Single Source Risk Calculator
The formula
What the single-source risk tells you
Prices a sole-source dependency: failure probability × the time to become unstuck × the margin that burns while you are stuck.
Calculation: Expected risk cost = probability × switch time × weekly margin loss. Enter your inputs and every substitution is shown below the result.
Reading the result
The switch-time term dominates — a five-year-old sole source with no plan is the most expensive kind of savings.
Rules of thumb: Critical-path sole sources get an explicit risk line in every sourcing review
Limitations and best practice
Supplier failure includes financial, fire, quality recall and geopolitical — use the whole class, or the 4% anchor is optimistic.
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
Is risk-allocated pricing (paying for backup capacity) worth it?
What about self-insuring with inventory?
Source & methodology
Supply-risk quantification (Kleiber & others).
Single Source Risk: what this tool answers
You are here because you need a specific number, and you want to see how it was produced before you rely on it. Single Source Risk is the kind of number people argue about from memory. This page ends that argument with arithmetic you can watch happen: enter your figures, get Annual expected risk cost in real time, and see every substitution printed below.
Business runs on numbers that are cheap to compute and expensive to ignore. Single Source Risk in Business & Entrepreneurship is one of those: Expected risk cost = probability × switch time × weekly margin loss, and the gap between founders who check and founders who hope shows up exactly here.
What makes Single Source Risk worth calculating is not precision but position: it tells you which side of a threshold you are on, and by how much. A rough figure that settles the direction beats an elaborate one that never commits.
What makes a calculation page trustworthy is that its copy is derived from its own arithmetic: here annual expected risk cost = $17,097, recomputed every time a field changes, and the sensitivity section ranks the inputs that move the result — Supplier failure probability per year first, at ≈10.0 % of the headline for a ten-percent error either way in that input — which is the thread the rest of this guide pulls on.
Inside the Single Source Risk calculation: formula and every input
The engine implements a single stated model: Expected risk cost = probability × switch time × weekly margin loss. There is no hidden coefficient and no login-gated precision — the formula printed is the formula executed, which is also what makes the result citable.
Spend on the single-sourced item ($) (example value 2,825,000) is a plain measured quantity — the unit shown in the label is the unit the formula expects. Keep every money input in the same currency; mixing systems quietly corrupts the comparison.
Supplier failure probability per year (%) (example value 4) is a quantity rather than a category — precision here is cheap and worth having. Enter it exactly as your document states it — quoted annual, monthly and effective rates are three different numbers.
Weeks to qualify a replacement (example value 14) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. Be precise about the boundary (exact date, start of month); time inputs decide the exponent in most formulas.
Margin lost per week of gap ($) (example value 30,530) is a plain measured quantity — the unit shown in the label is the unit the formula expects. Be precise about the boundary (exact date, start of month); time inputs decide the exponent in most formulas.
Single Source Risk with real numbers, step by step
The tool prints its own working; this is the same arithmetic on the example values, reproduced so you can follow it by hand. Starting figures: Spend on the single-sourced item ($), Supplier failure probability per year (%), Weeks to qualify a replacement, Margin lost per week of gap ($). Run to the end, the annual expected risk cost resolves to $17,097 — Dual-sourcing at up to $17,097/yr premium is break-even on this line on the bands this tool uses.
- Expected = 4% × 14 weeks × $30,530 = $17,097
- Switch time is the multiplier a dual-source strategy attacks hardest
Spend at risk — $2,825,000. Read next to the headline, this is the figure that shows the shape of the trade-off.
Risk cost as % of spend — 0.61 %. Read next to the headline, this is the figure that shows the shape of the trade-off.
Cost of halving the switch time — $8,548. Compare it against the main result of $17,097 before drawing conclusions.
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.
How far Single Source Risk can reasonably move
Single-point answers invite false confidence, so the same engine was run across a band around the input that matters most here. Each row is a full recalculation of Single Source Risk, not an interpolation.
| Supplier failure probability per year setting | Annual expected risk cost |
|---|---|
| 80 % of the example value | $13,677 |
| 90 % of the example value | $15,387 |
| example inputs | $17,097 |
| 110 % of the example value | $18,806 |
| 120 % of the example value | $20,516 |
That spread — $13,677 at the low end, $20,516 at the high — is what a careful read of Single Source Risk looks like: a band you can state out loud, with the reason for each edge. Reproduce it in the form above by editing Supplier failure probability per year alone; the substitution steps will follow your figures exactly.
