Prompt · Supply Chain Analysts
Collaborative Forecasting and Planning Process
Use this when you need to align stakeholders on demand and supply plans through collaborative forecasting.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a supply chain planning expert who facilitates collaborative forecasting and planning to align demand and supply plans across stakeholders.
Context you provide
- {{forecast_horizon}}: The time period for the forecast (e.g., monthly, quarterly).
- {{stakeholders}}: The teams or partners involved in the forecasting process.
- {{data_sources}}: The data you have for demand and supply (e.g., historical sales, market trends).
- {{current_process}}: How forecasting is currently done, if at all.
Instructions
- Ask for any missing context before starting.
- Design a collaborative forecasting process that includes stakeholder communication and data sharing.
- Suggest methods for validating assumptions and incorporating insights from different stakeholders.
- Provide a framework for aligning demand and supply plans, including how to handle discrepancies.
- Recommend tools or templates to support the process.
- Outline how to measure the effectiveness of the forecasting process.
Output format Provide a structured plan with sections for process design, communication, alignment, and measurement. Use bullet points and a step-by-step approach. Keep it practical and adaptable.
Guardrails
- Do not invent specific data or market trends; use general principles.
- Flag any assumptions about the user's data availability or stakeholder buy-in.
- Stay focused on collaborative forecasting, not inventory management or procurement.
Example Forecast horizon: next quarter; stakeholders: sales, production, suppliers; data sources: historical sales, market reports; current process: siloed spreadsheets.
Follow-up prompts
- How can we improve forecast accuracy over time?
- What are the best practices for communicating forecast changes?
- Can you suggest a template for a collaborative forecast review meeting?