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Kanban Show Case
AI & Store PODs
Shadan Ashfaie- August 2015
PURPOSE
Share AI and Store PODs experience
about Scrum practice and transition to
Kanban.
OUTCOMES
By the end of this meeting:
• We will understand challenges of scrum practice
for AI pod and how Kanban practice might solve
some of them, so we can share our experience to
support other teams.
• Opportunity for you to ask question about
Kanban.
• Opportunity to have a discussion with your peers
about interests and challenges.
What's in it for me?
• You learn how Kanban process solves some of
existing scrum practice challenges for infra teams.
• You will see what steps we took to move from
Scrum to Kanban
• You will see our Kanban board design and how it
can help to support Agile values at POD level.
• Kanban process might not be for all PODs.
Agenda
• Scrum process challenges for AI POD/ Store
POD
• Kanban Vs Scrum in a nutshell
• Kanban in a nutshell
• Kanban Principals
• Kanban Board( Visualizing Workflow)
• Kanban Metrics
• Your Feed Back through Idea Board
Scrum process challenges for AI POD
AI/ Seamless PODs Structure:
• 10 engineers as core team
• 5 engineers as helpers
• 3 technical managers
• Consist of two pods ( AI and Oracle Retail)
• Supporting 15 to 20 projects in each iteration
Scrum process challenges for AI POD
We never fully committed scrum:
• Priority changes impacted the sprint plan
• We never finished what we planned for.
• We never had an iteration planning that we
could commit
• We never had a defined sprint backlog (
stories coming to sprint everyday)
Scrum process challenges for AI POD
• We didn’t have the ability to plan in release
level because we didn’t know all application
requests and they were not prioritized before
they get to POD.
• We had more user stories added during sprint
than when the sprint started.
Scrum process challenges for AI POD
• Metrics in Sprint Reports were not effective:
– Mainly based on velocity of entire POD capacity
but in reality each engineering practice has it is
own capacity and velocity.
– User story sizing was not effective( place holders
with 10 points staying in progress for two weeks)
so measuring velocity and cycle time was not
based on realistic data.
Kanban vs Scrum in a Nutshell
Scrum / Iterative
Kanban vs Scrum in a Nutshell
Kanban vs Scrum in a Nutshell
• Responsiveness to Change: When priorities
change very frequently, Kanban is ideal (15 to
20 projects needs support from AI POD in
each sprint. Their priorities changes and there
are last minute requests. Commitment to two
weeks delivery is not feasible).
• Removing 2 weeks commitment for work.
Kanban vs Scrum in a Nutshell
• Removing Sprint backlog and just have a
general backlog
• Removing sprint planning meeting. Story
huddles and backlog grooming will continue
• Retrospective meetings will continue
• Scrum measure velocity as main metric for
improvement opportunities, Kanban measure
cycle time as main metric for improvement
opportunities
Kanban in a Nutshell
Kanban Principals:
– Visualize the workflow
– Limit Work-in-Progress (WIP)
– Manage Flow( Limited to Jira GAP workflow)
– Make Policies Explicit( Working Agreement)
– Implement Feedback Loops
– Improve Collaboratively, Evolve Experimentally
Kanban in a Nutshell
Kanban board( Visualizing workflow)
– Identify Sources of Work
– Identify Types of Work ( Class Of Services)
– Identify Outputs
– Map your Workflow
– Design your Board
– Create Policies for each column on the board
– AI Pod Board:
https://jira.gid.gap.com/secure/RapidBoard.jspa?rapidView=4230
– Store Pod Board:
https://jira.gid.gap.com/secure/RapidBoard.jspa?rapidView=3910
Kanban in a Nutshell
Kanban Metrics:
– Cycle Time – The time between starting on the
work and when item is ready for delivery.
• Cycle Time Depends on the Rate of the Bottleneck.
• The rate of the bottleneck is the rate of the entire
system.
– Lead Time – The time it takes to complete a
particular unit of work. The total time the client is
waiting for an item to be delivered.
