Workload & Capacity Planning¶
Kiket's Workload & Capacity Planning feature provides real-time visibility into team resource allocation, helps identify workload imbalances, and offers AI-powered recommendations for optimal task distribution.
Overview¶
The capacity planning dashboard gives managers and team leads a comprehensive view of:
- Team Utilization: See how work is distributed across team members
- Resource Heatmaps: Visual timeline of capacity over multiple weeks
- Effort Allocation: Breakdown of work by project and issue type
- Load Balancing: AI-powered recommendations for reassigning work
Accessing the Dashboard¶
Navigate to the Capacity Dashboard from the main menu or use the command palette:
- Click Capacity in the main navigation
- Or press
Cmd/Ctrl + Kand search for "capacity"
Dashboard Features¶
Team Capacity Overview¶
The main dashboard shows all team members with their current workload status:
| Status | Utilization | Meaning |
|---|---|---|
| Available | 0-50% | Has significant capacity for new work |
| Balanced | 50-80% | Healthy workload level |
| Busy | 80-100% | At or near capacity |
| Overallocated | >100% | Overloaded, may need work redistribution |
Each team member card displays:
- Utilization percentage - Current workload vs. available capacity
- Open tasks - Number of assigned issues not yet started
- In progress - Issues currently being worked on
- Blocked - Issues that cannot proceed
- Weekly velocity - Historical throughput indicator
Resource Heatmap¶
The heatmap visualization shows capacity across multiple weeks:
- Rows: Team members
- Columns: Weeks (configurable: 2-8 weeks)
- Colors: Intensity indicates utilization level
This helps identify:
- Upcoming capacity crunches
- Team members with available capacity
- Patterns in workload distribution
Effort Allocation View¶
See how work is distributed across:
- Projects - Work breakdown by project
- Issue Types - Distribution of bugs, tasks, features, etc.
- Status - Breakdown by workflow state
The allocation view includes pie charts and detailed tables showing:
- Total estimated hours
- Committed vs. available capacity
- Per-contributor breakdowns
Load Balancing Recommendations¶
The AI-powered recommendations engine analyzes team workload and suggests:
- Reassignment opportunities - Issues that could be moved from overloaded to available team members
- Priority adjustments - High-priority items that may need attention
- Risk identification - Potential bottlenecks or delivery risks
Each recommendation includes:
- The issue to reassign
- Source (overloaded) team member
- Target (available) team member
- Reason for the suggestion
- One-click reassignment action
User Capacity Settings¶
Each team member can configure their personal capacity settings:
Weekly Hours¶
Set the standard weekly working hours (default: 40 hours). This affects utilization calculations.
Working Days¶
Select which days you typically work. Common patterns:
- Monday-Friday (default)
- Monday-Thursday (compressed schedule)
- Custom patterns for part-time workers
Capacity Exceptions¶
Add temporary adjustments for specific weeks:
- Vacation - Set hours to 0 for time off
- Reduced hours - Partial availability
- Training days - Account for non-project time
Exceptions use the ISO week format (e.g., 2025-W02 for the second week of 2025).
User Drilldown¶
Click on any team member to see detailed workload information:
- Full list of assigned issues with status, priority, and due dates
- Recent time entries (if time tracking is enabled)
- Workload trends over time
- Direct link to capacity settings
Export & Reporting¶
Export capacity data for reporting and analysis:
CSV Export¶
Download team capacity data in CSV format, including:
- Team member names and emails
- Utilization percentages
- Open/in-progress/blocked task counts
- Available hours
- Status classifications
JSON Export¶
Get structured data for integration with other tools:
{
"period": {
"start": "2025-01-06",
"end": "2025-01-12"
},
"team": [
{
"id": 123,
"name": "Jane Developer",
"utilization_percentage": 75.5,
"open_tasks": 3,
"available_hours": 10,
"status": "balanced"
}
],
"summary": {
"total_members": 8,
"overallocated_count": 1,
"available_count": 2,
"average_utilization": 68.5,
"health_score": 85
}
}
API Access¶
The Capacity API enables programmatic access to capacity data. Available endpoints:
| Endpoint | Method | Description |
|---|---|---|
/api/v1/capacity/team |
GET | Team capacity overview |
/api/v1/capacity/recommendations |
GET | Load balancing suggestions |
/api/v1/capacity/export |
GET | Export data in JSON format |
/api/v1/capacity/user/:id/drilldown |
GET | User workload details |
/api/v1/capacity/settings |
GET/PATCH | Capacity settings |
/api/v1/capacity/reassign |
POST | Execute reassignment |
Example: Get Team Capacity¶
curl -X GET "https://kiket.dev/api/v1/capacity/team" \
-H "Authorization: Bearer YOUR_TOKEN" \
-H "Content-Type: application/json"
Example: Update User Settings¶
curl -X PATCH "https://kiket.dev/api/v1/capacity/settings" \
-H "Authorization: Bearer YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"weekly_hours_available": 32,
"working_days": [1, 2, 3, 4]
}'
MCP Server Integration¶
For AI agent integration, the Kiket MCP server exposes capacity tools:
| Tool | Description |
|---|---|
getCapacity |
Get team capacity overview |
getUserCapacity |
Get user workload details |
getCapacityRecommendations |
Get load balancing suggestions |
findAvailableAssignees |
Find team members with capacity |
updateCapacitySettings |
Update user settings |
addCapacityException |
Add temporary capacity exception |
reassignWithCapacityCheck |
Reassign with capacity validation |
exportCapacity |
Export capacity data |
Command Palette¶
Quick actions available via command palette (Cmd/Ctrl + K):
- View Team Capacity - Open the capacity dashboard
- My Workload - View your personal capacity details
- Capacity Settings - Configure your availability
- Show Overallocated - Filter to overloaded team members
- Find Available - Show team members with capacity
- View Heatmap - Open the resource heatmap
- Export Capacity Report - Download capacity data
Best Practices¶
For Managers¶
- Weekly reviews: Check the heatmap at the start of each week
- Act on recommendations: Review AI suggestions regularly
- Balance proactively: Don't wait for overallocation to occur
- Update capacity exceptions: Keep vacation and training time current
For Team Members¶
- Maintain accurate settings: Keep weekly hours and working days current
- Plan ahead: Add capacity exceptions for known time off
- Flag blockers early: Blocked work affects utilization metrics
- Update issue status: Keep work items in accurate states
Related Features¶
- SLA Monitoring - Track delivery commitments
- Analytics Engine - Deep dive into team metrics
- Board Management - Visualize work in progress
- Team Calendar - Sync capacity with calendars