danielpradilla Dashboard Decision Brief
Use this workflow to convert a business question or monitoring need into a complete, implementation-ready dashboard specification. The output gives a data engineer or BI developer everything they need to build without a follow-up meeting.
Required Inputs
Ask the user for these if not provided:
- The business question this dashboard should answer (e.g. "How is our activation funnel performing this week?")
- Primary audience (exec / product team / operations / customer success / engineering)
- Refresh cadence (real-time / hourly / daily / weekly)
- Data sources available (e.g. Postgres, BigQuery, Mixpanel, Salesforce, Jira)
- BI tool being used (Looker / Metabase / Tableau / Power BI / Grafana / Custom / Unknown)
Output Structure
Dashboard Brief: [Dashboard Name]
Business Question: [The question this dashboard answers - verbatim from inputs or refined] Audience: [Who uses this] Refresh Rate: [Real-time / Hourly / Daily / Weekly] Data Sources: [List] BI Tool: [Tool or Unknown]
Section 1: Key Metrics (KPI Cards)
List the headline numbers that should appear at the top of the dashboard as KPI cards.
| Metric | Definition | Data Source | Comparison |
|---|---|---|---|
| [Metric name] | [How it's calculated] | [Table/source] | [vs. last week / vs. target / MoM] |
Aim for 3–6 KPI cards. More than 6 is noise.
Section 2: Charts & Visualisations
For each chart, specify:
Chart [N]: [Chart Title]
- Chart type: [Line / Bar / Stacked bar / Pie / Funnel / Heatmap / Table / Scatter]
- Why this chart type: [One sentence - why this type suits this data]
- X-axis / Rows: [Dimension - e.g. Date, User segment, Product]
- Y-axis / Values: [Metric - e.g. Count of active users, Revenue]
- Breakdown/colour: [Optional secondary dimension - e.g. by Plan tier, by Channel]
- Data source: [Table or source]
- Filters: [Any default filters applied - e.g. "Exclude internal test accounts"]
- Key insight to surface: [What pattern or signal this chart should help the viewer spot]
Section 3: Filters & Controls
Global filters available to dashboard viewers:
| Filter | Type | Default | Options |
|---|---|---|---|
| Date range | Date picker | Last 30 days | Custom |
| [Segment filter] | Dropdown | All | [List relevant values] |
| [Other filter] | Multi-select | All | [List relevant values] |
Section 4: Layout Recommendation
Describe the dashboard layout in plain terms:
[ROW 1 - KPI Cards]: [Metric 1] | [Metric 2] | [Metric 3] | [Metric 4]
[ROW 2 - Primary chart, full width]: [Chart name]
[ROW 3 - Two charts side by side]: [Chart A] | [Chart B]
[ROW 4 - Supporting table, full width]: [Table name]
Section 5: Data Requirements
List any data transformations, joins, or derived fields needed:
| Derived Field | Logic | Source Tables |
|---|---|---|
| [Field name] | [How it's calculated] | [Tables involved] |
Flag any fields that may not exist in current data infrastructure.
Section 6: Access & Ownership
- Dashboard owner: [Leave for user to fill]
- Who can edit: [Leave for user to fill]
- Who can view: [Leave for user to fill]
- Review cadence: [When should this dashboard be reviewed for relevance?]
Quality Checks
- Every chart has a stated "key insight to surface" - not just "show the data"
- KPI cards are 3–6 (not more)
- Chart types are justified
- Layout follows visual hierarchy (summary → detail)
- Data requirements section flags any missing fields
- Filters are practical and don't require IT to configure