Build vs Buy Calculator
The formula
What the build vs buy tells you
The size and shape of the move between two figures — total percent, absolute delta and the annualised rate — for build vs buy.
Calculation: change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1. Enter your inputs and every substitution is shown below the result.
Reading the result
Compare the annualised line with the same measure from a rival or a baseline; the raw percent flatters long periods and punishes short ones.
Limitations and best practice
Percentage-point vs percent confusion: a move from 4 % to 6 % is +50 % relatively but +2 points — state which you mean.
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 percent change symmetric?
Why annualise?
Source & methodology
Standard growth arithmetic.
Build vs Buy: the number, the method and the caveats
This page was written for one job: turning your own inputs into a defensible figure, with the working shown. Build vs Buy 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 Build vs Buy in real time, and see every substitution printed below.
The useful way to hold Build vs Buy is as a ratio with a story attached: change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1 says how the parts combine, and the 35.71% figure above is simply that sentence written in numbers. Everything that follows unpacks one clause of the sentence at a time.
A calculation like this one is worth roughly as much as a careful sentence: it forces several vague considerations into one comparable quantity. Once Build vs Buy is on the table, the argument can stop being about impressions.
Nothing below is stock text pasted around a number: the worked example computes build vs Buy = 35.71% from this tool’s own defaults, and the sensitivity section ranks the inputs that move the result — Before first, at ≈42.2 % 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 Build vs Buy calculation: formula and every input
One formula, published in full: change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1. Anything you can read, you can reproduce in a spreadsheet, and that reproducibility is the whole point of printing it rather than hiding it behind a button.
Before (example value 98) is a plain measured quantity — the unit shown in the label is the unit the formula expects. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
After (example value 133) is a measured number in the unit named by the label; the formula does not convert for you. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
Periods between (years) (example value 4) is a plain measured quantity — the unit shown in the label is the unit the formula expects. If the period is partial, decide whether you mean elapsed or planned time and keep that meaning across every field.
The default Build vs Buy calculation, written out in full
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: Before, After, Periods between (years). The computed build vs Buy comes out at 35.71%, which the interpretation band labels “Solid growth”.
- Δ = 133.00 − 98.00 = 35.00
- Percent = 35.00 ÷ 98.00 × 100 = 35.71 %
- Annualised = (133.00 ÷ 98.00)^(1/4.0) − 1 = 7.93 %
Absolute change — 35.00. Compare it against the main result of 35.71% before drawing conclusions.
Per-period (annualised) — 7.93%. Compare it against the main result of 35.71% before drawing conclusions.
Multiple — 1.36 ×. Compare it against the main result of 35.71% before drawing conclusions.
Keep this worked example open while you enter your own figures: matching the shape of the substitution is the fastest way to spot a unit or convention mistake.
The Build vs Buy corridor: your result across a realistic band
Read this table as the practical error bar on the headline figure. It answers the question people actually have after seeing a single number: how wrong could this be if the main input is off by ten or twenty percent?
| Before setting | Build vs Buy |
|---|---|
| 80 % of the example value | 69.64% |
| 90 % of the example value | 50.79% |
| example inputs | 35.71% |
| 110 % of the example value | 23.38% |
| 120 % of the example value | 13.10% |
The corridor runs from 13.10% to 69.64% across that band — which is the range worth planning inside rather than the single 35.71% point estimate. Reproduce it in the form above by editing Before alone; the substitution steps will follow your figures exactly.
Sensitivity: which inputs change Build vs Buy the most
Generic advice says “it depends on your inputs”; this section says exactly how much. Each field was perturbed by ±10 % in isolation and the build vs Buy recomputed, so the ranking below is measured rather than asserted. It is the fastest honest answer to “what matters most in Build vs Buy?” — and it is specific to these defaults, because sensitivity moves with the starting point.
- Before +10 % → Build vs Buy = 23.38% · −10 % → 50.79% (the build vs Buy shifts ≈42.2 %)
- After: ten percent up gives 49.29%, ten percent down gives 22.14% — ≈38.0 % of the build vs Buy either way
Before is the dominant lever here: ten percent either way moves the result by about 42.2 %, from 23.38% to 50.79%. Spend your verification effort there first, and treat After as the second priority (≈38.0 % per ten percent). The rest of the inputs earn only a rounding-error of attention, and that asymmetry is the practical payoff of measuring rather than asserting.
Interpreting the Build vs Buy verdict
Nobody acts on a bare figure — they act on a figure with a comparison attached. On the example inputs the band reads “Solid growth”; your own figures place you on a different rung of the same ladder. Before treating the band as fact, note its width: ten percent either way on Before already spans 23.38% to 50.79%. The practical reading rules: read the band as a starting hypothesis, then test it: change the two dominant inputs by ten percent and see whether the verdict survives. Verdicts that survive stress are the ones worth acting on.
In Technology & Computing, Build vs Buy is one instrument in an orchestra: on its own it is a number, next to Absolute change and Per-period (annualised) it becomes a diagnosis. The tools linked above exist so the headline never has to carry that weight alone.
How people get Build vs Buy wrong
Percentage-point vs percent confusion: a move from 4 % to 6 % is +50 % relatively but +2 points — state which you mean. 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.
Reporting the headline and quietly discarding Absolute change. The companions are where the shape of the trade-off survives the rounding.
One mistake is specific to this engine: assuming every input matters equally. The computation above shows Before dominating — a careful figure there beats false precision everywhere else.
Another is comparing across contexts: a Build vs Buy computed with one set of conventions should never be lined up against a figure computed with another. Check the inputs behind both before ranking them.
