CMMI High Maturity Best Practices HMBP 2010: Implementation of High Maturity Model In an...
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SDE For public use Page 1 May 2010 Implementation of High Maturity Model In an Organization -Rajesh TV Amit Chauhan (Siemens)
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Implementation of High Maturity Model In an Organization -Rajesh TV Amit Chauhan (Siemens)presented at 1st International Colloquium on CMMI High Maturity Best Practices held on May 21, 2010, organized by QAI
Transcript of CMMI High Maturity Best Practices HMBP 2010: Implementation of High Maturity Model In an...
SDE For public use
Page 1 May 2010
Implementation of High Maturity Model
In an Organization
-Rajesh TV
Amit Chauhan
(Siemens)
SDE © SIS India - All rights reserved.
Implementation of High Maturity
Model in an Organization
Amit Chauhan
Sr. Consultant
Rajesh TV
Chief Manager
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Page 3 May 2010
Objective
From Maturity Level 2 to 3, organization is more reactive to the past as
compare to the future
Although organizations know when corrective actions must be taken,
organization may not be able to predict the effectiveness of these corrective
actions
Our focus is to share key steps in defining and implementing High Maturity Level
4 processes based on our experience and lessons learnt
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To Start with….Moving from Hygiene to High Maturity Processes
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High Maturity Processes Implementation Evaluation
Balance Scorecard reflects Organization strategy for it’s vision Current vs “to be”
“ What is the Focus”
Business Goal Matrix specifies Selection of Key Indicators to measure the
progress of strategy achieved“How do we measure”
Process Baseline Report determines Current capability to achieve organization
vision/goal Scope of improvement
(short/medium/Long term)
“Where are we”
Process Prediction Model evaluates Certainty to achieve organization goal
based on current capability
“How do we perform”
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High Maturity – Quick View
Business Goals
Process
Objectives (Y)
Process
Selection
Controllabl
e Factors
(X)
Goals for XCapability
Baseline for X
Prediction
Model
Process
Composition
Improvement
Opportunity
Organization LevelProject Level
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Business Goal Matrix Plan
Senior Management evaluate and select business goals for critical to customer and
critical to business
Voice of Business Business Issues Critical to Quality/
Critical to Business
Customer Issues Voice of Customer
Reduce cycle time to
deliver Quality
product with in Budget
High Cycle Time On time Delivery High Cost due to late
delivery
Defect Free
economical product
Variation in Effort Productivity
Improvement
High Cost due to <
agreed efforts
High Defects with
Delivery
Reduce Defect High Defect
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Business Goal Matrix: Flow Down
Business goal must be validated and prioritize with the help of Business goal matrix plan
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Organization Procedure for Process and Quality Performance
Define Measures for common understanding and to avoid any ambiguity
Process Objective Processes DefinitionScope of
Measurement
Controllable X
Factors
Schedule Variance should
not be greater than 5%
Schedule
Estimation and
Monitoring
Difference in between planned
date of completion with actual
date of completion
At each
Milestone
Actual Efforts
Skill Level
Improve Productivity by
5% every quarterEngineering
Ratio of actual efforts and
actual size
At each
Milestone
Actual Efforts
Skill Level
Review Methods
Review Cycles
Delivered Defect Density
<1defect/per unit
Review, Testing
Estimation and
Monitoring
Less than 1 defects (review +
Testing defects ) per actual unit
size
At each
Milestone
Actual Efforts
Skill Level
Review Methods
Review Cycles
Establish Measurement Procedure
Define process and measurement system to determine organization process performance
Define goal for process as well as individual controllable factor
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Page 10 May 2010
Organization Baseline: Key Ingredients
Base Data: Data for each controllable X factor should be: Independent Repeatable Time series based Measurable Impact on Y
Statistical tool as per data type : Discrete (Attribute) or Continuous (Variable) Histogram Box Plot Control Chart Individual X Chart Trend Chart Cause Effect Diagram/Fishbone Correlation and Regression
Test of Stability : Ensure data is free from special causes
Inference Detail: Stability and Capability based on control limits and specification limits
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Organization Baseline Report
Data stratification is the critical step before development of organization baseline report
Data stratification should be based on organization strategy for it’s vision
Data Stratification can be done in different levels. For ex: Stratification based on
Life Cycle
Technology
Customer type
Market type
Estimation technique
Data Stratification
Estimation Technique
Life Cycle
Technology
Feature Point, Use Case Estimation
Development, Maintenance
Microsoft, Java
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Base Data: Test for Stability
Check for Data
stability using
control charts and
Box Plot
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Organization Baseline Report
Control Limits are
considered as +/- 3
Sigma Limits
Conclusion of each
baseline should clearly
define the “Stability” and
“Capability” of process
and also corrective
preventive actions
Generate Baseline Report for each process and sub process for all controllable factors
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Establish Project Objectives
Project specific goals are defined as per organization as
well as customer specific objectives
Sensitive processes are identified and controlled
Organization Objective
Customer Specific Objectives
Project Specific Goals
Part of Project Quality Plan
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Data Distribution
Each process has a trend of distribution
Selection of right distribution from more
than 12 distribution are critical
Implement “mistake proofing” in project quality reporting.
