A service design learning I’m bringing into UX research

One of the concepts that stayed with me from a recent service design cohort was the distinction between value demand and failure demand.

The concept comes from systems thinking and is deceptively simple. Value demand represents the reasons customers engage with a service in the first place. They want to accomplish something the service exists to help them do.

Failure demand, a concept associated with systems thinker John Seddon, is different. It is demand created when an organization fails to do something, or fails to do it right, for the customer.

A customer contacts support because an online process was unclear. They reach out again because the first interaction did not resolve the issue. An employee has to intervene manually because the intended process cannot accommodate what the customer needs.

Each interaction may appear individually as another service request. Viewed as part of a broader system, however, it tells a different story.

That distinction made me think about UX research.

UX researchers are accustomed to identifying friction. We observe behavior, uncover unmet needs, identify pain points, understand why people struggle, and translate those findings into opportunities for improvement.

A pain point itself can emerge for any number of reasons. It may reflect a usability issue, a process constraint, a business rule, a regulatory requirement, a technical limitation, or some combination of factors.

Understanding the source matters, but that is not where I see the primary opportunity in borrowing from failure demand.

The opportunity comes in what we do with the finding once we have identified it.

A conventional research narrative might move from:

Pain point → Evidence → Severity → Opportunity

But what if, for certain findings, we extended that narrative by asking another question:

What additional demand is this experience generating?

Applying a failure-demand lens could extend the narrative to:

Pain point → Evidence → Failure demand → Customer impact → Operational impact → Measurable consequence → Opportunity

The intent is not to replace established research frameworks or suggest that every finding requires this level of analysis. Rather, it provides another lens for findings where the consequences extend beyond the immediate interaction.

Consider something relatively ordinary: a customer encounters difficulty completing a task.

Research may reveal confusing terminology, unclear information hierarchy, an interaction that does not align with the customer’s mental model, or another source of friction.

The experience, however, may not end there.

The customer may try again. They may contact support. An employee may need to investigate. The issue may require escalation or manual intervention. The customer may abandon the task altogether.

Those consequences do not necessarily explain why the original experience problem exists. They tell us something different: what the customer and the organization are absorbing because it exists.

This is where I believe borrowing failure demand from systems thinking can add another dimension to UX research.

Qualitative evidence can help explain what customers are experiencing and why. Behavioral data can help establish how frequently something occurs. Operational measures can reveal whether the same issue is generating additional work elsewhere.

Repeat contacts. Escalations. Rework. Manual intervention. Employee effort. Abandonment.

Where reliable financial data is available, cost can become another useful signal.

The goal is not to attach a dollar value to every pain point. Not everything meaningful can or should be reduced to a financial measure. Depending on the problem, contact volume, completion rates, employee hours, escalation rates, or another operational measure may tell the story more appropriately.

The larger opportunity is connection.

Bringing these signals together allows a finding to communicate not only the severity of the customer problem, but its broader consequences across the service.

For leaders evaluating competing priorities, that additional context can be meaningful.

A finding that tells us customers are confused identifies an experience problem.

A finding that shows the same confusion is contributing to repeat contacts, manual intervention, or abandonment begins to reveal its impact across the system.

The research remains grounded in the human experience, but its implications become visible through measures that other parts of the organization already understand and use to make decisions.

Research into failure demand across service environments reinforces the broader principle behind this thinking: problems created within a service can generate additional demand and consume organizational capacity. Customer experience research has similarly demonstrated the relationship between improving end-to-end journeys, reducing unnecessary service interactions, and improving cost to serve.

The experience and the operation, after all, are not separate systems.

What customers encounter during an interaction can create work elsewhere. What employees must compensate for behind the scenes can signal friction within the experience. What appears to one team as call volume, rework, or an escalation may have begun somewhere else as an unmet customer need.

For UX research, this does not mean becoming responsible for operational analytics, financial modeling, or service performance. Those capabilities may already exist across analytics, operations, product, finance, customer service, and service design.

The opportunity is to connect the evidence.

There is also an important distinction to preserve. Not every repeat interaction represents failure demand. Customers legitimately return to organizations with new needs, changing circumstances, questions, and ongoing service requirements. Understanding why the demand exists from the customer’s perspective remains essential before determining what it represents.

Perhaps the opportunity, then, is not for UX research to become more operational.

It is for research to make more of the consequences of experience visible.

Borrowing a lens from another discipline does not change the fundamental purpose of UX research. In this case, it may simply help us tell a more complete story about what we already uncover.

When we can connect what customers struggle with to what that struggle generates across a broader service system, research can communicate not only what should improve for the customer, but why addressing it may create value well beyond the immediate interaction.

That is one learning from service design that I intend to carry forward in my own research practice.

References

This reflection emerged from a concept I explored during a recent service design cohort and began considering through the lens of my own UX research practice. It was further informed by research on systems thinking, failure demand, customer experience, and service operations. Selected references include:

Seddon, J. Systems thinking and the concepts of value demand and failure demand in service organizations.

Walley, P., Found, P., & Williams, S. Research examining failure demand within service environments.

Morris, G., & Walley, P. Research examining failure demand reduction as part of demand management.

McKinsey & Company. Research on customer journeys, service interactions, and cost to serve.