{"id":72772,"date":"2025-08-06T09:44:08","date_gmt":"2025-08-06T08:44:08","guid":{"rendered":"https:\/\/www.cxtoday.com\/?p=72772"},"modified":"2025-11-25T08:33:03","modified_gmt":"2025-11-25T08:33:03","slug":"failure-demand-in-cx-the-hidden-cost-ai-can-solve-enghouse","status":"publish","type":"post","link":"https:\/\/www.cxtoday.com\/contact-center\/failure-demand-in-cx-the-hidden-cost-ai-can-solve-enghouse\/","title":{"rendered":"Failure Demand in CX: The Hidden Cost AI Can Solve"},"content":{"rendered":"

Failure demand isn\u2019t a new concept, but it is one that CX teams often overlook.<\/p>\n

It\u2019s the kind of interaction that clogs up your lines, eats into agent time, and chips away at customer satisfaction.<\/p>\n

It isn\u2019t because someone is asking for help; it\u2019s because something has already gone wrong. And more often than not, the problem didn\u2019t start in the contact center.<\/p>\n

\u201cYou\u2019re getting demand that\u2019s not necessarily fixable in the contact center,\u201d explains Simon Adnett<\/strong>, VP of Sales for the UK&I \/ EMEA at Enghouse Interactive<\/strong>.<\/p>\n

It\u2019s happening because a process has gone wrong in another part of the business. But your agents are the ones dealing with it \u2013 over and over again.<\/p><\/blockquote>\n

It\u2019s a cost, both in terms of time and money, that doesn\u2019t show up neatly on your dashboards. And because it\u2019s caused by issues outside of CX, it\u2019s often ignored.<\/p>\n

With the rise of AI-powered analytics and quality monitoring, failure demand is finally becoming visible. This means that, for the first time, it\u2019s also fixable.<\/p>\n

Not All Demand is Good Demand<\/h2>\n

Most contact center leaders know the shape of their demand. What they often miss is the quality of it.<\/p>\n

Some contacts are productive. When a customer needs support, a quote, or an update, that\u2019s value demand.<\/p>\n

But when someone\u2019s calling because they didn\u2019t get a delivery, or because they\u2019re chasing an SLA that\u2019s already slipped, or because a repair wasn\u2019t done when promised, that\u2019s failure demand.<\/p>\n

And it stacks up fast.<\/p>\n

Adnett details how \u201cmost contact centers have the same challenge.<\/p>\n

\u201c You have significant demand coming in and a headcount that often doesn\u2019t match.<\/p>\n

\u201cSo what do you do? You look at automation, at AI, at anything to close that gap. But if a chunk of that demand is self-inflicted? You\u2019re solving the wrong problem.\u201d<\/p><\/blockquote>\n

Failure demand has a unique sting.<\/p>\n

It doesn\u2019t just waste resources; it actively damages the customer experience. And the frustrating part is that it usually originates somewhere else entirely.<\/p>\n

Broken Processes, Missed Promises, and the Domino Effect<\/h2>\n

Failure demand rarely looks like a neat root-cause ticket.<\/p>\n

It will often surface as a repeat call, a chase-up, or a vague question that usually starts with: \u201cjust checking on\u2026\u201d<\/p>\n

These instances all sound harmless enough until you spot the pattern.<\/p>\n

Although it can often be attributed to a logistics issue, sometimes it\u2019s internal friction where data hasn\u2019t been passed between teams or responsibilities are unclear.<\/p>\n

In these scenarios, while SLAs are technically being hit, customers are still unhappy, as Adnett explains:<\/p>\n

It might be a supplier issue or a breakdown between teams. But the result is the same: unnecessary, preventable contact.<\/p><\/blockquote>\n

And most of the time, it slips under the radar.<\/p>\n

Why Traditional QA Misses the Signs<\/h2>\n

One major reason customer service and experience teams miss failure demand is that most QA programs sample just a fraction of total interactions.<\/p>\n

Some companies analyze just one or two percent of their interactions. This is enough to check a compliance box, but not enough to spot recurring friction.<\/p>\n

