dashboard-redesignlisted

# Dashboard Redesign Design a decision instrument, not a wall of metrics. Preserve useful density, expose the comparisons that matter, and make data quality and scope legible. ## 1. Establish the decision model Identify: - users: primary role, expertise, frequency, environment, devices, display duration, accessibility, and export needs; - decisions: required actions, monitoring cadence, acceptable time to notice, and the workflow from signal through investigation to action; - data: metric definitions, owners, sources, freshness, and latency; - context: required comparisons, targets, thresholds, and segments. If these are unknown, state assumptions and mark metric semantics for owner validation. Never infer that a visible number is a KPI. **Checkpoint:** State assumptions, have the data owner validate metric meaning and thresholds, revise the decision matrix and affected representations, then re-check until every unresolved semantic question is explicitly marked for decision. Classify the surface using [references/dashboard-models.md](references/dashboard-models.md). A monitoring board, executive scorecard, operational queue, and analytical workspace need different density and interaction. ## 2. Inventory decisions before widgets Build a compact matrix: `Decision | Signal | Comparison | Grain | Freshness | Action | Failure cost` Synthetic example: `Which route needs intervention? | Risk state | Operations threshold and shift target | Route | Per vehicle | Open incid