Stranded Asset Risk Calculator
The formula
What the stranded asset risk tells you
The 5×5 matrix the risk industry actually uses, for stranded asset risk: gross likelihood × impact, discounted by how well your controls actually work.
Calculation: gross = likelihood × impact (1–25); net = gross × (1 − controls). Enter your inputs and every substitution is shown below the result.
Reading the result
Scores rank attention; they do not price losses. Anything 15+ gets a treatment plan with a named owner.
Rules of thumb: Most organisations carry 3–5 reds; more usually means likelihood inflation, not danger.
Limitations and best practice
Control ratings drift optimistic — audit one control’s evidence and re-mark the rest against it.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
Why discount by controls?
Do these scores compare across teams?
Source & methodology
ISO 31000-aligned qualitative risk matrices.
Stranded Asset Risk: what this tool answers
This page was written for one job: turning your own inputs into a defensible figure, with the working shown. Searchers land on a Stranded Asset Risk page for three reasons — to plan, to compare options, and to check that somebody else’s arithmetic is honest. This tool serves all three, and everything after the calculator explains the model instead of hiding it.
In plain terms, Stranded Asset Risk answers the question "Net risk score?". The measurement matters because it converts a situation that feels complicated — several inputs pulling in different directions — into a single number you can act on. Within Environmental & Sustainability, Carbon & Climate is the context where this figure is quoted most often, and professionals treat it as a first-pass screen rather than a verdict.
There is a habit that separates people who get useful answers from Carbon & Climate numbers: they decide what question the figure answers before they compute it. Stranded Asset Risk answers “Net risk score?” — and nothing else, which is precisely why the result is trustworthy.
Nothing below is stock text pasted around a number: the worked example computes net risk score = 5.3 / 25 from this tool’s own defaults, and the sensitivity section ranks the inputs that move the result — Likelihood (1 = rare … 5 = almost certain) first, at ≈10.0 % of the headline for a ten-percent error either way in that input — which is the thread the rest of this guide pulls on.
The Stranded Asset Risk formula, explained
Here is the complete model this tool runs — gross = likelihood × impact (1–25); net = gross × (1 − controls) — with each input explained below. If a competitor’s page gives you a different answer from the same inputs, this is the text that settles which of you is right.
Likelihood (1 = rare … 5 = almost certain) (example value 3) is a quantity rather than a category — precision here is cheap and worth having. The example value is there to demonstrate the mechanics, not to describe your situation — overwrite it.
Impact (1 = negligible … 5 = severe) (example value 3) is a measured number in the unit named by the label; the formula does not convert for you. Replace the example with the figure from your own records — the tool recomputes instantly and the printed steps follow your numbers.
Control effectiveness (0–100 %) (example value 41) is a quantity rather than a category — precision here is cheap and worth having. Check the convention first: if the source says “6.5 % per year”, type 6.5 and let the formula do the rest.
Stranded Asset Risk on the example inputs: the complete substitution
Abstract formulas are hard to trust, so here is the complete substitution using the default inputs, written the way an examiner would want it. Starting figures: Likelihood (1 = rare … 5 = almost certain), Impact (1 = negligible … 5 = severe), Control effectiveness (0–100 %). The computed net risk score comes out at 5.3 / 25, which the interpretation band labels “Low-moderate — monitor at cadence”.
- Gross = 3 × 3 = 9
- Net = 9 × (1 − 41 %) = 5.3
Gross score — 9 / 25. Compare it against the main result of 5.3 / 25 before drawing conclusions.
Control credit — 3.7 pts. Read next to the headline, this is the figure that shows the shape of the trade-off.
Likelihood × impact band — Mixed. If your inputs change, this is usually the first companion figure to move.
Overwrite any input above and every line of this example updates with it — the substitution is live, not a screenshot of somebody else’s numbers.
The Stranded Asset Risk corridor: your result across a realistic band
The honest version of any estimate is a corridor, and this one is cheap to produce: Stranded Asset Risk was recomputed at 5 points along the dominant input, with every other field left untouched.
| Likelihood (1 = rare … 5 = almost certain) setting | Net risk score |
|---|---|
| 80 % of the example value | 4.2 / 25 |
| 90 % of the example value | 4.8 / 25 |
| example inputs | 5.3 / 25 |
| 110 % of the example value | 5.8 / 25 |
| 120 % of the example value | 6.4 / 25 |
The corridor runs from 4.2 / 25 to 6.4 / 25 across that band — which is the range worth planning inside rather than the single 5.3 / 25 point estimate. Reproduce it in the form above by editing Likelihood (1 = rare … 5 = almost certain) alone; the substitution steps will follow your figures exactly.
The levers behind Stranded Asset Risk, ranked by effect
Generic advice says “it depends on your inputs”; this section says exactly how much. Each field was perturbed by ±10 % in isolation and the net risk score recomputed, so the ranking below is measured rather than asserted. It is the fastest honest answer to “what matters most in Stranded Asset Risk?” — and it is specific to these defaults, because sensitivity moves with the starting point.