Feedback
Idea Board:
http://www.ideaboardz.com/for/Kanban%20Show%
20Case/2015099

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Kanban show case

  • 1. Kanban Show Case AI & Store PODs Shadan Ashfaie- August 2015
  • 2. PURPOSE Share AI and Store PODs experience about Scrum practice and transition to Kanban.
  • 3. OUTCOMES By the end of this meeting: • We will understand challenges of scrum practice for AI pod and how Kanban practice might solve some of them, so we can share our experience to support other teams. • Opportunity for you to ask question about Kanban. • Opportunity to have a discussion with your peers about interests and challenges.
  • 4. What's in it for me? • You learn how Kanban process solves some of existing scrum practice challenges for infra teams. • You will see what steps we took to move from Scrum to Kanban • You will see our Kanban board design and how it can help to support Agile values at POD level. • Kanban process might not be for all PODs.
  • 5. Agenda • Scrum process challenges for AI POD/ Store POD • Kanban Vs Scrum in a nutshell • Kanban in a nutshell • Kanban Principals • Kanban Board( Visualizing Workflow) • Kanban Metrics • Your Feed Back through Idea Board
  • 6. Scrum process challenges for AI POD AI/ Seamless PODs Structure: • 10 engineers as core team • 5 engineers as helpers • 3 technical managers • Consist of two pods ( AI and Oracle Retail) • Supporting 15 to 20 projects in each iteration
  • 7. Scrum process challenges for AI POD We never fully committed scrum: • Priority changes impacted the sprint plan • We never finished what we planned for. • We never had an iteration planning that we could commit • We never had a defined sprint backlog ( stories coming to sprint everyday)
  • 8. Scrum process challenges for AI POD • We didn’t have the ability to plan in release level because we didn’t know all application requests and they were not prioritized before they get to POD. • We had more user stories added during sprint than when the sprint started.
  • 9. Scrum process challenges for AI POD • Metrics in Sprint Reports were not effective: – Mainly based on velocity of entire POD capacity but in reality each engineering practice has it is own capacity and velocity. – User story sizing was not effective( place holders with 10 points staying in progress for two weeks) so measuring velocity and cycle time was not based on realistic data.
  • 10. Kanban vs Scrum in a Nutshell Scrum / Iterative
  • 11. Kanban vs Scrum in a Nutshell
  • 12. Kanban vs Scrum in a Nutshell • Responsiveness to Change: When priorities change very frequently, Kanban is ideal (15 to 20 projects needs support from AI POD in each sprint. Their priorities changes and there are last minute requests. Commitment to two weeks delivery is not feasible). • Removing 2 weeks commitment for work.
  • 13. Kanban vs Scrum in a Nutshell • Removing Sprint backlog and just have a general backlog • Removing sprint planning meeting. Story huddles and backlog grooming will continue • Retrospective meetings will continue • Scrum measure velocity as main metric for improvement opportunities, Kanban measure cycle time as main metric for improvement opportunities
  • 14. Kanban in a Nutshell Kanban Principals: – Visualize the workflow – Limit Work-in-Progress (WIP) – Manage Flow( Limited to Jira GAP workflow) – Make Policies Explicit( Working Agreement) – Implement Feedback Loops – Improve Collaboratively, Evolve Experimentally
  • 15. Kanban in a Nutshell Kanban board( Visualizing workflow) – Identify Sources of Work – Identify Types of Work ( Class Of Services) – Identify Outputs – Map your Workflow – Design your Board – Create Policies for each column on the board – AI Pod Board: https://jira.gid.gap.com/secure/RapidBoard.jspa?rapidView=4230 – Store Pod Board: https://jira.gid.gap.com/secure/RapidBoard.jspa?rapidView=3910
  • 16. Kanban in a Nutshell Kanban Metrics: – Cycle Time – The time between starting on the work and when item is ready for delivery. • Cycle Time Depends on the Rate of the Bottleneck. • The rate of the bottleneck is the rate of the entire system. – Lead Time – The time it takes to complete a particular unit of work. The total time the client is waiting for an item to be delivered.