Which tickets will breach, and which just feel urgent?

The question this file answersWho on my support team knows, right now, which ticket breaches its SLA in the next hour?

Fits: SaaS and IT teams handling 50–500+ tickets a day.

Typical day

What the desk looks like today

Typical, from the software playbook (support): 50–500+ tickets a day, a share of them repeat issues with a known answer; the playbook gives no split by SLA. Every ticket is treated as a fire, including those well inside the clock; the one about to breach surfaces when the customer escalates.

What changes

What Monday looks like after

At the start of a shift, the support lead sees a short list ordered by time-to-breach with the customer's history beside each ticket, while the FAQ answers went out already. The credit conversation, when there is one, is still the lead's.

Typical, not a measured client result. Every figure here comes from the playbook source named below.

Closed

known issues closed from the knowledge base, breaches to an owner — our IT-ticket build with a clock; no published figure for SLA desks

Before: every ticket is treated as a fire, including the ones well inside the clock. After: known issues close from the knowledge base and the list is ordered by time-to-breach. The percentage stays on the IT-ticket file.

No published figure for this desk. The range lives on the parent file: Known issues from the knowledge base; outages to engineers →

How this file is built

SLA-breach triage has no benchmark of its own. Freshworks/Zendesk (2023) report 40–60% faster L1 resolution — a routine-ticket figure that lives on the parent file and is not transferred here. Not an SLA-credit promise.

What we install

What we put in front of the systems you already run

Your help desk and monitoring stay — Zendesk, Freshdesk, Intercom, PagerDuty or the ones you run. This is our IT-ticket triage build with the SLA clock added:

each ticket is classified and its deadline read from the plan and priority in the help desk
known issues inside the clock are answered with the knowledge-base article and closed pending the customer's reply
tickets near or past breach, VIP accounts and anything touching a live incident go to a named owner with the history and the remaining time shown.

What stays human — and what this will not do

The customer. The credit. Novel bugs. Anything that is not a FAQ.

Not an SLA-credit promise.

What can go wrong — and what we do about it

A stale knowledge base closes tickets with wrong answers; the pilot starts with the articles an engineer has checked, and everything else stays in the queue. If SLA terms live in contracts rather than in the help desk, the clock cannot be read — loading them is audit work. Freshworks/Zendesk's 40–60% faster L1 resolution lives on the parent file and is about routine tickets; nothing here promises fewer credits.

What it costs to get there

The path: free 60-second estimate → free 20-minute review → paid audit of this one process (€1.5–3K, typically two weeks) → pilot with your people in the loop (€10–20K, weeks, not quarters). No transformation programme. Prices are public, on the services page →

Scoped in the audit — the playbook has no estimate for this exact desk.

This is about you if…

Are SLA deadlines held per plan in your help desk, so breach is computed, not felt?
Is a meaningful share of your tickets known issues with a knowledge-base answer?

What does this mean in euros?

That depends on your volumes and wage costs — this page will not invent the number. The free 60-second estimate runs that calculation from your answers, with every multiplier sourced.

Get your free savings estimate 60 seconds · no sales call Or write first → Map an ops process like this one — free, 60 seconds →

Not a named Aperanda client. Process file · Ops.

Short process file. Same build as its parent file; the playbook has no separate volume or benchmark for this desk.

All process files