- Likelihood (1 = rare … 5 = almost certain): ten percent up gives 5.8 / 25, ten percent down gives 4.8 / 25 — ≈10.0 % of the net risk score either way
- Nudge Impact (1 = negligible … 5 = severe) by ±10 % and Stranded Asset Risk lands between 4.8 / 25 and 5.8 / 25 (sensitivity ≈10.0 %)
- Nudge Control effectiveness by ±10 % and Stranded Asset Risk lands between 4.9 / 25 and 5.7 / 25 (sensitivity ≈6.9 %)
Likelihood (1 = rare … 5 = almost certain) is the dominant lever here: ten percent either way moves the result by about 10.0 %, from 4.8 / 25 to 5.8 / 25. Measure that input from a document rather than from memory, and Impact (1 = negligible … 5 = severe) is effectively tied with it (≈10.0 % for the same nudge), so verify the pair together. Everything below that can stay approximate, which is a licence to stop chasing data that would not change the decision.
Reading the result: bands, zones and thresholds
A number on its own is trivia; a number against a range is intelligence. On the example inputs the band reads “Low-moderate — monitor at cadence”; your own figures place you on a different rung of the same ladder. The sensitivity list shows how far a modest input error moves you along that ladder: for Likelihood (1 = rare … 5 = almost certain), ±10 % covers 4.8 / 25 to 5.8 / 25. The practical reading rules: ask what would have to change to move you one band. If the answer is “a small, plausible input difference”, the band itself is not the finding — the uncertainty is.
Set Stranded Asset Risk beside its neighbours and it usually plays a specific role: this figure establishes the size of something, and the neighbouring tools establish whether that size is acceptable. Skipping the first step makes the second one arbitrary.
How people get Stranded Asset Risk wrong
Control ratings drift optimistic — audit one control’s evidence and re-mark the rest against it. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Reading Stranded Asset Risk as a promise rather than a conditional. Every number here is of the form “if these inputs, then this result”; when an input moves, the honest response is to recompute rather than to defend the old figure.
Attention is also misallocated between fields. Having measured this engine, we can say where it belongs: Likelihood (1 = rare … 5 = almost certain) first, everything else second.
A final trap is presentation: reporting Stranded Asset Risk to more decimal places than the inputs support. The tool prints what the arithmetic gives; you should quote only what your least precise field justifies.
Six things to confirm before acting on Stranded Asset Risk
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Recompute once with the dominant input deliberately set low, and see whether the decision changes.
- Check Likelihood (1 = rare … 5 = almost certain) before anything else: it is the measured dominant input, ≈10.0 % of Stranded Asset Risk per ten percent.
- Re-run the calculation with a ±10 % stress on the two most sensitive inputs.
- Verify each input against its original source document, not memory.
- Repeat the ±10 % test on the inputs that matter and see whether the decision — not just the number — still holds.
Five steps from raw inputs to a figure you can defend
The tool does the arithmetic; the routine below is what makes the arithmetic trustworthy. Five steps, a minute total — and afterwards you will know not just what the number is, but which assumption produced it.
Step 1 — one document, one pass. Open the statement, label or record that holds likelihood (1 = rare … 5 = almost certain), impact (1 = negligible … 5 = severe), control effectiveness (0–100 %) and transcribe straight into the form. Transcription from a single source removes the mismatch errors that appear when figures are assembled from three different places. Comparisons are cheap: run the identical calculation for the alternative and look at the gap.
Step 2 — start from the case you can defend. Enter pessimistic-but-honest figures first; the optimistic run is a ceiling, not a plan. A conclusion that holds on conservative inputs holds everywhere. Say the answer out loud before you save it; if it sounds wrong, the model did not change, your understanding did.
Step 3 — isolate your variables. Change one field, observe, revert. The live sensitivity list does the ranking for the default inputs; verify it against your own, because dominance shifts when the starting point shifts. Half of a good calculation is knowing which input you would hate to be wrong about.
Step 4 — ask what would have to be true. Take the result you want and work backwards through the inputs until you find the assumption that produces it; then decide honestly whether that assumption is defensible. If the verdict changes with a ten-percent nudge, report the nudge alongside the number.
Step 5 — record the context, not just the number. Note today’s date and the inputs alongside the 5.3 / 25 output. Six months from now the context is what turns this figure into a trend. Rounding early is the quietest way to introduce a permanent error.
Where Stranded Asset Risk matters in practice
Environmental & Sustainability arguments end at arithmetic or they do not end. Stranded Asset Risk is the arithmetic: 5.3 / 25 on the example inputs, reproducible by anyone who types the same numbers. Compare the calculation to the rough guess you arrived with, and ask why they differ.
The companion outputs — Gross score and Control credit — exist for the second stage of that screen: the headline sizes the prize, while the companions describe the trade-off you are accepting to get it. If a result feels obviously right, that is the moment to check the inputs hardest.
