TICKET MANAGEMENT
Rebalance ClickUp support tasks when forecasted load exceeds agent capacity
Hourly, compares forecasted incoming ticket volume against the current ClickUp assignee workload and reassigns or surfaces overflow tasks before due dates start slipping.
How it runs
The automated pipeline, trigger to output.
- TriggerEvery hour
- ActionFetch open support tasks with assignees + due datesClickUp
- LogicForecast per-assignee completion vs capacity
- LogicDetect overloaded assignees projected to slip
- ActionReassign overflow tasks to free agentsClickUp
- OutputNotify affected agents + lead in SlackSlack
What it does
This workflow looks at where your ClickUp support tasks are forecast to pile up and rebalances them before deadlines slip. It estimates near-term inflow from the recent arrival rate, sums each assignee's open workload and remaining capacity, and detects when a given agent's queue is projected to blow past their due dates.
When to use it
Use this when ticket work lives in ClickUp and breaches happen because of uneven load, not slow agents. It catches the overloaded-assignee problem early enough to redistribute.
How it works
- 1A schedule fires hourly.
- 2Pulls all open support tasks from the ClickUp list with assignees, due dates, and effort estimates.
- 3Forecasts each assignee's projected completion time from their open load plus expected new arrivals.
- 4A branch identifies assignees whose forecast pushes any task past its due date.
- 5Reassigns overflow tasks from overloaded agents to those with spare capacity in ClickUp.
- 6Sends each affected agent and the team lead a Slack summary of what moved and why.
Set it up
What you configure once, before turning it on.
- 1Connect ClickUpDocs + tasks + chats in one workspace.
- 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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