OBJECTIVE VISIONARY OF CMMI HIGH MATURITY PRACTICES WITH AGILE & DEVOPS
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1 OBJECTIVE VISIONARY OF CMMI HIGH MATURITY PRACTICES WITH AGILE & DEVOPS NAME: Wael Philops TITLE: Manager QA & Risk ORGANIZATION: ITS
2 AGENDA Who are we? ITS Development methodology Transformation To Agile / DevOps Maintaining L4 and L5 Requirements with Agile / DevOps Pitfalls and Benefits
3 WHO ARE WE? I ITS has been a leading integrated information technology and software services provider, offering robust solutions to customers. We have a long proven and successful track record in implementing cutting-edge IT solutions across the region. ITS portfolio offers world class solutions and services in a wide range of industry segments - including financial services, education, enterprise, energy, communication and government professionals 350+ client base across 24 nations Regional offices in 7 countries Global reach through channels
4 WHO ARE WE? II Turnkey Systems Financial Services We are developing Financial services business applications that will enable our customers to gain business agility, accelerate innovation and achieve targeted business aspiration. Services Solutions We are enhancing and expanding our services capabilities to target across industries. Our services portfolio includes managed services, outsource IT and support services.
5 WHO ARE WE? III ETHIX financial solution is the result of over 30 years of experience in the banking sector combined with services solutions. Targeted Segments It is a state-of-the-art comprehensive, integrated, modular core banking solutions that can be flexibly deployed to support technology and business objectives. ISLAMIC BANKING RETAIL/CORPORATE CONVENTIONAL BANKING RETAIL/CORPORATE SAVING & LOAN INSTITUTION The solutions empower institutions to achieve operational excellence, cost leadership, growth trajectory. MICRO FINANCE INSTITUTION INVESTMENT INSTITUTION LEASING INSTITUTION Banking development center certified as CMMI level 5. Our comprehensive portfolio demonstrates our know-how In developing, consulting, implementing and maintaining financial services solutions.
6 THE STORY
7 ITS DEVELOPMENT METHODOLOGY BEFORE AGILE (THE PAIN) Incremental Waterfall High Schedule Variance High Rework Efforts High Effort Variance High Cost Variance Root Causes Lack of understanding the business requirements Always under Estimation, in spite FP was implemented Lack of identification of integration requirements Lack of managing the changes Lack of measuring the productivity
8 BASELINE BEFORE AGILE I
9 BASELINE BEFORE AGILE II
10 TRANSFORMATION TO AGILE High Risks Losing the continuity of baselines Estimate the new projects Set the company objectives using historical baseline Do not know if you are doing good or bad (before and after ) Data integrity Agile is rely on people more than process Lack of tools to EtoE tracking of the requirements Customer Experience with Agile Resistance to change the scope Fixed cost against cost plus
11 CONTAINMENT PLAN Avoid big bang strategy Use the Agile principles to mange the transformation of the company Slicing the requirements Retrospective / Risk base transformation process Continues feedback to top management ( almost every month) Iterative implementation Build data governance team to keep L4 practices up and run (Performance Team) Continues Calibration to metric schemes and models by the DGT Build the agile coach capabilities to lead the transformation program Teach our customer and include selected customers in the transformation program Adopt the proper tools to govern the agile process (DevOps)
12 ITS AGILE / DEVOPS MODEL MAIN CHARACTERISTICS Adopt DevOps concepts Continues Integration Continues Delivery Continues Deployment Adopt Flavor of Agile User Story and slicing Build Collaborative Environment Iterative Build Customer Feedback Time Boxed Retrospective / CAR and Risk
13 DEVOPS MAIN CHARACTERISTICS Continuous Integration Continuous Delivery Continuous Deployment Requirement Management Configuration Management & Build Testing Automation Release and Deployment Operate, Scale and Collaborate Implement the requirement traceability plan using identified tools Upload / create project s specific documents in collaboration tools Agile scrum based activities to be in sync with requirement management tool Develop integrated source code repository Set-up artifacts management server Import code as generated via App Mod to code repository Conduct training program on DevOps framework Version control of all test artifacts. 30% automation of functional and nonfunctional test suites using identified tools 50% deployment automation in lower environments Auto roll back of minor releases Deployment in lower environment within mins of down time. Monitoring of lower environment and critical applications 30% automation of penetration testing. notification post daily health check of lower environment
14 CMMI / AGILE / DEVOPS FRAMEWORK
15 HIGH RISK IN AGILE LACK OF DATA INTEGRITY Affect setting realistic company objectives Affect the project planning and estimation process Affect the quality of delivery and ultimate product quality Affect customer satisfaction index Affect the prediction models Etc It creates a chaos in the organization, it is like a cancer slowly spread out in the organization body.
