vendors, teams, or business units against each other. Useful when you want relative comparison rather than absolute thresholds.

Example: In a vendor assessment program, quartile analysis quickly identifies your best and worst performing vendors.

Choosing the Right Layer