HR & RECRUITING

Internal Peer Parity Check on New Offers

For each pending offer, this pulls the salaries of current employees in the same role and level, computes how the new offer compares to that internal cohort.

CategoryHR & Recruiting
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerOffer marked 'ready for review' in AirtableAirtableAirtable
  • ActionQuery HRIS Postgres for active peers in same role + levelPostgreSQLPostgres
  • LogicCompute percentile, detect compression or inversion
  • ActionTag 'parity OK' offers back in AirtableAirtableAirtable
  • OutputSend parity-risk brief to comp partner in SlackSlack

What it does

Goes beyond the published band to test fairness against real internal peers. It gathers current pay for everyone already in the same role and level, then checks whether the new offer would create salary compression (new hire near or above tenured peers) or inversion (new hire above the team).

When to use it

Use this when band compliance alone isn't enough and you care about internal parity — especially in markets where new-hire comp has outrun existing staff and you want to catch morale-risking gaps before they happen.

How it works

  1. 1An offer row marked 'ready for review' in Airtable starts the run.
  2. 2The flow queries the Postgres HRIS for active employees matching the same role and level, returning their base salaries.
  3. 3A logic step computes the offer's percentile against the peer cohort and detects compression or inversion thresholds.
  4. 4Clean offers are tagged 'parity OK'.
  5. 5Risky offers generate a parity brief — the cohort distribution, the new offer's position, and the affected peers — delivered to the comp partner in Slack for a decision.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AirtableBases, tables, views, automations.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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