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CMMI High Maturity Best Practices HMBP 2010: Implementation of High Maturity Model In an Organization by Rajesh TV and Amit Chauhan
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CMMI High Maturity Best Practices HMBP 2010: Implementation of High Maturity Model In an Organization by Rajesh TV and Amit Chauhan

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mplementation 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

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CMMI High Maturity Best Practices HMBP 2010: Implementation of High Maturity Model In an Organization by Rajesh TV and Amit Chauhan CMMI High Maturity Best Practices HMBP 2010: Implementation of High Maturity Model In an Organization by Rajesh TV and Amit Chauhan Presentation Transcript

  • Implementation of High Maturity Model In an Organization -Rajesh TV Amit Chauhan (Siemens) SDE For public use Page 1 May 2010
  • Implementation of High Maturity Model in an Organization Amit Chauhan Sr. Consultant Rajesh TV Chief Manager SDE © SIS India - All rights reserved.
  • 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 SDE For public use Page 3 May 2010
  • To Start with….Moving from Hygiene to High Maturity Processes SDE For public use Page 4 May 2010
  • 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” SDE For public use Page 5 May 2010
  • High Maturity – Quick View Business Goals Process Improvement Objectives (Y) Opportunity Process Process Composition Selection Controllabl Prediction e Factors Model (X) Capability Goals for X Baseline for X SDE Project Level Organization Level For public use Page 6 May 2010
  • 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/ Customer Issues Voice of Customer Critical to Business Reduce cycle time to High Cycle Time On time Delivery High Cost due to late Defect Free deliver Quality delivery economical product product with in Budget Variation in Effort Productivity High Cost due to < Improvement agreed efforts High Defects with Reduce Defect High Defect SDE Delivery For public use Page 7 May 2010
  • Business Goal Matrix: Flow Down Business goal must be validated and prioritize with the help of Business goal matrix plan SDE For public use Page 8 May 2010
  • Organization Procedure for Process and Quality Performance  Define Measures for common understanding and to avoid any ambiguity Scope of Controllable X Process Objective Processes Definition Measurement Factors Schedule Difference in between planned Schedule Variance should At each Actual Efforts Estimation and date of completion with actual not be greater than 5% Milestone Skill Level Monitoring date of completion Actual Efforts Improve Productivity by Ratio of actual efforts and At each Skill Level Engineering 5% every quarter actual size Milestone Review Methods Review Cycles Actual Efforts Review, Testing Less than 1 defects (review + Delivered Defect Density At each Skill Level Estimation and Testing defects ) per actual unit <1defect/per unit Milestone Review Methods Monitoring size 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 SDE For public use Page 9 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 SDE For public use Page 10 May 2010
  • 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 Data Stratification  Estimation technique Feature Point, Use Case Estimation Estimation Technique Life Cycle Development, Maintenance Technology Microsoft, Java SDE For public use Page 11 May 2010
  • Base Data: Test for Stability Check for Data stability using control charts and Box Plot SDE For public use Page 12 May 2010
  • 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 SDE For public use Page 13 May 2010
  • Establish Project Objectives Customer Specific Objectives Organization Objective Project Specific Goals Part of Project Quality Plan  Project specific goals are defined as per organization as well as customer specific objectives  Sensitive processes are identified and controlled SDE For public use Page 14 May 2010
  • 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. SDE For public use Data quality is very critical else prediction will mislead you Page 15 May 2010
  • High Maturity Process Evaluation  High Maturity Processes are evolved and not revolutionized Added “SKILL” as process composition Identified and updated more factors for process Maturity composition Trade off between Defects and Efforts Updated PPM with process composition using “Efforts” Prediction Model for Productivity SDE For public use Time Page 16 May 2010
  • 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 Matrix Plot of CRY, Developer Co, Design Rewor, Coding Rewor, ... CRY 7 6 Developer Competency 5 20.00% 10.00% Design Rework Effort 0.00% 8.00% 4.00% Coding Rework Effort 0.00% 20.00% 10.00% Design Review Effort 0.00% 30.00% 15.00% Coding Review Effort 0.00% 5 10 155 6 70.00% 10.00% 20.00% 0.00% 4.00% 8.00% 0.00% 10.00% 20.00% SDE Select and prioritize X factors based on co-relationship For public use Page 17 May 2010
  • Compose Defined Processes  Project defined process is based on historical stability and capability of data  Project defined Process consists of Process with high  Selecting sub processes variation  Adjusting / trade off level and depth of intensity of application of the sub- processes or resources Process Composition Prediction SDE For public use Page 18 May 2010
  • Process Composition: Skill Matrix SDE For public use Page 19 May 2010
  • 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 SDE For public use Page 20 May 2010
  • Execution and Analysis of Process Prediction Model Selected : Process Composition 1: Code Review 80% offline and 20% Walkthrough Planned Effort: 55 man hours At Start of Project End of Requirement Phase: Not a sensitive process End of Design Phase: 2nd most sensitive process SDE End of Code Review: Sensitive Process use For public Page 21 May 2010
  • Control Sensitive Processes Control chart for sensitive process shows “process is stable and capable” SDE For public use Page 22 May 2010
  • Summary: Golden Rules for High Maturity Processes Implementation…some 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 SDE For public use Page 23 May 2010
  • 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” SDE For public use Page 24 May 2010
  • Discussion: Q & A SDE For public use Page 25 May 2010
  • Click here for: High Maturity best practices HMBP 2010 Presentations organized by QAI Click here SDE For public use Page 26 May 2010