statistical analysis of new product development (npd) cycle-time data
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Quality and Business Excellence
Celebration
ASQ Vancouver 25th Anniversary
Statistical Analysis of New Product Development (NPD) Cycle-time Data Including Applications of Results
Steve Pratt, MEng., PE, CSSBB Director of Engineering, Alpha Technologies
Alpha Technologies
Company Background
Alpha is a Full Service Power
Systems Provider to Multiple Markets
Pratt – Slide 1
Power Modules
Indoor Power Systems
Outdoor Power Systems
Alpha’s Power Solutions Products
Pratt – Slide 2
Phase-Gate New Product
Development (NPD) Process
Deliverables: • Product Concept • Business Case • Preliminary Plan
Deliverables: •High-Level Design •Requirements •Complete Project Plan
Deliverables: • Design Outputs • DFx Reviews • Preliminary Test
Reports
Deliverables: • Pilot Doc Pack • Pilot Build • Sales Forecasts
Deliverables: • Compliance
Certifications • Training • MarCom docs
Deliverables: • Sustaining Eng • Repair/Support • Cost Reduction
Phase 2 Planning
Phase 1 Concept
Phase 3 Development
Phase 4 Qualification and Pre-Production
Phase 5 LA and Production Ramp-up
Phase 6 GA and MOL
Pratt – Slide 3
Concurrent Engineering via Cross-
Functional Core Teams
Service Supply Chain
Product Management
Program Manager
Quality
Engineering
Manufacturing
Pratt – Slide 4
Motivation for Study
Continuous Improvement:
• general perception that NPD takes too long
• lack of proper management of resources
• desire to establish performance benchmarks
Pratt – Slide 5
NPD Data Collected and Analyzed
Schedule Data
• Recorded Dates: Start, Gate 1, Gate 2, Gate 3, Gate 4 (LA) & Gate 5 (GA)
• Program Plans: estimated time to LA, estimated time to GA
• Calculated: total time, time per phase, actual vs. plan
Cost Data
• Timecard System: actual total effort (man-hours)
• Program Plans: estimated total effort
• Calculated: effort by function, effort by phase, remaining effort, actual vs. plan
Pratt – Slide 6
Tools Used in the Study
JMP – Statistical Discovery Software Analyze-Distribution Platform: • Calculations: Quantiles, Moments • Plots: Histogram, Quantile Box, Normal Quantile • Fit Distribution: Normal, Beta, Goodness of Fit Tests
Fit Y by X Platform: Bivariate Analysis • Fit Line, Fit Polynomial, Summary of Fit
Fit Y by X Platform: One-way Analysis • Calculations: Means and Standard Deviations • Plots: Mean Diamonds • Analysis of Variance (ANOVA)
Fit Model Platform • Calculations: Standard Least Squares, Summary of Fit, Effect Tests • Plots: Actual by Predicted, Effect Leverage, Residual by Predicted • Two-way ANOVA with interactions
Microsoft Excel and PowerPoint
Pratt – Slide 7
External Benchmarking Data – PDMA
Best Practices Research
Provides industry-average NPD Cycle-Time based on complexity of programs:
• new-to-the world • new-to-the firm • next-gen improvements • incremental improvements
Pratt – Slide 8
Source: Griffin A., “Product development cycle time for business-to-business products,” Industrial Marketing Management 2002;31: 291-304 *
Average NPD Cycle-Time Benchmarking
Pratt – Slide 9
Planned vs. Actual NPD Cycle-Time
Pratt – Slide 10
ANOVA to Identify Significant Factors
for Schedule Data
Pratt – Slide 11
ANOVA to Identify Significant Factors
for Effort Data
Pratt – Slide 12
Categorizing NPD Programs into 9
Buckets
Product Types:
Modules (power modules, shelves, controllers) Indoor Systems (rack-based systems, racks, distribution) OSP (outside plant power/battery systems)
Program Complexities:
A – major program requiring advanced development B – completely new, but no advanced development C – new with incremental development
Pratt – Slide 13
NPD Summary Data –
Schedule (Gate 2 to LA)
Pratt – Slide 14
NPD Summary Data –
Schedule (Gate 2 to GA)
Pratt – Slide 15
NPD Summary Data –
Effort (Total Development Hours)
Pratt – Slide 16
NPD Schedule & Effort Continuous
Probability Distributions
Pratt – Slide 17
Additional Analyses
• plan vs. actual – schedule and effort
• schedule and effort variance by phase
• time spent per phase
• total effort by function and phase
• default team size and composition
Pratt – Slide 18
Applications
