Business Intelligence & Forecasting

Vantage transforms raw data into executive-ready intelligence with purpose-built tiles for forecasting, scenario planning, and AI-generated insights. Every tile supports popup AI chat for on-demand analysis, making your dashboards not just displays — but interactive analytical tools.

Build an Executive KPI Dashboard with AI Insights

Build a real-time executive dashboard that tracks KPIs, detects anomalies, and generates written insights automatically.

Scenario: A COO needs a single dashboard that shows the health of the entire business — revenue, costs, customer metrics, and operational efficiency — with AI-generated commentary explaining what's changing and why.

Workflow Steps:

1. Schedule Trigger — Run every 30 minutes during business hours
2. Database Query (PostgreSQL) — Pull revenue, order volume, and average order value by business unit
3. Database Query (MSSQL) — Pull operational costs: labor, materials, overhead by department
4. List Customers (Stripe) — Pull active subscriber count, MRR, and churn events
5. Zendesk — Count Tickets — Pull open ticket count, average resolution time, and CSAT score
6. Join — Merge financial, operational, and customer metrics into a single executive dataset
7. Computed Column — Calculate derived KPIs:
   • Gross margin = (revenue - COGS) / revenue * 100
   • Customer acquisition cost = marketing_spend / new_customers
   • Efficiency ratio = revenue / total_headcount
8. Aggregation — Roll up by business unit and time period (daily, weekly, monthly)
9. AI Enrichment — Detect anomalies: flag any KPI that deviates > 2 standard deviations from its 30-day rolling average
10. Dashboard Output — Populate:
    • Metric Tile — Top-line KPIs: Revenue, MRR, Active Customers, Gross Margin (each with sparkline and trend indicator)
    • BI Intelligence Tile — AI-generated narrative: "Revenue is up 8% week-over-week, driven primarily by the Enterprise business unit. Customer acquisition cost increased 12%, potentially due to the Q4 marketing campaign. Support ticket volume spiked 23% — investigate the 'Billing' category for root cause."
    • Comparison Tile — This month vs. last month, this quarter vs. same quarter last year
    • Line Tile — Revenue trend with 12-month history
    • Bar Tile — Revenue and costs by business unit
    • Predictive Insights Tile — AI-detected anomalies with probability and impact assessment

Key Nodes: Schedule Trigger, Database Query (PostgreSQL, MSSQL), List Customers (Stripe), Zendesk Count Tickets, Join, Computed Column, Aggregation, AI Enrichment, Dashboard Output

Forecast Revenue and Model Budget Scenarios

Generate rolling revenue forecasts based on historical data and model budget scenarios.

Scenario: A CFO needs to compare actual revenue against budget and forecast the remainder of the fiscal year, with the ability to model different scenarios (optimistic, base, pessimistic).

Workflow Steps:

1. Schedule Trigger — Run weekly on Monday mornings
2. Database Query (PostgreSQL) — Pull 24 months of historical revenue data by product line, region, and channel
3. Database Query (MSSQL) — Pull the approved annual budget by the same dimensions
4. Join — Merge actuals with budget on period + dimension
5. Computed Column — Calculate:
   • Budget variance: (actual - budget) / budget * 100
   • Year-to-date actuals vs. YTD budget
   • Run rate: (YTD_actual / months_elapsed) * 12
6. Aggregation — Sum by product line and by quarter
7. AI Enrichment — Generate forecast adjustments: analyze trend momentum, seasonality patterns, and known upcoming events (product launches, price changes) to refine projections
8. Dashboard Output — Populate:
   • Forecast Tile — 6-month forward projection with confidence intervals (P10/P50/P90)
   • Scenario Planner Tile — Three scenarios:
     • Optimistic: top-line growth accelerates 15%
     • Base: current trajectory continues
     • Pessimistic: 20% demand reduction
   • Comparison Tile — Actual vs. budget by quarter
   • Waterfall Tile — Budget → favorable variances → unfavorable variances → actual
   • Line Tile — Historical + projected revenue trendline
   • Table Tile — Detailed budget-vs-actual by line item

Key Nodes: Schedule Trigger, Database Query, Join, Computed Column, Aggregation, AI Enrichment, Dashboard Output

Analyze Operational Efficiency Across the Business

Measure and optimize operational efficiency across departments with AI-powered benchmarking.

