The future IS ours to see - actionable metrics for product development

2. Ready Doing Done
Seeing
problems
Embracing
variation
Actionable
measures
Scaling
problems

3. Ready Doing Done
Embracing
variation
Actionable
measures
Scaling
problems
Seeing
problems

4. Direction
vs.
Destination

5. Are we there yet?

6. Typical Product Roadmaps show a
single route

7. More useful Roadmaps show
options

8. Bungay – “Directed Opportunism”
Knowing our goal,
capabilities and constraints
we’re free to pursue options
that emerge in context

9. Annual by Product Management
Bi-annual by Product Management
Quarterly by Product Owner
(Bi-)monthly by Team
Daily by Team
The Planning “Onion”

10. The Planning “Telescope”

11. The Planning “Weakness”

12. Late learning
knowledge

13. We ask the wrong questions
• When will this be done?
• Can we offer enough on a given date?
• How much will this cost?
• How much will we invest to learn?
• Can we build this?

14. We ask the wrong questions
• When will this be done?
• Can we offer enough on a given date?
• How much will this cost?
• How much will we invest to learn?
• Can we build this?
• Can we provide value?

15. Decomposing work
Story
Epic
Project

16. Story-maps

17. Delivery patterns
60% of project
What we plan for
The S-curve
features
time

18. Delivery patterns
The S-curve
60% of project
What we plan for
What we should plan for
features
time

19. Ready Doing Done
Actionable
measures
Scaling
problems
Seeing
problems
Embracing
variation

20. Our unfortunate reality:
We live in a non-linear,
probabilistic world, yet…
continue to make projections using
deterministic, single-point
predictions guesses.

21. Point vs. range forecasts
• How long did it take you to get to work
today?
• Yesterday?
• Last week on this day?
• Tomorrow?
• Would you budget the average travel time
if you absolutely had to be present?

22. Variation

23. Variation
“Normal”
distribution

24. Thanks Alexei Zheglov! @az1
But we’re not normal!

25. Without
deviations
from the norm
progress isn’t
possible.
Frank Zappa

26. Ready Doing Done
Scaling
problems
Seeing
problems
Embracing
variation
Actionable
measures

27. “People who don't know how to
measure what they want, settle for
wanting what they can measure.”
Russel Ackoff

28. Roy Rappaport, Netflix

29. Understanding team capacity
• What data will help us make decisions?
~~~~~~
• How much can we do?
• How long does it take?
• Does it work?
• Is this pace sustainable?
• On what basis can we improve?

30. Actionable Metric #1: Throughput

31. Actionable Metric #2: Cycle Time

32. Actionable Metric #3: Escaped Defects

33. Actionable Metric #4: Team health

34. Ready Doing Done
Seeing
problems
Embracing
variation
Actionable
measures
Scaling
problems

35. Scaling up - Random Branch Sampling
Story
Epic
Project

36. RBS Algorithm:
1.Randomly select one of the epics
2.Count the number of stories in the sampled
epic
3.Use formula (1) to calculate one estimate of the
total number of stories in the project
4.Repeat steps 2-4 between 7 and 11 times
5.Use formula (2) to calculate the total number of
stories for the project
6.Divide by the team’s throughput

39. Ready Doing Done
Seeing
problems
Embracing
variation
Actionable
measures
Scaling
problems

40. Take-away ideas
• Have a clear directional goal
• Decompose your work (as you understand
it) and make it visible!
• Count completed stories
• Record variation of story time-in-process
• Adjust for escaped defect experience
• Use evidence to forecast a probable future

41. References
• David Nicolette, 2015, Software Development Metrics, Manning
• Daniel S. Vacanti, 2015, Actionable Agile Metrics for Predictability:
An Introduction, Leanpub
• Anderson, D.J., 2003,Agile Management for Software Engineering.
Prentice Hall.
• Ellen Gottesdiener + Mary Gorman, 2012, Discover to Deliver, EBG
Publishing
• Alexei Zheglov, 2014, lead-time-and-iterative-software-development,
http://connected-knowledge.com
• Dimitar Bakardzhiev, 2015, probabilistic-project-sizing,
http://www.infoq.com
• Alistair Cockburn, 2013, Disciplined+Learning,
http://alistair.cockburn.us

42. Andrew Annett
andrew.annett@d2l.com
andrew@leanintuit.com
@akannett
Questions?