Here’s a simple way to make “risk budget” feel like a real, live dashboard rather than a dusty policy—plus the one visualization that best explains “budget burn” to PMs.

### First, quick background (plain English)

* **Risk budget** = how much unresolved risk we’re willing to carry for a release (e.g., 100 “risk points”).
* **Burn** = how fast we consume that budget as unknowns/alerts pop up, minus how much we “pay back” by fixing/mitigating.

### What to show on the dashboard

1. **Heatmap of Unknowns (Where are we blind?)**

   * Rows = components/services; columns = risk categories (vulns, compliance, perf, data, supply-chain).
   * Cell value = *unknowns count × severity weight* (unknown ≠ unimportant; it’s the most dangerous).
   * Click-through reveals: last evidence timestamp, owners, next probe.

2. **Delta Table (Risk Decay per Release)**

   * Each release row compares **Before vs After**: total risk, unknowns, known-high, accepted, deferred.
   * Include a **“risk retired”** column (points dropped due to fixes/mitigations) and **“risk shifted”** (moved to exceptions).

3. **Exception Ledger (Auditable)**

   * Every accepted risk has an ID, owner, expiry, evidence note, and auto-reminder.

### The best single chart for PMs: **Risk Budget Burn-Up**

*(This is the one slide they’ll get immediately.)*

* **X-axis:** calendar dates up to code freeze.
* **Y-axis:** risk points.
* **Two lines:**

  * **Budget (flat or stepped)** = allowable risk over time (e.g., 100 pts until T‑2, then 60).
  * **Actual Risk (cumulative)** = unknowns + knowns − mitigations (daily snapshot).
* **Shaded area** between lines = **Headroom** (green) or **Overrun** (red).
* Add **vertical markers** for major changes (feature freeze, pen-test start, dependency bump).
* Add **burn targets** (dotted) to show where you must be each week to land inside budget.

### How to compute the numbers (lightweight)

* **Risk points** = Σ(issue_severity_weight × exposure_factor × evidence_freshness_penalty).
* **Unknown penalty**: if no evidence ≤ N days, apply multiplier (e.g., ×1.5).
* **Decay**: when a fix lands *and* evidence is refreshed, subtract points that day.
* **Guardrail**: fail gate if **unknowns > K** *or* **Actual Risk > Budget** within T days of release.

### Minimal artifacts to ship

* **Schema:** `issue_id, component, category, severity, is_unknown, exposure, evidence_date, status, owner`.
* **Daily snapshot job:** materialize totals + unknowns + mitigations per component.
* **One chart, one table, one heatmap** (don’t overdo it).

### Copy‑paste labels for the board

* **Top-left KPI:** “Headroom: 28 pts (green)”
* **Badges:** “Unknowns↑ +6 (24h)”, “Risk retired −18 (7d)”, “Exceptions expiring: 3”
* **Callout:** “At current burn, overrun in 5 days—pull forward libX fix or scope‑cut Y.”

If you want, I can mock this with sample data (CSV → chart) so your team sees exactly how it looks.