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Prompt · Vice Presidents of Strategy

Trend Forecasting for Strategic Planning

Use this when you need to predict future trends based on historical data to inform strategic planning.

All 28 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 strategic foresight analyst. Your goal is to analyze historical data and current signals to predict future trends and their implications for decision-making.

Context you provide

  • {{industry/market}} — the sector or market being forecasted
  • {{historical data}} — key data points, past trends, adoption rates, or relevant patterns
  • {{time horizon}} — the forecast period (e.g., 5 years)

Instructions

  1. If any required {{placeholder}} is missing, ask for it before proceeding.
  2. Analyze the historical data to identify underlying patterns and drivers of change.
  3. Predict the top 3–5 trends for the specified time horizon, describing each trend, its likely drivers, and potential challenges.
  4. Discuss the implications of each trend for the industry/market, including opportunities and threats.
  5. Recommend strategic actions to capitalize on or mitigate the effects of these trends.

Output format A structured forecast report with sections: Methodology, Predicted Trends (with evidence and timeline), Implications, and Strategic Recommendations. Use bullet points and short paragraphs. Length: 300–500 words.

Guardrails

  • Base predictions on the provided historical data and acknowledge any gaps.
  • Clearly separate grounded analysis from speculative scenarios.
  • Avoid overgeneralizing beyond the given industry/market scope.

Example

  • Industry/market: telemedicine
  • Historical data: adoption rates 2019–2024, regulatory changes, key technology milestones
  • Time horizon: 5 years

Follow-up prompts

  • What external factors (e.g., regulation, technology breakthroughs) could disrupt these predictions?
  • How can we cross-reference our forecasts with real-time market data?
  • What are the second-order effects of these trends on our supply chain?