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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:

  1. Click Capacity in the main navigation
  2. Or press Cmd/Ctrl + K and 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:

  1. Reassignment opportunities - Issues that could be moved from overloaded to available team members
  2. Priority adjustments - High-priority items that may need attention
  3. 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

  1. Weekly reviews: Check the heatmap at the start of each week
  2. Act on recommendations: Review AI suggestions regularly
  3. Balance proactively: Don't wait for overallocation to occur
  4. Update capacity exceptions: Keep vacation and training time current

For Team Members

  1. Maintain accurate settings: Keep weekly hours and working days current
  2. Plan ahead: Add capacity exceptions for known time off
  3. Flag blockers early: Blocked work affects utilization metrics
  4. Update issue status: Keep work items in accurate states