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MethodOperations, Supply Chain & ManufacturingSupply chain & procurementIntermediate

Map supply chain risk

A multi-tier supply map with single points of failure, risk scores and mitigation plan.

This is a practical, copy-paste process for after a disruption (port closure, supplier failure, tariff).. Use it when you want a clear structure, then add your own details and the linked evidence.

Published by Deepstory Research. Reviewed Sep 2026.

How to use this method

  1. 1. Copy or downloadCopy the prompt below, or download the method file and attach it to your chat.
  2. 2. Paste into any AIChatGPT, Claude, Gemini or Copilot. Replace each [PLACEHOLDER] with your details, or let the AI ask you.
  3. 3. Add evidenceAttach the evidence files listed on this page so the AI works from sourced numbers, not guesses.

The prompt

Paste it as-is. The AI will ask for anything still in [BRACKETS].

Download .md
# Map supply chain risk
Method by Deepstory Research: deepstoryresearch.com/method/supply-chain-risk-map

You are a supply-chain risk manager. Follow the method below step by step. Goal: A multi-tier supply map with single points of failure, risk scores and mitigation plan.

## My inputs
- Product or category: [PRODUCT_OR_CATEGORY]  (example: lithium battery packs)
- Key suppliers and locations: [KEY_SUPPLIERS_AND_LOCATIONS]  (example: list tiers you know)
- Shipping routes: [SHIPPING_ROUTES]  (example: Shanghai → Jebel Ali)
- Annual spend: [ANNUAL_SPEND]  (example: $4M)

Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source.

## Steps to follow
1. Map tiers from raw materials to your warehouse.
2. Identify single-source and single-route dependencies.
3. Score risks (likelihood × impact) including geopolitical, logistics, financial, quality.
4. Propose mitigations: dual sourcing, buffer stock, alternate routes, contracts.
5. Define early-warning indicators.

## Deliver the output in this structure
- Supply map
- Risk register
- Heat map
- Mitigation plan
- Monitoring indicators

## Quality rules
- Separate known supplier facts from assumptions about tier-2+.
- Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION.
- If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED].
- End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.

What you need to give the AI

InputPlaceholderExample
Product or category[PRODUCT_OR_CATEGORY]lithium battery packs
Key suppliers and locations[KEY_SUPPLIERS_AND_LOCATIONS]list tiers you know
Shipping routes[SHIPPING_ROUTES]Shanghai → Jebel Ali
Annual spend[ANNUAL_SPEND]$4M

Use it when

  • After a disruption (port closure, supplier failure, tariff).
  • Annual risk review.

What you get

  • Supply map
  • Risk register
  • Heat map
  • Mitigation plan
  • Monitoring indicators

The procedure, step by step

Read this before you run it, so you can check the AI actually followed the method.

  1. 1

    Map tiers from raw materials to your warehouse.

  2. 2

    Identify single-source and single-route dependencies.

  3. 3

    Score risks (likelihood × impact) including geopolitical, logistics, financial, quality.

  4. 4

    Propose mitigations: dual sourcing, buffer stock, alternate routes, contracts.

  5. 5

    Define early-warning indicators.

Quality checks built into the prompt

  • • Separate known supplier facts from assumptions about tier-2+.
  • • Every number labelled FACT, ESTIMATE or ASSUMPTION; claims outside attached evidence tagged [UNVERIFIED].

Evidence to use with this method

Methods tell the AI how to think. Evidence gives it sourced numbers to think with. Download a context file and attach it with the prompt.

Run next

Methods that chain well after this one.

Deepstory methods are process guidance for AI tools. Review AI output before relying on it; legal, tax, medical and investment decisions need a qualified professional.