Attrition Early-Warning Monitor for Your Business Unit

What This Builds

A scheduled check that reads engagement scores and standard roster data for your business unit and flags patterns worth a conversation, before someone has already resigned. It replaces the version of retention work that only starts after an exit interview with one that surfaces a signal while there is still time to act on it.

This flags patterns for you to look at. It never decides anything about a person on its own.

Prerequisites

• A recurring, aggregable export of engagement scores and basic roster data (tenure, department) for your business unit
• Sign-off from HR leadership and legal on exactly which fields feed this automation, completed before you turn it on (see the caution below: this is the one step in this guide you cannot skip)
• A Zapier account on a plan that supports multi-step Zaps and a scheduled trigger
• A Claude account for the pattern-review step
• Total ongoing cost if you do not already have these: $29.99/month for Zapier's Professional plan, plus $20/month for Claude

The Concept

Think of this as a smoke detector, not a fire marshal. It does not tell you who to let go of a role or who deserves a raise. It notices a pattern (a dip in scores, a shift in a data point you already track) and tells you it might be worth a conversation. What happens after that is entirely a judgment call you make, the same way you always have.

Build It Step by Step

Part 1: Decide which fields go in, with legal and HR leadership

Before you build anything, sit down with HR leadership and legal and agree on exactly which fields feed this automation. This is not a formality. Using leave usage or absence data as a flight-risk signal can flag employees on protected FMLA or ADA leave, which risks disparate impact and real legal exposure. Engagement scores and tenure are generally safer starting points than attendance data. Write down the approved field list before you move to Part 2.

Part 2: Standardize the data source

Pick one Google Sheet as the fixed destination for your recurring engagement and roster export, using only the fields approved in Part 1. Keep the tab name and column headers stable across cycles, since the automation reads by header name.

Part 3: Build the scheduled trigger

1. In Zapier, click Create Zap
2. For the trigger, search Schedule by Zapier and set it to run monthly
3. Add a step: Google Sheets → Lookup Row(s), pointed at your approved-fields tab

What you should see: A scheduled trigger that pulls the current data automatically, with no manual step required to start each run.

Part 4: Add the pattern-review step

1. Add a step: Claude (Zapier's Claude/Anthropic integration) → Send Prompt
2. Pass in the data from the previous step with instructions like: "Review this aggregated engagement and tenure data by team. Flag any team where scores dropped more than 10 points from the prior period, or where a cluster of employees under 18 months tenure shows declining scores. Do not draw conclusions about any named individual. Describe patterns at the team level only, and phrase every flag as 'worth a conversation,' not a recommendation or a conclusion."
3. Test the step and confirm the output reads as team-level observations, not judgments about specific people

What you should see: A short written flag, naming a team or pattern, phrased as something worth checking rather than a verdict.

Part 5: Restrict where the output goes

Add a final step: Email by Zapier or Gmail → Send Email, addressed only to yourself. Do not add the business-unit leader, the affected manager, or any shared channel as a recipient. This output is a private prompt for your own follow-up, not a report for distribution.

Part 6: Turn it on and set a review habit

Publish the Zap. When a flag arrives, treat it as a starting point: look at the underlying data yourself, decide whether a conversation is warranted, and have that conversation the way you always would. The automation's job ends at "worth a look." Everything after that is still yours.

Real Example: A Team Flagged for Follow-Up

Setup: The monitor runs on the first of each month against an approved data set: engagement scores and tenure, nothing else, for one business unit.

Input: This month's export shows a five-person team's average engagement score dropped from 7.8 to 6.1, and three of the five have under a year of tenure.

Output: Claude's flag reads: "The [team name] shows a notable engagement drop this period, concentrated among newer tenure employees. Worth a conversation with the manager to understand what changed." No names, no recommendation about any individual, no action taken automatically.

Time saved: Turns a pattern that might otherwise surface only after an exit interview into something you notice while there is still time to have the conversation.

What to Do When It Breaks

• No flag email arrives on schedule, even when you would expect one → This is the failure you will not notice unless you check for it. Review Zapier's Task History monthly and turn on Zapier's built-in "notify me on Zap error" setting so a failed run emails you instead of silently going quiet.
• Claude's output starts naming individuals or making judgment calls → Your prompt needs tightening. Reinforce "team-level only, no individual conclusions, phrase as worth a conversation" and re-test before the next scheduled run.
• The flag rate feels too noisy (something flagged every month) → Adjust your threshold in the prompt (the point-drop or tenure-cluster size that triggers a flag) so it surfaces genuine shifts, not routine month-to-month variation.
• A field you did not approve ends up in the export → Stop the Zap, remove the field from the source sheet, and confirm with legal before restarting. Treat this as a real pause, not something to fix quietly and move past.

Variations

• Simpler version: Run this as a manual quarterly review instead of a monthly automation, if your business unit is small enough that patterns are visible without a monthly check
• Extended version: Add a comparison against your unit's historical baseline (prior four quarters) so flags account for normal seasonal dips rather than any single-period drop

What to Do Next

• This week: Have the field-approval conversation with HR leadership and legal, before building anything
• This month: Build the Zap with the approved fields and run one full cycle to calibrate your flag threshold
• Advanced: Pair a flag with a lightweight personal tracker of which conversations you had and what you learned, so you can tell over time whether the signal is actually useful

Advanced guide for HR Business Partner professionals. This is the automation in this guide series to be most careful with. Exclude any leave, absence, or medical-related field entirely, since those can act as proxies for protected FMLA or ADA status. Get explicit sign-off from HR leadership and legal on the approved field list before turning this on, restrict the output to yourself rather than a shared dashboard, and remember this automation flags patterns for your judgment. It never makes or recommends a decision about a specific person's employment, rating, or pay.