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skills/powerbi-revenue-digital-twin/SKILL.md
2.09 KB · Oct 5, 2026 · 18:32 UTC
--- name: powerbi-revenue-digital-twin description: Use when designing or running a Power BI revenue digital twin for sales forecasting, target-gap simulation, backlog-to-invoice scenarios, what-if revenue paths, budget attainment, and forecast-to-cash decision support from an open Power BI Desktop model or exported forecast CSVs. --- # Power BI Revenue Digital Twin Use this skill when the user wants to move beyond a static sales forecast into scenario simulation: "How do we still hit budget?", "What if delivery slips?", "Which backlog must convert?", or "Which customers/products close the revenue gap?" ## Workflow 1. Start read-only. Use the open Desktop model through `Invoke-PowerBIAIForecast.ps1` or existing forecast CSVs. Do not write to PBIX/PBIP unless explicitly requested. 2. Establish the current target gap by month: AI forecast, roll forecast, budget, actual-to-date, open backlog, expected backlog revenue. 3. Build scenario levers: - backlog acceleration or delay - conversion probability changes - customer/product demand uplift or erosion - working-day and holiday impact - budget or roll target constraint - supply or delivery risk 4. Produce at least three scenarios: - base case from the current AI forecast - target case showing what must change to hit budget or roll - risk case showing likely downside if weak backlog or volatile segments slip 5. Rank the smallest set of customer/product/month changes that explain or close the gap. ## Required outputs - `forecast_month` - `target_metric` such as Budget or Roll - `current_ai_forecast` - `target_gap` - `required_backlog_conversion` - `required_residual_demand` - `top_gap_drivers` - `scenario_name` - `scenario_forecast` - `scenario_probability` - `explanation` ## Quality gates - Mark a scenario `not_actionable` when it depends on segments already flagged `advisory_only`, `biased`, or `sparse` without human validation. - Separate controllable levers from non-controllable statistical demand. - Never present a single scenario as truth; show assumptions and sensitivity.
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