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A process taking “about five minutes” does not, by itself, justify a requirement that it must finish within five minutes. An observation, an estimate, a performance target and an acceptable limit are different claims. Before turning a time—or any other measured value—into a hard requirement, establish where it came from, what it represents and what happens if it shifts.
Why “five minutes” can sound more certain than it is
Dieter Goetz uses the sentence “The process shall complete within five minutes” to illustrate how an informal observation can acquire the force of a contractual or test boundary. Someone may have recalled a duration in an interview, timed one instance, or described a typical result. None of those facts alone tells a reader whether five minutes is an average, a maximum, a target, a variable outcome or an estimate.
Once the number is written as a firm requirement, engineers, testers, suppliers and project managers may treat it as settled. The sentence is measurable, but measurability is not proof that the limit reflects the evidence or anyone’s needs. Goetz’s article, published October 5, 2026, frames the issue as requirements discipline—not as a claim that five minutes is inherently a bad threshold. Read the article on HackerNoon.
Separate the observation, its meaning and the boundary
A sound requirement keeps three things distinct: what was observed, what the observation means, and the boundary a system is expected to meet. For example, a single run that took about five minutes is evidence of one run under particular conditions. It does not establish typical performance, a worst case or an acceptable service limit.
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- Observation: What happened, and how was it measured or recalled?
- Interpretation: Is the value an average, a single instance, a target, an estimate or something else?
- Boundary: What threshold must the system meet, and what evidence or consequence justifies it?
When these are collapsed into one precise-sounding sentence, the requirement can claim more certainty than its source supports. As Goetz puts it: “Precision in the specification should never exceed precision in the evidence without a reason.”
Trace where the number came from
Start with the question “Where did the five minutes come from?” A useful answer identifies the source and the measurement conditions, rather than repeating the number as if its meaning were self-evident. If the value came from an estimate or a remembered example, say so; if it came from timed runs, clarify what those runs represent. The article does not report an empirical study establishing how common false precision is or quantifying its costs, so avoid treating the problem as a measured rate or financial impact.
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Then ask “What evidence justifies this precision?” The answer should explain why the requirement uses a specific cutoff rather than a looser target, a statistical condition or no time limit at all. A measured value can be useful input without automatically becoming the acceptance boundary.
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A threshold should matter to someone or something. Goetz suggests asking: “If ‘5 minutes’ became 5 minutes 10 seconds, would anybody care?” He also raises a 5 minutes 30 seconds variation and asks where a stakeholder, user, process or physical constraint would notice the difference. These are diagnostic questions, not measured findings.
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If modest deviations have no meaningful operational effect, the original number may not belong as a hard requirement. If users, a dependent process or a physical constraint would be affected, identify that consequence and use it to explain why a boundary is needed. Do not assume that a round or memorable number is important merely because it is easy to test.
Review a precise requirement before accepting it
For a conspicuously precise number, work through these questions before treating it as a pass-or-fail limit:
- Identify the evidence: Is the number a single observation, repeated observations or an estimate?
- Name its meaning: Is it an average, a target, a maximum, a minimum, a contractual threshold or a safety boundary?
- Record the conditions: What process and circumstances produced the measurement, and do they match the requirement’s intended use?
- Test the consequence: What would change for users or operations if the value moved slightly?
- Choose the boundary separately: State the acceptable tolerance only after the evidence and practical consequence are clear.
- Keep the trace: Preserve the source information and the interpretation that connect the evidence to the final threshold.
This is a practical review sequence based on Goetz’s advice, not a formal standard. Where two candidate thresholds are being considered, compare their evidence basis, what each value means, measurement conditions, allowed variation and consequences—not just which number looks more precise.
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A requirement can make its scope clearer by stating how much of a set of transactions must meet a duration. Goetz gives this illustrative sentence: “95% of transactions shall complete within six minutes.” It is an example of wording, not a measured result or a recommended threshold for any particular service. The appropriate percentage and duration depend on the use case, supporting evidence and stakeholder agreement.
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If a percentile is used, make sure the requirement explains what population or set of transactions it applies to and how completion time is assessed. Statistical wording does not repair a weak basis for the chosen number; it makes the intended tolerance more explicit only when the underlying choices are justified.
What a good requirement should let a reader understand
A reader should be able to see what was observed, how that evidence was interpreted, and why the resulting limit matters. If that chain is missing, a precise time can still be misleading. The aim is not to avoid numbers; it is to make the stated precision earn its place.
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