Project & Task Management

Vantage integrates with Jira and Asana to pull project and task data into automated reporting workflows. Build dashboards that track progress across multiple projects, identify resource bottlenecks, automate status reports, and alert stakeholders when milestones are at risk.

Build a Cross-Project Portfolio Dashboard

Consolidate project data from Jira and Asana into a single portfolio status dashboard.

Scenario: A PMO director oversees 25 active projects across 6 teams. They need a single dashboard showing portfolio health — on track, at risk, and behind — without manually checking five different project boards.

Workflow Steps:

1. Schedule Trigger — Run every 2 hours during business hours
2. Search Issues (Jira) — Pull all issues across active project boards: project, issue type, status, assignee, sprint, story points, created date, due date, resolved date
3. Search Tasks (Asana) — Pull tasks from Asana projects: project, section, assignee, due date, completion status
4. Union — Merge Jira and Asana data into a unified project dataset
5. Aggregation — Calculate project health metrics:
   • Completion rate: completed items / total items
   • Velocity: story points completed per sprint
   • Overdue items: count with due date < today and status ≠ Done
   • Burndown trajectory: projected completion date based on current velocity
6. Computed Column — Calculate project health score:
   • On Track: completion rate ≥ 80% of schedule consumed, velocity stable, < 5% overdue
   • At Risk: completion rate 60–80%, velocity declining, or 5–15% overdue
   • Behind: completion rate < 60%, velocity declining > 20%, or > 15% overdue
7. Filter — Projects at risk or behind schedule
8. AI Enrichment — Generate status insights: "Project Alpha is at 62% completion with 78% of the timeline consumed. Velocity dropped 30% in the last 2 sprints due to 3 engineers reassigned to Project Beta. At current velocity, projected completion is March 15 (2 weeks late). Recommend either restoring headcount or reducing scope for Sprint 12."
9. Multi-Conditional — Route by health:
   • Behind → Send Email to project sponsor and PMO director + Send Message (Slack #project-alerts)
   • At Risk → Send Message (Slack) to project manager + Dashboard Output
   • On Track → Dashboard Output only
10. Dashboard Output — Populate:
    • Gantt Tile — Project timelines with milestones and current progress
    • Step Tile — Phase completion: Planning → Design → Build → Test → Launch
    • Metric Tile — Total projects, on-track %, at-risk %, behind %
    • Table Tile — Portfolio summary: project name, health, % complete, projected end date
    • Bar Tile — Team capacity utilization (assigned points vs. available capacity)
    • Comparison Tile — This sprint velocity vs. 3-sprint running average
    • Predictive Insights Tile — Schedule risk predictions based on velocity trends

Key Nodes: Schedule Trigger, Search Issues (Jira), Search Tasks (Asana), Union, Aggregation, Computed Column, Filter, AI Enrichment, Multi-Conditional, Send Email, Send Message, Dashboard Output

Relevant Integrations: Jira, Asana, Slack, Teams Chat

Generate Sprint and Status Reports Automatically

Generate and distribute sprint review reports with AI-generated analysis, eliminating manual status writing.

Scenario: Every two weeks, project managers spend 2+ hours compiling sprint reports. This workflow generates them automatically from Jira data and posts them to the appropriate channels.

Workflow Steps:

1. Schedule Trigger — Run biweekly on sprint end day (Friday at 5 PM)
2. Search Issues (Jira) — Pull all issues for the completed sprint: key, summary, type, status, story points, assignee, labels, time logged
3. Aggregation — Calculate sprint metrics:
   • Points committed vs. completed
   • Sprint completion rate
   • Carryover items: committed but not completed
   • Bug-to-feature ratio
   • Time logged vs. estimated
4. Computed Column — Calculate sprint health indicators:
   • Commitment accuracy: completed / committed * 100
   • Scope change: (end_scope - start_scope) / start_scope * 100
   • Team capacity utilization: time_logged / available_hours * 100
5. AI Summary — Generate a narrative sprint report: "Sprint 14 completed 34 of 38 planned story points (89% commitment accuracy). Key accomplishments: Payment API v2 shipped, dashboard redesign 80% complete. Carryover: 4 items related to the reporting module moved to Sprint 15 due to dependency on the data team. Velocity is trending up 8% over the last 3 sprints."
6. Write PDF — Generate a formatted sprint report with:
   • Executive summary (AI-generated)
   • Sprint metrics table
   • Completed items list
   • Carryover items with reasons
   • Upcoming sprint plan
7. Send Email (Gmail) — Email the report to stakeholders
8. Send Message (Slack) — Post the AI-generated summary to the team channel
9. Dashboard Output — Populate:
   • Bar Tile — Sprint burndown: committed vs. completed by sprint (last 6 sprints)
   • Line Tile — Velocity trend over 12 sprints
   • Pie Tile — Work breakdown: features, bugs, tech debt, ops
   • Metric Tile — Commitment accuracy, velocity, carryover count

Key Nodes: Schedule Trigger, Search Issues (Jira), Aggregation, Computed Column, AI Summary, Write PDF, Send Email, Send Message, Dashboard Output

Plan Resource Allocation and Prevent Capacity Overload

Track team capacity, identify over-allocated individuals, and forecast resource needs for upcoming sprints.

