Framework Metrics & Scoring: How Scores Are Computed

Metrics are the bridge between the data your clients submit and the scores they receive. Each pillar in your framework is scored from one or more metrics, and those pillar scores combine into the composite score the client sees. This guide explains how metrics work, how to configure them, how per-tier overrides change the weighting, and how it all connects to what clients submit.

💡 Tip — Who can use this For firm admins. Read the Framework Basics guide first — this builds on it.

Quick reference

Step 1 — Understand how metrics drive scores

Here's the scoring chain, from client input to the number on their dashboard:

1. The client submits data on the Submit Data page — financial metrics, people metrics, operational metrics, strategic priorities (rocks), and transformation initiatives.
2. Each metric is scored against a benchmark. For "higher is better" metrics (like margin or on-time delivery), the score rises as the actual value approaches or beats the benchmark. For "lower is better" metrics (like churn or attrition), the score rises as the value drops below the threshold. Each metric gets a 0–100 score.
3. The pillar score is computed from its metrics, weighted by the weights you set in the Metrics section. If a pillar has multiple metrics, each contributes its weighted share.
4. The composite score blends the pillar scores using the pillar default weights (or per-tier overrides), producing the single 0–100 number the client sees as their Strategic Health Score.

📝 Note — The framework defines the formula; the client's data provides the inputs Your framework's metrics, weights, and benchmarks define how scoring works. The client's submitted data provides what gets scored. A well-designed framework produces meaningful scores from the data your clients actually submit — so choose metrics your clients can and will report on.

💡 Tip — Metrics map to submission fields Every metric in the dropdown corresponds to a specific field (or set of fields) the client enters. For example, "Gross Profit Margin" reads the margin field from their financial submission; "Rocks On-Track Ratio" reads the status of their strategic priorities. If a client doesn't submit the field a metric depends on, that metric (and potentially its pillar) shows "No data."

Step 2 — Add and configure metrics

Open a pillar's Metrics section (collapsed by default — click to expand). Click + Add Metric to add a metric row.

Each metric row has:

• Metric — a dropdown of the 19 scoreable metrics (Revenue Targets Met, Gross Profit Margin, Delivery On-Time Rate, Initiative Completion Rate, Voluntary Attrition Rate, Average Tenure, Time-to-Fill, Training Hours, Rocks On-Track Ratio, Customer Retention, Cash-to-Revenue, Issue Resolution, Initiative Stage Progression, Investment Intensity, Decision Velocity, Employee Engagement, Avg Issue Resolution, Customer Churn, Rocks Off-Track Count). Pick the metric(s) that best represent this pillar.
• Weight — how much this metric contributes to the pillar's score (entered as a decimal: 0.5 = 50%). Metric weights within a pillar should ideally sum to 100%.
• Required — if checked, the pillar can't score without this metric's data. If a required metric is missing, the pillar shows "No data" rather than a partial score.
• Gated by — an optional condition that must be met before this metric counts (advanced; usually left as "no gate").
• Remove — deletes the metric row.

A live warning shows the current sum of metric weights: "Metric weights sum to X% — the engine re-normalizes at score time, but 100% is recommended."

📝 Note — What "re-normalizes" means If your metric weights don't sum to exactly 100%, the scoring engine automatically rescales them so they do at score time. For example, if two metrics each have 50% weight (totaling 100%), each contributes half the pillar score. If they each have 30% (totaling 60%), the engine scales them up proportionally — each still contributes half. This prevents errors, but setting weights to sum to 100% explicitly keeps your intent clear and avoids surprises.

💡 Tip — Choose metrics that fit the pillar Pick metrics that genuinely reflect what the pillar measures. For a "Financial Health" pillar, Gross Profit Margin and Cash-to-Revenue make sense; for an "Operational Excellence" pillar, Delivery On-Time Rate and Issue Resolution Speed fit. Avoid stuffing unrelated metrics into a pillar just because they're available — it muddies the score's meaning.

Step 3 — Set per-tier weight overrides

Each pillar has a default weight (set in the pillar header — see the Basics guide). But you can override how much a pillar counts for clients on specific tiers. Expand the Per-Tier Weight Overrides section to see five tier slots: trial, pulse_ai, access, partner, and executive.

Enter a weight (decimal) for any tier where you want the pillar to count differently from the default. A tier with no override uses the pillar's default weight.

📝 Note — Why per-tier overrides exist Different engagement levels deserve different strategic emphasis. On an Executive engagement, you might weight Transformation and Intelligence more heavily (forward-looking, strategic pillars) and Results less (the executive already knows their financials). On an Access engagement, the opposite might be true. Per-tier overrides let one framework serve multiple engagement depths without creating separate frameworks for each tier.

⚠️ Warning — Tier overrides must also total 100% If you set overrides for a tier, the overridden pillar weights for that tier must still sum to 100%. Only override pillars where you want a different weight — leave the rest blank to use their defaults, and make sure the total (including defaults for non-overridden pillars) reaches 100%.

The connection to client-submitted data

This is the most important thing to understand: your framework only scores what clients submit.

Every metric in your framework reads from specific submission fields. When a client submits their monthly data:

• Metrics with submitted data are scored against their benchmarks.
• Metrics without submitted data are skipped (the pillar shows "Partial data" if some metrics are present, "No data" if none are).
• Flag rules (see the Flag Rules guide) check submitted values against thresholds and raise amber/red flags.

So if your framework uses metrics your clients don't submit, those pillars will consistently show partial or no data. Design your framework around the data your clients can realistically report.

💡 Tip — Audit your framework against the submission form Open the Submit Data page (as a partner reviewing a client) and compare its fields to your framework's metrics. Every metric should map to a field the client is asked to fill in. If a metric has no corresponding submission field, either remove it from the framework or work with your admin to add the field to the submission form.

Related guides:

• Framework Basics — pillars, weights, descriptions, and the editor overview.
• Framework Flag Rules — configuring the thresholds that raise flags.