SME Software Strategy

Software requirements for custom projects: what should be clear before you build?

A practical requirements checklist for custom software, AI workflows, portals, dashboards, and internal tools.

Ingmar van Maurik17 min read

In short

Before building custom software, clarify users, workflow steps, permissions, data sources, edge cases, integrations, acceptance criteria, and ownership. Good requirements describe decisions and outcomes, not only screens.

Why this matters: A practical requirements checklist for custom software, AI workflows, portals, dashboards, and internal tools.

What to do next

  • 1Define user roles.
  • 2Map the workflow end to end.
  • 3List integrations and data sources.
  • 4Write acceptance criteria for the first release.

What to look at first

Requirements should make the first build smaller and clearer, not turn into a heavy document nobody uses.

  • Define user roles.
  • Map the workflow end to end.
  • List integrations and data sources.
  • Write acceptance criteria for the first release.

What the result should be

Clear requirements lower build risk and make fixed-fee project scope easier to price.

Start with the outcome and the work as it happens today

Useful requirements explain why a process must change, not only what a screen should contain. Observe current steps, waiting time, hand-offs, errors and manual checks. Define the result that should improve, such as quote turnaround or duplicate entry. This gives the delivery team room to design the strongest answer without turning an early interface preference into a permanent constraint. Every significant feature should connect to an operating result or a necessary control.

  • Record the business objective, baseline and intended improvement.
  • Watch representative users perform real work and exceptions.
  • State which decisions remain with people.
  • Link major capabilities to measurable process outcomes.

Write scenarios that include exceptions

The happy path rarely defines the real effort. For each scenario, name the initiating role, required information, rules and completion point. Add missing data, duplicate requests, rejection, correction and service failure. Exceptions often consume more engineering time than the main path and cause the most operational pain. Use plain language and real examples first; the team can turn them into user stories, data models and technical tasks after the process is understood.

  • Trigger and accountable role.
  • Required input, source and quality check.
  • Normal flow, alternatives and recovery paths.
  • Outcome, notification and required audit record.

Make non-functional requirements measurable

Performance, security and resilience are part of the product. A workflow that works in a demo but fails at month end is not complete. Define expected volumes, response time, permissions, audit history, retention, accessibility, recovery and support. Avoid labels such as 'secure' or 'fast' without a test. Requirements such as multifactor authentication for administrators, an agreed recovery point and a tested peak-volume response can be accepted objectively.

  • Users, record volumes, concurrent activity and seasonal peaks.
  • Role permissions, sensitive fields and audit events.
  • Availability, backups, recovery objectives and incident ownership.
  • Supported devices, browsers, accessibility and languages.
  • Monitoring, support cover and expected response times.

Define data ownership and integration behaviour

Projects frequently struggle because nobody agrees which record is authoritative. For each important field, define the owning system and the team responsible for quality. An integration requirement should cover authentication, direction, frequency, retries, duplicate prevention and behaviour during an outage. Supply representative examples with personal data removed where possible. Migration and integration can then be validated during design rather than discovered immediately before launch.

  • Maintain a shared glossary for customers, orders, candidates and statuses.
  • Assign one authoritative source for every core data object.
  • Specify synchronisation, failure queues and reconciliation.
  • Document migration rules for history, duplicates and missing values.

Prioritise and accept requirements with evidence

Not every request belongs in release one. Prioritise only after discussing business impact, dependency and risk, and state what is deliberately deferred. Give each core requirement an owner and a concrete acceptance example. During review, a user should be able to complete the scenario with realistic roles and data. New learning is expected, but it should enter visible change control so time, cost and displaced scope are considered together.

  • Group requirements around complete user goals.
  • Publish exclusions and later phases beside the launch scope.
  • Test real roles, realistic records and known exceptions.
  • Keep decisions and changes traceable to the affected requirement.

Written and reviewed by

Ingmar van Maurik

Founder, AI JOB TEAM

Builds practical AI, automation, and custom software systems for growing companies that need less tool sprawl and more ownership.

Editorial note

Written for decisions, not generic search traffic

AI JOB TEAM uses AI-assisted drafting for research structure and coverage checks. Ingmar van Maurik reviews the positioning, examples, and final recommendations so every article stays practical for growing companies.

Industry applications

See how this topic translates into a concrete workflow for a specific business type.

FAQ

Where should a growing company start?

Start with one workflow where volume, cost, or customer impact is already visible. That keeps scope small and learning fast.

When is this worth a deeper roadmap?

It is worth a roadmap when the topic touches multiple teams, systems, or recurring decisions.

How detailed should requirements be?

Detailed enough for people to share and accept the same scenario, but not so technical that the solution is predetermined. High-risk rules and exceptions deserve the most detail.

Who owns the requirements?

An internal product or process owner. A supplier can analyse and document them, but the organisation must confirm business rules, priority and acceptance.

Can AI write our requirements?

AI can organise interviews and point out unanswered questions. Users and specialists still need to validate every scenario; a polished document is not evidence that the process is correct.

Next step

Turn this into a software decision

Use the Software Scan to compare SaaS spend, ownership risk, and the first workflow worth replacing.

Related articles

Topic cluster

Continue with closely related pages in this content cluster.