PROJECT MANAGEMENT

Mirror Asana overcommit to Monday and suggest rebalance moves

When an Asana assignee crosses their capacity ceiling, finds under-loaded teammates with matching skills and proposes reassignment moves.

CategoryProject Management
Enginesim
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerAsana assignee crosses capacity ceilingAsanaAsana
  • ActionGather team headroom and skill tagsAsanaAsana
  • LogicRank candidates by headroom and skill match
  • ActionUpdate Monday resourcing board rowmonday.com
  • OutputComment suggested move and notify managerSlack

What it does

When someone tips over capacity in the Asana sprint, this workflow doesn't just flag it. It scans the rest of the team for people with headroom and overlapping skills, drafts concrete reassignment suggestions, and updates a Monday resourcing board so resource managers see the live overcommit picture next to who can absorb the work.

When to use it

Use it when the bottleneck isn't spotting overload but deciding who should take the work instead. It pairs the overcommit signal with actionable rebalance options and keeps a cross-tool resourcing view in sync.

How it works

  1. 1An Asana webhook fires when an assignee's committed hours cross their capacity ceiling.
  2. 2The workflow gathers all sprint assignees, their remaining headroom, and their skill tags.
  3. 3Logic ranks candidate recipients by available headroom and skill match against the overflowing task.
  4. 4It updates the matching person's row on the Monday resourcing board to reflect the overcommit state.
  5. 5It writes the top reassignment suggestions as an Asana comment on the offending task.
  6. 6It notifies the resource manager in Slack with the recommended move.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AsanaTasks, projects, milestones — everywhere.
  2. 2
    Connect monday.comVisual work management for teams.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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