\u201cI remember a CX leader sharing how they\u2019d built a strong QA team, invested in tools, everything,\u201d says Adnett.<\/p>\n

\u201cBut the complaints kept coming. So they brought in auditors, who systematically went through every interaction over a set period and found the issue . It was a broken process.<\/p>\n

\u201cCustomers were falling through the cracks.\u201d<\/p><\/blockquote>\n

Small samples give you surface-level reassurance. They don\u2019t reveal the systemic issues that drive failure demand and cause damage to your brand. For that, you need a much wider lens.<\/p>\n

The AI Difference: From Gut Feel to Hard Evidence<\/h2>\n

This is where AI shifts things. Properly applied, it can analyze 100 percent of your interactions \u2013 not just for what\u2019s said, but how it\u2019s said, and why.<\/p>\n

It can look at the sentiment of the call, including any sentiment shift, and provide a categorisation of what types of interactions are driving the most positive or negative sentiment and the volumes associated with those.<\/p>\n

Adnett sums this up nicely, detailing how \u201cAI lets you turn the micro into the macro,\u201d and allows users to \u201cspot the hotspots, then dive into the detail.\u201d<\/p>\n

With automated sentiment analysis, category detection, and heatmap-style dashboards, teams can quickly surface recurring issues.<\/p>\n

\u201cYou can see the warning,\u201d he adds. \u201cYou know where the problem is. That\u2019s your starting point for fixing it.\u201d<\/p>\n

Clarity in Context: Real-World Use Cases<\/h2>\n

In discussing specific examples of AI helping organizations to combat failure demand, Adnett points to Enghouse\u2019s housing customers.<\/p>\n

Whereas previously, repeated calls about repairs used to blend into the noise; now, they\u2019re being correctly flagged, not just as service requests, but often as signs of deeper complaints or systemic issues.<\/p>\n

Adnett expounded on this, noting:<\/p>\n

\u201cSometimes what looks like a simple query is actually a complaint in disguise. AI helps bring that clarity.\u201d<\/p><\/blockquote>\n

Once organizations have that insight, they can address the problems by improving processes, holding third-party suppliers accountable, or fixing persistent issues in their service delivery model.<\/p>\n

The Real ROI: Less Firefighting, More Resolution<\/h2>\n

Like any AI implementation, how it impacts a business\u2019s bottom line will always be important.<\/p>\n

Cutting failure demand reduces contact volume, frees up agent capacity, improves first-contact resolution, and cuts the cost to serve.<\/p>\n

Fixing failure demand also helps boost NPS because fewer customers are stuck in loops, and more get the resolution they wanted the first time around.<\/p>\n

What\u2019s Next: From Insight to Action<\/h2>\n

So, what\u2019s next for failure demand?<\/p>\n

Adnett sees a future where AI isn\u2019t just diagnosing failure demand, but helping triage and, in some cases, resolve it.<\/p>\n

With the right integrations, technologies like agentic AI and RPA could handle certain issues automatically.<\/p>\n

\u201cI think there\u2019s potential,\u201d he says.<\/p>\n

\u201cBut you don\u2019t want AI with free rein over resolutions. That\u2019s where human oversight remains essential.\u201d<\/p><\/blockquote>\n

He\u2019s also cautious about generalist AI models, arguing that companies need to deploy specialist tools that are trained on the right domains, or else they risk missing \u201cthe nuance that makes failure demand so tricky to catch.\u201d<\/p>\n

You can learn more about failure demand and Enghouse Interactive’s full suite of services and solutions by <\/em>visiting the website today<\/em><\/a>.<\/em><\/p>\n

You can also gain more insights into Enghouse Interactive’s AI approach by reading this CX Today article<\/a> and watching this <\/em>exclusive interview with Simon Adnett<\/em><\/a>.<\/em><\/p>\n

