When setting customer/stakeholder expectations, proper estimation is what ultimately pays the bills. So, why isn’t there more discussion around what makes a good estimation strategy when developers expected to know how to do it and do it well? Join Michael Godeck, a business analyst from a global pharmaceutical company, and learn a new approach— identifying uncertainty to improve estimation accuracy. Get the practical techniques and secrets to better software estimation.

1. MICHAEL GODECK | BUSINESS ANALYST | APPNOVATION | @AUGUST1914
Estimation as uncertainty reduction
What is this estimation thing, anyway?

2. MICHAEL GODECK | BUSINESS ANALYST | APPNOVATION | @AUGUST1914
Estimation as uncertainty reduction
What is this estimation thing, anyway?

3. Time and Materials
Estimation is like of a problem of topography…

4. One Bad Bid
…layers of tar and gravel, all hidden below the surface.

5. It’s not what you don’t know
that’ll hurt you,
it’s what you know
that ain’t so. – Mark Twain
Leveraging Uncertainty

6. Words get written
Words get twisted
Old meanings move in the drift of time
– Jethro Tull
What is this Estimation Thing?

7. “It all ends in tears anyway.”
– Jack Kerouac
Expert Opinion

8. …we substitute uncertainty
with assumptions on what
they might turn out to be.
Assumptions in discrete value estimates

9. Range Estimates
…a range estimate allows you to quantify
what you’re uncertain about.

10. You don’t have to commit to
anything that you’re
uncertain about.
Expressing uncertainty

11. A Concept of measurement
An iterative process of
reducing uncertainty about
something that matters.
– Douglas Hubbard

12. – Douglas Hubbard
A Concept of measurement
– Douglas Hubbard
A quantitatively expressed
reduction of uncertainty
based on observations.

13. …Shannon postulated that
information is the amount of
uncertainty reduction in a signal.
A Mathematical Theory of Communication

14. …the amount of uncertainty reduction in a signal
…uncertain values become first class citizens…

15. Information Entropy
…2 coins, four possible outcomes, 2 bits of entropy.

16. Information Entropy
What is that average time
spent in meetings?

17. Information Entropy
…how much does 5 random values reduce entropy?

18. Information Entropy
…a measurement doesn’t have to vanquish uncertainty.

19. Confidence Interval
…something less than perfect certainty.

20. Tool Calibration
…when we think of calibration,
usually we think about tools.

21. Tool Calibration
……Calibration is a procedure
where you measure against
a known quantity.

22. Bias influences expert
opinion resulting in
inconsistent estimates
Eliminate Bias

23. …Estimation calibration relies on arbitrary
questions as known quantities to identify
over and under confidence.
Measuring against a known quantity

24. Measurement Methods

25. 1. Nominal
2. Ordinal
3. Rational
4. Interval
A taxonomy of measurement scales
Stanley Smith Stevens

26. Rational Scales: Time and Money

27. Interval Scales: Story Points
The interval scale arbitrary
baseline is key to understanding
scrum story points.

28. Mohs Scale of Mineral Hardness

29. Are five one star movies as good
as one five star movie?
Ordinal Scales - 5 Star Rating

30. Neither fish nor fowl nor good red herring.
Conflating ordinal and rational scales

31. Ordinal Scales: The Cockburn Scale
A brontosaurs is any story that’s too big to go into work.

32. Ordinal Scales: OWASP Risk Scale
it definitely matters how much bigger
one Tyrannosaurus Rex is from another;

33. Nominal Scales

34. Nominal ScalesNominal Scales

35. …a starting point
Range Validation: The Absurdity Test

36. Range Validation: Imagine you are wrong

37. Range Validation: Mid-point Anchoring

38. Range Validation: Equivalent Bet

39. Range Validation: Arbitrage

40. “Information is the resolution of uncertainty”
The only estimates that have value are
those that inform decisions we face.
– Claud Shannon

41. This session developed the concept, object and methods of estimation,
with a focus on range estimation and confidence intervals.
Companion sessions that build on this foundation are:
• “Story Decomposition: right-size your stories
and the world is your oyster.”
• “Estimation for Release Planning:
understanding the impact of queue time on
when work will really be done.”
• “Monte Carlo Simulations for project
estimation: range estimating techniques for
complex scenarios such as project planning.”
Diving Deeper …

42. Story Decomposition
…right-sizing stories is half the battle.

43. “Predictability builds and holds trust,
a core Agile value, better than does
delivering more with less reliability.”
— David Anderson
Release Planning and Queue Time

44. Monte Carlo Simulations for Project Estimation