TICKET MANAGEMENT
SLA Pause Auditor: Restate Monthly Attainment in BigQuery After Removing Gamed Pauses
Once a month, recomputes every agent's SLA attainment in BigQuery by subtracting paused intervals that overlapped a real customer reply.
How it runs
The automated pipeline, trigger to output.
- TriggerMonthly schedule fires at period close
- ActionQuery raw tickets, SLA events, and pauses from BigQueryBigQuery
- LogicJoin pauses to customer comment timestamps to find overlaps
- LogicReclassify overlapping paused minutes as active time
- ActionWrite restated per-agent attainment table to BigQueryBigQuery
- OutputNotify analytics channel that restated numbers are readySlack
What it does
This is a warehouse-side reconciliation. It reads the raw Zendesk SLA and audit data already landed in BigQuery, identifies every 'waiting on customer' pause that overlapped an inbound customer comment, and treats that paused time as if the clock had kept running. It then restates each agent's and team's monthly SLA attainment and writes the corrected figures to a dedicated table so leadership compares reported vs. honest numbers side by side.
When to use it
Use it for monthly business reviews when headline SLA attainment feeds comp or QBR decks and you need a defensible, auditable correction rather than a spot check.
How it works
- 1A monthly schedule triggers the restatement at period close.
- 2Query raw tickets, SLA policy events, and pause intervals from BigQuery.
- 3Join pauses against customer comment timestamps to find overlaps.
- 4Branch: reclassify overlapping paused minutes as active SLA time.
- 5Recompute attainment per agent and team for the closed month.
- 6Write the corrected attainment table back to BigQuery.
- 7Notify the analytics channel that restated numbers are ready.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect SlackChannels, DMs, threads, mentions.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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