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Agile Metrics Driven Management
 

Agile Metrics Driven Management

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Excel depicts how do we bring upon Accountability and Transparency using Metrics Driven Management as a tool for distributed teams....

Excel depicts how do we bring upon Accountability and Transparency using Metrics Driven Management as a tool for distributed teams.
These Metrics are more useful for the traditional Top management guys than the actual team.

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    Agile Metrics Driven Management Agile Metrics Driven Management Presentation Transcript

    • Collecting ReportingS No Metric Business Objective Metric Category Measures to be Collected Formula UOM Frequency Frequency To Measure How Captured as Number Of After Completion Backlogs / Long Work Comments From Demo - Backlogs Demo Comments From 1 Delivery Timeliness. Number Ongoing of the Iteration Iteration Items/Features (I.e [Enhancements will be Marked Uniquely] Product Owner Feature Completeness Product Debts) are waiting in the Queue Defects Number Of Defects Raised After Completion Number of Defects Raised By the Product 2 Injected / Improve Quality of Iteration Quality Test Team against the Iteration Build. in Bugzilla against the Number Ongoing of the Iteration Iteration Deliverables. Team Iteration Build. Improve Productivity, After Completion Capacity (Team Size) 3 Velocity Improve Cost Productivity Delivered Quantity (User Stories/ Taks) (Delivered/Capacity)*100 of the Iteration Effectiveness % On Going It contains three components viz Prevention cost – Training To meet Delivery, (Product/Technology/Process). Captured as Effort After Completion Cost Of 4 Quality and Cost of ROI Appraisal Cost * - Testing & Review. Expressed as % of Total % Ongoing of the Iteration Quality the Project for ROI Failure cost – Rework Effort
    • Improve Cost Effectiveness by continuously reducing the Overheads/Obstacles Examples: 1. Business Value Captured as Effort After Completion Cost Of Added or Reduce Effort Spent in Handling/Addressing/Solving5 Expressed as % of Total % Ongoing of the Iteration NonQuality Nonnegotiable Waste Overheads/Impediments the Overheads and Obstacles Effort like Setting Up System etc and 2. Minimizing Non- Value Added or pure waste like waiting long for Clarrifications etc The RTF metric RTF - shows, at every moment in the Readiness For a Number Of Features Running Number of Features/User Stories Passing6 project, how many Potentially Shippable Passing Tests / Total % Ongoing Daily Tested the Acceptance Tests For the Iteration features are passing Product Number Of Features *100 Features all their acceptance tests.
    • Mode of Notes Tools Consolidation 1. Rationale is to measure Commited Vs Delivered User Story Completeness.By Iteration / 2. New Enhancements (Demo Commenets) even Excel/WikiPhase though Captured as part of the Iteration Backlogs shall be Marked Uniquely. Using Bugzilla - By Defects that are Injected During the IterationBy Iteration / Asking Tester to Development is Key & Defects that are not RelatedPhase Use the Keyword Should be Captured separately at Product level. against the BuildAs On Date Change in Template& Of Burndown ChartConsolidated By Capturing VelocityIteration / PhaseConsolidated By ClarityIteration / Phase
    • Aggregate of time, money, and opportunity costConsolidated By losses resulting from doing things wrong. CONQ is ExcelIteration / Phase estimated by time taken to fix a Defect/Overheads/Obstacles by Total Effort. The desired software is broken down into named features which are part of what it means to deliverAs On Date the desired system.& For each named feature, there are one or more ExcelConsolidated By automated acceptance tests which, when theyIteration / Phase work, will show that the feature in question is implemented.
    • S No Metric Data Notes Acceptence Criteria Met. 1 Backlogs / Iteration 1 Change Request 2 Defects Injected / Iteration NA Product Testing has not Started 3 Velocity- By Story Points 44 Normalized Story Points Under Control 4 Cost Of Quality 24% [Acceptable Range: 20% to 28%] Closely Monitor 5 Cost Of NonQuality 13% [Acceptable Range: < 8%] 6 RTF - Running Tested Features 100% JUnit & Manual Integration Tests
    • Backlogs Per Iteration Iteration1 Iteration3 Iteration4Audi A6 1 2 2Falcon 1 0 0Mustang 2 3 1 BacklogsPerIteration 3.5 3 3 2.5 # of Backlogs 2 2 2 2 Audi A6 1.5 Falcon 1 1 1 1 Mustang 0.5 0 0 0 Iteration1 Iteration3 Iteration4
    • Defects Injected PerIteration Iteration1 Iteration3 Iteration4Audi A6 0 0 0Falcon 0 11 5Mustang 0 0 0 DefectsInjectedPerIteration 12 11 10 8 # of Defects Audi A6 6 5 Falcon 4 Mustang 2 0 0 0 0 0 0 0 0 Iteration1 Iteration3 Iteration4
    • CostOfQuality Iteration1 Iteration3 Iteration4Audi A6 24.5 13.9 20.3Falcon 24 24 35Mustang 22 24 23Total COQ 23.5 20.6 26.1 Cost Of Quality 40.0 35 35.0 30.0 26.1 24.5 24 23.5 24 24 23 Percentage 25.0 22 20.6 Audi A6 20.3 20.0 Falcon 13.9 15.0 Mustang 10.0 Total COQ 5.0 0.0 Iteration1 Iteration3 Iteration4
    • CostOfNonQuality Iteration1 Iteration3 Iteration4Audi A6 24.5 13.9 20.3 * Dummy Data marked in yellowFalcon 17 22.5 13.6Mustang 22 34 20.5Total CONQ 21.2 23.5 18.1 Cost Of NonQuality 40.0 34 35.0 30.0 24.5 23.5 Percentage 25.0 22 21.2 22.5 Audi A6 20.3 20.5 20.0 17 18.1 Falcon 13.9 13.6 15.0 Mustang 10.0 Total CONQ 5.0 0.0 Iteration1 Iteration3 Iteration4
    • RTF Iteration1 Iteration3 Iteration4Audi A6 100.0 100.0 100.0Falcon 100 90 100Mustang 100 100 100 RTF 102.0 100.0100 100 100.0 100 100.0100 100 100.0 98.0 96.0 Percentage 94.0 Audi A6 92.0 90 Falcon 90.0 Mustang 88.0 86.0 84.0 Iteration1 Iteration3 Iteration4