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LEAN METRICS HOW TO PREDICT THE FUTURE Phil Ledgerwood PowerPoint is Terrible and I’m Sorry

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Estimating software projects, feature delivery dates, and even task completion times are notoriously difficult and unwieldy even for experienced teams. Guessing the future in terms of gut feeling or past experiences is a hit or miss practice that often leaves teams working overtime to meet unrealistic deadlines. Some simple metrics tracking borrowed from Lean software development can help. In this session, you'll learn very simple techniques that enable you to project timelines and determine probabilities that are based on a team's actual performance instead of a guess.

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Page 1: Lean Metrics

LEAN METRICSHOW TO PREDICT THE FUTURE

Phil LedgerwoodPowerPoint is Terrible and I’m Sorry

Page 2: Lean Metrics

PLATINUM SPONSORS

GOLD SPONSORS

SILVER SPONSORS

Page 3: Lean Metrics

Phil LedgerwoodApplication Developer

Netchemia, LLCwww.Netchemia.com

Twitter: @pledgerwoodLinkedIn: http://www.linkedin.com/in/philledgerwood

Page 4: Lean Metrics

The Estimation Process

Page 5: Lean Metrics

Let’s Play a Game

How long does it take you to go to the store to buy bananas? Traffic? Accident? Johnson County moms

talking in aisle? Person in front of you

pays with check and has no id?

Yes, we have no bananas?

Page 6: Lean Metrics

Your Estimates Suck Because… They are based on your view of your own

productivity. They assume all unknowns take zero

time. You have never written that software

before.

People are terrible estimators.

Page 7: Lean Metrics

Stopping the Foolishness

Here Come Metrics!

Page 8: Lean Metrics

Metrics are Awesome Because… They are based on your actual productivity. They factor in unknowns, divergent sizes, and

when Steve goes on vacation, but he didn’t tell anyone he was going on vacation until like two days before he did, and he’s gone for two weeks and it’s like, oh great, thanks a lot, Steve.

You can identify impediments visually.

They are eerily accurate because Math.

Page 9: Lean Metrics

Estimates vs. Metrics

Estimates Based on guessing Deviate over long

timespans False sense of

security Can easily be gamed Take a long time to

generate Up for debate Pretty much useless

Metrics Based on actuals Become more

accurate over long timespans

Cold, hard reality Can’t be gamed Take almost no time

to generate Not up for debate Ignore at your peril

Page 10: Lean Metrics

Scatterplot Diagram

The Control Chart

Page 11: Lean Metrics

Lead Time

Record the date something enters your workflow and the date something leaves it.

This amount of time is called “Lead Time”

End points need some agreed definition When an item is ready for work? When you start work on an item? When an item is ready for release? When an item is actually deployed?

Typical Lead Time: Ready for Work >> Deployed

Page 12: Lean Metrics

Control Chart Data

Dates (or day # of project) along the X axis

Number of days along Y axis Lead times are plotted on chart as items

are completed Median Lead Time Standard Deviations Percentages of Lead Time values (ex.

“75% of our lead times are 10 days or less”)

Page 13: Lean Metrics

What Can This Tell Us?

How fast we’re delivering

The likelihood of an item taking a certain amount of time

Predictability When events occur

that screw everything up

Trends in velocity

Page 14: Lean Metrics

Hey Let’s See One

Page 15: Lean Metrics

CFD (But you could probably figure that out)

Cumulative Flow Diagram

Page 16: Lean Metrics

Value Stream

How things get from “idea” to “delivered” For developers, it usually looks something like

this: Analysis (Acceptance Criteria) Design (Automated Tests) Code Test Deploy

“To Do,” “Doing,” and “Done” is ok for chore lists, but not so good for organization workflow management

Page 17: Lean Metrics

Cumulative Flow Data

Dates (or day # of project) along the X axis

Number of work items along Y axis Plot stacked series of # of items in each

“value stream state” from day to day

Page 18: Lean Metrics

What Can This Tell Us?

Horizontal distance: Lead Time Vertical distance: Work in Progress (WIP) Slope of Top Line: Average arrival rate Slope of Bottom Line: Average

completion rate

Page 19: Lean Metrics

LOL WUT?

Where are our bottlenecks? Where are things flowing smoothly? What is our predictability? Do we have too much WIP? Are we

starting more than we’re finishing?

Page 20: Lean Metrics

And I Care About This Why?

“Improvement comes by managing flow, not trying to get faster.” –Phil Ledgerwood, Just Now, 2013

Improve the flow, and the speed will come.

How do you improve flow? Limit WIP Give love to the area that needs it most Look at what is skewing the lines and

respond

Page 21: Lean Metrics

Hey Let’s See One

Page 22: Lean Metrics

What Metrics Don’t Tell You

Page 23: Lean Metrics

Metrics Tell You What, But Not Why

Charts and numbers are a catalyst for conversation, not a substitute for it

You cannot manage “by the numbers” Data is not a substitute for cultural

analysis, critical thinking, people’s stories, or just being in the trenches.

Data can show you your trends and provide fodder for discussions, but productivity and workflow is ultimately a people issue.

Page 24: Lean Metrics

Appendix A: The Retrospective Are you tired of retrospectives being free

form whine sessions? I am also tired of it. Your whining, I mean.

The metrics represent your current state. Ask the team what a better state would

look like. Ask the team for ideas on moving closer

to that state. Pick one, try it, and see if the metrics

change.

Page 25: Lean Metrics

I’m Phil

Phil Ledgerwood I work at Netchemia Blog: http://thecuttingledge.com/ Twitter (rare): @pledgerwood LinkedIn (often):

http://www.linkedin.com/in/philledgerwood

Ask me for a business card or something, because, man, I’ve got a ton of ‘em.