A quick check for any Build vs Buy figure
- Re-run the calculation with a ±10 % stress on the two most sensitive inputs.
- Compare the output against one published benchmark or a colleague’s independent estimate.
- Check Before before anything else: it is the measured dominant input, ≈42.2 % of Build vs Buy per ten percent.
- Recompute once with the dominant input deliberately set low, and see whether the decision changes.
- Note the date and the inputs beside the number so the figure can be audited later.
- Confirm the answer against one independent method or published benchmark for Build vs Buy.
How to use the Build vs Buy 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 before, after, periods between (years) 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. When two sources disagree, it is almost never the arithmetic that differs.
Step 2 — enter the conservative case first. Resist the flattering scenario. Type the inputs you would defend in front of a sceptical reader, read the Build vs Buy (35.71% for the example values), and note the verdict band. Re-running a number costs seconds; retracting a decision costs considerably more.
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. The fastest sanity test is to guess the answer first and see how far the calculation disagrees.
Step 4 — stress before you commit. A decision that survives a ten-percent squeeze on its two biggest inputs needs no luck to be sound. One that does not survive is a decision about hope, not about arithmetic. The point of transparency is that a reader can disagree with a specific line rather than with you.
Step 5 — write the one-line memo. “Build vs Buy = 35.71% on this date, from these inputs.” That line is the entire deliverable; everything else on this page is how you earned the right to write it. The fastest sanity test is to guess the answer first and see how far the calculation disagrees.
The real-world conversations Build vs Buy settles
Numbers earn their keep in conversations, and Build vs Buy is no exception. In Technology & Computing discussions around Software Development, this figure decides whether an option stays on the table: it converts an opinionated debate into an arithmetic one, and arithmetic is the only referee both sides accept. Precision is a promise you make about your data; make sure your inputs can keep it.
Used properly this is a five-minute filter that saves weeks. Compute Build vs Buy, reject what fails, and only then bring in the expensive analysis for the survivors. Precision is a promise you make about your data; make sure your inputs can keep it.
There is a personal-administration use people overlook: periodic self-checking. Build vs Buy quietly drifts as life changes — rates move, bodies change, costs compound — and re-running it a few times a year catches drift while correction is still cheap. When two sources disagree, it is almost never the arithmetic that differs.
The questions that come up most about Build vs Buy
What affects Build vs Buy the most?
Measured on this engine, Before is the dominant lever: moving it ±10 % shifts the build vs Buy across 23.38% to 50.79% — about 42.2 % of the headline, with After next at ≈38.0 %. The ranked list in the sensitivity section is computed live, not asserted from a template.
Which matters more: after or before?
For Build vs Buy, Before wins the head-to-head (≈42.2 % against ≈38.0 % per ten-percent change). Knowing which input dominates is the difference between careful work and merely slow work.
What is a typical Build vs Buy?
With the example inputs on this page the result is 35.71%, labelled “Solid growth”. “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 Build vs Buy by hand?
Three steps: write the formula (change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1), insert your values, and simplify. The worked example section shows exactly that chain for the default inputs; replicating it once on paper teaches you more about Build vs Buy than any number of calculator runs.
What happens to Build vs Buy if before changes by 10 %?
Try it in the form above and the printed substitution will follow you; the pre-computed answer for the defaults is 23.38% to 50.79% across the ten-percent probe, i.e. ≈42.2 % sensitivity on the build vs Buy.
Is the Build vs Buy result of 35.71% good or bad?
Good and bad are comparisons, so the honest test is three questions: where does your own Build vs Buy sit against the 35.71% reference above, how far would a plausible input error move it (≈42.2 % per ten percent on Before), and what does the alternative option compute to?
Why is my measured value different from Build vs Buy?
Real hardware and networks add contention, throttling, and overheads that first-principles Build vs Buy assumes away. Expect the measured number to sit below 35.71%; if it sits far below, that gap itself is the diagnostic.
How often should I check Build vs Buy?
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. Build vs Buy is a snapshot, not a subscription; stale snapshots are the most common silent error in Technology & Computing planning.
Is percent change symmetric?
No — up 25 % needs down 20 % to undo. The multiple output keeps the round trip honest.
Why annualise?
It puts unequal time spans on one scale, making 4-year and 9-month comparisons legible.
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.
The vocabulary of Build vs Buy
- Absolute change
- 35.00 on the example inputs — a companion figure printed beside the headline of Build vs Buy so that no result is read in isolation.
- Per-period (annualised)
- 7.93% on the example inputs — a companion figure printed beside the headline of Build vs Buy so that no result is read in isolation.
- Multiple
- 1.36 × in the default Build vs Buy calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Build vs Buy
- The primary output of this tool: 35.71% for the default inputs, computed exactly from change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1.
- Worked example
- Every substitution in order, from the example inputs to 35.71% — the audit trail for the headline figure.
- Verdict band
- The plain-language label — here “Solid growth” — mapping the computed figure onto experience-based ranges for Technology & Computing.
- Sensitivity (±10 %)
- How far the Build vs Buy moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Method, sources and what this tool cannot tell you
Everything above runs on one stated formula, applied without hidden coefficients: change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1. Source of record: Standard growth arithmetic. 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.
Nothing here replaces a qualified professional, and nothing here is approximate either — the arithmetic is exact, and the honesty is in the inputs you supply. What that buys you is reproducibility — two people, two browsers, the same arithmetic, and a printed trail from inputs to result that either of them can audit.
Turning this Build vs Buy into a decision
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 Technology & Computing, a dated figure is a trend, and an undated one is a rumour.