HR & RECRUITING
Weekly Exit-Interview Theme Digest to Leadership
On a weekly schedule, aggregates the past seven days of classified exit-interview themes from BigQuery, drafts a plain-English summary of the dominant attrition drivers.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule fires
- ActionQuery trailing 7-day exit driversBigQuery
- LogicBranch on whether any exits occurred
- ActionSummarize dominant drivers and trend shiftOpenAI
- OutputPost digest to leadership Slack channelSlack
What it does
This workflow produces a recurring leadership-ready readout of why employees left in the last week. It reads already-classified exit data, computes the top drivers and notable shifts, and delivers a concise narrative to Slack so executives stay current without opening a dashboard.
When to use it
Use it once exit interviews are being captured and classified, and leadership wants a steady weekly pulse on attrition causes rather than ad-hoc queries.
How it works
- 1A weekly schedule trigger fires every Monday morning.
- 2The workflow queries BigQuery for all exit-interview driver records from the trailing seven days.
- 3A branch checks whether any exits occurred; if none, it posts a short "no exits this week" note and stops.
- 4When exits exist, an OpenAI model summarizes the dominant drivers, highlights the largest week-over-week change, and surfaces one representative anonymized quote.
- 5The digest is posted to the designated leadership Slack channel as a formatted message.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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