What do poker, Greek oracles, an Italian mathematician from the Middle Ages, and the path of hurricanes have in common? Given the title of this presentation, chances are it has something to do with estimation, and you’ll have to attend this session to get the full connection. Kent McDonald explores the challenges and realities of trying to estimate software-related knowledge work—analysis, testing, development, and the entire project effort. A major challenge is that there are no guaranteed ways to arrive at perfectly accurate estimates, which not surprisingly is why they are called estimates. Kent introduces and gives you a chance to practice quick and practical estimating techniques that will work in different situations—guesstimating, break it down and add it up, and planning poker. Kent has found that these “lite” estimation techniques are almost always just as informative as the ones you just spent six weeks formulating.

1. Estimating in Software
Development:
No Silver Bullets Allowed
Kent J. McDonald
@beyondreqs

2. Disclaimer

3. A Familiar Situation?
Issues with Estimating
Estimating Techniques

4. Don’t worry, we’ll get to these…

5. Has this ever happened to you?
Ok, great. The Sales
How long will it
VP promised an I just found out
take to build the
estimate to the about it this
commission
CEO next Monday. morning, so I’ll need
system?
It better be right. to do some analysis .

6. Issues with Estimating
Initial Uncertainty Accuracy/Effort Tradeoff
False Precision Differing Skill Levels

7. Initial Uncertainty

8. Cone of Uncertainty

9. Cone of Uncertainty a Practical Use

10. Hurricane Sandy – Actual Path

11. Accuracy/Effort
Tradeoff

12. Point of Diminishing Returns

13. False Precision

14. How precise do you have to be?
How long, and Approximately 374
how much? days and
$2,548,931.27.

15. Differing
skill levels

16. People finish tasks at different speeds

17. Estimating Techniques
Guestimate Break it down, add it up
Relative Estimating

18. Guestimate

19. Aka “Gut Feel” or “Ball Park”
How long, and
how much? About a year and
$2.5 million.

20. Comparison to Past Projects
$1,000 $100K $10M
??
$1M

21. Your turn…
Want to create an online application for Mortgage Insurance
How long to deliver the online
application for Mortgage
Insurance?
A ballpark answer is sufficient.

23. Does it address our issues?
Initial Uncertainty Accuracy/Effort Tradeoff
False Precision Differing Skill Levels

24. When to use it

25. Break it down
Add it up

26. Break overall effort into bits

27. Assign factor to each small bit
Tasks Time Factor # of Total Time
(hour/bit) bits (hours)
Interfaces
GUI - Simple 8
GUI - Medium 16
GUI - Hard 24
System Interface - Simple 12
System Interface - Complex 30
Total Interfaces
Processes
Simple Process 16
Medium Process 32
Complex Process 48
Total Processes

28. Where do we come up with the
factors?

29. This is where time cards may be
useful…
 Know ahead of time
what you want to track
 Build up information
over time
 Often requires
excruciating detail in
time collection.

30. Identify How Many Bits
Tasks Time Factor # of Total Time
(hour/bit) bits (hours)
Interfaces
GUI - Simple 8 3
GUI - Medium 16 2
GUI - Hard 24 1
System Interface - Simple 12 3
System Interface - Complex 30 2
Total Interfaces 11
Processes
Simple Process 16 5
Medium Process 32 4
Complex Process 48 3
Total Processes 12

31. Do the math to get an estimate
Tasks Time Factor # of Total Time
(hour/bit) bits (hours)
Interfaces
GUI - Simple 8 3 24
GUI - Medium 16 2 32
GUI - Hard 24 1 24
System Interface - Simple 12 3 36
System Interface - Complex 30 2 60
Total Interfaces 11 176
Processes
Simple Process 16 5 80
Medium Process 32 4 128
Complex Process 48 3 144
Total Processes 12 352

32. This gives us development hours

33. What about analysis & testing &…
 Percentage of
development hours
 Estimate tasks
separately
 You mean we have to
estimate analysis &
testing?

34. Data Warehouse Example
Adding a new source to
data warehouse
 Count of sources
 Count of tables/source
 Count of
elements/table
 Considerations of
complexity

35. Data Warehouse Example
1. Gather all the info
2. Plug it into a
spreadsheet
3. Look at the resulting
(realistic but “too
high”) number
4. Revise…

36. Your turn…
Want to create an online application for Mortgage Insurance
How long to deliver the online
application for Mortgage
Insurance?
Identify how you would break
this down to estimate

38. Of Course there’s always
Function Points…

39. Or, you could always add up tasks

40. Does it address our issues?
Initial Uncertainty Accuracy/Effort Tradeoff
False Precision Differing Skill Levels

41. When to use it

42. Another Look - Decomposition

43. Calibrated Estimates in Ranges
Manage Moderate Manage Build Manage
Tracks Content Deadlines Program Venue
1 – 2 Days 3 – 5 Days 1 – 2 Days 4 – 6 Days .5 – 1 Days
9.5 – 16 Days
@ $100/hour & 8 hours/day
$7,600 – $12,800
Note, Entire team calibrated and
involved in determining these estimates.

44. For More information
How to Measure Anything:
Finding the Value of
Intangibles in Business
by
Douglas W. Hubbard
HowToMeasureAnything.com

45. Where it Helps
Initial Uncertainty Accuracy/Effort Tradeoff
False Precision Differing Skill Levels

46. Relative Estimating

47. Ah ha! Here’s the poker connection!

48. Discuss (briefly) the item to estimate
As an Event Organizer
I want to know how
audience members vote by
athlete by gender So That
I can determine if men
and women vote differently.

49. The Delphi Technique

50. Everyone selects an estimate

51. Estimating Scales
(Modified) Fibonacci
Sequence:
0, ½, 1, 2, 3, 5, 8, 13, 20,
40, 80, 100
Using a regular deck of
cards:
A, 2, 3, 5, 8, King
Team Member Hands:
1–5
Leonardo Pisano Bigollo aka Fibonacci
Italian Mathematician

52. Reveal estimates all at once

53. Discuss outliers
Well, we changed the voting
I wasn’t sure we knew how
machines to ask gender a
Andwhy did youthe two
So how about pick during
Yeah, what she said.
to tell an audience
sign in last iteration, so it
king?
aces?
member’s gender.
should be easy

54. Repeat until convergence

55. Extrapolate based on Velocity
Assumptions:
 2 week iterations
 Overall backlog size: 600 points
 Planning Velocity: 30
 5 Person Team
 Avg Cost/person/wk: $4,000
Estimate: $800,000

56. Your turn…
Determine relative sizes of these various
features using the scale 1,2,3,4,5
Based on this feature being sized an 1.

58. Does it address our issues?
Initial Uncertainty Accuracy/Effort Tradeoff
False Precision Differing Skill Levels

59. When to use it

60. An Alternative to Planning Poker
1 2 3 5 8
User Story User Story User Story User Story
User Story User Story User Story User Story
User Story User Story
User Story User Story

61. How should we approach estimating
for a project?

62. Calibrated
Guestimate
Phase Based
Estimates
Break it
down add
it up
Set
expectation
for revisions

63. Agile
Comparison
Calibrated
to past
Estimates
projects Extrapolate
from
Velocity
Set
expectation
for revisions

64. If you remember nothing else
Initial Don’t spend
uncertainty more effort
means you will than it’s
not be accurate. worth.
Don’t imply Incorporate
more precision multiple
than is perspectives.
possible.

65. Questions?
Kent J. McDonald
kent@kentmcdonald.com
www.BeyondRequirements.com
Twitter: @BeyondReqs
Slides available from:
http://www.knowledgebridgepart
ners.com/presentations/software
estimating/
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