- Despite employees encountering tech problems, including slow applications, intermittent performance degradation and device conflicts, they typically adapt their behaviour.
- As traditional service models struggle to surface these problems, the gap between what tech monitoring captures and what employees truly experience continues to widen.
- When issues do reach the service desk, they are often diagnosed several times as they move between support teams, largely because the original context is missing. This is when engineers spend time piecing together what happened from fragments of information, which slows resolution and discourages users from escalating similar problems in future.
- The same gap helps explain why many automation and intelligence initiatives struggle to deliver the productivity gains hoped for by leadership teams.
- For IT teams responsible for digital employee experience (DEX), the challenge is increasingly about understanding how work actually runs in everyday conditions rather than relying solely on system status indicators.
- For DEX and IT operations teams, the priority is simply knowing where work slows down and what employees experience when it does. With clearer operational context, teams can address recurring issues earlier and make decisions based on how technology performs in practice, not just how systems report their own health.
Most organisations believe they have a reasonable understanding of how well their tech environments are performing. Systems are monitored and uptime reviewed, while incident volumes and service levels continue to dominate reporting. On paper, everything looks under control. However, that confidence often proves misplaced.
Across enterprises, a large proportion of daily IT friction never reaches dashboards or support queues. Despite employees encountering IT problems, including slow applications, intermittent performance degradation and device conflicts, they typically adapt their behaviour. Work often continues, just more slowly, and the impact is absorbed into everyday operations rather than recognised as an incident.
A useful indicator of the scale of this problem comes from the 2025 Work Relationship Index. Only around 20 per cent of employees report a healthy relationship with work, a sharp decline from the previous year, with recurring technology frustrations frequently cited as a contributing factor. In large organisations, that disengagement represents substantial lost output, even when no individual system appears to be failing.
Why many execution failures never surface
Enterprise IT has traditionally relied on two primary signals to understand system health: automated monitoring and user-reported incidents. That’s although neither was designed to reflect how work is actually executed across today’s distributed environments.
Monitoring tools detect outages and clear threshold breaches reliably. However, partial degradation and context-specific issues often pass unnoticed. Many environments report strong availability metrics even when applications remain slow or inconsistent for users.
A major constraint is limited quality data. Most organisations lack continuous, contextual, and trustworthy execution data that reflects how work is actually performed across devices, applications, and environments. Without that foundation, leadership decisions are based on inferred system health rather than observed work conditions.
Incident data fills part of that gap, but it depends heavily on human behaviour. Service desks often see this first: systems show as available, yet users report delays that never register as incidents. Intermittent or tolerable problems are more likely to be worked around, because reporting them interrupts work and often leads to prolonged troubleshooting.
Many users simply adapt and this behaviour reflects a broader organisational pattern in which visible tickets represent only a fraction of the execution issues affecting productivity. As traditional service models struggle to surface these problems, the gap between what technology monitoring captures and what employees truly experience continues to widen.
Silent sufferers and rational workarounds
These blind spots give rise to what practitioners often refer to informally as ‘silent sufferers’: employees who are persistently affected by tech issues but rarely appear in support metrics.
This behaviour is rarely about engagement or training. It reflects how people behave under pressure. Employees are measured on output, not on how they report technology issues. When adapting to friction is quicker than escalating it, silence becomes the rational choice.
When issues do reach the service desk, they are often diagnosed several times as they move between support teams, largely because the original context is missing. This is when engineers spend time piecing together what happened from fragments of information, which slows resolution and discourages users from escalating similar problems in future.
The invisible productivity gap
Over time, this creates an invisible productivity gap, which is the difference between perceived system health and real execution conditions. This widening disconnect is increasingly understood as a digital employee experience (DEX) issue that focuses on whether tech genuinely supports day-to-day work. Leadership dashboards often suggest stability, while employees experience work as slower and more fragmented. Tasks take longer and concentration is repeatedly broken, while small frustrations gradually accumulate into measurable inefficiency.
This gap is not theoretical as a 2025 Deloitte study on workforce capacity found that employees spend roughly 41 per cent of their work time on activities that add little direct organisational value. In practice, much of this time disappears into everyday workarounds: switching between tools, retrying failed actions, waiting for applications to respond or finding alternative ways to complete tasks instead of raising a ticket. Work still gets done, which means the underlying problems often never appear as incidents, even though their cumulative impact on productivity is significant.
The same gap helps explain why many automation and intelligence initiatives struggle to deliver the productivity gains hoped for by leadership teams. IDC’s FutureScape 2026 forecasts indicate that close to half of AI-driven digital initiatives are likely to miss their expected ROI. A common factor is the absence of reliable execution data, which makes it difficult for organisations to understand how work actually unfolds across systems and devices. When that visibility is missing, automation and AI programmes tend to reproduce existing operational blind spots rather than resolve them.
Why execution-level visibility matters now
IT leaders are under growing pressure to show that tech investment improves productivity, but uptime figures rarely explain why employees still struggle to complete everyday tasks. Service desks often see systems reported as healthy while users continue to experience delays, slow responses or inconsistent performance.
This is where digital employee experience (DEX) becomes critical. Improving experience requires visibility into how work actually performs across devices, applications and environments over time, particularly when problems emerge gradually rather than as clear incidents.
For IT teams responsible for digital employee experience (DEX), the challenge is increasingly about understanding how work actually runs in everyday conditions rather than relying solely on system status indicators. A device or application may appear healthy from a monitoring perspective while employees still encounter delays, inconsistent behaviour or repeated interruptions during routine tasks. Greater visibility into execution conditions gives DEX teams the context needed to identify where effort is being lost and why problems persist even when traditional metrics suggest everything is operating normally.
Turning visibility into outcomes
Productivity cannot be managed effectively if it cannot be seen. Organisations that rely only on alerts and reported incidents tend to underestimate how much everyday tech friction affects work.
For DEX and IT operations teams, the priority is simply knowing where work slows down and what employees experience when it does. With clearer operational context, teams can address recurring issues earlier and make decisions based on how technology performs in practice, not just how systems report their own health.
Undetected technology friction carries organisational consequences beyond IT operations. In an environment where tech spending is under closer scrutiny, improving execution visibility has become a practical requirement for turning digital investment into measurable productivity gains.
Oli Giordimaina is chief product and AI officer at Lakeside Software
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