Are you wondering why your IT modernization & Digital Transformation projects aren't proceeding as desired your adoption of agile, scrum & SAFe aren't delivering the results you hoped for?
This presentation will visually explain many of the challenges you face, in a way that even your boss and stakeholders can understand.
I'll show you:
1. How to explain why math prevents you from accurately estimating project timelines and are therefore never actually behind schedule.
2. The negative impacts of deadline-driven development and how to avoid them.
3. How to explain the difference between startup agile and enterprise agile, and what happens you confuse the two.
4. Why you need to design and architect for the 1% of your customers that drive 80% of your complexity and 50+% of your revenue.
5.The concept of minimum viable replacement and how to think about modernization/migration projects.
6. Why throwing away work is a good engineering practice and how it can save you money
7. How to avoid confusing in market with market ready.
48. 48
Why do we continually pick designs and continue to plow
money into them when we know they’re not ideal?
Despite adopting agile processes, organizations still have waterfall mindset and
believe:
1. Teams should have been able to design everything correctly up front
2. Experimenting with multiple designs is a waste because you should already
know everything
3. Learning and wisdom can’t be quantified and therefore are not valued
4. Progress should be a straight line measured quantitatively and anything that
veers from that is waste
5. Throwing away work represents failure not learning and good judgement
49. 49
Fear-driven development results in sinking money into
suboptimal designs that ultimately need to be replaced at
3-5X the cost of having experimented early on
StartFast.Limited
investmentinarchitecture&
discovery
Technical & UX debt and risk
being accrued
Incremental costs & time to do it right
Cost of Doing it Wrong
Cost & time to:
1. Develop wrong solution
2. Develop new architecture
3. Rip out and replace old
architecture
4. Rip out and replace dependent
components designed for the
wrong architecture
Opportunity cost of spent mitigating
technical debt vs. delivering value
50. 50
And the more you invest in the wrong thing, the greater
differential between cost & perceived value
Perceived Customer Value Being Delivered
51. 51
Ultimately if the mistakes are embedded into the core
design and foundation, they may prevent you from ever
achieving your initial goals
52. 52
SAF recommends set-based design to avoid being locked into a
design that may not work but requires leadership to embrace
throwing away work as a good engineering practice not a failure
53. 53
And that doing it right, usually costs more up front
but results in time and cost savings in the long run
54. 54
Set-based design practices provide a framework for
success
Run experiments in parallel
Solve the hardest problems first
Ruthlessly discard what doesn’t work
Keep the knowledge gained
55. 55
Run experiments in parallel
“I have not failed, I’ve just found 10,000 ways that don’t work”
Thomas Edison
56. 56
Solve the hardest problems with the most risk first, not later
We installed the engine,
painted it, polished it, even
turned it on and everything
worked great, until we
tested it under load & the
plane won’t take off, but
doesn’t it look beautiful!
57. 57
Ruthlessly discard what doesn’t work and keep only the
knowledge gained
Thank you! Deadlines
shmeadlines! You’re a
hero, you saved us a
ton of rework & lost
opportunity.
Uh… We won’t hit the deadline but we
learned a lot! By doing destructive
testing & usability research early, we
discovered the initial design won’t
work so we’re tossing it & trying some
new concepts based on our learnings.
58. 58
Ruthlessly discard what doesn’t work and keep only the
knowledge gained
And you people, are
fired for hiding the
truth!
60. 60
Difference between startup agile and enterprise agile is
like the difference between building a custom home and
a skyscraper.
61. 61
Startup agile requires little planning, low risk and can
easily leverage existing infrastructure
Need to answer:
•Is it useful?
•Is it valuable?
•Is it usable?
62. 62
Enterprise agile requires lots of planning, high risk and
often entirely new infrastructure and architectural
approaches to deal with the challenges of scale
Need to answer:
•Is it useful?
•Is it valuable?
•Is it usable?
•Can it scale?
63. 63
Startup agile enables you to deliver value to market
much faster
Great job! That
was a quick win!
64. 64
But good luck scaling
I can’t believe I
fell for the quick
win again!
65. 65
The higher you go, the deeper you need to dig!
But the longer it may take
to deliver the initial value
67. 67
The Pareto Principle says to focus on the 80%, but the
question is which 80%?
• Is it the 80% of your customers?
• Is it the 80% that are the most profitable overall?
• Is it the 80% that have the highest average profit?
68. 68
The Pareto Principle says to focus on the 80%, but the
question is which 80%?
• Or is it the one percent that drives the 60% of
your revenue and 80% of your complexity?
