Workflow Optimization Strategies

Workflow optimization is about removing friction between work starting and value delivered. Every wait, handoff, and unnecessary step adds delay. Optimizing workflow means finding and eliminating these delays to create smooth, fast flow from idea to production.

Workflow Analysis

Understanding Your Workflow

Mapping Current State

WORKFLOW MAPPING
════════════════

STEP 1: IDENTIFY STAGES
─────────────────────────────────────
List every state work passes through:

Backlog → Refined → Sprint → In Progress →
Code Review → QA → Staging → Production

Include waiting states:
├── Waiting for review
├── Waiting for QA
├── Waiting for deployment
├── Waiting for approval
└── Often hidden but significant

STEP 2: MEASURE TIME IN EACH
─────────────────────────────────────
Track actual time per stage:

┌─────────────────────────────────────────────────────────┐
│  Typical Task Timeline                                 │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  Backlog:        5 days  ████████████████████          │
│  In Progress:    2 days  ████████                      │
│  Code Review:    3 days  ████████████                  │
│  QA Testing:     1 day   ████                          │
│  Deployment:     2 days  ████████                      │
│  ─────────────────────────────────────────────          │
│  Total:         13 days                                │
│                                                         │
│  Active Work:    3 days (23%)                          │
│  Waiting:       10 days (77%)                          │
│                                                         │
└─────────────────────────────────────────────────────────┘

INSIGHT: 77% waiting, not working.
Optimization opportunity is huge.

STEP 3: FIND BOTTLENECKS
─────────────────────────────────────
Bottleneck = Stage where work piles up

Signs:
├── Items waiting to enter stage
├── Long time in that stage
├── Previous stages starved
├── Downstream stages starved
└── Everyone blames this stage

Common bottlenecks:
├── Code Review (not enough reviewers)
├── QA (manual testing)
├── Deployment (complex process)
├── Approval (stakeholder availability)
└── Single person (vacation = blocked)

Optimization Strategies

Reduce Wait Time

ELIMINATING WAIT TIME
═════════════════════

CODE REVIEW WAIT:
─────────────────────────────────────
Problem: PRs wait 2-3 days for review

Solutions:
├── Review SLA (24 hours max)
├── Pair review time (daily block)
├── Auto-assign reviewers
├── Smaller PRs (faster to review)
├── Review queue visibility
└── Incentivize review (counts as work)

Result: 3 days → 1 day

APPROVAL WAIT:
─────────────────────────────────────
Problem: Waiting for stakeholder approval

Solutions:
├── Define who can approve what
├── Escalation if no response
├── Async approval (not meetings)
├── Default-approve with timeout
├── Reduce what needs approval
└── Empower team decisions

Result: 2 days → 4 hours

DEPLOYMENT WAIT:
─────────────────────────────────────
Problem: Deployment only on Tuesdays

Solutions:
├── CI/CD automation
├── Feature flags (decouple deploy from release)
├── Smaller, safer deployments
├── Rollback capability
├── Deploy on merge
└── Remove deployment windows

Result: Weekly → Daily → Continuous

Reduce Handoffs

MINIMIZING HANDOFFS
═══════════════════

PROBLEM WITH HANDOFFS:
─────────────────────────────────────
Every handoff has:
├── Context loss
├── Communication overhead
├── Wait time for pickup
├── Blame opportunity
├── Quality risk
└── Time cost

Before:
Dev → Code Review → QA → Deploy → Ops
(4 handoffs)

After:
Dev (includes review, testing, deploy)
(0 handoffs)

STRATEGIES:
─────────────────────────────────────
1. CROSS-FUNCTIONAL TEAMS
   ├── Team has all skills
   ├── No external dependencies
   ├── Own end-to-end
   └── No handoffs to other teams

2. PAIR/MOB PROGRAMMING
   ├── Review built-in
   ├── Knowledge shared instantly
   ├── No waiting for review
   └── Higher quality, fewer handoffs

3. DEVELOPER TESTING
   ├── Developers write/run tests
   ├── Automated testing
   ├── Shift left
   └── No handoff to QA team

4. YOU BUILD IT, YOU RUN IT
   ├── Teams deploy their code
   ├── Teams handle incidents
   ├── No handoff to ops
   └── Faster feedback, better quality

Limit Work in Progress

WIP LIMITS
══════════

WHY WIP LIMITS:
─────────────────────────────────────
More WIP = Longer cycle time

Example:
├── 10 items, 1 finishes per day
├── All started at once: Each takes 10 days
├── Started one at a time: First done in 1 day

Little's Law:
Lead Time = WIP ÷ Throughput

Lower WIP = Lower Lead Time
(Same throughput, less waiting)

