LESS TICKET NOISE. MORE ENGINEERING TIME.
This is a hypothetical example of my approach. It is not a delivered client project, a Commercial Networks result or a promised outcome.
A fictional example of how better alert rules and escalation could change a service desk’s workload.
(600 − 180) × 5 assumed minutes ÷ 60 = 35 hours per month. All figures are fictional.
Simplified workflow illustration · no live systems connected
THE PROBLEM.
Imagine 600 repetitive RMM-generated tickets each month. Some are duplicates, transient conditions or alerts without a clear action. Assume five minutes of engineer handling per ticket.
HOW I WOULD APPROACH IT.
This is a worked example of my proposed method, not a delivered project or a measured Commercial Networks result. I would establish a baseline and agree which alerts require an engineer before changing rules.
THE PROPOSED WORKFLOW.
Find the repeat offenders
Group tickets by monitor, device, customer and condition. Read resolution notes and distinguish noise from genuine incidents.
Improve escalation
Add persistence thresholds, recovery checks and duplicate-ticket tracking. Preserve critical alerts and assign owners to exceptions.
Compare equivalent periods
Measure actionable tickets, repeat incidents and missed issues alongside volume and handling effort.
MAKE IT TRUSTWORTHY.
Shadow existing rules, review proposed suppressions with the service desk and pilot selected monitors. Revert changes if important incidents stop reaching engineers.
Controls that matter
- Preserve critical alerts
- Review missed incidents
- Pilot changed monitors
- Track duplicate state
- Compare equivalent periods
WHY IT MATTERS.
In this fictional scenario, noise tickets fall from 600 to 180 per month. At an assumed five minutes each, that is 35 hours less handling per month. It is illustrative capacity, not a measured saving or a staffing reduction.
LESS NOISE ONLY HELPS IF THE SIGNAL GETS BETTER.
Improving patch compliance
GOT SOMETHING
WORTH AUTOMATING?
Tell me where your RMM is creating work.
Let’s look at what could run better —
and how to get there.