What are non-functional requirements?
An order-management system may work well in a demonstration with a few users and then slow down when the sales team starts work. Staff submit again because no response appears, then spend time checking which orders were recorded. Every screen is present, yet the working day does not go as expected.
This hypothetical situation shows why a feature list cannot establish whether a system will work in practice. Expected demand, operating hours, data consistency and the response to failures also need to be defined. These are among the concerns addressed through non-functional requirements.
1. What are non-functional requirements?
Functional requirements describe what software must do, such as create orders, reserve stock or produce reports. Non-functional requirements describe the quality, operating conditions and constraints under which it must do those things. Being able to search for orders is different from providing an acceptable search experience when many people work simultaneously.
The boundary is not always absolute. A security requirement may lead to permission-management functions, while traceability may require a change-history screen. The important outcome is a requirement that can be designed and verified, with clear ownership, rather than an unresolved debate about its category.
Discuss these requirements when defining scope. Discovering near acceptance that all branches must work concurrently or that order-taking cannot stop during business hours may require changes to data design and deployment. A seemingly simple operating condition can have substantial technical consequences.
Read more: What Is Requirements Analysis? A First Step Toward Clearer Development
2. Which requirements should your business clarify?
Before filling in a technical checklist, walk through an end-to-end task with the people doing it. In the hypothetical order system, staff find a customer, check stock, submit an order, receive confirmation and hand it to the warehouse. At each point, ask who is affected by delay, incorrect information or failure, and how work would continue.
The following table illustrates that analysis, rather than a mandatory specification for every system. Answers may produce performance, recovery, security or operating requirements, and some also need to become explicit functional rules.
| Situation | What to clarify | What can go wrong |
|---|---|---|
| Many users search at the start of the day | Critical actions, concurrency, data volume and acceptable response time | A small demonstration works while actual usage slows down |
| A user resubmits while confirmation is missing | How receipt is checked and duplicate processing is prevented | One request is processed more than once |
| A connected service is unavailable | Retained state, permitted retries and notification ownership | Users do not know whether to wait or resubmit |
| Data is changed incorrectly or the system stops | Recovery scope, acceptable interruption and who confirms usability | A copy exists but order-taking cannot resume |
| A list is exported or responsibility changes | Who may view, export and edit, and which actions need recording | Information escapes its intended scope or changes cannot be attributed |
Usability and operations also need a task-based view. A message saying only “failed” may leave staff unsure whether an order exists. A technical alert with no recipient does not resolve an interruption. Describe what the user must understand and what operations needs to see to respond.
Distinguish staying available from being recoverable. A system may rarely stop but lack a suitable response to incorrect data changes. Conversely, having a backup does not mean service resumes immediately. These are different questions and may need different verification.
3. How do you write requirements that can be tested?
A useful structure identifies the user scenario, measurement conditions, required result, verification and owner. It makes the subject of the assessment explicit. “The system is fast” does not name an action; “supports many users” does not establish whether those users are reading data or submitting transactions.
The following invented numbers illustrate wording, not an industry benchmark or a Fenix commitment: “Using an agreed test environment, a dataset of 200,000 orders and a scenario with 50 concurrent users, at least 95% of successful searches must display results within two seconds.”
To make that usable, also define tested filters, the start and end of measurement, representative devices and networks, and the workload. Record failed and timed-out requests separately with their own acceptance conditions. Do not omit them and report only the speed of successful requests.
A percentage target is different from an average: a low average can coexist with some very long waits. If the remaining searches affect critical work, define the relevant limits and handling too. Add metrics because they address an identified risk, not to make the document look sophisticated.
If evidence is insufficient, do not invent a target. Use current operating data, observe peak periods or run an investigation, marking assumptions and decision dates. Business owners explain acceptable impact, the technical team assesses feasibility and cost, and both agree the target.
4. Set targets that balance business needs and cost
Higher targets can require different arrangements and costs. If an internal report is only needed by the next working day, immediate reporting may add little value. Order confirmation may deserve more attention because a customer is waiting and the warehouse is preparing dispatch. Prioritize workflows rather than impose one target everywhere.
Discuss options and consequences. Is a notified maintenance window acceptable? Can a large report run in the background and notify users when ready? These choices may meet the real need more economically, but affected users must agree and the scope must describe them.
Separate the business objective from a technical choice. Avoiding lost orders when a component fails is a need to clarify; requiring a particular architecture already chooses a solution. Unless a confirmed constraint applies, let the technical team propose and demonstrate an approach rather than fixing the technology first.
5. Verify requirements during acceptance testing and operation
Approved requirements need to feed into design and testing. Business owners confirm scenarios and impact, the technical team prepares measurement and evidence, and an authorized person decides whether deviations are acceptable. A line in an initial document without verification planning offers little protection for either side’s expectations.
Keep test conditions with the results. Tests using little data or a substantially different environment need explicit limitations rather than an unqualified pass. For interruptions, check transaction state, recovery and resuming work, not merely whether the server restarts.
Software acceptance: What should your business test?
Revisit assumptions when users, branches or integrations grow. If targets are no longer met, distinguish changed demand from failure to meet the original agreement. Requirement history and test evidence help explain the issue rather than relying on the impression that software has suddenly become slow.
For a project discussion, bring three things: work that must not be interrupted, significant usage periods or volumes, and previous incidents that created extra work. With Fenix, clarify required conditions, further investigation and verification. The value of non-functional requirements is turning quality expectations into decisions that business and technical teams can act on.