Scenario: An engineering manager needs to balance workload across 20 engineers, identify who's over-committed, and plan capacity for the next quarter's project roadmap.

Workflow Steps:

1. Schedule Trigger — Run daily
2. Search Issues (Jira) — Pull all assigned issues: assignee, story points, due date, sprint, status
3. Search Tasks (Asana) — Pull additional task assignments not tracked in Jira
4. Union — Merge all work items
5. Aggregation — Calculate capacity metrics per person:
   • Total points assigned this sprint
   • Points completed vs. remaining
   • Active issues count
   • Items due this week
6. Computed Column — Calculate:
   • Utilization: assigned_points / capacity_points * 100
   • Over-allocation: anyone > 120% capacity
   • Under-allocation: anyone < 60% capacity
   • Projected remaining work: remaining_points / personal_velocity * days
7. Filter — Flag over-allocated and under-allocated team members
8. AI Enrichment — Generate rebalancing recommendations: "Sarah has 45 points assigned this sprint (150% of capacity). 12 points are P3 tasks that could be moved to Sprint 16. Recommend reassigning to Mike (60% utilized) or reducing sprint commitment."
9. Multi-Conditional — Route by condition:
   • Over-allocated (> 130%) → Send Message (Slack) to engineering manager with rebalancing suggestion
   • Under-allocated (< 50%) → Dashboard Output to capacity planning queue
10. Dashboard Output — Populate:
    • Bar Tile — Utilization by team member (color-coded: green/yellow/red)
    • Pivot Tile — Person × Sprint capacity allocation matrix
    • Metric Tile — Team average utilization, over-allocated count, under-allocated count
    • Forecast Tile — Capacity needed vs. available for next 4 sprints based on roadmap
    • Table Tile — Team roster with current assignments, velocity, and utilization

Key Nodes: Schedule Trigger, Search Issues (Jira), Search Tasks (Asana), Union, Aggregation, Computed Column, Filter, AI Enrichment, Multi-Conditional, Send Message, Dashboard Output

Track Milestones and Automate Stakeholder Reporting

Track project milestones, detect schedule risks, and generate automated stakeholder updates.

Scenario: A program manager running a product launch with 15 dependent milestones across 4 teams needs automated schedule risk detection and executive status updates.

Workflow Steps:

1. Schedule Trigger — Run daily at 8 AM
2. Database Query (PostgreSQL) — Pull milestone registry: milestone name, owner, planned date, forecast date, status (not started, in progress, complete, at risk), dependencies, critical path flag
3. Search Issues (Jira) — Pull work items linked to each milestone to calculate actual completion %
4. Join — Merge milestones with underlying work item progress
5. Computed Column — Calculate:
   • Days until planned date
   • Schedule variance: forecast - planned (positive = late)
   • Completion %: completed items / total items per milestone
   • Dependency risk: are upstream milestones on track?
6. Filter — Milestones at risk:
   • Forecast date > planned date (projected late)
   • On critical path AND < 80% complete with < 2 weeks remaining
   • Blocked by upstream milestone that is itself at risk
7. AI Enrichment — Generate risk assessment: "Milestone 'API Integration Complete' is forecast 5 days late (Feb 28 → Mar 5). This blocks 'QA Regression Testing' and 'UAT Sign-off,' creating a cascading delay risk to the March 15 launch target. Recommend: pull in 2 additional engineers or reduce API scope to core endpoints only."
8. Multi-Conditional — Route by risk:
   • Critical path at risk → Send Email to executive sponsor + Send Message (Slack #program-mgmt) with AI risk assessment
   • Non-critical delay → Send Message (Slack) to milestone owner
9. Write PDF — Generate weekly program status report with milestone Gantt, risk register, and AI commentary
10. Send Email — Distribute to stakeholders
11. Dashboard Output — Populate:
    • Gantt Tile — Full milestone timeline with dependencies and critical path highlighting
    • Step Tile — Phase gates: Initiate → Plan → Execute → Test → Launch → Post-Launch
    • Table Tile — Milestone detail: name, owner, planned, forecast, variance, status
    • Metric Tile — Milestones on track %, days to launch, critical risks count
    • Timeline Tile — Decision log: key decisions and their dates

Key Nodes: Schedule Trigger, Database Query, Search Issues (Jira), Join, Computed Column, Filter, AI Enrichment, Multi-Conditional, Write PDF, Send Email, Send Message, Dashboard Output

Example Dashboard: PMO Portfolio Dashboard

Build this dashboard to give your PMO or engineering leadership portfolio-wide visibility into project health, team capacity, and schedule risk.

Row 1 — Portfolio Health

Row 2 — Project Timeline

Row 3 — Sprint & Resource

Row 4 — Risk & Milestones

Row 5 — Velocity & AI Insights

Row 6 — Work Breakdown & Activity

Getting Started

To build project management workflows:

1. Connect Jira and/or Asana — Authenticate under Integrations
2. Start with portfolio health — Build a Schedule Trigger → Search Issues → Aggregation → Dashboard Output workflow for project status
3. Automate sprint reports — Use AI Summary to generate narrative reports every sprint
4. Track capacity — Aggregation and Computed Column to calculate team utilization
5. Build the PMO dashboard — Gantt, Step, Metric, and Bar tiles for portfolio visibility