The reality is that products and features will fail. How do we make sure they don't fail in vain? The F.A.I.L. framework helps us make sure that products won't fail in vain. F.A.I.L. provides the tools and techniques which unlock valuable information and learnings that we need to make sure that even if our products do fail, they don’t fail in vain. 

6. Thomas J. Watson
If you want to increase
your success rate,
double your failure rate”
“

7. I

8. If you’re not embarrassed
by the first version of your
product you’ve launched
too late”
“
Reid Hoffman

9. I’m f***ing embarrassed
alright”
“

10. I’m f***ing embarrassed
alright”
“
Marc Abraham

12. Marc Abraham
Learning
how to F.A.I.L.
@maa1
Making sure products don’t fail in vain

15. Thomas Edison
I have not failed.
I have just found ten
thousand ways that
don’t work“
“

16. Learning
Time
Sunk
investment
Experimental
playground
Not all is lost

18. Learning
Time
Learning
upfront
Sunk
investment
Experimental
playground
Not all is lost

19. Product Manager mantra 1:
“The sooner I can call time
on a product or feature,
the better”

20. Problem risk
Solution risk
Execution risk
Timing risk

25. Product Manager mantra 2:
“My job is to continuously
assess, prioritise and
mitigate risk”

27. Area
Problem impact
Solution adoption
Effort required
Expected value
Confidence Level

28. Quick Win
Area
Problem impact
Solution adoption
Effort required
Expected value
HIGH
HIGH
HIGH
LOW
Confidence Level

29. Big Bet
Area
Problem impact
Solution adoption
Effort required
Expected value
HIGH
LOW
LOW
HIGH
Confidence Level

30. EXPLOIT
Quick
win Big bet
EXPLORE
+
Source: “The Explore and Exploit Continuum” by Strategyzer

31. What - Data about the problem
Who - Data about the customer
How - Data about the solution
When - Data for decision-making

32. F.A.I.L.

33. F
A
I
L
Feature
Assumption
Impact
Learning

34. F
eatures + assumptions
Impact + Learning

36. F

41. Problem risk
Solution risk
Execution risk
Timing risk

42. F
A
I
L
Feature
Assumption
Impact
Learning

43. F
Feature

44. If you're actually
inventing something,
you shouldn't know
what you're doing”
Caterina Fake
“

45. Situation Motivation Expected outcome
When I want to So I can
Feature
Assumption
Impact
Learning
F
A
I
L

46. Situation Motivation Expected outcome
When So I can
I buy a home I want to avoid surprises complete quickly
Feature
Assumption
Impact
Learning
F
A
I
L

48. Understand the problem
Features
Products don’t fail in vain if we:

49. A
Assumptions

50. We believe that our (target)
customers have a need to
Currently, our (target) customers
Problem assumptions
Feature
Assumption
Impact
Learning
F
A
I
L

51. Currently, our (target) customers
We believe that our (target)
customers have a need to
discover property issues late in
the process, which puts the
home purchase at risk
buy a home without any hassle
Problem assumptions
Feature
Assumption
Impact
Learning
F
A
I
L

52. Candy Vitamin Painkiller

53. We believe that our users are
and that they value
User assumptions
Feature
Assumption
Impact
Learning
F
A
I
L

54. We believe that our users are first time home buyers
and that they value timely info about the property they want to buy
User assumptions
Feature
Assumption
Impact
Learning
F
A
I
L

55. “I want to get on the property ladder.
Not having bought a home before,
I don’t know what I don’t know”
Head of Technology
Buy a home that is affordable,
in the right location and is
likely to increase in value
Needs to understand
whether the home seller is
in a chain
Unfamiliar with people needed to
buy a house, e.g. surveyor, lawyer,
etc.
Buying a house currently feels
like a black box to this buyer
This buyer relies on estate
agents, lawyers and surveyors
to guide them through the
process of buying a home
Buying decision made based
the amount of work that needs
to be done to the house
Unfamiliar with the process
Limited budget
Complete home
purchase as quickly
as possible
Avoid extra costs
due to home repairs
Ask the right
questions about the
home
Challenges
Use Cases
Solution Pain Points Jobs to be done
Goals
First Time Home Buyer

