ROI【🔏Classified File】 No. X051 | What Are the 7 Wastes of TPS

Bad Practice:
- Making 120 units when ordered 100
- Producing next month's quota this month
- Making extras "just in case"
- Overproducing to maximize machine utilization

Consequences:
- Excess inventory accumulation
- Warehouse space compression
- Capital immobilization
- Obsolescence risk

Bad Practice:
- Implementing unused features
- Building features that might be needed someday
- Over-engineering design documentation
- Sophisticated implementation users don't want

Consequences:
- Wasted development effort
- Increased maintenance costs
- Release delays
- Time shortage for truly needed features

Bad Practice:
- Sending emails uniformly to unresponsive segments
- Mass-producing unread whitepapers
- Creating massive content before measuring effectiveness
- Expanding ads with unclear targets

Consequences:
- Wasted content production costs
- Customer information fatigue
- Brand image deterioration
- Underinvestment in effective initiatives

Psychological Factors:
- "Since we're making it anyway" mentality
- Misconception that 100% utilization is good
- Anxiety about wanting buffers
- Resistance to stopping production

Organizational Factors:
- Evaluation based on output quantity
- Culture that doesn't tolerate idle machines/people
- Inaccurate demand forecasting
- Pursuit of local optimization

Just-in-Time:
- What is needed
- When it is needed
- In the amount needed

Concrete Implementation:
- Kanban system (pull from downstream)
- Small-lot production
- Demand leveling
- Pull production (not push)

Bad Practice:
- Workers waiting due to upstream delays
- Production line stopped from machine breakdown
- Work halted pending approvals
- Waiting for material delivery

Consequences:
- Wasted labor costs
- Delivery delays
- Productivity decline
- Motivation decrease

Bad Practice:
- Development stopped awaiting code review
- Engineers idle awaiting specification finalization
- Next development blocked awaiting deploy approval
- Waiting for QA team confirmation

Consequences:
- Decreased development velocity
- Inefficiency from context switching
- Increased lead time
- Developer frustration

Bad Practice:
- Work stopped pending supervisor approval
- Waiting for responses from other departments
- Idle until meeting start time
- Waiting for system processing completion

Consequences:
- Time wastage
- Decreased concentration from parallel tasks
- Delivery delays
- Delayed value delivery to customers

Standardized Work:
- Uniform work timing
- Identify and improve bottleneck processes
- Multi-skilling (different work during waiting)

Jidoka (Automation with Human Intelligence):
- Automatic stop on abnormality
- Humans focus on exception handling
- Delegate to machines what can be automated

Bad Practice:
- Long-distance movement within factory
- Warehouse and factory separation
- Multiple loading/unloading transfers
- Circuitous layouts

Consequences:
- Transportation costs
- Time wastage
- Damage/loss risk
- Increased lead time

Bad Practice:
- Copy-pasting data between multiple tools
- Manual file transfers
- File sharing via email
- Duplicate information entry

Consequences:
- Time wastage
- Human errors
- Information fragmentation
- Version control chaos

Bad Practice:
- Circulating paper documents between departments
- Moving for approval stamps
- Travel time to meeting rooms
- Walking to retrieve distant materials

Consequences:
- Wasted movement time
- Document loss risk
- Process delays
- Reduced time for essential work

Layout Improvement:
- U-shaped lines (minimize movement distance)
- Optimal workstation placement
- Needed items within arm's reach

Single-Piece Flow:
- One piece at a time, not bulk transport
- Batch size reduction
- Intermediate inventory elimination

Bad Practice:
- Processing to precision customers don't require
- Excessive finishing of invisible parts
- Unnecessary inspection steps
- Over-specification

Consequences:
- Increased processing time
- Rising costs
- Delivery delays
- Reduced price competitiveness

Bad Practice:
- Implementing sophisticated features users won't use
- Excessive abstraction/design pattern application
- Unnecessary performance optimization
- Creating detailed documentation nobody reads

Consequences:
- Wasted development time
- Increased complexity
- Higher maintenance costs
- Lack of focus on essential value

❌ Not about lowering quality
✅ Precisely matching customer-required quality

Key Points:
- Don't make it 100% when 80% suffices
- Eliminate work not directly tied to customer value
- [MVP](/behind_case_files/articles/X036_MVP) philosophy
- Avoiding the perfectionism trap

Bad Practice:
- Excess inventory "just in case"
- Materials sleeping in warehouses
- Large finished goods stockpiles
- Dead stock

Consequences:
- Warehouse costs
- Capital immobilization
- Obsolescence/deterioration risk
- Problem concealment (inventory masks issues)

Bad Practice:
- Unreleased completed features
- Accumulation of unused code
- Implemented but untested features
- Bloated backlog

Consequences:
- Maintenance costs
- Delayed discovery of integration issues
- Obsolescence (market changes make it unnecessary)
- Delayed feedback

Just-in-Time:
- Zero inventory as ideal
- Single-piece flow production
- Pull from downstream process

Revealing Problems Hidden by Inventory:
- Reduce inventory → problems become visible
- Solve problems → reduce inventory further
- Continuous improvement cycle

Bad Practice:
- Searching for tools
- Turning around, bending down
- Changing grip
- Working in unnatural postures