Better Estimating
Pratt – Slide 19
More Accurate Gate 2 Point Estimates
of Schedule and Effort
Previous estimates were:
- subject to negotiation
- overly optimistic and aggressive
- “rose-colored” recollections of past
Pratt – Slide 20
Alpha’s Historical Schedule
Estimation Accuracy
Median MRE = 44%
Pratt – Slide 21
NPD Schedule Point-Estimation via
Historical Mean Values
Median MRE = 19%
Pratt – Slide 22
Basic Schedule Equation Using Historical Mean Effort Values
Median MRE = 21%
Pratt – Slide 23
Informal Comparisons Equation Using
NPD Mean Values
Median MRE = 20%
Pratt – Slide 24
Mean Magnitude of Relative Error –
Schedule Estimates
Pratt – Slide 25
Alpha’s Historical Effort
Estimation Accuracy
Median MRE = 36%
Pratt – Slide 26
NPD Effort Point-Estimation via
Historical Mean Values
Median MRE = 18%
Pratt – Slide 27
Mean Magnitude of Relative Error –
Effort Estimates
Pratt – Slide 28
Determine the “Cone of Uncertainty”
Pratt – Slide 29
Cone of Uncertainty for NPD Project
Estimates
Pratt – Slide 30
Cone of Uncertainty for NPD Project
Schedule Data
Pratt – Slide 31
Cone of Uncertainty Applied to the 9
NPD Project Buckets
Pratt – Slide 32
Schedule Cone of Uncertainty Quantified by Program Phase
Pratt – Slide 33
Effort Cone of Uncertainty Quantified
by Program Phase
Pratt – Slide 34
Effort Estimate Ranges by Program
Phase
Pratt – Slide 35
Applications
Top-Down Project Planning
Pratt – Slide 36
Creation of Top-Down Program
Schedules
Pratt – Slide 37
NPD – Time Spent per Phase
Pratt – Slide 38
How Much Time Should Be Spent on
Planning?
Pratt – Slide 39
Applications
Performance Goal Setting
Pratt – Slide 40
SMART Performance Improvement
Goals
• fact-based and statistically valid
• objective and quantifiable
• deterministic at the start of a program
• consistent across all types of programs
• an enabler of continuous improvement
• unambiguous and easy to calculate
An ideal performance improvement measure is:
Pratt – Slide 41
RSD: a Normalized Measure of
Dispersion
Pratt – Slide 42
Program Scoring: RSD as Performance
Unit-of-Measure
Pratt – Slide 43
2013 NPD Cycle-Time Performance
Pratt – Slide 44
Earned-Value Milestones to Score
WIP NPD Programs
Pratt – Slide 45
Applications
Better Project Selection
Pratt – Slide 46
Deterministic Business Case Analysis
“Figures of Merit”
Pratt – Slide 47
Probabilistic Business Case Analysis
Beta Distribution
Pratt – Slide 48
Monte Carlo Simulation of
Cash Flows ($000)
Trial #1 Trial #2 Trial #3 Trial #4 Trial #5000
NPV $556 $461 $681 $447 $621
NRE 562 560 597 530 664
GM$ year1
348 274 241 220 274
GM$ year2
604 653 407 579 635
GM$ year3
451 651 644 447 558
Pratt – Slide 49
Probability-Based Figures of Merit
Pratt – Slide 50
Applications
Resource Management
Pratt – Slide 51
Default Team Size and Composition
Effort divided by Schedule represents number of individuals
Pratt – Slide 52
Roadmap and Budget Planning
Pratt – Slide 53
Program Resource Management
Engineering Pokémon board
• visual resource management tool
• 9 program type/complexity buckets
• default team size/composition
Pratt – Slide 54
NPD Programs are Represented by a
Series of Magnetic Trays
Pratt – Slide 55
Program Trays Incorporate Default
Team Size/Composition
Pratt – Slide 56
NPD Team Members are Represented
by a Series of Cards
Pratt – Slide 57
Engineering Pokémon – Additional
Pieces
Program Status Indicators
Bonus Targets Add-on Resource Trays “Ghost” Cards
Important Date Indicators
Clear Plastic Overlays
Pratt – Slide 58
The Board in Action
Pratt – Slide 59
Resulting Improvements
Pratt – Slide 60
Improved New Product Development
Better planning and management of resources…
• more stability and focus / less chaos
• increased efficiency
• enhanced organizational understanding
• faster NPD cycle-time
Pratt – Slide 61
In Conclusion:
It is never too late to start recording data!
- even simple data such as key dates and time spent on activities can facilitate powerful analyses
- capture data in real-time; don’t rely on memory or post mortem activities
Pratt – Slide 62
Questions???
Pratt – Slide 63
Thank You!
STEVEN PRATT, MEng., PE
Director of Engineering
www.alpha.ca
Pratt – Slide 64
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