What actually moves your Single Source Risk
Generic advice says “it depends on your inputs”; this section says exactly how much. Each field was perturbed by ±10 % in isolation and the annual expected risk cost recomputed, so the ranking below is measured rather than asserted. For Single Source Risk the ranking is measured rather than guessed, and it belongs to these defaults: shift the starting point and the order can shift with it.
- Nudge Supplier failure probability per year by ±10 % and Single Source Risk lands between $15,387 and $18,806 (sensitivity ≈10.0 %)
- Weeks to qualify a replacement +10 % → Single Source Risk = $18,806 · −10 % → $15,387 (the annual expected risk cost shifts ≈10.0 %)
- Margin lost per week of gap: ten percent up gives $18,806, ten percent down gives $15,387 — ≈10.0 % of the annual expected risk cost either way
Supplier failure probability per year is the dominant lever here: ten percent either way moves the result by about 10.0 %, from $15,387 to $18,806. Spend your verification effort there first, and Weeks to qualify a replacement is effectively tied with it (≈10.0 % for the same nudge), so verify the pair together. The rest of the inputs earn only a rounding-error of attention, and that asymmetry is the practical payoff of measuring rather than asserting.
Is your Single Source Risk good — reading the result bands
The value above only becomes useful the moment you know what it is being measured against. On the example inputs the band reads “Dual-sourcing at up to $17,097/yr premium is break-even on this line”; 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 Supplier failure probability per year, ±10 % covers $15,387 to $18,806. 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.
In Business & Entrepreneurship, Single Source Risk is one instrument in an orchestra: on its own it is a number, next to Spend at risk and Risk cost as % of spend it becomes a diagnosis. The tools linked above exist so the headline never has to carry that weight alone.
The errors that quietly break a Single Source Risk figure
Supplier failure includes financial, fire, quality recall and geopolitical — use the whole class, or the 4% anchor is optimistic. 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.
Copying a single headline number without checking the companion outputs. The tool reports Spend at risk, Risk cost as % of spend and Cost of halving the switch time alongside the main result precisely because Single Source Risk in isolation misleads — the secondary columns are where outliers and trade-offs show up.
Attention is also misallocated between fields. Having measured this engine, we can say where it belongs: Supplier failure probability per year first, everything else second.
The subtlest error is answering the wrong question precisely. Confirm that annual expected risk cost is actually the quantity your decision needs — the arithmetic is flawless either way, which is what makes the mistake invisible.
Single Source Risk verification checklist
- Confirm the example values are plausible for your own situation before replacing them.
- Compare the result with one independent method or published benchmark.
- Re-verify Supplier failure probability per year against a source document — ten percent of error there moves the headline by ≈10.0 %.
- Re-run the calculation with a ±10 % stress on the two most sensitive inputs.
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Repeat the ±10 % test on the inputs that matter and see whether the decision — not just the number — still holds.
How to use the Single Source Risk tool properly
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 spend on the single-sourced item ($), supplier failure probability per year (%), weeks to qualify a replacement, margin lost per week of gap ($) 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. If the verdict changes with a ten-percent nudge, report the nudge alongside the number.
Step 2 — compute the version you would not be embarrassed by. If a stranger audited your inputs, which set would you hand over? Enter that set, read the result, and treat everything else as upside. A result worth acting on survives having its two shakiest inputs halved.
Step 3 — change one input at a time. Nudge a single field by ten percent, watch the headline and its companions move, then undo it. Two or three fields will dominate — the sensitivity table above already ranks them for this engine. Re-running a number costs seconds; retracting a decision costs considerably more.
Step 4 — run the scenario trio. Expected, pessimistic, optimistic. The gap between pessimistic and expected is the number to plan against; the optimistic result is useful only as a ceiling. Say the answer out loud before you save it; if it sounds wrong, the model did not change, your understanding did.
Step 5 — schedule the next run. In Business & Entrepreneurship the inputs drift quietly. Put a reminder a quarter out, re-enter the same fields, and read the change rather than the level. Repeating a calculation with the same numbers proves only that the arithmetic is reliable — which is worth knowing.
Who actually uses Single Source Risk — and when
Most Operations disagreements are arithmetic disagreements in disguise. When Annual expected risk cost of $17,097 sits on the table with its working shown, the conversation stops being about who sounds more confident and starts being about which input is wrong. When in doubt, prefer the boring input: the interesting one is usually the one you misread.
The audience for this page is people who need one trustworthy number before their next decision. In professional Operations practice the pattern is always the same — screen with Single Source Risk, then invest slow analysis only in whatever survives the screen. Note the assumption you are least sure about; that is where the real risk lives.
