Service desk performance has long been measured by how quickly IT responds when something breaks. But faster resolution doesn’t solve a more fundamental problem: Why is IT fixing the same issue again next week?
That question is pushing more organizations toward an evolving shift-left model, where the goal is to identify familiar problems earlier, automate repeatable fixes, and prevent routine incidents from repeatedly consuming the same resources.
The reality is that digital friction rarely stays inside the IT department. Employees lose time due to slow applications, failed connections, and other technology problems. TeamViewer research estimates employees lose an average of 1.3 workdays per month to digital friction. A recurring technical issue may look small in a ticket queue, but when repeated across hundreds or thousands of employees, it becomes a productivity problem.
The ticket is only part of the problem
Reactive IT starts with an alert. Something breaks, an employee opens a ticket, and IT investigates. Once the incident is resolved, the ticket closes. That model makes sense for unusual problems, but recurring tickets can add operational expense. When an issue or ticket is already understood, that "expense" mounts in the form of:
- IT personnel spending time on repetitive work instead of higher-priority workloads.
- Technical debt mounting in favor of a "quick fix," rather than addressing the larger issue causing recurring tickets.
- Lost productivity from the employee waiting for their issue to be resolved.
Proactive IT, on the other hand, takes a known problem with a known response and triggers that response immediately when the issue occurs — crucially, before employees even need to raise a ticket. “Instead of waiting for another employee to report the problem, IT can apply a proven fix as it happens,” says Jason Keogh, Vice President of Solutions at TeamViewer.
That changes the objective. Instead of asking how to close a recurring ticket faster, IT can ask how to stop that ticket from being created in the first place.
Keogh describes one customer who had been receiving roughly 100 tickets a week tied to a recurring VPN problem. After the known fix was automated, the remediation ran approximately 1,000 times per week. The gap revealed something the ticket queue had obscured. Many employees had been dealing with the problem without ever contacting IT.
“The tickets are the tip of the iceberg,” Keogh says. “When you drive proactive automations, you fix the whole iceberg.”
Turn every fix into institutional knowledge
Getting there requires more than adding automation. IT first needs enough visibility to understand what’s happening across endpoints and enough context to recognize patterns.
One IT team member may solve a problem in five steps, while another reaches the same result in a slightly different way. Across a large service desk, those individual fixes can disappear into vague resolution notes.
The opportunity is to capture how technicians identify recurring paths to resolution and turn proven responses into repeatable workflows. That means:
- Documenting how issues are actually resolved, not just whether the ticket was closed.
- Spotting patterns across incidents to see which problems keep returning and which fixes consistently work.
- Standardizing proven fixes into self-service or automated workflows that can be reused at scale.
Over time, each resolved issue becomes institutional knowledge that can be turned into a one-click or automated fix the next time the problem appears.
That’s where digital employee experience (DEX) data becomes especially useful. Rather than treating employee experience as a survey metric alone, IT can combine experience and performance signals to identify where friction occurs and resolve the issues causing the most disruption.
The result is a practical “fix once, fix forever” mindset. Not every problem can be permanently eliminated. But once a recurring issue becomes a known quantity, the organization shouldn’t have to rediscover the same solution every time it appears. Proven fixes can be standardized and automated to reduce repeat tickets and free IT for higher-value work.
Let human workers go where their expertise adds value
The human payoff is considerable. Repetitive troubleshooting consumes capacity that could go toward harder problems and more strategic priorities. It also leaves employees waiting for solutions IT may already know how to deliver.
The evolution from “shift left” to predictive IT can, in turn, move routine work toward self-service or automated remediation while leaving exceptions, judgment calls, and unfamiliar problems with people. That makes automation a way to increase the value of human expertise and enrich the work experience.
Build trust as automation expands
Governance becomes more important as organizations expand that model. Keogh argues that organizations should distinguish between allowing technology to recommend an automation and allowing it to deploy one without review.
“Autonomy requires trust, and you need to see it to trust it,” he said.
That principle keeps the near-term goal grounded: automate where the problem and response are understood, keep people in control, and expand as confidence grows.
Platforms are increasingly designed around that operating model. TeamViewer ONE, for example, connects digital experience and endpoint insight with automation and remote support, helping IT move from identifying friction to acting on it from a more unified environment.
Predictive IT is the North Star. But organizations don’t need to wait for that future to make meaningful progress today. The best starting point is simple. Find the recurring problems, understand why they happen, and ensure IT never has to solve them from scratch again.
