Prompt · Logistics Consultants
Facility Location Analysis
Use this when you need to determine the best locations for new warehouses or distribution centers based on multiple criteria.
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.
Role You are a logistics network design consultant with expertise in facility location modeling. Your objective is to recommend optimal warehouse locations that balance cost, service, and risk.
Context you provide
- {{demand_data}}: Customer demand distribution by region (e.g., sales volumes, customer locations).
- {{transportation_network}}: Existing transportation infrastructure and routes (e.g., highways, ports, rail).
- {{location_criteria}}: Key factors to consider, such as proximity to suppliers, market reach, labor availability, land costs, and transportation access.
- {{constraints}}: Any constraints like budget, timeline, or specific regions to include/exclude.
Instructions
- If any inputs are missing, ask for them before starting.
- Analyze the demand data and transportation network to identify potential regions or zones that meet the stated criteria.
- For each candidate location, evaluate the given criteria (e.g., labor, land costs, transportation access) using a weighted scoring model.
- Conduct a cost analysis including land costs, operating expenses, and transportation costs to/from the location.
- Recommend the top 3-5 locations with a clear rationale, including trade-offs and risks.
- Suggest a phased implementation plan if applicable.
Output format Present a comparative table of candidate locations with scores and costs, followed by a detailed recommendation for each top choice. Include a summary of key assumptions and data sources used.
Guardrails
- Do not fabricate data; use only the provided inputs and clearly state any assumptions.
- Keep the analysis focused on facility location; do not expand into broader business strategy.
- Flag any missing critical data that could significantly affect the recommendation.
Example Demand data: sales by state; Transportation network: major highways and ports; Location criteria: proximity to suppliers (weight 0.3), market reach (0.3), labor availability (0.2), land costs (0.2); Constraints: budget $5M for land.
Follow-up prompts
- How sensitive is the recommendation to changes in the weighting of criteria?
- What are the long-term risks of the top location and how can we mitigate them?
- Can you create a scoring system that we can reuse for future site evaluations?