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# bd Metrics Guide
This guide covers the key metrics for tracking work in bd.
## Cycle Time vs. Lead Time
**Two distinct time measurements:**
### Cycle Time
- **Definition**: Time from "work started" to "work completed"
- **Start**: When task moves to "in-progress" status
- **End**: When task moves to "closed" status
- **Measures**: How efficiently work flows through active development
- **Use**: Identify process inefficiencies, improve development speed
```bash
# Calculate cycle time for completed task
bd show bd-5 | grep "status.*in-progress" # Get start time
bd show bd-5 | grep "status.*closed" # Get end time
# Difference = cycle time
```
### Lead Time
- **Definition**: Time from "request created" to "delivered to customer"
- **Start**: When task is created (enters backlog)
- **End**: When task is deployed/delivered
- **Measures**: Overall responsiveness to requests
- **Use**: Set realistic expectations, measure total process duration
```bash
# Calculate lead time for completed task
bd show bd-5 | grep "created_at" # Get creation time
bd show bd-5 | grep "deployed_at" # Get deployment time (if tracked)
# Difference = lead time
```
### Key Differences
| Metric | Starts | Ends | Includes Waiting? | Measures |
|--------|--------|------|-------------------|----------|
| **Cycle Time** | In-progress | Closed | No | Development efficiency |
| **Lead Time** | Created | Deployed | Yes | Total responsiveness |
### Example
```
Task created: Monday 9am (enters backlog)
↓ [waits 2 days]
Task started: Wednesday 9am (moved to in-progress)
↓ [active work]
Task completed: Wednesday 5pm (moved to closed)
↓ [waits for deployment]
Task deployed: Thursday 2pm (delivered)
Cycle Time: 8 hours (Wednesday 9am → 5pm)
Lead Time: 3 days, 5 hours (Monday 9am → Thursday 2pm)
```
### Why Both Matter
- **Short cycle time, long lead time**: Work is efficient once started, but tasks wait too long in backlog
- Fix: Reduce WIP, start fewer tasks, finish faster
- **Long cycle time, short lead time**: Work starts immediately but takes forever to complete
- Fix: Split tasks smaller, remove blockers, improve focus
- **Both long**: Overall process is slow
- Fix: Address both backlog management AND development efficiency
### Tracking Over Time
```bash
# Average cycle time (manual calculation)
# For each closed task: (closed_at - started_at)
# Sum and divide by task count
# Trend analysis
# Week 1: Avg cycle time = 3 days
# Week 2: Avg cycle time = 2 days ✅ Improving
# Week 3: Avg cycle time = 4 days ❌ Getting worse
```
### Improvement Targets
- **Cycle time**: Reduce by splitting tasks, removing blockers, improving focus
- **Lead time**: Reduce by prioritizing backlog, reducing WIP, faster deployment
## Work in Progress (WIP)
```bash
# All in-progress tasks
bd list --status in-progress
# Count
bd list --status in-progress | grep "^bd-" | wc -l
```
### WIP Limits
Work in Progress limits prevent overcommitment and identify bottlenecks.
**Setting WIP limits:**
- **Personal WIP limit**: 1-2 tasks in-progress at a time
- **Team WIP limit**: Depends on team size and workflow stages
- **Rule of thumb**: WIP limit = (Team size ÷ 2) + 1
**Example for individual developer:**
```
✅ Good: 1 task in-progress, 0-1 in code review
❌ Bad: 5 tasks in-progress simultaneously
```
**Example for team of 6:**
```
Workflow stages and limits:
- Backlog: Unlimited
- Ready: 8 items max
- In Progress: 4 items max (team size ÷ 2 + 1)
- Code Review: 3 items max
- Testing: 2 items max
- Done: Unlimited
```
### Why WIP Limits Matter
1. **Focus:** Fewer tasks means deeper focus, faster completion
2. **Flow:** Prevents bottlenecks from accumulating
3. **Quality:** Less context switching, fewer mistakes
4. **Visibility:** High WIP indicates blocked work or overcommitment
### Monitoring WIP
```bash
# Check personal WIP
bd list --status in-progress | grep "assignee:me" | wc -l
# If > 2: Focus on finishing before starting new work
```
### Red Flags
- WIP consistently at or above limit (need more capacity or smaller tasks)
- WIP growing week-over-week (work piling up, not finishing)
- WIP high but velocity low (tasks blocked or too large)
### Response to High WIP
1. Finish existing tasks before starting new ones
2. Identify and remove blockers
3. Split large tasks
4. Add capacity (if chronically high)
## Bottleneck Identification
```bash
# Find tasks that are blocking others
# (Tasks that many other tasks depend on)
for task in $(bd list --status open | grep "^bd-" | cut -d: -f1); do
echo -n "$task: "
bd list --status open | xargs -I {} sh -c "bd show {} | grep -q \"depends on $task\" && echo {}" | wc -l
done | sort -t: -k2 -n -r
# Shows tasks with most dependencies (top bottlenecks)
```