Agile Gurugram 30-31Aug 2024 | Smart Governance: Data driven insights and Risk Forecasting by Roma Jain
- 1. Patent # : 11941559
- 3. Assistant Vice President, Genpact with 26 years of experience across Development, Project/Program Governance, Delivery excellence using Global Distributed Team Model Agile Transformation Expert, with a proven track record in transforming teams towards agility, high performing with data driven adoption Holds patent (# 11941559) Agile Coach, SPC trainer, certified 100+ individuals on SAFe and trained 1000+ on Agile Holds certifications for Leading SAFe, CSM, CSPO, CSP, PMP, AZ900, AI900 Volunteer as Speaker/Trainer in conferences, NGOs, passionate about women empowerment Authored articles on Linked in, Genome Genpact training platform Extensive Exposure to International Work Culture Roma Jain Introduction
- 9. 1 7 6 5 4 3 2 EHI Quality Automation Scope Agility Schedule VOC Risks Execution Health Index (EHI) Parameters Quality Defect Removal Effectiveness(DRE) JIRA/VSTS Open defects Trend JIRA/VSTS Defect Density JIRA/VSTS Pre-Production Defect Escape Ratio(ER) Manual/JIRA Production Defect Escape Ratio(ER) Manual/JIRA Defect Bounce Rate(BR) JIRA/VSTS Security Status Checkmarx/Fortify Unit Test Code Coverage SonarQube/JaCoCo Product roadmap availability AHA Velocity Trend JIRA/VSTS Story Point Completion Ratio(SCR) JIRA/VSTS Alignment with Product roadmap Excel+JIRA Alignment to the Published Release plan JIRA/VSTS Schedule Scope Sanity test case Automation VSTS Regression test case Automation VSTS CI/CD Automation VSTS Agile Maturity Index Excel Automation Team Agility Net promoter score (NPS) Survey Customer Satisfaction (CSAT) Survey Sprint feedback Survey Release feedback Survey Resource risks Technology risks Environment risks VOC Risks
- 10. Arriving at EHI Parameters Teams share data (Jira/Sonarcube) Formula driven Individual metrics Weighted Composite Score EHI Prj A Engineering Metrics Weightage LCL UCL Score Scale 1-3 Quality Defect Removal Effectiveness(DRE) 5% 70% 90% 105.88% 3 Open defects Trend 20% 33.45 1 Defect Density 20% 50% 20% 4.60% 1 Pre-Production Defect Escape Ratio(ER) 5% 20% 10% Production Defect Escape Ratio(ER) 15% 10% 3% 7.36% 2 Defect Bounce Rate(BR) 15% 15% 5% 20.86% 1 Security Status 5% 0.14% 3 Unit Test Code Coverage 15% 70% 85% 75.00% 2 Overall Quality Indicator 1.5 Quality Scope Schedule Automation Agility Weightage of metrics 25% 25% 25% 15% 10%
- 11. EHI Parameters Prj A Prj B Prj C Prj D Prj E Engineering Metrics Score Scale 1-3 Score Scale 1-3 Score Scale 1-3 Score Scale 1-3 Score Scale 1-3 Quality Defect Removal Effectiveness(DRE) 124.9% 3 49.8% 1 70.97% 2 61.4% 1 110.2% 3 Open defects Trend 364 1 206 1 5.5 3 9.1 1 105.55 1 Defect Density 18.2% 1 88.8% 1 10.5% 1 NA 1 Pre-Production Defect Escape Ratio(ER) 36.7% 1 23.8% 1 0.00% 3 13.7% 2 0.0% 3 Production Defect Escape Ratio(ER) 0.4% 3 1.0% 1 NA NA NA Defect Bounce Rate(BR) 34.2% 1 17.3% 1 0.00% 3 2.5% 3 23.4% 1 Security Status 0.6% 1 0.5% 3 NA 1 3.1% 1 NA 1 Unit Test Code Coverage 31.0% 1 NA 50.00% 1 10.0% 1 Overall Quality Indicator 1.4 1.1 2.3 1.41 1.3 Scope Product roadmap availability 100.0% 3 100.0% 3 33.33% 1 0.0% 0 100.0% 3 Velocity Trend 101.9% 3 96.2% 3 89.37% 2 115.9% 3 79.3% 2 Story Point Completion Ratio(SCR) 13.6% 1 82.1% 2 38.30% 1 75.5% 2 79.2% 2 Alignment with Product roadmap 47.9% 1 90.00% 3 50.0% 1 61.5% 1 Overutilization of Capacity for Technical debt Overutilization of Capacity for Customer requests/defects Scope Alignment 2.2 2.6 1.70 1.60 2.2
- 13. EHI Parameters (Case Study 1) 0.0 0.0 1.7 2.2 0.0 2.2 1.3 2.6 2.2 0 0.5 1 1.5 2 2.5 3 Prj A Prj B Prj C Prj D Prj E Prj F Prj G Prj H Prj I Automation Persona : Leadership
- 14. Month on Month Comparison(Feb, Mar, Apr 2024) EHI < =2.0 1.4 1.6 2.2 1.5 3.0 0 0.5 1 1.5 2 2.5 3 3.5 Quality Scope Automation Agility Schedule Prj B 1.4 2.2 0.0 2.0 1.0 0 0.5 1 1.5 2 2.5 3 Quality Scope Automation Agility Schedule Prj A UCL LCL Last month (n-2) Last month Current month 0 0.5 1 1.5 2 2.5 3 3.5 Quality Scope Automation Agility Schedule Prj D 0 0.5 1 1.5 2 2.5 3 3.5 Quality Scope Automation Agility Schedule Prj C Personas : Scrum Master/ QA Lead/ Engineering Mgr
- 15. More Case Studies ERP Defects Apr 5 - Apr 11 Apr 12 - Apr 18 Apr 19 - Apr 25 Apr 26 May 1 Total open Defects 15 15 16 14 New Defects opened 17 15 15 4 Closed 2 21 14 9 Reopened Defects 10 7 10 9 Executed Test Scripts 55% 60% 64% 67% Ageing Team1 Team2 Customer IT Grand Total <1 Week 1 1 3 5 > 1 Week 1 3 4 > 5 Weeks 1 1 Grand Total 2 1 7 10 1. Customer hesitance resolved through data transparency. 2. Identified IT issues led to partial payment acceptance, full payment later. Case Study 2A Case Study 2B Case Study 2C Case Study 3 Customer Operations
- 16. Traversing the road through AI Data Collection Automated Extraction: Seamlessly gather data from Jira and other tools Natural Language Processing: Convert comments and logs into actionable insights Decision Making Sentiment Analysis: Monitor team morale and stakeholder feedback Anomaly Detection: Identify unusual patterns to pre-emptively address risks Predictive Analysis Trend Forecasting: Use historical data to predict future project outcomes Risk Assessment: Identify and mitigate potential issues before they escalate
- 18. Thank You Patent # : 11941559