Write the premise before reading the result
Specify what changes and what stays constant. A temporary processing interruption is different from a permanent loss of feedstock or a delayed future project. Define the time horizon and the decision the scenario should inform. Without that premise, a dramatic network result can be mistaken for a prediction of what will happen.
IEA research on critical-mineral concentration provides strategic context for examining disruption. A company-level scenario still needs its own route evidence and assumptions; aggregate concern does not supply those inputs.
IEA: Export controls and critical-mineral supply concentration (2025) ↗
Separate three layers of the result
First show the documented operations and relationships. Second identify assumed transmission: whether a connection is affected, what substitution is allowed and how buffers are treated. Third show the resulting implications within that model. Label unknown flow shares and customer allocations instead of treating them as measured exposure.
Run a sensitivity around the assumption most likely to change the decision. If inventory or alternative qualification is unknown, explain how the conclusion depends on it. A scenario that identifies the decisive missing input can be more useful than a precise-looking loss estimate built from unsupported numbers.
Illustrative scenario boundary
A separator is assumed unavailable for one month. The network identifies downstream operations to investigate, but route shares and stocks are undisclosed. The defensible output is a set of potentially affected relationships and required follow-ups. It is not automatically the sum of every connected factory's annual production.
Keep the model legible
| Layer | Label |
|---|---|
| Observed | Source-backed operation or relationship |
| Assumed | Duration, transmission or substitution premise |
| Unresolved | Quantity, stock or allocation needing evidence |
Your review checklist
- Define the disruption and time horizon.
- Keep future project delays separate from current outages.
- Expose transmission and substitution assumptions.
- Test the unknown that could reverse the decision.
Investigate with Oreline
Oreline combines a researched network with assumption-based scenarios so your team can examine the chain behind a disruption question. Inspect the evidence and analytical limits alongside the result, then use the findings to prioritise follow-up.
Follow the evidence through the supply chain.
Explore Oreline’s guided investigations. No account required.
Explore the sandbox →Frequently asked questions
Does a scenario predict the probability of an outage?
No. It examines a selected premise and its implications within the model, not the likelihood that the premise occurs.
Can all connected output be called lost supply?
No. Flow shares, inventory, alternative routes, duration and customer allocation need support before estimating a loss quantity.