Designing for complex systems: Traditional UX research methods are not enough

Traditional UX research methods such as interviews and contextual inquiries are invaluable tools for designers. However, when it comes to researching users who work on domain specific complex applications, this is not the case! We need to be flexible and adapt these methods to uncover notable insights. A few simple tweaks to traditional UX research approaches will result in gaining the insights we require to reduce the learning curve and improve the speed and accuracy of users of complex systems.

What is meant by a complex system?

A complex system is any application supporting the broad, unstructured goals or nonlinear workflows of highly trained users in specialized domains. Complex apps certainly vary in the type of workflows and end users they support — from research scientists to military professionals to financial analysts, for example. But they often share similar qualities. For example, complex apps frequently:

• Support highly trained users with specialized knowledge
• Help users navigate and manage large underlying data sets and enable advanced sensemaking or data analysis
• Support problem solving or end goals with unknown or variable underlying tasks
• Require handoff or collaboration among multiple roles, tools, or platforms
• Mitigate the risks of executing high-impact (or high-value) tasks, where high loss (e.g., revenue or even lives) is at stake