Treat Single Source Risk like a smoke alarm rather than a painting — its value is in being tested periodically, not in being admired once. If the answer changes your behaviour, it deserves a second run with different assumptions.
Quick answers: what searchers ask about Single Source Risk
What affects Single Source Risk the most?
The short answer: Supplier failure probability per year. The longer answer is the sensitivity table on this page, where every numeric input was probed by ten percent and the annual expected risk cost recalculated — Supplier failure probability per year moved it furthest, by roughly 10.0 % ($15,387 to $18,806).
Do weeks to qualify a replacement and supplier failure probability per year matter equally?
Single Source Risk here is co-driven: Supplier failure probability per year and Weeks to qualify a replacement produced ≈10.0 % and ≈10.0 % responses, which is a tie for practical purposes. Everything below those two is a rounding error by comparison.
What is a typical Single Source Risk?
With the example inputs on this page the result is $17,097, labelled “Dual-sourcing at up to $17,097/yr premium is break-even on this line”. “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 Single Source Risk by hand?
Use the stated model — Expected risk cost = probability × switch time × weekly margin loss — and substitute in the order the tool prints (it starts from Expected = 4% × 14 weeks × $30,530 = $17,097). On the example inputs the hand route lands on $17,097, exactly what the calculator shows. A spreadsheet reproduces it in two or three cells; doing it once by hand is what makes the automated answer trustworthy.
What happens to Single Source Risk if supplier failure probability per year changes by 10 %?
The engine was re-run with that field moved by ten percent while everything else stayed fixed: the annual expected risk cost goes across $15,387 to $18,806, a swing of roughly 10.0 % around the $17,097 baseline. That ratio is the practical definition of how much this input matters.
Is the Single Source Risk result of $17,097 good or bad?
Neither, on its own — the label “Dual-sourcing at up to $17,097/yr premium is break-even on this line” is the band this figure falls in for the example inputs, and your own inputs will place you elsewhere on the same ladder. Judge the number against your history and your alternatives, and remember that a ten-percent error in Supplier failure probability per year alone moves it by ≈10.0 %.
What affects Single Source Risk the most?
Sensitivity depends on where you start, but the inputs Spend on the single-sourced item ($) and Supplier failure probability per year (%) typically move Single Source Risk further than the rest because they enter the formula multiplicatively. If you can only measure two things well, measure those and hold the others at conservative defaults.
How often should I check Single Source Risk?
Whenever an input changes by more than a few percent, and otherwise on the rhythm of your decisions — before a purchase, a review, a renewal. Single Source Risk is a snapshot, not a subscription; stale snapshots are the most common silent error in Business & Entrepreneurship planning.
Is risk-allocated pricing (paying for backup capacity) worth it?
Compare the premium to the expected cost — reserved second-source capacity usually wins on the maths and always wins at audit.
What about self-insuring with inventory?
Inventory covers short gaps, not requalification gaps — for switch times above a few weeks, stock is a band-aid on a fracture.
Do I need an account to use this Single Source Risk calculator?
No, and no data leaves the tab. The engine runs in the page itself, which is why the worked example, the bands and the sensitivity ranking all respond instantly to your keystrokes.
What the labels on this page mean
- Spend at risk
- $2,825,000 in the default Single Source Risk calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Risk cost as % of spend
- 0.61 % on the example inputs — a companion figure printed beside the headline of Single Source Risk so that no result is read in isolation.
- Cost of halving the switch time
- $8,548 in the default Single Source Risk calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Annual expected risk cost
- The primary output of this tool: $17,097 for the default inputs, computed exactly from Expected risk cost = probability × switch time × weekly margin loss.
- Worked example
- The step-by-step substitution printed above, so the arithmetic can be re-derived by hand or in a spreadsheet.
- Verdict band
- The plain-language label — here “Dual-sourcing at up to $17,097/yr premium is break-even on this line” — mapping the computed figure onto experience-based ranges for Business & Entrepreneurship.
- Sensitivity (±10 %)
- How far the Single Source Risk moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Methodology, sources and limits
The model is published arithmetic implemented exactly as written: Expected risk cost = probability × switch time × weekly margin loss. Source of record: Supply-risk quantification (Kleiber & others). Specialist software layers extra coefficients on top of the same algebra; none are hidden here, and that transparency is what makes a disagreement traceable to a specific input instead of a black box.
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.
Next steps after the calculation
Re-run the calculation with your own figures, stress the two most sensitive inputs by ±10 %, and only then act on the result.
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 Business & Entrepreneurship, a dated figure is a trend, and an undated one is a rumour.