Executive KPI Dashboard

Generate executive KPI monitoring dashboards for the latest closed month.

Creates both Excel dashboards (for analysis) and PowerPoint one-pagers (for meetings).

Arguments

Data Discovery

Before fetching any numbers, discover what the org actually has: list_data_models for the financials table, then get_fields_by_id / list_aliased_fields for its fields. Never assume field names, scenario values, or metric availability — they differ per org.

Async fetch — aggregations and distinct values run as start → poll. start_aggregation_by_id/_by_alias and start_distinct_values_by_id/_by_alias take the same arguments as the retired blocking calls (dimensions/metrics/filters; table id + field id, or alias + field alias) and return immediately with {"status": "pending", "handle": {...}}. Echo that handle back verbatim to the matching get_aggregation_result_by_* / get_distinct_values_result_by_* tool: a {"status": "running", "retry_after_seconds": N} response means poll again with the same handle after ~N seconds (≈5s) — it is not an error, and large jobs may take several polls; when ready, the result arrives in the familiar shape (for distinct values, pass limit to the result tool). An expired/unknown-handle error means restart with the start_* tool. Transitional fallback: if the start_* tools aren't available on the connector (older server), the blocking twins get_aggregated_data_by_* / get_distinct_values_by_* still work with the same arguments.

Data-scope discovery — run before any aggregate (reuse anything already discovered this conversation).

1. Scenario domain. Pull distinct values of the scenario field (start_distinct_values_by_alias/_by_id → poll the matching result tool) — never assume a scenario name exists (Budget frequently doesn't; many orgs carry only {Actuals, Forecast}). For budget/plan questions, if no budget-like scenario exists, look for a planning-version-like field (alias/name matching /plan|version|cycle|budget/i) and use its versions as the plan side; if neither exists, say so and offer a comparison across the scenarios that do exist.
2. Account grain. Pull distinct values of each account-hierarchy level field (L0/L1/L2-like). Use the level whose values partition P&L flows into revenue/COGS/opex-like buckets — on many orgs the top level is the balance-sheet equation (ASSET/LIABILITY/EQUITY/INCOME) and P&L line items live one level deeper. For P&L work, scope to P&L flows and exclude balance-sheet buckets; never present asset/liability/equity totals as revenue or expenses.
3. Period scope. Discover the date field's range (distinct values of the reporting-month field, or MIN and MAX in two separate calls — one aggregation per field per call). Default every P&L question to the latest complete fiscal year (or trailing 12 closed months) — never an unscoped all-time total: financials tables are multi-year cumulative and mix balance-sheet stock with P&L flow. Label every output with the period + scenario it covers.
4. Reading GROUP BY responses. Each response returns exactly one row per requested group — no subtotal rows and no grand-total row. A total is obtained by summing the rows — there is no total row to read. Null groups arrive explicitly labeled [null] and are real groups; read null counts from that bucket. Defensive filter: keep only rows in which every requested dimension key is present — a roll-up row omits one or more keys entirely, whereas a genuine null is present with the value [null]. On a correct response this is a no-op; it guards against a stale cached response still carrying legacy subtotal and grand-total rows, each of which equals the whole total and would inflate any sum. When COUNT-ing rows per group, aggregate a different field than the GROUP BY dimension itself — a same-field COUNT of the grouped dimension can 500.
5. Truncated results. Any data tool may return {"data": [...], "truncated": true, "total_rows": N, "returned_rows": M, "guidance": "..."} when the result exceeds the response size limit (~100 KB). The data prefix is incomplete — never compute totals, shares, or trends from it, and never present it as the full result. Follow the guidance: narrow the query (fewer dimensions, more filters, fewer selected columns) or use a business metric for a named KPI, then re-fetch.

Key Metrics Included

Render only KPIs you can source. A KPI may come from (a) the org's metric catalog — list_business_metrics (ungated) for discovery; the get_business_metric_* data tools are feature-gated and may be absent, and USER-kind metrics often return empty — or (b) aggregation over the discovered P&L grain (revenue, expense buckets, gross/operating margin when COGS/OpEx-like buckets exist). SaaS/unit-economics metrics (ARR, MRR, churn, LTV, CAC, burn, runway, NRR) are not derivable from a P&L table — include them only if discovered as populated metrics; otherwise omit the card/slide entirely. Never render a placeholder, estimate, or fabricated value for a KPI you could not source.

The lists below are candidates, not guarantees — each card renders only when sourceable per the rule above:

Growth & Revenue:

• ARR (Annual Recurring Revenue)
• Revenue
• MoM/QoQ growth rates

Health & Efficiency:

• Churn rate (%)
• LTV (Lifetime Value)
• CAC (Customer Acquisition Cost)

Operational:

• Burn rate (monthly)
• Runway (months of cash)
• Burn multiple

Custom Metrics: Any KPI in your data (adapts to profile)

Datarails Brand Styling

When generating Excel or PowerPoint files, apply Datarails brand styling:

Font: Poppins (fall back to Calibri if unavailable). Weights: 400 regular, 600 semibold, 700 bold.

