Closed Tickets Fill SOC Dashboards While Root Causes Go Undocumented

A SOC dashboard full of closed tickets tells leadership that the team is executing. It does not tell them whether root causes were documented, whether the same exposure will recur next week, or whether the fix in one layer shifted risk into another. Ticket closure tracks a workflow state. Risk reduction requires evidence that the underlying problem was understood, and in most environments, that evidence is missing.

Paddy Patnaik is Managing Director of AI, Analytics, and Digital Transformation at Evalueserve, a global research and analytics firm. With over 20 years of leading technology services and transformation programs across financial services, capital markets, and regulated sectors, Patnaik has managed ITSM implementations, delivery portfolios for major investment banks, and enterprise AI strategy. He frames the ticket closure problem as a failure of foundational ITSM discipline that AI is now positioned to fix, but only under human supervision.

"If a ticket or the volume of tickets is not closed with root cause analysis, then you tend to lose out," Patnaik says. "Even though you could have found an event of risk or an issue that could potentially be a risk, doing a deep-dive analysis is necessary to find out what led that issue to happen."

How tickets get closed without answers

The mechanics are straightforward. An analyst resolves an L1 or L2 alert within the SLA window. While documenting the closure, another critical alert arrives. The analyst parks the documentation and moves to the new issue. A meeting follows. The documentation backlog grows. Eventually, a compliance manager asks why tickets remain open, and the analyst bulk-closes everything without filling in the details.

"Procrastination comes," Patnaik says. "That's typically what leads to this bulk of tickets getting closed with no resolution. A compliance manager says, why have you not closed everything you've resolved? The analyst just goes in and closes everything without giving proper due credit to that issue." The result is what he calls "hurried data" in dashboards that leadership reads as operational health.

The ITSM principle underneath is basic: recurring incidents signal a problem that needs holistic resolution. Without documented root causes, the pattern analysis that identifies systemic issues never happens. "It goes back to foundational ITSM principles," Patnaik says. "Number of incidents recurring becomes a problem, and that problem needs to be solved in a holistic manner."

Ticket closure cannot represent the stack

Modern infrastructure emits signals from every layer. Application, middleware, data, and platform each produce their own monitoring and analytical information. Ticket closure captures what happened in the workflow. It does not capture whether the resolution addressed exposure across those layers or whether a fix in one layer cascaded risk into another.

"A super dashboard has to correlate these different things, then correlate them with ticket closure before a decision is made," Patnaik says. "You have access to a lot of information now. It is to your advantage how you use that additional information to get multiple dimensions and insights." Speed metrics like mean time to detect and mean time to resolve still matter, but they distort the picture when they reward fast closure without requiring evidence that the root cause was identified and recurrence was addressed.

AI helps but compounds errors if unsupervised

Patnaik sees AI agents as the practical bridge. An agent can analyze an issue, generate a root cause summary, and present it for the analyst to confirm and close. That saves the documentation time that currently gets sacrificed to the next alert. "AI can save time by generating or analyzing that issue, creating a root cause analysis, and providing a summary to the user," he says. "Agent-assisted documentation is going to be a big benefit." The economics have shifted: documentation work that had no business case before AI now has one because the cost of doing it has dropped.

But the risk of unsupervised RCA is compounding. If an agent produces an inaccurate root cause and that analysis enters the data that future agents and analysts rely on, the baseline degrades.

"If inaccurate RCA has been done without human supervision, all of this will go into greater hallucination towards the later stages because agents are checking that data," Patnaik says. "The basis will go wrong." Humans remain the decision authority because they carry context that the agent does not have: why the system was built, who depends on it, and what the business criticality actually is.

The path forward is not abandoning ticket closure as a metric, but stopping the practice of treating it as the primary indicator of whether risk was reduced. "100% weightage to ticket closure cannot be taken as a basis for judgment," Patnaik says. "You need multiple dimensions. Ticket closure should not be the only one."