56. We believe that we can solve our
customers’ problems through
solution
We believe that users will adopt
this solution because they will get
this benefit from
our solution
Solution assumptions
Feature
Assumption
Impact
Learning
F
A
I
L

57. We believe that we can solve our
users’ problems through
putting homes on the site with all
survey info, highlighting any
issues for buyers to be aware of
We believe that users will adopt this
solution because
they will have much more
confidence in the home they are
buying and will be able to move
in much sooner
Solution assumptions
Feature
Assumption
Impact
Learning
F
A
I
L

58. “Innovation is nothing
more, and nothing less,
than a new combination
of old ideas”
Sheena Iyengar

63. What could go wrong from a product perspective?
What could go wrong from
a user perspective?
What could go wrong from
a legal perspective?
Pre-Mortem
Feature
Assumption
Impact
Learning
F
A
I
L

64. “Lawyers won’t agree to share
all survey and property data upfront”
“Home buyers don’t appreciate
the new way of buying homes”
“We won’t be able to automate
the entry of property data from
a range of sources”
Pre-Mortem
Feature
Assumption
Impact
Learning
F
A
I
L

65. Learn early and often about critical assumptions
Assumption
Products don’t fail in vain if we:

66. I
Impact

67. We believe that this statement is true
We will know we’re [right / wrong] when we see the following
feedback from the market [quantitive / qualitative] or [KPI change]
Hypothesis Statement
Feature
Assumption
Impact
Learning
F
A
I
L

68. We believe that Settled Plus will increase the completion of
home purchases
We will know we’re right when we see 90% of properties sold
through Settled Plus being completed
Hypothesis Statement
Feature
Assumption
Impact
Learning
F
A
I
L

69. How would you feel if you could
no longer use this product?
Not disappointed
Somewhat disappointed
Very disappointed
Not applicable
Feature
Assumption
Impact
Learning
F
A
I
L

70. Demand
reduction
Customer
Demand
generation
HABIT ANXIETY
PUSH PULL
Source: Alan Klement on jtbd.info
Forces of Progress
Feature
Assumption
Impact
Learning
F
A
I
L

71. Have a clear hypothesis that we can act on early
Impact
Products don’t fail in vain if we:

72. L
Learning

73. It’s only when you
risk failure that you
discover things”
Lupita Nyong’o
“

74. What happened?
What did we learn?
What do we decide?
Feature
Assumption
Impact
Learning
F
A
I
L

75. Why? Because users didn’t adopt the feature
Why? Because they didn’t see the value of the feature
Why? Because they are used to competitive feature X
Why? Because they find that feature is easy to understand and use
Why? Because that feature has 3 key steps and ours has 10
Feature
Assumption
Impact
Learning
F
A
I
L

77. What happened?
Not even close to our hypothesis
What did we learn?
Value proposition wasn’t compelling
What do we decide?
Back to the drawing board
Scenario 1 - Abject Failure
Feature
Assumption
Impact
Learning
F
A
I
L

79. Scenario 2 - Near Miss
What happened?
Unproven hypothesis but strong signals
What did we learn?
Onboarding was a hurdle
What do we decide?
Let’s go again, iterate onboarding
Feature
Assumption
Impact
Learning
F
A
I
L

80. V

81. What happened?
Strong hypothesis validation
What did we learn?
Users got value out of the product
What do we decide?
Let’s optimise!
Bull’s Eye!
Feature
Assumption
Impact
Learning
F
A
I
L

82. Problem Impact Learning
What are we solving for? Will it move the needle? Will we learn?
Feature
Assumption
Impact
Learning
F
A
I
L

83. Are clear on the why
Learning
Products don’t fail in vain if we:

84. Avoid
failureat
allcost!

85. Learning
Have a clear hypothesis that we can act on early
Impact
Learn early and often about critical assumptions
Assumption
Understand the problem
Features
Products don’t fail in vain if we:
Are clear on the why
Learning

86. F
A
I
L
Feature
Assumption
Impact
Learning

87. Marc Abraham
@maa1
KEEP F.A.I.L.ing!