work -> data -> insight -> action...work -> data -> insight -> action “let’s...

Work -> Data -> Insight -> Action“Let’s Play Agile Coach!” with Agile Metrics Case Studies

Jim DamatoPMI-ACP, SA, CSP, CSM, PMP, ITILSolutions Architect, CA Technologiesjames.damato@ca.com

5/9/2016

2016 Agile Project and Portfolio SummitHarrisburg University

Rally Software is now part of CA Technologies

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Memes!

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Me (without gray hair)

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You?

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Why a presentation

on metrics?

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Why a presentation

on metrics?

Too many organizations don’t measure

anything

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Why do we measure?

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Why do we measure?

If you can’t measure it, you can’t

manage it

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What are metrics for?

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What are metrics for?

Finding your problems(aka Continuous Improvement)

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Virtue vs Sin

As a lever to drive someone else's

behavior

For feedback to improve your own

performance

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What’s the most

important measurement

in Agile?

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Working software is the

primary measure of progress.

What’s the most

important measurement

in Agile?

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9,192,631,770

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9,192,631,770

Don’t be fooled by the fallacy of

precision

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Let’s look at some

practice metrics

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Total Task Hours To Do

Total PointsAccepted

Ideal Task Hours Burndown

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Unfinished iteration planning

Accepted half of user stories planned

Accepted user stories late in iteration

Remaining work has peaked

Burndown is flat period in the middle

Consistent acceptance once started

Problem Solved?

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Accepted

Defined In-Progress

Completed

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Late acceptance

Incomplete acceptance

Drop in work on 7th day

Lots of Work in Progress

Work carried over from previous iteration

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Considerations

– You’re an Agile

coach

– Arrived today

– Know no history

– Have the metrics

– What do we see in

the data?

– What would we

recommend?

Agile

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Scenario 1

• Company 1

– Large engineering program (15 Teams)

– Adopted SAFe (Scaling Agile)

• Team 1 Data:

– Velocity - Iteration 2.3 thru 5.3

– Iteration 5.1, 5.2 & 5.3

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Scenario 1 - Team 1 - Velocity

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Scenario 1 - Team 1 - Velocity

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Scenario 1 - Team 1 - Iteration 5.1

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Scenario 1 - Team 1 - Iteration 5.2

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Scenario 1 - Team 1 - Iteration 5.3

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Scenario 1 - Observations

Team 1

• Inconsistent Velocity

•Acceptance work at iteration end

•Lots of WIP

•Not planning iteration well

•Adding scope during iteration

•Changing iteration length

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Scenario 2

• Same Company 1

– Large engineering program (15 Teams)

– Adopted SAFe (Scaling Agile)

• Team 2 Data:

– Velocity - Iteration 2.3 thru 5.3

– Iteration 5.1, 5.2 & 5.3

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Scenario 2 - Team 2 - Velocity

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Scenario 2 - Team 2 - Velocity

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Scenario 2 - Team 2 - Iteration 5.1

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Scenario 2 - Team 2 - Iteration 5.2

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Scenario 2 - Team 2 - Iteration 5.3

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Scenario 2 - Observations

Team 2

Good velocity, trending upward

Not entering defects

Early acceptance of work

Better control of WIP

Good planning of iteration

Consistent scope during iteration

Changing iteration length

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Scenario 3

• Same Company 1

– Large engineering program (15 Teams)

– Adopted SAFe (Scaling Agile)

• Team 1 vs 2 Data:

– Impact of changing timebox length

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When are these the same?

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/ hour / hour and a half

When are these the same?

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35 35

28

35

35

28

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Scenario 3 - Observations

Team 1 vs 2

DON’T CHANGE TIMEBOX!!!

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Scenario 4

• New Company!!!

– Single Agile Team

– Practicing Agile for 2 years

– Dedicated ScrumMaster

– Distributed team

– 2 wk sprints; 3 mo releases

• Single Team Data:

– Single Iteration

– Entire Release

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Scenario 4 - Iteration

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Scenario 4 - Iteration

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Scenario 4 - Release

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Scenario 4 - Observations

Iteration

- Task actuals increase

- Task burndown flat

- Late acceptance

- Work carrying over from

previous iterations

- Unfinished work moved to next

iteration

- Iterations are consistently over

committed

- Iterations velocity is consistent,

but obviously lower than what

the scope of the release is.

Release

- Shows the inconsistent nature

of acceptance and late

acceptance.

- Release burndown depicts that

work is getting done at the

same rate as it is being added.

- However, there is a gap

between remaining and scope

at the end of the release.

What would we recommend?

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Scenario 5 - Expert Level

• New-New Company!!!

– Single Agile Team

– Practicing Agile for 2 years

– Dedicated ScrumMaster

– 2 wk sprints; 3 mo releases

• Single Team Data:

– Single Iteration

– Entire Release

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Scenario 5 - Expert Level

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Scenario 5 - Performance Analytics

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Scenario 5

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Scenario 5 - Observations

What would we recommend?

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How do I get metrics like

that?

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The first key to

success?

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The first key to

success?

Estimation!

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The second key to

success?

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The second key to

success?

Daily updates of progress

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(I moustache you a question!)

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The End