Colors:

Excel layout:

• Content starts at column B (column A is a narrow gutter)
• Rows 1-6: header banner with navy background, white title text, white subtitle
• Gridlines OFF. Freeze panes at B7.
• Footer as last row with generation date
• Every cell must have font, fill, alignment, and number format set

Number formats: _(* #,##0_);_(* (#,##0);_(* "-"_);_(@_) (default), $#,##0 (dollars), $#,##0.0,,"M" (millions), 0.0% (percent)

Variance coloring: Any cell showing a delta/change: green (2ECC71) if favorable, red (E74C3C) if unfavorable. Apply automatically based on value sign and metric context.

PowerPoint: Navy (0C142B) background, 16:9 widescreen, Poppins font, white text, amber (FFA30F) accent lines, card backgrounds 001F37.

DR.GET Formulas — Authoring Contract

If asked to add live / refreshable Datarails formulas (DR.GET) to a generated workbook, the only valid form is:

=DR.GET(Value, "[DimensionName]", CellRef, "[DimensionName]", CellRef, ...)

• Never transliterate an MCP/API call into a formula. DR.GET takes no table, field, or aggregation arguments — =DR.GET(Value,"financials","Amount","SUM",...) is invented syntax that the Datarails Add-in cannot parse or refresh.
• Dimension names go in square brackets inside quotes ("[Scenario]"). Dimension values are always cell references, never hardcoded strings.
• Date cells referenced by formulas hold end-of-month date serials computed from the calendar — never raw epoch timestamps from API responses (epochs land a day early with a time component and never match).
• Before writing any formula, create the workbook-scoped defined name Value referring to the string constant "Value" (wb.defined_names.add(DefinedName("Value", attr_text='"Value"'))) — otherwise Excel autocorrects the bare token to its built-in VALUE() and the formula breaks.
• Bare =DR.GET(...) only — never wrapped in IFERROR/IF/ROUND.

The get-formula skill (/dr-get-formula) is the full reference — parameter cells, validated dimension values, report layouts. Prefer it for whole formula workbooks; apply this contract when adding DR.GET formulas to a workbook here.

Output

Excel Dashboard

• Summary sheet with top KPIs
• All Metrics sheet with complete list
• Current values
• Status indicators (✅ or ⚠️)
• Period + scenario label on every sheet and figure

PowerPoint One-Pager

• Single professional slide
• Top metrics in boxes
• Color-coded for quick scanning
• Period + scenario stated on the slide
• Generated timestamp
• Perfect for executive team syncs

Examples

Generate dashboard for the latest closed month

/dr-dashboard

Output (illustrative — your org's period, metric count, and values will differ):

📊 Generating dashboard for 2026-02...
  📈 Fetching KPI metrics...
  📊 Calculating trends...
  📋 Generating Excel dashboard...
  🎯 Generating PowerPoint one-pager...

✅ Dashboard generated successfully

==================================================
EXECUTIVE DASHBOARD
==================================================
Period: 2026-02
Metrics: 7

Outputs:
  Excel: tmp/Executive_Dashboard_2026-02-03_143022.xlsx
  PowerPoint: tmp/Dashboard_OnePager_2026-02-03_143022.pptx
==================================================

Specific month

/dr-dashboard --period 2025-12

With custom locations

/dr-dashboard \
  --output-xlsx reports/dashboard.xlsx \
  --output-pptx reports/dashboard.pptx

Use Cases

Daily Executive Sync

/dr-dashboard  # Use PowerPoint for standup

Weekly Team Update

# Share Excel for details, PowerPoint for overview
/dr-dashboard

Monthly Board Package

# Generate for month-end
/dr-dashboard --period 2026-01

Investor Demo

# Professional one-pager
/dr-dashboard --output-pptx investors_dashboard.pptx

Performance

• Generation: <2 minutes
• Real-time KPI data
• Scales to 100+ metrics
• Efficient aggregation

Color Coding

• ✅ Green - Positive metrics (high revenue, low churn)
• ⚠️ Yellow - Needs attention (rising burn, declining growth)
• 🔴 Red - Critical (low runway, high churn)

Features

Excel Dashboard:

• Sortable data
• Easy drill-down
• Print-friendly
• Shareable format

PowerPoint One-Pager:

• Executive-ready
• Meeting-ready (1 slide)
• Branded template
• Easy to share

Automated Updates

Schedule weekly updates:

# Every Monday at 8 AM
0 8 * * 1 /dr-dashboard \
  --output-pptx reports/weekly_dashboard.pptx

Integration

Works with:

• /dr-insights - Understand why metrics changed
• /dr-reconcile - Validate KPI accuracy
• /dr-anomalies-report - Check data quality
• /dr-extract - Get latest data

Related Skills

• /dr-insights - Detailed trend analysis
• /dr-reconcile - Validate KPI accuracy
• /dr-anomalies-report - Check data quality
• /dr-forecast-variance - Forecast vs actual