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Unrelenting IT Issues Cost Millions of Hours in Lost Productivity

Poor DEX directly costs global businesses an average of 470,000 hours per year, equivalent to around 226 full-time employees, according to a new report from Nexthink, Cracking the DEX Equation: The Annual Workplace Productivity Report. This indicates that digital friction is a vital and underreported element of the global productivity crisis.

The report finds that the average employee suffers 14 negative digital experiences a week. These include device crashes, application glitches, or slow load times, and can reduce productivity and collaboration while also increasing employee frustration and stress. Crucially, the research also indicates a strong inverse correlation between an organization's DEX score and productivity loss. For every 10-point increase to the overall DEX score, employees would recoup an average of 22 productive minutes each week.

"Quantifying the immense cumulative impact of bad DEX is truly eye-opening," commented Pedro Bados, CEO and Co-Founder of Nexthink. "Employees who constantly have frustrating digital experiences suffer eight times the productivity loss compared to those who have consistently good experiences. All told, enterprises are losing millions of hours every year because of malfunctioning technology. This is unacceptable, yet it's regarded by many as just another cost of doing business."

The research also suggests that these consistent disruptions are not just a threat to enterprise productivity, but also to the quality of work employees produce. The average negative event lasts a little under 3 minutes (167 seconds), yet research from the American Psychological Association suggests that even delays of less than 5 seconds are enough to triple people's error rate. Moreover, research from the University of California has shown that if when employees are taken out of their flow state it takes around 23 minutes for them to return, further increasing the amount of lost time.

Averaging lost time by industry shows significant variation with retailers, healthcare providers, and financial service companies suffering 1.7x the time loss of the tech industry. The number of disruptive events per week was almost identical, regardless of industry however, suggesting that the variance in time loss is down to the severity of events rather than the volume.

"Even small digital disruptions can cascade into hours of lost productivity," added Bados. "But often these incidents are much bigger with employees losing whole days as a result. This isn't just about overall enterprise productivity, it's also about digital friction pushing people to boiling point because they feel stuck and abandoned — a feeling that is being turbo-charged in the AI era. If IT departments don't address these fundamental issues, the business will lose talented people to competitors, become less collaborative, and fall behind in the innovation race, all of which will inevitably have serious implications for their bottom line."

Methodology: Nexthink's analysis is based on proprietary data from more than 20m endpoints across 474 global businesses. The figures in this report are derived from aggregated, anonymized telemetry from organizations largely in the early stages of DEX management.

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Unrelenting IT Issues Cost Millions of Hours in Lost Productivity

Poor DEX directly costs global businesses an average of 470,000 hours per year, equivalent to around 226 full-time employees, according to a new report from Nexthink, Cracking the DEX Equation: The Annual Workplace Productivity Report. This indicates that digital friction is a vital and underreported element of the global productivity crisis.

The report finds that the average employee suffers 14 negative digital experiences a week. These include device crashes, application glitches, or slow load times, and can reduce productivity and collaboration while also increasing employee frustration and stress. Crucially, the research also indicates a strong inverse correlation between an organization's DEX score and productivity loss. For every 10-point increase to the overall DEX score, employees would recoup an average of 22 productive minutes each week.

"Quantifying the immense cumulative impact of bad DEX is truly eye-opening," commented Pedro Bados, CEO and Co-Founder of Nexthink. "Employees who constantly have frustrating digital experiences suffer eight times the productivity loss compared to those who have consistently good experiences. All told, enterprises are losing millions of hours every year because of malfunctioning technology. This is unacceptable, yet it's regarded by many as just another cost of doing business."

The research also suggests that these consistent disruptions are not just a threat to enterprise productivity, but also to the quality of work employees produce. The average negative event lasts a little under 3 minutes (167 seconds), yet research from the American Psychological Association suggests that even delays of less than 5 seconds are enough to triple people's error rate. Moreover, research from the University of California has shown that if when employees are taken out of their flow state it takes around 23 minutes for them to return, further increasing the amount of lost time.

Averaging lost time by industry shows significant variation with retailers, healthcare providers, and financial service companies suffering 1.7x the time loss of the tech industry. The number of disruptive events per week was almost identical, regardless of industry however, suggesting that the variance in time loss is down to the severity of events rather than the volume.

"Even small digital disruptions can cascade into hours of lost productivity," added Bados. "But often these incidents are much bigger with employees losing whole days as a result. This isn't just about overall enterprise productivity, it's also about digital friction pushing people to boiling point because they feel stuck and abandoned — a feeling that is being turbo-charged in the AI era. If IT departments don't address these fundamental issues, the business will lose talented people to competitors, become less collaborative, and fall behind in the innovation race, all of which will inevitably have serious implications for their bottom line."

Methodology: Nexthink's analysis is based on proprietary data from more than 20m endpoints across 474 global businesses. The figures in this report are derived from aggregated, anonymized telemetry from organizations largely in the early stages of DEX management.

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In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.