Catalog
concept#Product#Software Engineering#Quality Assurance

Human Factors

An interdisciplinary approach to designing systems that consider human abilities, limitations, and behaviours.

Human Factors is the interdisciplinary study of how humans interact with systems, products and environments, focusing on usability, ergonomics and cognitive load.
Established
High

Classification

  • Medium
  • Organizational
  • Design
  • Intermediate

Technical context

Design systems and pattern librariesProduct analytics and telemetry platformsUser research tools (remote tests, surveys)

Principles & goals

User-centred: Prioritize user needs and contexts.Error tolerance: Design systems so errors are detected and corrected early.Consistency: Uniform patterns and language reduce cognitive load.
Discovery
Enterprise, Domain, Team

Use cases & scenarios

Compromises

  • Misinterpreting user data leads to wrong design decisions.
  • Overfitting to test conditions instead of real usage.
  • Neglecting accessibility may have legal consequences.
  • Test early with low-fidelity prototypes
  • Use a mix of qualitative and quantitative methods
  • Ground design decisions with clear metrics

I/O & resources

  • User profiles and personas
  • Prototypes or production interfaces
  • Tasks and usage scenarios
  • Usability reports and recommendations
  • Prioritized improvement backlog items
  • Metrics to monitor user success

Description

Human Factors is the interdisciplinary study of how humans interact with systems, products and environments, focusing on usability, ergonomics and cognitive load. It guides design choices to reduce errors, improve efficiency and enhance user satisfaction across technical and organizational contexts. It provides evaluation criteria, requirements and trade-offs.

✔

  • Lower error rates and safer operation.
  • Increased efficiency and faster task completion.
  • Higher user satisfaction and better product adoption.

✖

  • Requires access to representative users for valid insights.
  • Can be time- and resource-intensive initially.
  • Not all findings transfer directly between domains.

  • Task success rate

    Percentage of users who complete a defined task successfully.

  • Error rate

    Number of critical and non-critical errors per user or task.

  • Time on task

    Average time users take to complete a task.

Checkout process optimization

An online retailer reduced checkout drop-offs by 20% through redesign and clearer error messaging.

Industrial control panel

A manufacturer reduced operator errors via standardized layouts and color hierarchy.

Mobile app onboarding

Optimizing onboarding steps decreased registration time and improved retention.

1

Align stakeholders on goals and target users

2

Define representative user profiles and tasks

3

Plan, run and operationalize iterative tests

⚠️ Technical debt & bottlenecks

  • No documented design principles and patterns
  • Outdated components in the design system
  • Missing telemetry for user interactions
limited-user-researchlegacy-interfacescomplex-workflows
  • Treating a single usability test as sufficient validation
  • Considering feedback only from power users
  • Making design decisions without considering organizational processes
  • Overvaluing small A/B effects without context
  • Ignoring fringe user groups with high risk
  • Unclear metric definitions lead to misinterpretation
UX research and test moderationInteraction design and information architectureData analysis for user behaviour
Achievable usability for target usersError tolerance and recoverability of critical flowsAccessibility and regulatory requirements
  • • Privacy and testing conditions with real users
  • • Budget and time limits for studies
  • • Technical restrictions of existing platforms