Achieving Predictability with Agile - Doing Scrum in a complex multi-disciplinary environment - Elbit Case study By Gil Ari @ AgileIL12 http://agilesparks.com/ElbitCaseStudy-GilAri

1. Achieving Predictability with Agile
a case study
Agile Israel 2012
27-June-2012
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2. What made us start?
Projects milestones are not meet
Budget overrun
Integration Hell
Product quality
Management awareness
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3. The Project – A/C Upgrade
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4. Before…
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5. …and after
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6. The Project - Complexity
System of Systems
Lots of interfaces
Multidisciplinary:
Pilots
System
Software
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7. SCRUM Team - Concepts
Working Software
Predictability
Definition Of Done (DoD) for each US
Done is Done – no bugs
Team Commitment – as many US per PO priority
Early Feedback
Measure the team, not the individual developer
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8. SCRUM Team Measurements
Comitted Done
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9. End to End Flow
Discovery Team
Manages the
end-to-end flow
(using Kanban)
Scrum Team
Manages the
development per
iteration
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10. Kanban – managing the end to end flow
Visualize the workflow Pioneered by
Limit WIP (work in progress) David
Anderson
Measure & optimize flow in 2004
Explicit policies (definition of Done, WIP limits, etc)
Backlog Dev UAT Deploy Done
5 3 2 3
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FLOW 12
Avg lead time: days
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11. End to End Flow – The States
Backlog New
Discovery Scrum
Analysis Selected Ready Story
Elaborating Elaborating
Development
In Process Done
(SCRUM)
Acceptance Free Run Mini FQT Formal FQT Closed
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12. Discovery Team – Practical Notes
Who is in the team
Technical Manager
Operational
System
Software
Discovery Forum
Once a week
Review WIP
Visibility tools
SCRUM Team – board & notes – Tasks
Discovery – TFS – User Stories
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13. Discovery Team – Continuous Flow
Analysis Acceptance
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14. Discovery Team - Tools
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15. Discovery Team – Story Points
Rough estimate (range) Min Max Story Tshirt
[days] [days] Point Size
Estimates may be wrong XS
Team Velocity is per Backlog S
estimates M
Team estimates (Scrum L
XL
planning) are not related to
XXL
Backlog estimates (Backlog
XXXL
preparation)
Velocity : Done is Done
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16. Commitment
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17. Team Velocity & Predictability
Remaining Future
Iterations:
Remaining Story Points:
Calculated Values Normal Worst Case
Current Velocity:
Estimates
Remaining Capacity:
Outstanding Story
Points:
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18. Cumulative Flow Diagram
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19. Our Conclusions
Manage the entire process
Manage the flow
Before Iteration – Planning preparations
During Iteration – Early feedback; Free run tests
After Iteration –
Fix bugs ASAP
Mini FQTs (avoid Integration hell)
Multi disciplinary discovery team
Work as a team
Focus on ready stories
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20. Our Conclusions
Predictability
Team Velocity as a parameter
Data Analysis
How to increase Team Velocity
Always Retrospect
Ready Story
Remove impediments
Team size – Diminishing Marginal Utility
Trust the Team
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21. Questions?
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22. The End
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