16 REMEDIATION Build a strong data governance team, best people and best training program Adopt a powerful tool for DevOps that allows customization Develop a data integrity model and to be integrated with DevOps tools Implement poka-yoke concept Inject test cases on the raw data level Continues calibration and feedback to project manager for corrective actions
17 DATA INTEGRITY TEST CASES I Source of data is the backlog:- Story Status vs. % Work Complete, if Story Status is "Delivered" while the Work% is NOT 100% Effort NOT Mapped, check if there is Actual effort in schedule could not be mapped to any of the process activities. Story Status vs. Act. Delivery Date., If the Status is "Delivered" while there in NO Actual Delivery Date in the backlog If the Status is "In Progress" or "Partially Delivered" while there is Actual Delivery Date in the scope sheet. If Actual Delivery Date is in future.
18 DATA INTEGRITY TEST CASES II Source of data is schedule (EPM) :- Baseline Finish Vs. Baseline Start, if Baseline Start/Finish date in schedule is Blank or Baseline Finish date <= Baseline Start date. Actual Finish Vs. Actual Start If Actual Start date in schedule is Blank. If Work Completed 100%., Failed, if Actual Finish date in schedule is Blank or Actual Finish date <= Actual Start date. Actual Start/Finish Vs. Future FALSE if Actual Start date in schedule is in future. FALSE if Actual Finish date in schedule is in future.
19 DATA INTEGRITY TEST CASES III Source of data is defect & schedule :- Design Rework Vs. Des. Rev. Defects, FALSE, if there is Design Rework effort without Design Review defects. Coding Rework Vs. Code Rev. Defects, FALSE, if there is Coding Rework effort without Code Review defects or UT defects. Fixing/Retest Vs. FT Defects, FALSE, if there is Bug Fixing effort or Retest effort without Testing Defects. Unspecified Phase Injected, FALSE, if number of missed out Phase Injected of Closed/Resolved defects > 0 AND there is NO Actual Finish Date. FALSE, if number of missed out Phase Injected is greater than Zero AND there is Actual Finish Date.
20 TREND ANALYSIS OF DATA INTEGRITY
21 RESULTS OF DATA INTEGRITY Create robust models Continues improvement Prediction of the impact Real time corrective actions Prediction of the effect Etc..
22 L4 IMPLEMENTATION MODELING I EV = Rework Func. Test effort dist. R-Sq = 88.65% R-Sq(adj) = 86.62% REW= Design Preparation Efforts Dist Dist. Defects Detected Coding (DDC) R-Sq = 91.59% R-Sq(adj) = 88.25% Rework FT DDC HLD
23 L4 IMPLEMENTATION MODELING II Setting Sub-process goals: (what-if analysis) Probability after increasing mean of DDC by 30% is 74% Probability after increasing mean DDC 50% and decrease STDDEV 30% is 87% New goals for DDC are: Mean is = 40% STDEV is = 10% USL is = Mean + STDEV LSL is = Mean - STDEV DDC New sub process Goals Goal USL LSL 40% 50% 30% - DDC mean value now needs to be increased from 26% to 40% - Therefore; we do CAR to achieve this
24 L4 IMPLEMENTATION MODELING III
25 MAPPING L4 & L5 PRACTICES TO AGILE CMMI Generation of PPMs Implementation of PPMs Generation of PPBs Implementation of PPBs QPM Agile Outside Agile team govern by the QA Data Governance team Retrospective session after each iteration Corrective actions to be implemented on the next iteration Outside Agile team govern by the QA Data Governance team During the Estimation process, Agile team uses the baselines. During the projects execution, Agile team uses the process models to control and predict the outcomes and take corrective actions to align the plan and enhance the quality.
26 BENEFITS
27 POST IMPLEMENTATION BASELINE I Mean STDEV UCL LCL Goal USL LSL Mean STDEV UCL LCL Goal USL LSL % Change in mean % Change in variation % 20% 87% 0% 20% 30% 10% % 17% 69% 0% 20% 30% 10% -28% -16% % 17% 69% 0% 20% 30% 10% % 8% 35% 0% 13% 21% 6% -42% -52% 26% 20% 11% 8% -58% -60%
28 POST IMPLEMENTATION BASELINE II Mean STDEV UCL LCL Goal USL LSL Mean STDEV UCL LCL Goal USL LSL % Change in mean % Change in variation % 32% 50% -68% -10% 10% 20% % 34% 96% -147% -10% 10% 20% -140% 8% % 34% 50% -68% -10% 10% 20% % 20% 96% -147% -10% 10% 20% 14% -43% from first to last 20% 32% -9% 20% -146% -38%
29 POST IMPLEMENTATION BASELINE FINANCIAL IMPACT - III Year No. of Projects Total Actual PDs Contracted Total Resources Avg. Sellable Days (per person) Utilization (216 PDs) , % , % , % , % %
30 CUSTOMER SATISFACTION INDEX CSS Index Trend Analysis
31 PITFALLS Big bang implementation Not considering risks like Technology risks Culture change risks Data and baseline risks Not adopting the right tool (DevOps) from the beginning Dropping the schedule (EPM) Dropping the project manager role Using waterfall concept to plan for agile transformation Lack of transparency to all non-agile teams Not building the coaching layer in the organization
32 THANK YOU Contacts LinkedIn
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