Writing requirements that encode value

Most product requirements documents are quietly dishonest.

They claim to describe what a product must do, but in reality they describe what a product must not fail at. Accuracy thresholds, operating ranges, response times, regulatory clauses, interface constraints — all necessary, all measurable, and all largely orthogonal to why anyone buys the product in the first place.

These are hygiene factors. They keep you in the game. They do not win it.

The problem is not that teams write bad requirements. It is that they write requirements that systematically exclude the very thing that creates value for users and buyers.

The Comfort of Pass/Fail Thinking

Engineering teams gravitate toward binary requirements because they are safe. A statement such as “the instrument shall measure luminance with ±2% accuracy over the specified range” is easy to verify, easy to trace, and easy to defend in reviews.

Yet in practice, this requirement says nothing about whether the instrument is useful.

Consider a low-light measurement instrument used by technicians across multiple shifts. Two instruments may both meet the ±2% accuracy requirement. One produces occasional unexplained deviations that require re-measurement or cross-checking. The other behaves predictably day after day, with any drift clearly signalled.

Both pass. Only one creates value.

A requirement that states “the user shall be able to trust that repeated measurements under unchanged conditions remain consistent within defined limits over a working shift” forces a very different design discussion. It pushes the team toward stability, observability, and confidence — not just numerical accuracy at acceptance.

Value Appears After Shipping, Not at Acceptance

Many requirements are implicitly written for factory acceptance testing. They define what must be true on the day the product ships.

Users, however, experience value over months.

Take calibration as an example. A typical requirement might say “the system shall support calibration using an external reference.” This is easy to verify and easy to trace. It also says nothing about the cost of calibration in time, disruption, or skill.

A value-encoded requirement might instead state: “under normal operating conditions, the system shall not require user-initiated recalibration more than once every six months.”

This requirement immediately constrains the design. It discourages architectures that rely on frequent tuning or software compensation of unstable hardware. It encourages intrinsic stability, margin, and conservative design choices. It also directly addresses user burden — a primary source of dissatisfaction that never appears in traditional specifications.

From Features to Outcomes

Requirements often describe features because features feel tangible. Displays, interfaces, outputs, and modes are easy to enumerate.

But users do not buy features. They buy outcomes.

A common example is data presentation. A requirement might specify a high-resolution graphical display with a defined refresh rate. That tells you what the product has, not what it enables.

A value-oriented requirement might instead state: “the user shall be able to determine, within 10 seconds and without external tools, whether a measurement result is valid under current operating conditions.”

That single sentence drives decisions about error visibility, confidence indicators, reference measurements, and user feedback. It also implicitly deprioritises cosmetic perfection in favour of interpretability — a trade that many teams only confront painfully late.

Buyers Value Risk Reduction, Not Performance Peaks

Requirements documents often reflect the needs of users while neglecting the concerns of buyers. In many markets, especially regulated or capital equipment markets, these are not the same people.

A buyer evaluating a specialised instrument is often asking questions such as:
How likely is this product to become a support problem? How predictable is its behaviour across units? How difficult will it be to justify its results to auditors or customers?

Yet these concerns rarely appear explicitly in requirements.

A requirement that states “all units shall demonstrate equivalent measurement behaviour within defined limits without per-unit tuning” encodes buyer value directly. It legitimises spending effort on manufacturing consistency and architectural robustness. It also reduces long-term commercial risk, even if it slightly increases development cost.

Requirements as Design Levers

When requirements encode value, they stop being passive documentation and start shaping the product.

A requirement that limits acceptable user effort legitimises investing in stability rather than calibration complexity. A requirement that prioritises interpretability legitimises additional internal reference measurements. A requirement that addresses buyer risk legitimises conservative component selection and architectural clarity.

These choices are never free. What changes is that their cost is weighed against explicit value, rather than justified retrospectively after problems appear in the field.

The Shift That Matters

The most important shift is subtle but profound: moving from requirements that ask “does the product meet this condition?” to requirements that ask “does the product reliably create this benefit?”

This does not mean abandoning verifiability or regulatory discipline. It means recognising that value can be specified — even if it cannot always be reduced to a single number. Bounded, outcome-oriented requirements are often more truthful than artificially precise thresholds.

Products fail far more often because they solve the wrong problem precisely than because they solve the right problem imperfectly. Requirements that encode value make that failure mode much harder to reach.

Done well, they ensure that when a product finally passes all its tests, it also earns its place on the user’s bench — and in the buyer’s budget.