Data quality is very critical else prediction will mislead you
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High Maturity Process Evaluation
High Maturity Processes are evolved and not revolutionized
Prediction Model
for Productivity
Updated PPM
with process
composition
using “Efforts”
Trade off between
Defects and
Efforts
Identified and
updated more
factors for process
composition
Added “SKILL” as
process
composition
Time
Ma
turi
ty
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Process Prediction Model
Select tool to determine co relationship to predict future performance like regression model
With the help of Crystal Ball, process prediction model have been developed using regression
equations
7
6
520.00%
10.00%
0.00%
8.00%
4.00%
0.00%
20.00%
10.00%
0.00%
15105
30.00%
15.00%
0.00%
765 20.00%10.00%0.00% 8.00%4.00%0.00% 20.00%10.00%0.00%
CRY
Developer Competency
Design Rework Effort
Coding Rework Effort
Design Review Effort
Coding Review Effort
Matrix Plot of CRY, Developer Co, Design Rewor, Coding Rewor, ...
Select and prioritize X factors based on co-relationship
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Compose Defined Processes
Project defined process is based on historical stability and capability of data
Project defined Process consists of
Selecting sub processes
Adjusting / trade off level and depth of intensity of application of the sub-
processes or resources
Process
Composition
Process with high
variation
Prediction
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Process Composition: Skill Matrix
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Process Composition
Process Composition 1: Code Review 80% offline and 20% Walkthrough
Process Composition 2: Code Review 20% offline and 80% Walkthrough
With change in code review method, overall efforts and defects are impacted
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Execution and Analysis of Process Prediction Model
Selected : Process Composition 1: Code Review 80% offline and 20% Walkthrough
At Start of Project End of Requirement Phase: Not a sensitive process
End of Design Phase: 2nd most sensitive process End of Code Review: Sensitive Process
Planned Effort:
55 man hours
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Control Sensitive Processes
Control chart for sensitive process
shows “process is stable and
capable”
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1. Business goal must be validated and prioritize with the help of Business goal matrix plan
2. Involve practitioners, constitute various task forces such as
Metric Task Force (MTF): Having members with good skills on statistics and
business
Tailoring Approval Task Force (TATF): Good process knowledge
*Tailoring will have impact on productivity
3. Support from Management and buying from project stakeholders is critical
4. Select and prioritize X factors based on co-relationship
5. Must have minimum 15 data points to determine the data distribution, stability and
capability
Summary: Golden Rules for High Maturity Processes
Implementation…some
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Summary: Golden Rules for High Maturity Processes
Implementation…some
6. Implement Mistake proofing in project quality reporting. Data quality is very critical else
prediction will mislead you
7. Encourage sharing the implementation high maturity practices and lessons learnt by
each project on a periodic basis
8. Constitute process award to encourage of process implementation
9. Implement high maturity processes with evolutionary mode
10.Don’t implement all controllable factors in “one go”
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Discussion: Q & A
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Page 26 May 2010
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