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Lessons Learned from a Journey to High Maturity
Mary Gretchen Silos Mondragon
Accenture Philippines
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Agenda
Going for process high maturity Level 4 or 5 can be challenging.
Here are some of the lessons learned from the journey.
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Get Management Support
Senior management support is critical!
Set quality and process performance goals and commit to them
Set up steering committeeSponsor, key project leads
Give direction, resolve journey issues
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Establish a Core Team
Select key representatives
Coaches, Metrics, Methods, Tools
Drive the high maturity journey
Report to the steering committee
Resolve project issues
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Plan Early
Engage your lead appraiser early
Book LA schedule 1.5 years before appraisal
Balance LA interpretations Model interpretations vary by LA
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Deal with Statistical Requirements
Hire a Statistician
Handle the complexities of technical statistical tests
Provide relevant statistical approaches and strategies
Train the metrics team
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Invest in Appropriate Tools
Select tools to establish baselines and to build models
Minitab
Crystal Ball
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Invest in Appropriate Tools
Select tools for statistical process control for use by projects
SPC for MS Excel
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Train on High Maturity
Take SEI Understanding High Maturity
Get context on what the model requires
Be more capable to resolve issues
Be confident in challenging ideas
Ask questions during the training!
Be prepared prior to the training
List applicable questions
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Enable the Project Managers
Train PMs on basic statistics
Interpret, analyze control charts
Perform simple tests via given tools
Handhold and coach PMs
Understand and realize
benefits of process high maturity
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Enable the Project Managers
Establish easy‐to‐use checklists
List key steps
via flyers, e‐cards
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Establish Baselines
Collect, validate, analyze data
Data accuracy and reliability
Level of detail• Release, requirement, component
When to collect, analyze, recalibrate• Daily, weekly, monthly, quarterly
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Establish Baselines
Ensure homogeneity of data
Stratify data
Manage number of stratifications
Prove stratifications statistically
• Hypothesis test
• ANOVA – analysis of variance
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Establish Baselines
Set Baseline Standards
Set data count thresholds
• 6, 7‐24, 25‐30
Perform stability tests
• 8‐4‐2‐1 rule
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Establish Baselines
Test for significance
Eye fit
Statistical tests – Hypothesis tests
• F test ‐
difference in variance
• T Test ‐
shifting of means
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Establish Baselines
Test for process capability
Cp, Cpk
• Measure process capability
• Compare stable process performance with goals or specification limits
– more capable as value approaches 1
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Build Usable Models
Determine the right approach
Regression –
sufficient data
Bayesian – limited data
Logistic – non‐variable, categorical data
Link models to goals
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Build Usable Models
Set model standards
Adjusted R2
• Predictability of model based on factors
• Variation of y as explained by factors x
• the higher the better
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Build Usable Models
Set model standards
P value
• Significance of factors
• Identification of critical factors or sub processes
• Normality of data
• <
0.05
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Build Usable Models
Set model standards
VIF (Variance Inflation Factor)
• Multi‐collinearity or dependency
• the lower the better, within threshold
Error rate
• Accuracy of predicted vs. actual values
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Build Usable Models
Set model standards
Normality
Constancy of variance of errors
Number of factors in the model
Logic of coefficient signs (+/‐) of factors
Probabilistic and not deterministic
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Build Usable Models
Cover >30% of projects
End to end, Lower level models
Manageable number of models
Assess usability of models
Monitor project usage regularly
Recalibrate models
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Look for Improvements
Identify sustainable improvements
Focus on a goal
Use available models
Determine assignable, common causes
Consider pilot results and white papers of other similar organizations
Use six sigma
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Measure Improvements
Use cost or effort
What does the client want?
Reduce cost no matter how small?
Measuring at lower sub process may result in higher percentage
Translate into dollars?
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Assess Impact of Improvements
Determine return on investment
Bunch related improvements
Bunch common costs and expenses
Make short and long term projections
• Benefits may not be realized right away
Apply statistical tests
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Sustain Improvements
Reward and recognize improvement
Motivate continuous improvement
Link rewards and recognition with goals to allow faster achievement of goals