Consequences:
- Time wastage
- Fatigue accumulation
- Workplace injury risk
- Productivity decline

Bad Practice:
- Back-and-forth between mouse and keyboard
- Eye movement between multiple screens
- Time spent searching for documents
- Repetitive copy-pasting

Consequences:
- Accumulated micro time losses
- Decreased concentration
- Physical fatigue
- Increased errors

Principles of Motion Economy:
- Use both hands simultaneously
- Symmetrical movements
- Shortest distance
- Rhythmic motion

5S Activities:
- Sort (discard unnecessary items)
- Set in order (place needed items for immediate access)
- Shine (clean)
- Standardize (maintain cleanliness)
- Sustain (make it habitual)

Bad Practice:
- Defective products
- Inspection failures
- Customer complaint handling
- Recalls

Consequences:
- Double consumption of materials/labor
- Delivery delays
- Loss of customer trust
- Brand damage

Bad Practice:
- Bug occurrence
- Rebuilding due to misunderstood specifications
- Problems from insufficient testing
- Production environment troubles

Consequences:
- Debugging effort
- Customer impact
- Team morale decline
- Lost opportunities

Poka-Yoke (Error-Proofing):
- Mechanisms that prevent mistakes
- Physical design allowing only correct methods
- Checklist utilization

Jidoka:
- Stop immediately on detecting abnormality
- Don't pass defects to next process
- Investigate and address root causes immediately

Problems:
- Workers walk to products
- 10-20km walking per day
- 70% of picking time spent moving

Results:
- Low productivity
- Worker fatigue
- Long delivery times

Kiva Robots Introduction (now Amazon Robotics):
- Shelves come to workers
- Workers pick from fixed positions
- Robots transport via optimal routes

Effects:
- 75% reduction in movement time
- 50% increase in warehouse capacity
- Half the order processing time

Traditional:
- Can't pack until all items gathered
- Can't ship until packing complete
- Waiting time between processes

Anticipatory Picking:
- Position products nearby before order confirmation
- Start packing moment order placed
- Parallel processing of multiple orders

Effects:
- Hours from order to shipment
- Next-day delivery for Prime members

Traditional Retail:
- Large store inventory
- Unsold inventory risk
- Obsolescence

FBA (Fulfillment by Amazon):
- Consolidate seller inventory in Amazon warehouses
- Data-driven demand forecasting
- Optimal regional inventory placement

Effects:
- Dramatically improved inventory turnover
- Reduced seller risk
- Shortened delivery times

Problem:
- Implementing unused features
- Large-scale releases

Solution:
- Squad system (small autonomous teams)
- Small, fast releases
- Validate with A/B testing before scaling

Effects:
- Increased development velocity
- Minimized failure costs

Problem:
- Release delays pending approvals
- Dependencies on other teams

Solution:
- Autonomous deployment authority
- Microservices architecture
- Continuous Delivery

Effects:
- 100+ deployments per day
- Dramatic feature addition acceleration

Problem:
- Bug discovery in production
- Large-scale failures

Solution:
- Comprehensive automated testing
- Canary releases
- Immediate rollback mechanisms

Effects:
- Minimized failure impact scope
- Confident high-velocity releases

For same production volume:
- Inventory: 1/10 of competitors
- Production lead time: 1/2 of competitors
- Defect rate: 1/5 of competitors
- Factory floor space: 2/3 of competitors

Results:
- Overwhelming profit margins
- Price competitiveness
- Market share expansion

High Inventory State:
- Problems covered by inventory
- Issues remain hidden
- Root causes unclear

After Inventory Reduction:
- Problems immediately surface
- Immediate response
- Continuous improvement

Inventory Reduction:
- Decreased fixed assets
- Cash preservation
- Created investment capacity

Lead Time Reduction:
- Improved turnover rate
- Better cash cycle

Small-Lot Production:
- Immediate response to demand changes
- Multi-product capability
- Easy customization

Results:
- Market adaptability
- Competitive advantage

❌ Wrong Application:
"Cost cutting for waste elimination"
→ Reducing value creation

✅ Correct Understanding:
"Waste elimination for value creation"
→ Customer value takes priority

Problems:
- Supply chain disruption vulnerability
- Unable to respond to demand spikes
- Supply stoppage from disasters/pandemics

Countermeasures:
- Balance with risk analysis
- Maintain strategic inventory
- Supplier diversification

Initial Phase:
- First realize (ignore efficiency)
- Manual work acceptable
- Even 100 copy-pastes tolerated

Maturity Phase:
- After identifying bottlenecks
- Improve with 7 Wastes
- Gradual efficiency enhancement

Critical: Don't mistake the timing

Failure from Technique-Only Introduction:
- Kanban system introduced
- But push production continues
- TPS in form only

Keys to Success:
- Organization-wide improvement culture
- Shop floor autonomy
- Top management commitment

Lean Software Development:
- Overproduction → MVP, staged releases
- Waiting → CI/CD, automation
- Defects → TDD, automated testing

Growth Hacking:
- Overproduction → Small-scale experiments
- Overprocessing → Simple landing pages
- Inventory → Immediate content publication

Hospital Operations:
- Waiting → Optimized appointment systems
- Transportation → Electronic medical records
- Motion → Improved traffic flow design