In the first two posts of this series, we explored how alert noise emerges from design decisions, and why notification lists fail to create accountability when responsibility is unclear.
There’s a deeper issue underneath both of those problems. Many alerting systems are designed without being clear about the outcome they’re meant to produce.
When teams don’t explicitly decide what they want to happen as a result of a signal, they default to the loudest option available. Over time, that choice creates noise, confusion, and disengagement; even when the underlying intent is reasonable.
A useful question to ask of any alert is simple:
What do we expect someone to do when they receive this?
If the answer is unclear, or if the answer is “nothing, really”, then what you’re designing is not an alert. It’s something else, visibility, reassurance, reporting, or record-keeping; and treating it as an alert will eventually undermine all of those goals.
After many years of working with engineering teams, one pattern shows up again and again. Alerts are often used to solve problems they were never designed to address.
It’s common to see alerts sent to managers, directors, or wider stakeholder groups “to keep them in the loop”.
The motivation is understandable. People want to know when there’s been downtime, when customers might be affected, or when something went wrong overnight. But if the recipient is not expected to act, then an alert is the wrong tool.
Repeated exposure to signals that don’t require action teaches people a very specific lesson; that this can be safely ignored.
At first, they skim. Then they mute. Eventually, they unsubscribe or mentally filter the message entirely. At that point, even genuinely important signals struggle to cut through.
The failure here isn’t one of discipline. It’s a mismatch between the signal and the outcome it’s trying to achieve.
High-performing teams tend to make a clear distinction between different kinds of information, based on what they want to happen next.
Some signals exist to prompt immediate action.
Others exist to provide situational awareness.
Others exist to support reflection and learning over time.
Alerts are appropriate for the first category only.
If no action is expected, then interruption is a cost with no corresponding benefit. In those cases, mechanisms like status pages, dashboards, or periodic reports are usually far more effective. They provide visibility without demanding attention, and they build trust rather than fatigue.
Clarity here doesn’t reduce transparency. It improves it.
When alerts are explicitly designed for action, several things become easier.
Ownership becomes clearer, because someone is expected to respond. Content becomes sharper, because only information relevant to that response is included. And escalation paths become simpler, because the system knows what should happen next if nothing happens.
Crucially, alerts designed this way don’t need to go to many people. They need to go to the right one. That can feel risky at first, especially for teams used to broadcasting widely. Over time, it creates calmer responses, faster decisions, and far less noise.
The system stops asking people to interpret intent, and starts supporting them in acting.
None of this is about using the “right” alerting product or platform. It’s about being disciplined in how signals are designed.
Before adding a new alert, it’s worth pausing to ask:
If those questions can’t be answered clearly, then the signal probably shouldn’t be an alert.
Designing for outcomes doesn’t just reduce noise. It restores trust in the signals that remain.
In the final post of this series, we’ll bring these ideas together and look at alerting as a socio-technical system. This is a system that encodes assumptions about responsibility, confidence, and how people behave under pressure.
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