Six Sigma Case Study: GM Defense Service Parts Catalog Optimization
Project Overview
Organization: General Motors Defense
Department: Joint Ventures - Service Engineering
Project Duration: March 2024 - September 2024
Methodology: DMAIC + Theory of Constraints
Belt Level: Black Belt
DEFINE
Business Problem
The GM Defense catalog creation department was experiencing significant bottlenecks in processing Part and Accessory Change Notices, resulting in delayed service parts releases for multiple defense vehicle platforms. Production errors averaged 8.5% across catalog illustration legend data, creating downstream issues for field serviceability.
Project Goals
Reduce production errors by at least 10%
Increase catalog creation throughput by 10%
Eliminate bottlenecks in supplier resourcing workflow
Maintain zero safety/compliance incidents
Project Scope
In Scope: Catalog creation processes, service parts release workflows, electronic parts catalog (EPC) illustration data, cross-functional coordination with product engineering
Out of Scope: Vehicle platform engineering specifications, external supplier manufacturing processes
Stakeholders
Product Engineering Teams
Supply Chain Management
Quality Assurance
Joint Venture Partners
Field Service Technicians
MEASURE
Current State Metrics (Baseline)
Production Error Rate: 8.5%
Average Cycle Time: 14.2 days per catalog update
Catalog Creation Throughput: 3.2 releases per week
Rework Rate: 18%
Customer Service Inquiries (Partech): 47 per month
Data Collection Methods
Process observation (40 hours)
Partech inquiry database analysis
Time-motion studies of catalog creation workflow
Defect tracking via ERP system
Cross-functional team interviews (n=23)
Process Capability
Sigma Level: 2.8σ (unacceptable)
DPMO: 122,750 defects per million opportunities
ANALYZE
Root Cause Analysis
Constraint Identification (Theory of Constraints): Primary constraint identified at the "Change Notice Review" stage, where 73% of cycle time was consumed by sequential approval processes.
Fishbone Diagram - Key Findings:
People:
Lack of standardized training for new catalog creators
Knowledge silos between engineering and catalog teams
Process:
Sequential approval workflow created bottlenecks
No standardized templates for Part and Accessory Change Notices
Manual data entry for illustration legend data (high error rate)
Technology:
EPC system lacked automated validation checks
No integration between supplier resourcing database and catalog system
Materials:
Inconsistent technical documentation from suppliers
Missing serviceability specifications on 34% of new parts
Statistical Analysis
Pareto Analysis: 80% of errors traced to 3 root causes (manual data entry, missing supplier specs, approval delays)
Correlation Study: Strong negative correlation (r = -0.78) between approval cycle time and overall throughput
IMPROVE
Solutions Implemented
1. Constraint Elimination (Theory of Constraints)
Converted sequential approvals to parallel review process
Established dedicated "Change Notice Champion" role
Implemented daily stand-up meetings for bottleneck resolution
2. Process Standardization
Created standardized templates for Part and Accessory Change Notices
Developed training program for catalog creators (reduced onboarding time 40%)
Implemented peer review system before formal approval
3. Technology Enhancement
Automated validation checks in EPC system (caught 87% of data entry errors pre-submission)
Integrated supplier resourcing database with catalog system
Developed real-time dashboard for tracking Change Notice status
4. Supplier Collaboration
Established serviceability specification requirements in supplier contracts
Conducted quarterly supplier training on documentation standards
Pilot Results (8-week trial)
Production errors reduced to 6.1% (-28%)
Cycle time reduced to 10.8 days (-24%)
Throughput increased to 3.9 releases per week (+22%)
CONTROL
Control Mechanisms
1. Statistical Process Control
Implemented X-bar and R charts for error rate monitoring
Established control limits: UCL = 7.5%, LCL = 4.0%
Weekly review of control charts with team
2. Standard Operating Procedures
Documented 12 new SOPs for catalog creation workflow
Quarterly SOP reviews and updates
New hire certification program (100% completion required)
3. Continuous Monitoring
Real-time dashboard tracking (error rate, cycle time, throughput)
Monthly audits of catalog data integrity
Quarterly stakeholder satisfaction surveys
4. Sustainment Plan
Assigned process owner for ongoing DMAIC reviews
Scheduled six-month process capability study
Integrated metrics into departmental KPIs
RESULTS
Final Metrics (6-Month Post-Implementation)
MetricBaselineTargetActualImprovementProduction Error Rate8.5%7.7%7.5%-12%Cycle Time14.2 days12.8 days11.4 days-20%Throughput3.2/week3.5/week3.5/week+10%Rework Rate18%14%12%-33%Partech Inquiries47/month40/month35/month-26%
Process Capability Improvement
New Sigma Level: 3.4σ
New DPMO: 75,000 (39% reduction)
Financial Impact
Hard Savings: $187,000 annually (reduced rework, faster releases)
Soft Savings: $94,000 annually (reduced customer service burden, improved field serviceability)
Total Annual Benefit: $281,000
Additional Benefits
Zero safety/EEO incidents maintained throughout project
Strengthened cross-functional relationships (supplier satisfaction +22%)
Established problem-solving culture adopted by adjacent departments
Successful major supplier resourcing launch (valued at $2M+)
LESSONS LEARNED
What Worked Well
Theory of Constraints methodology rapidly identified true bottleneck
Parallel approval process dramatically reduced cycle time
Automated validation caught errors before they reached production
Daily stand-ups maintained team alignment and momentum
Challenges Overcome
Initial resistance to parallel approvals (addressed through pilot demonstration)
Integration complexity between legacy systems (solved with middleware solution)
Training resource constraints (solved with peer mentorship model)
Recommendations for Future Projects
Apply ToC constraint analysis earlier in project lifecycle
Invest in automation upfront (ROI realized within 4 months)
Establish clear process ownership from project inception
Maintain daily focus on the constraint until eliminated
PROJECT TEAM
Black Belt: Andrew Dunn
Champion: [GM Defense Senior Leadership]
Process Owner: Service Engineering Manager
Team Members: Product Engineering (3), Catalog Creators (5), IT Support (2), Supply Chain (2)
Certification Note: This project contributed to Six Sigma Black Belt certification (Six Sigma Academy Amsterdam, July 2024) and demonstrated mastery of DMAIC methodology, statistical analysis, and Theory of Constraints principles in a defense manufacturing environment.