use cases · R&D / Engineering leadership
The platform team is bleeding, and everyone's blaming pay
Your platform team is leaving faster than anyone — and you're sure it's pay. The data says otherwise.
For who
What it finds
What you get
Binding constraint
The situation
A ~200-person scaleup is losing platform/infra engineers faster than any other team. Exit interviews are vague ('better opportunity'). Leadership's working hypothesis is compensation — people are leaving for higher offers — and they're about to spend on retention bonuses and a comp-band reset.
How the walkthrough goes
- 01customer-situation
Your platform team is leaving faster than anyone — and you're sure it's pay.
200-person scaleup. Infra/platform attrition climbing. Exit interviews vague. A retention-bonus pool and a comp-band reset are already on the finance agenda.
- 02problem-cost
You're about to spend big on a hunch.
A comp reset is expensive and hard to walk back. If pay isn't the cause, the budget's gone and the team still leaves.
- 03insight
Most teams blame comp. The data says the binding constraint is Support.
Platform engineers have no line of sight to who uses what they ship — the recognition/relatedness gap that sustains the work. Pay isn't what separates the leavers from the stayers.
- 04desired-outcome
Keep the team — without the wasted spend.
Aim the budget at the condition that's actually binding (visibility/recognition), not the comp band.
- 05product-path
Performix finds the constraint; AnyComp rules out pay.
Protected feedback + CAMS names the single binding condition; the comp engine confirms your leavers are already at or above market.
- 06proof
Conditions predict who leaves. Pay doesn't.
In the data, the Support/visibility items separate leavers from stayers; comp percentile doesn't.
- 07risk-reversal
Honest by construction.
Protected feedback (anonymity as a primitive) + a hard minimum-group-size gate. No individual is exposed.
- 08next-step
Run the diagnostic on the team that's actually leaving.
One read, before the comp reset. If it is pay, you'll know; if it isn't, you just saved the budget.
Grounded in the research
- — PFX-114 R&D/engineering dossier §2 (CAMS in engineering)
- — Grant (2007) — prosocial impact / 'who uses what I ship' visibility, chronically absent on platform teams
- — Deci & Ryan (SDT) — relatedness need; autonomous vs controlled motivation
- — Gilbert — environment-first: diagnose the conditions before blaming the person
Walkthrough data is composite and clearly labeled — shaped from the research to show the real shape of the finding, not a named client.
Reduce regretted platform-team attrition by fixing the binding condition (visibility/recognition) instead of comp — the decision-error avoided is a mis-targeted retention spend. Delta: share of attrition variance explained by conditions vs. by pay.