What's the actual cost of severity inflation across a 6-month backlog?
Been thinking about this a lot lately and I don't see it discussed enough.
Everyone talks about severity inflation as an annoyance engineers file everything Critical, the priority column becomes noise, PMs re-rank manually before every sprint. Frustrating, sure. But the actual cost runs deeper than lost time in sprint planning.
Here's what I think is actually happening over 6 months of inflated priorities:
You're shipping the wrong things. When everything is Critical, nothing is. The bugs that actually hurt paying customers the ones that silently corrupt data, that block key workflows, that churn enterprise accounts get lost in a sea of P1s filed by engineers who just wanted their ticket looked at.
Your backlog stops being a planning tool. After a few sprints of political triage, the backlog reflects who complained loudest, not what matters. At that point it's not a backlog it's a graveyard with bad metadata.
Stakeholder trust erodes. Sales stops believing the PM's priority calls because they've seen them get overridden. Engineering stops caring about severity labels because they know they're meaningless. Everyone stops using the system as intended and starts working around it.
The compounding effect: each sprint of bad triage makes the next one harder. You inherit the previous sprint's inflated backlog on top of new tickets. The signal-to-noise ratio gets worse over time, not better.
Curious if anyone has tried to actually quantify this, either the time cost or the downstream impact on retention or churn. Or is this just something teams accept as background noise?