Failure demand has been part of contact centre life for decades. A customer receives the wrong information, a process breaks, a digital journey fails, an action isn’t completed or something simply isn’t clear — and the customer contacts the organisation to get it fixed.
But while contact centres have become increasingly sophisticated at handling that demand, are we actually getting any better at preventing it?
That was the focus of a recent Contact Centre Network discussion with David Holmes, Director of Sales at SSE Energy Solutions, and James Ravel, experienced Contact Centre Director and Head of Customer Service, exploring how organisations can move beyond simply servicing failure and start turning customer contact into genuine value creation.
Failure demand is often an upstream problem
One of the biggest challenges is that the contact centre is frequently dealing with problems it didn’t create.
James described failure demand as:
“An upstream problem with a downstream address — and the contact centre is very much downstream.”
That distinction matters. Contact centres can improve scheduling, reduce average handling time, introduce new channels and increase productivity, but none of those interventions necessarily remove the underlying reason customers are getting in touch.
Failure might have originated in product design, billing, marketing, a website journey, an app, a policy decision or a poorly communicated process.
This means tackling failure demand requires a much broader organisational response.
James argued that before organisations rush towards solutions, they first need clarity around what customer service is actually there to achieve.
“You have to establish what good looks like, what the value proposition of the contact centre is, what is the value of the calls that we’re doing, and what exactly is failure.”
Importantly, that definition will differ between organisations. A contact that appears avoidable on a spreadsheet may be entirely appropriate when vulnerability, complexity or customer circumstances are taken into account.
Stop managing the symptoms
Contact centres have traditionally been very good at reacting to demand.
- Volumes increase? Add resource.
- Queues increase? Reduce handling time.
- Customers repeat contact? Focus on first contact resolution.
But an operational response to a process problem can quickly become a cycle of managing symptoms rather than removing causes and James summarised the challenge perfectly:
“You can’t efficiently manage your way out of failure demand. You have to dissect that and then take it out of your operating model.”
That requires contact centre leaders to look beyond the traditional boundaries of their operation. Marketing teams, digital teams, product owners, IT, finance and process owners all need visibility of what customers are actually experiencing.
Listening to customer conversations can be particularly powerful. Instead of the contact centre continually absorbing the consequences of poor journeys, customer interactions become evidence that can drive improvements elsewhere.
David made the point that failure demand, although undesirable, provides organisations with something extremely valuable: intelligence.
“The great thing about failure demand is it tells you a lot about your business if you want to learn from it.”
Every repeat contact, complaint, escalation and confused customer is effectively highlighting friction somewhere within the organisation. The question is whether anyone is listening.
Are our metrics reinforcing failure?
There is also a danger that traditional contact centre measures unintentionally encourage organisations to process failure more efficiently rather than eliminate it. Average handling time, speed of answer, tickets closed and even first contact resolution can drive the wrong behaviours if they become objectives rather than indicators.
David questioned whether many traditional targets genuinely reflect the customer outcome.
“If you’re going to put a target around anything, what’s the problem you’re trying to solve?”
An advisor might technically close an interaction within the required time and achieve their target, yet the customer contacts the organisation again several weeks later because the underlying issue was never resolved. In that scenario the metric looks positive, while the customer journey remains broken. The better question becomes: did we achieve the right outcome for the customer?
That requires organisations to think beyond individual transactions and towards longer-term measures including repeat demand, effort, retention and customer lifetime value.
Complaints can become an intelligence engine
Complaints are perhaps one of the clearest examples of failure demand being treated purely as a cost. They require additional handling, investigation and often specialist resource. But James argued that organisations should see something else within them: opportunity.
“Someone has taken the time and they still care enough to get involved and to want you to do something about it.”
Handled effectively, a complaint creates two potential sources of value. Firstly, there is an opportunity to recover the relationship and potentially turn a detractor into an advocate and secondly, complaints provide rich intelligence about what is failing across the customer journey.
Rather than the contact centre being the organisation’s downstream recipient of problems, James suggested it should become the:
“Downstream agitator rather than the downtrodden downstream producer.”
That requires customer service leaders to take insight back into the wider organisation and challenge the processes creating unnecessary contact.
Don’t boil the ocean with data
Most organisations no longer suffer from a lack of data. The bigger problem is knowing what to do with it.
Speech analytics, CRM data, interaction analytics and increasingly AI can expose thousands of potential areas for improvement. Trying to solve everything simultaneously, however, can quickly result in very little actually changing.
David recommended starting with one simple question:
“Where’s your biggest customer pain point?”
Identify it. Understand its root cause. Fix it. Measure the impact. Then move onto the next problem.
James proposed an equally practical 30-30-30 approach.
- Use the first 30 days to analyse conversations and identify the three largest failure points.
- Use the next 30 days working with the people who genuinely have the ability to change those processes.
- Then spend the final 30 days measuring whether those changes created value.
It creates a much stronger improvement story than attempting a huge transformation programme from day one.
AI should expose failure – not hide it
Inevitably, the conversation turned to AI. Automation creates a major opportunity to handle simple transactions efficiently, analyse huge volumes of conversations and identify patterns that humans could never manually uncover.
But there is also a significant risk, if AI makes failure demand significantly cheaper to service, organisations may lose the incentive to remove it. Automating a broken journey doesn’t necessarily fix it, as James put it:
“You’re not going to fix customer effort just by automating a problem. You’re just going to make it quicker to get the customer frustrated.”
David offered a similar warning about equating speed with success.
“People need to get away from the concept that velocity equates to value. Just because something’s quick doesn’t make it good.”
AI therefore needs to become an enablement tool for continuous improvement, not simply another layer placed over legacy processes. Human oversight remains critical. Organisations still need people reviewing automated journeys, analysing outcomes and asking whether the original problem should exist at all.
Start at the coalface
Perhaps the simplest advice came towards the end of the conversation. When asked where an operational leader struggling with failure demand should begin, David’s answer was straightforward:
“Go sit with your teams and find where the answers are. Get onto the coalface.”
Technology can help, analytics can accelerate discovery and AI can analyse thousands of interactions, but none of those replace understanding what customers and frontline employees experience every day. The biggest opportunity for contact centres may therefore not be handling failure faster or more cheaply.
It is becoming the part of the organisation that understands why customers need help in the first place and using that intelligence to make sure fewer of them need to ask for it again.
That is when failure demand stops simply being an operational cost and starts becoming a source of value.
So what’s the key message?
Failure demand should not simply be treated as a contact centre problem to manage more efficiently. It is often a symptom of wider process, product or journey issues elsewhere in the organisation. By using customer conversations, complaints and analytics to identify root causes, leaders can move from reacting to demand towards preventing it. AI can accelerate that insight, but the real value comes from combining data with frontline experience and using both to remove the problems creating unnecessary customer contact in the first place.
What’s your thoughts? How do you turn failure demand into value creation?
