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