HOW TO SET WIP LIMITS:
─────────────────────────────────────
Start: WIP = Team Size × 1.5
├── 5-person team: WIP limit of 7-8
├── Adjust based on observation
├── Too tight: Idle people
├── Too loose: No improvement
└── Experiment to find sweet spot

WIP BY STAGE:
─────────────────────────────────────
┌─────────────────────────────────────────────────────────┐
│  Kanban Board with WIP Limits                          │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  To Do    In Progress   Review     Done                │
│    ∞          4            2          ∞                │
│ ─────────────────────────────────────────────          │
│ │ T1 │    │ T2 │ T3 │  │ T4 │ T5│  │     │            │
│ │ T6 │    │ T7 │ T8 │  │      │    │     │            │
│ │ T9 │    │    │    │  │      │    │     │            │
│                                                         │
│  Status: Review at limit (2/2)                         │
│  Action: Help clear review before pulling new work     │
│                                                         │
└─────────────────────────────────────────────────────────┘

AT WIP LIMIT:
├── Help clear bottleneck
├── Don't start new work
├── Swarm on stuck items
└── Make problem visible

Automation

Automate Repetitive Steps

WORKFLOW AUTOMATION
═══════════════════

WHAT TO AUTOMATE:
─────────────────────────────────────
Testing:
├── Unit tests on commit
├── Integration tests on PR
├── E2E tests on merge
└── No manual test execution

Code Quality:
├── Linting on save
├── Formatting on commit
├── Security scanning
├── Dependency checking
└── No manual code review for basics

Deployment:
├── Build on merge
├── Deploy to staging automatically
├── Promote to production on approval
├── Rollback on failure
└── No manual deployment steps

Status Updates:
├── PR merged → Task done
├── Build failed → Task blocked
├── Deployed → Notify stakeholders
└── No manual status changes

AUTOMATION PRIORITY:
─────────────────────────────────────
Automate first:
├── High frequency (happens often)
├── Rule-based (no judgment needed)
├── Error-prone manually
├── Time-consuming
└── Boring for humans

GitScrum Optimization

Workflow Configuration

GITSCRUM WORKFLOW OPTIMIZATION
══════════════════════════════

WORKFLOW STATES:
─────────────────────────────────────
Keep minimal:
├── To Do
├── In Progress  (WIP limit: 4)
├── Review       (WIP limit: 2)
├── Done
└── Fewer states = Less overhead

Add only if needed:
├── Blocked (makes blockers visible)
├── Testing (if separate QA phase)
├── Deployed (if different from Done)
└── Each state should trigger different action

AUTOMATIONS:
─────────────────────────────────────
├── Status change → Notify assignee
├── WIP exceeded → Alert team
├── Stale → Flag for review
├── PR merged → Move to Done
└── Reduce manual work

METRICS:
─────────────────────────────────────
Dashboard shows:
├── Cycle time by stage
├── WIP current
├── Bottleneck visibility
├── Flow efficiency
└── Trend over time

Review weekly:
├── Where is work stuck?
├── Is cycle time improving?
├── Are WIP limits working?
└── What to adjust?

Continuous Improvement

Improvement Cycle

WORKFLOW IMPROVEMENT CYCLE
══════════════════════════

1. MEASURE
─────────────────────────────────────
├── Current cycle time
├── Time per stage
├── WIP levels
├── Bottleneck location
└── Baseline established

2. IDENTIFY
─────────────────────────────────────
├── Biggest bottleneck
├── Root cause (not symptom)
├── One thing to improve
├── Expected impact
└── Focus on constraint

3. IMPLEMENT
─────────────────────────────────────
├── Make one change
├── Small experiment
├── Time-boxed trial
├── Team buy-in
└── Document the change

4. MEASURE AGAIN
─────────────────────────────────────
├── Did metric improve?
├── Any side effects?
├── Is it sustainable?
├── What did we learn?
└── Data-driven decision

5. REPEAT
─────────────────────────────────────
├── Keep change if worked
├── Revert if didn't
├── Find next bottleneck
├── Continuous cycle
└── Never done improving

Best Practices

For Workflow Optimization

1. Visualize flow — Can't improve what you can't see
2. Measure cycle time — Most important metric
3. Limit WIP — Less work in progress, faster flow
4. Remove handoffs — Every handoff adds delay
5. Automate repetitive — Free humans for thinking

Anti-Patterns

WORKFLOW MISTAKES:
✗ Complex multi-state workflows
✗ No WIP limits
✗ Optimizing non-bottlenecks
✗ Manual repetitive tasks
✗ Too many handoffs
✗ No measurement
✗ Big-bang changes
✗ Ignoring team feedback

Related Solutions

• Setting up agile workflows in GitScrum
• Workflow automation in GitScrum
• Managing work in progress limits