Treat Stranded Asset Risk like a smoke alarm rather than a painting — its value is in being tested periodically, not in being admired once. When two sources disagree, it is almost never the arithmetic that differs.
Quick answers: what searchers ask about Stranded Asset Risk
What affects Stranded Asset Risk the most?
The short answer: Likelihood (1 = rare … 5 = almost certain). The longer answer is the sensitivity table on this page, where every numeric input was probed by ten percent and the net risk score recalculated — Likelihood (1 = rare … 5 = almost certain) moved it furthest, by roughly 10.0 % (4.8 / 25 to 5.8 / 25).
Do impact (1 = negligible … 5 = severe) and likelihood (1 = rare … 5 = almost certain) matter equally?
On these inputs, yes: the two measured within a rounding error of each other — ≈10.0 % and ≈10.0 % of the net risk score per ten-percent change. Treat them as one pair to verify together rather than ranking them.
What is a typical Stranded Asset Risk?
With the example inputs on this page the result is 5.3 / 25, labelled “Low-moderate — monitor at cadence”. “Typical” varies with situation, which is why every result here ships with its verdict band and its sensitivity list: they turn one figure into a range you can locate yourself inside.
How do I calculate Stranded Asset Risk by hand?
gross = likelihood × impact (1–25); net = gross × (1 − controls) is the entire method. Work the inputs in that order — Gross = 3 × 3 = 9 — and you will reach 5.3 / 25 on the default figures, the same number this tool prints.
What happens to Stranded Asset Risk if likelihood (1 = rare … 5 = almost certain) changes by 10 %?
The engine was re-run with that field moved by ten percent while everything else stayed fixed: the net risk score goes across 4.8 / 25 to 5.8 / 25, a swing of roughly 10.0 % around the 5.3 / 25 baseline. That ratio is the practical definition of how much this input matters.
Is the Stranded Asset Risk result of 5.3 / 25 good or bad?
Neither, on its own — the label “Low-moderate — monitor at cadence” is the band this figure falls in for the example inputs, and your own inputs will place you elsewhere on the same ladder. Judge the number against your history and your alternatives, and remember that a ten-percent error in Likelihood (1 = rare … 5 = almost certain) alone moves it by ≈10.0 %.
Which emission/consumption scope does Stranded Asset Risk cover?
Whatever your inputs encode — typically direct consumption at the meter. Broader scopes (embodied, upstream) require adding their own inputs; do not compare a narrow Stranded Asset Risk against a whole-life figure.
How do I calculate Stranded Asset Risk manually?
Write down the inputs, then follow the printed steps in order — gross = likelihood × impact (1–25); net = gross × (1 − controls). A spreadsheet replicates it with two or three cells. The manual route is worth doing once to build intuition; after that the calculator saves time and eliminates transcription slips.
Why discount by controls?
A 20-score hazard half-mitigated is a 10, and 10s behave like a different risk class.
Do these scores compare across teams?
Only if the likelihood and impact scales are calibrated to the same definitions — the matrix is shared, the calibration is organisational.
Can this tool see the numbers I type?
It cannot. There is no submission step: the calculation happens in your browser and the result disappears when you close the page. Treat the fields above as a scratchpad rather than a form.
What the labels on this page mean
- Gross score
- 9 / 25 in the default Stranded Asset Risk calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Control credit
- 3.7 pts in the default Stranded Asset Risk calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Likelihood × impact band
- Mixed on the example inputs — a companion figure printed beside the headline of Stranded Asset Risk so that no result is read in isolation.
- Net risk score
- The primary output of this tool: 5.3 / 25 for the default inputs, computed exactly from gross = likelihood × impact (1–25); net = gross × (1 − controls).
- Worked example
- Every substitution in order, from the example inputs to 5.3 / 25 — the audit trail for the headline figure.
- Verdict band
- The interpretation attached to a result (“Low-moderate — monitor at cadence” on these inputs), which turns a bare number into a position on a scale.
- Sensitivity (±10 %)
- How far the Stranded Asset Risk moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Where the Stranded Asset Risk model comes from
There is no black box on this page — the engine evaluates gross = likelihood × impact (1–25); net = gross × (1 − controls). Source of record: ISO 31000-aligned qualitative risk matrices. Any other implementation of this model should return the same figure for the same inputs. If one does not, the difference is in its assumptions — which this page prints and that one probably does not.
Treat the output as a precise answer to the question you typed: exact arithmetic, transparent formula, published source, no hidden rounding. The sensitivity table above is part of that promise rather than a bonus: it lets you see how much of the result depends on how carefully you measured.
Turning this Stranded Asset Risk into a decision
Save the number together with its inputs and today’s date; a Stranded Asset Risk figure without context is unusable the moment an input changes.
Whoever you are (people who need one trustworthy number before their next decision), the next step is the same: replace the example inputs with your own, note the date, and re-run whenever a figure moves. In Environmental & Sustainability, a dated figure is a trend, and an undated one is a rumour.