PROJECT MANAGEMENT
Quarterly Over-Commitment Trend Report to Notion
At quarter close, reads every sprint's commitment-versus-delivered history from BigQuery, charts which teams chronically over-commit.
How it runs
The automated pipeline, trigger to output.
- TriggerEnd-of-quarter schedule
- ActionQuery commitment vs. delivered across sprints from BigQueryBigQuery
- LogicCompute per-team over-commitment rate and trend
- ActionRender trend chart imageImage generation
- ActionArchive data snapshot to S3AWS S3
- OutputPublish leadership review to NotionNotion
What it does
This workflow produces a quarterly retrospective on planning accuracy. It reads each sprint's committed-versus-delivered record from BigQuery, computes per-team over-commitment rate and trend, generates a summary chart, and publishes a leadership-ready review to Notion while archiving the underlying snapshot to S3.
When to use it
Use it for quarterly business reviews when leadership wants to see which teams are consistently planning beyond their velocity, not just one bad sprint. It turns sprint noise into a clear accountability trend.
How it works
- 1An end-of-quarter schedule triggers the run.
- 2The workflow queries BigQuery for commitment and delivered points across all sprints in the quarter.
- 3A logic step computes per-team over-commitment rate, variance, and quarter-over-quarter trend.
- 4It renders a trend chart image for the report.
- 5The review is published to a Notion leadership page, and the raw data snapshot is archived to S3.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect Image generationManaged Nano Banana image renders, metered per image.
- 3Connect NotionPages, databases, comments.
- 4Connect AWS S3Buckets, objects, signed URLs.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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