Chip Supply Risk Analyzer
Risk isn't one number. It's how concentrated you are, how likely each source is to fail, and how long recovery takes. Score your resilience and see exactly which lever to pull.
| Supplier | Share | Disrupt % | Recover wk | |
|---|---|---|---|---|
Supply risk console
Each bar is share × disruption-probability — the realistic contribution to expected supply loss. The biggest bar is where mitigation pays most.
Your supply base scores 56/100 resilience. Expected supply-at-risk is 7.2%, concentration HHI is 5200, and share-weighted recovery is 14 weeks.
Concentration is the dominant risk — Primary fab at 60% needs a qualified second source.
Measure raw concentration in Vendor Concentration; derive geographic probabilities in Taiwan Risk.
Why supply risk has three dimensions
Supply risk isn't one number — it's how concentrated you are, how likely each source is to fail, and how long recovery takes. A diversified base with slow recovery can be as risky as a single source with fast recovery.
A 5% disruption probability on your 80% supplier matters far more than a 20% probability on a 5% supplier. Weighting each source's failure likelihood by its share gives the realistic expected exposure.
Qualifying a new semiconductor source takes months. A disruption you recover from in two weeks is an inconvenience; one that takes six months to re-source is an existential threat — even at the same probability.
Every input here is a lever: add a source to cut concentration, qualify backups to cut recovery time, choose lower-risk geographies to cut probability. Resilience is the result of deliberate choices, scored here so you can target them.
Concentration is only the beginning
Concentration tells you the size of the hole a disruption could blow in your supply, but it doesn't tell you how likely the hole is to open or how long it stays open — and those two questions decide whether a concentrated supply base is a manageable bet or a ticking clock. A single source with a robust, multi-site, financially sound supplier in a stable geography is a different risk from the same concentration resting on a single fragile fab in an earthquake zone. Risk is the product of three dimensions, not one.
The second dimension is likelihood, and the trick is to weight it by share. People fixate on the scary small supplier with a high failure probability while ignoring the dominant one with a modest probability — but a five-percent chance on the supplier holding eighty percent of your volume dwarfs a twenty-percent chance on a five-percent source. Multiplying each source's disruption probability by its share and summing gives the expected supply-at-risk, which points attention to where exposure actually lives.
The third dimension, recovery time, is the one that turns a probability into a business outcome, and for semiconductors it is brutal. Qualifying a new source — process validation, reliability testing, ramp — takes months. A disruption you recover from in two weeks is an inventory blip; one that takes six months can idle production lines and lose design sockets. Two identical-probability, identical-share disruptions can have utterly different consequences depending on how fast you can re-source, which is why pre-qualifying backups is so often the highest-leverage mitigation.
What makes this analysis worth doing is that every dimension is a lever. Add a source to cut concentration, qualify backups to cut recovery, choose lower-risk geographies to cut probability — resilience is built, not given. Use this analyzer to score where you stand and see which dimension drags the score down, measure the raw structure in the Vendor Concentration calculator, and derive geographic disruption probabilities from the Taiwan and China risk tools.
Trusted by Resilience & Continuity Teams
“Decomposing risk into concentration, expected-at-risk and recovery is exactly how I brief the board — and the per-supplier contribution view shows that our 5% disruption odds on the 80% fab dwarf everything else. The recovery-time-as-multiplier point is the one that gets pre-qualification funded. Indispensable for resilience planning.”
“The share-weighting of disruption probability is what makes this honest — it stops people obsessing over a risky minor supplier while ignoring the dominant one. Running base-case vs heightened-tension scenarios on the probabilities is gold for our planning. Chains perfectly from the concentration calculator.”
“Clean, transparent risk score with every component visible — no black box. Applying it to the consolidated tier-3 dependency revealed our real exposure. Would love a Monte Carlo on the probabilities, but the deterministic expected-at-risk plus scenarios covers the planning need well.”
“Editable suppliers with probability and recovery in one screen, instant resilience score — a full risk assessment in minutes. The point that resilience is buildable, with every input a lever, reframes it from worry to action plan. Feeds straight into our Taiwan/China exposure work. Fast and clear.”
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expected at-risk = Σ(share × disruption prob) · resilience = 100 − f(HHI, at-risk, recovery) · Last reviewed: 2026-06