 <\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

Failure demand isn\u2019t a new concept, but it is one that CX teams often overlook. It\u2019s the kind of interaction that clogs up your lines, eats into agent time, and chips away at customer satisfaction. It isn\u2019t because someone is asking for help; it\u2019s because something has already gone wrong. And more often than not, […]<\/p>\n","protected":false},"author":4983,"featured_media":72773,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[11850],"class_list":["post-72772","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-contact-center","tag-agentic-ai","tag-agentic-ai-in-customer-service","tag-ai-agents","tag-artificial-intelligence","tag-autonomous-agents","brands_to_track-enghouse","editorial_type-interview","intent-evaluation","target_audience-dual"],"acf":[],"yoast_head":"\nFailure Demand in CX: The Hidden Cost AI Can Solve - CX Today<\/title>\n<meta name=\"description\" content=\"CX Today covers Contact Center & Omnichannel\u200b news including Agentic AI, Agentic AI in Customer Service\u200b, AI Agents, Artificial Intelligence, Autonomous Agents and more.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.cxtoday.com\/contact-center\/failure-demand-in-cx-the-hidden-cost-ai-can-solve-enghouse\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Failure Demand in CX: The Hidden Cost AI Can Solve\" \/>\n<meta property=\"og:description\" content=\"CX Today covers Contact Center & Omnichannel\u200b news including Agentic AI, Agentic AI in Customer Service\u200b, AI Agents, Artificial Intelligence, Autonomous Agents and more.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.cxtoday.com\/contact-center\/failure-demand-in-cx-the-hidden-cost-ai-can-solve-enghouse\/\" \/>\n<meta property=\"og:site_name\" content=\"CX Today\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/CXTodayNews\/\" \/>\n<meta property=\"article:published_time\" content=\"2025-08-06T08:44:08+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-11-25T08:33:03+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.cxtoday.com\/wp-content\/uploads\/2025\/08\/Failure-Demand-in-CX-The-Hidden-Cost-AI-Can-Solve.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"850\" \/>\n\t<meta property=\"og:image:height\" content=\"425\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Rhys Fisher\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@cxtodaynews\" \/>\n<meta name=\"twitter:site\" content=\"@cxtodaynews\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Rhys Fisher\" \/>\n\t<meta name=\"twitter:label2\" content=\"Estimated reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.cxtoday.com\/contact-center\/failure-demand-in-cx-the-hidden-cost-ai-can-solve-enghouse\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.cxtoday.com\/contact-center\/failure-demand-in-cx-the-hidden-cost-ai-can-solve-enghouse\/\"},\"author\":{\"name\":\"Rhys Fisher\",\"@id\":\"https:\/\/www.cxtoday.com\/#\/schema\/person\/8658137cddc02e8aa6da2b92ccf4a044\"},\"headline\":\"Failure Demand in CX: The Hidden Cost AI Can Solve\",\"datePublished\":\"2025-08-06T08:44:08+00:00\",\"dateModified\":\"2025-11-25T08:33:03+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.cxtoday.com\/contact-center\/failure-demand-in-cx-the-hidden-cost-ai-can-solve-enghouse\/\"},\"wordCount\":1101,\"publisher\":{\"@id\":\"https:\/\/www.cxtoday.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.cxtoday.com\/contact-center\/failure-demand-in-cx-the-hidden-cost-ai-can-solve-enghouse\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.cxtoday.com\/wp-content\/uploads\/2025\/08\/Failure-Demand-in-CX-The-Hidden-Cost-AI-Can-Solve.jpg\",\"keywords\":[\"Agentic AI\",\"Agentic AI in Customer Service\u200b\",\"AI Agents\",\"Artificial Intelligence\",\"Autonomous Agents\"],\"articleSection\":[\"Contact Center & Omnichannel\u200b\"],\"inLanguage\":\"en-GB\",\"copyrightYear\":\"2025\",\"copyrightHolder\":{\"@id\":\"https:\/\/www.cxtoday.com\/#organization\"}},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.cxtoday.com\/contact-center\/failure-demand-in-cx-the-hidden-cost-ai-can-solve-enghouse\/\",\"url\":\"https:\/\/www.cxtoday.com\/contact-center\/failure-demand-in-cx-the-hidden-cost-ai-can-solve-enghouse\/\",\"name\":\"Failure Demand in CX: The Hidden Cost AI Can Solve - 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