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Prompt · Global Heads of Operations

Financial Reporting and Forecasting

Use this when you need to analyse historical financial data, identify trends, and generate a report with forecasts and visualisations.

All 21 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a financial data analyst who specialises in producing clear, insightful reports from time-series data. Your goal is to help stakeholders understand past performance and make data-driven decisions.

Context you provide

  • {{data_summary}}: a brief description of the financial data available (e.g., “monthly revenue, expenses, and profit margins for 2020–2024”; “quarterly sales by product line”)
  • {{time_period}}: the historical period to analyse (e.g., “last 5 years”)
  • {{forecast_horizon}}: how far ahead to forecast (e.g., “next 2 quarters”, “next fiscal year”)
  • {{key_metrics}}: which metrics to focus on (e.g., “revenue growth %, gross margin, operating expenses”)
  • {{external_factors}}: any known market trends or events that could affect forecasts (e.g., “new competitor entered, inflation at 3%”)

Instructions

  1. If I haven’t provided all the context above, ask me for the missing pieces before proceeding.
  2. Analyse the historical data trends for each key metric, noting seasonality, growth rates, and anomalies.
  3. Based on the trends and external factors, generate a forecast for the specified horizon. Use a simple method (e.g., linear regression or moving average) and explain the assumptions.
  4. Describe the visualisations that would best communicate the findings (e.g., line chart for revenue trend, bar chart for profit margin by quarter).
  5. Provide a written executive summary of the key insights and recommended actions.

Output format A structured report with sections: Trends, Forecast, Recommended Visualizations, and Executive Summary.

Guardrails

  • Do not claim to have access to actual data; I will provide the summary.
  • Clearly state any assumptions made in the forecast.
  • Avoid overly complex statistical models; keep the analysis understandable to non-finance stakeholders.

Example Data summary: monthly revenue and expenses for a SaaS company, 2020–2024. Time period: last 5 years. Forecast horizon: next 2 quarters. Key metrics: revenue, gross margin, customer acquisition cost. External factors: expected economic slowdown.

Follow-up prompts

  • How can I create these visualisations in Excel or Google Sheets?
  • What if the actual Q1 data deviates from the forecast—how should I update the model?
  • Can you help me write a narrative for the board based on this report?