Defeat feature gluttony

2. How to defeat
feature gluttony

3. www.mrowcakasia.eu kasia@mrowca.co.uk

4. Gluttony
Source: http://www.pusheen.com/

5. Source: http://9gag.com/

6. Source: http://geek-and-poke.com/

7. How feature gluttony
affects product?

10. Number of features
Complexity

11. Number of features
Happinessoftheuser
Happy user

12. Number of features
Happinessoftheuser
Now I can’t find
anything!

13. How feature gluttony
affects backlog?

14. Problem 1: Road map

15. Problem 1: Road map
commitment

16. Problem 2: Backlog

17. Problem 2: Backlog size

19. Problem 3: priorities

21. Problem 4: documentation

22. Source: http://geek-and-poke.com/

23. Number of features
Complexity
Number of features
Happinessoftheuser
Now I can’t find anything!

24. Number of features
Complexity
Number of features
Happinessoftheuser
Now I can’t find anything!

25. Clean up!

26. Estimates…

27. … how about using story
points?

28. high estimate as a way to
scare the customer

29. high estimate as a way to
scare the customer
MISTAKE!

30. why huge estimates are not scary?
the customer…
… doesn’t understand Story Points
… is used to big estimates...
… maps estimates to magic numbers in excel
… doesn’t know that this implementation
is not beneficial for HIM

31. why huge estimates are not scary?
the customer…
… doesn’t understand Story Points
… is used to big estimates...
… maps estimates to magic numbers in excel
… doesn’t know that this implementation
is not beneficial for HIM

32. why huge estimates are not scary?
the customer…
… doesn’t understand Story Points
… is used to big estimates...
… maps estimates to magic numbers in excel
… doesn’t know that this implementation
is not beneficial for HIM

33. why huge estimates are not scary?
the customer…
… doesn’t understand Story Points
… is used to big estimates...
… maps estimates to magic numbers in excel
… doesn’t know that this implementation
is not beneficial for HIM

34. Clean up! Do it right!

35. How to start?

36. Road map: vision ahead!

37. Product tree

38. categories
(moduls)
featuresfurure
Method source: Innovation games

40. Love vs ROI

41. Love vs ROI

42. Love vs ROI

47. Metrics

51. ∞ ÷ 2 ≈ ∞

52. if you must use estimates

53. estimation methods
• Business Value – (simplifying) how profitable the feature is?
• additional estimate of risk

54. estimation methods
• Business Value – (simplifying) how profitable the feature is?
• additional estimate of risk

55. estimation methods
Story Points
User Story A
21

56. estimation methods
Story Points
User Story A
21
Risk
Business Value
XL
100

57. estimation methods
Story Points
User Story A
21
Risk
Business Value
XL
100
User Story A’
21
M
90

58. estimation methods
Story Points
User Story B
21
Risk
Business Value
L
20

59. how present alternatives?
• compare variants
Need 1
Need 2
Need 3
User Story A’ User Story A

60. add recommendation!

61. ok, how about… deleting?

62. Source: http://geek-and-poke.com/

63. Uncertainty causes fear

64. Uncertainty causes fear
…use automatic tests!

65. Wrap up

66. Number of features
Complexity
Number of features
Happinessoftheuser
Now I can’t find anything!

69. ∞ ÷ 2 ≈ ∞

70. Story Points
User Story A
21
Risk
Business Value
XL
100
User Story A’
21
M
90
∞ ÷ 2 ≈ ∞

72. www.mrowcakasia.eu
kasia@mrowca.co.uk