Scenario: A VP of Operations wants to identify bottlenecks, benchmark departmental efficiency, and surface improvement opportunities using data from across the business.

Workflow Steps:

1. Schedule Trigger — Run daily at 6 AM
2. Database Query (PostgreSQL) — Pull operational metrics: throughput, cycle time, error rate, utilization by department and process
3. Database Query (MSSQL) — Pull resource allocation: headcount, equipment hours, budget utilization
4. Join — Merge operational and resource data
5. Aggregation — Calculate efficiency metrics by department:
   • Throughput per FTE
   • Cost per unit processed
   • Error rate %
   • Capacity utilization %
6. Computed Column — Calculate efficiency index: (throughput_per_FTE * 0.3) + ((1 - error_rate) * 0.3) + (utilization * 0.2) + (budget_adherence * 0.2)
7. Sort — Rank departments by efficiency index
8. AI Enrichment — Generate recommendations: "Department 3 has the lowest efficiency index (62). Root cause analysis suggests the error rate (8.2%) is driving down the score. Implementing automated validation could reduce errors by an estimated 60%, improving the index to 78."
9. Dashboard Output — Populate:
   • Histogram Tile — Efficiency index distribution across all departments
   • Scatter Tile — Throughput vs. cost (identifies high-cost/low-output outliers)
   • Metric Tile — Company-wide efficiency index with trend
   • Pyramid Tile — Department ranking from most to least efficient
   • BI Intelligence Tile — AI-generated improvement recommendations
   • Predictive Insights Tile — Projected efficiency if recommendations are implemented

Key Nodes: Schedule Trigger, Database Query, Join, Aggregation, Computed Column, Sort, AI Enrichment, Dashboard Output

Aggregate Market and Competitive Intelligence

Combine internal performance data with external market intelligence for strategic decision-making.

Scenario: A strategy team wants to correlate internal sales performance with external market signals — news, competitor activity, and macroeconomic indicators.

Workflow Steps:

1. Schedule Trigger — Run daily
2. Database Query (PostgreSQL) — Pull internal sales volume, win rates, and pipeline value by industry vertical
3. GKG Search — Search the Global Knowledge Graph for relevant industry news, market events, and economic indicators
4. Web Scraper — Pull industry analyst reports, market sizing data, and competitor press releases from target URLs
5. URL Reader — Parse government economic data feeds (BLS, Census, Fed releases)
6. Union — Merge internal and external data streams
7. AI Enrichment — Correlate internal performance shifts with external events: "Sales in the Manufacturing vertical dropped 15% this month. This correlates with a 12% decline in the ISM Manufacturing Index reported on the 1st."
8. AI Summary — Generate a weekly strategic intelligence brief
9. Dashboard Output — Populate:
   • BI Intelligence Tile — AI-generated strategic narrative
   • Event Trends Tile — Market event timeline overlaid with internal performance
   • Comparison Tile — Internal growth rate vs. market growth rate by vertical
   • Pivot Tile — Performance matrix: industry vertical × region × channel
   • Forecast Tile — Market-adjusted revenue forecast

Key Nodes: Schedule Trigger, Database Query, GKG Search, Web Scraper, URL Reader, Union, AI Enrichment, AI Summary, Dashboard Output

Example Dashboard: Executive Intelligence Suite

Build this dashboard to give your C-suite a single-screen view of business performance with AI-generated insights and scenario modeling.

Row 1 — Executive KPIs

Row 2 — Trends & AI Insights

Row 3 — Forecasting & Scenarios

Row 4 — Business Unit Performance

Row 5 — Anomalies & Efficiency

Getting Started

To build your BI dashboard:

1. Connect your data sources — Add database connections for financial, operational, and customer data
2. Build your KPI workflow — Start with Schedule Trigger → Database Query → Aggregation → Dashboard Output
3. Add AI tiles — Include BI Intelligence, Predictive Insights, and Forecast tiles for automated analysis
4. Enable forecasting — The Forecast Tile uses historical data to project trends; provide at least 6 months of data for best results
5. Set up scenarios — Use the Scenario Planner Tile to model different business assumptions