Why run a team health check
What a health check measures, how ratings stay private, and why this is a pulse, not surveillance
A team health check is a short, repeated, structured survey that asks a team to rate a handful of named dimensions of how work feels — so drift shows up as a number before it shows up as a resignation.
Why
Teams rarely say "I'm burning out" in a 1:1 — they say it through slipping delivery, quieter standups and rising absence, which are easy to miss until they're a crisis. A recurring, aggregated pulse turns that into a trend you can watch instead of a feeling you can't act on. The format descends from the "squad health check" popularized by agile teams in the mid-2010s: a handful of themed questions, rated on a simple scale, repeated on a cadence. The point isn't to rank people — it's to catch a team-level pattern early enough to do something about it.
What SquadBear measures
Four built-in models cover different needs: Team Health 11 (traffic-light, 11 dimensions like Delivering value, Fun, Learning, Teamwork), Pulse 5 (happiness scale, 5 dimensions — Workload, Energy, Clarity, Support, Satisfaction — for a quick, frequent cadence), Engineering Health 8 (Likert scale, engineering-specific dimensions like code quality and on-call load), and eNPS (the classic 0–10 "would you recommend working here," scored −100 to 100 as promoters minus detractors). Admins can also build custom models at Team Health → Health settings.
How ratings work
Each run picks an anonymity mode — Named, Alias (pseudonym) or Anonymous. Whichever mode is chosen, nobody — including admins — ever sees another person's individual rating; every viewer only ever sees their own answers plus the aggregated result. Free-text comments carry your real name in Named mode, a per-run pseudonym in Alias mode, and nothing in Anonymous mode. Closing a run in Alias or Anonymous mode permanently destroys the link between people and their answers in the database — not hidden, destroyed, and it can't be recovered afterwards.
Trends and alerts
Every closed run's results feed a trend chart per dimension. If a dimension's average falls sharply against the previous run, an alert notifies facilitators — so a drop doesn't sit unnoticed until the next check-in. eNPS trends show the actual NPS score, never the raw 0–10 average. From a result, a facilitator can create an improvement action with an owner and a due date.
Worked example
Northlake runs a Pulse 5 check for its Platform team every few weeks, anonymous. One run shows Workload dropping sharply against the last — SquadBear flags the fall, and Marta opens an action: "Rebalance Platform's on-call rotation before the next sprint," due in a week.