69. 69
The 1% have such vastly different requirements from the
other 99% that trying to transform a system designed for
everyone else is almost impossible
70. 70
Design & Architect for the 1% while delivering for the
80% first.
• Identify the business and scalability requirements
for the largest, most complex customers first
• Deliver simpler solutions that meet the needs
of your less complex customers first that you
can deliver to market sooner while building
more complex solutions for later delivery
71. 71
Or develop entirely different systems to meet the very
different needs
Standard designs &
features for the 99%
Custom solutions for
the 1%
Shared Infrastructure
whenever possible
73. 73
Minimum Viable Product = Hypothesis that a certain
minimum level of functionality is enough to meet a
specific market need
Market segment A
Market segment B
Market segment C
Market segment D
Market segment E
Market segment F
Market segment G
Segment Revenue Opportunity
Simplesttomostcomplex
Smallesttolargest
MVP A
74. MVP G
MVP F
MVP E
MVP D
MVP C
MVP B
74
Minimum Viable Replacement = Sum total of all the
MVPs required to meet all customer needs required to
transition existing customers and retire existing system
Customer segment A
Customer segment B
Customer segment C
Customer segment D
Customer segment E
CustomersegmentF
Customer segment G
Segment Revenue Opportunity
Simplesttomostcomplex
Smallesttolargest
MVP A
75. Minimum Viable Replacement
MVP G
MVP F
MVP E
MVP D
MVP C
MVP B
75
Plus any additional enhancements/ inducements
required to get stakeholders and customers to change
and adopt new systems and processes
MVP A Customer segment A
Customer segment B
Customer segment C
Customer segment D
Customer segment E
CustomersegmentF
Customer segment G
Segment Revenue Opportunity
Simplesttomostcomplex
Smallesttolargest
76. Minimum Viable Replacement
MVP G 1,2,3,4, 5,6,7, 8, etc.
MVP F
MVP E
MVP D
MVP C
MVP B
76
And if individual customers are large enough to have
customer-specific requirements, then an MVP/MVR has
to be developed for each customer.
MVP A Customer segment A
Customer segment B
Customer segment C
Customer segment D
Customer segment E
CustomersegmentF
Customer segment G
Segment Revenue Opportunity
Simplesttomostcomplex
Smallesttolargest
77. Minimum Viable Replacement
MVP G 1,2,3,4, 5,6,7, 8, etc.
MVP F
MVP E
MVP D
MVP C
MVP B
77
The more customizations and changes required by
internal and external stakeholders, the more difficult the
migration will be
MVP A Customer segment A
Customer segment B
Customer segment C
Customer segment D
Customer segment E
CustomersegmentF
Customer segment G
Segment Revenue Opportunity
Simplesttomostcomplex
Smallesttolargest
78. Minimum Viable Replacement
MVP G
MVP F
MVP E
MVP D
MVPC
MVP B
MVP A
78
Of course, since you are dealing with icebergs, you often
have no idea what is required for each MVP
Customer segment A
Customer segment B
Customer segment C
Customer segment D
Customer segment E
CustomersegmentF
Segment Revenue Opportunity
Simplesttomostcomplex
Smallesttolargest
Customer segment G
79. 79
At the same time, you have to balance the desire to
meet your existing customers’ needs with the opportunity
to serve new market segments with different functionality
A Bird in the Hand? Two in the Bush
• Someone is always going to be unhappy, the question is who, what are
the consequences and which tradeoffs are you willing to make?
or
81. 81
Do not confuse your internal desire to declare victory
with the market requirements for a successful product
82. 82
Deadline driven development encourages people to believe
that in market and market ready are the same thing
In Market: Might be an MVP but
not ready for mass market
Market Ready: Actually ready for
mass market
83. 83
Market ready is ultimately determined by our customers and
stakeholders, who may have very different perceptions
depending upon their specific needs & expectations
What is
Productivity?
What is Customer
Experience?
What is
Scalability?
What is
Success?
Success
What is it?
7 7 10
So determine in advance which customers you are really trying
to serve and make sure they are the ones that say your product
is actually market ready
84. 84
So conduct testing early and often with your target users in
order to truly understand whether the product is truly
market ready!
Waterfall: Can and should know everything therefore can and should be able to forecast the future
The probability of successfully predicting the outcome of a specific task or an entire project is driven by the complexity, i.e. number of variables involved, and the probability of successfully achieving the goals for the task or project
Waterfall: Can and should know everything therefore can and should be able to forecast the future
The probability of successfully predicting the outcome of a specific task or an entire project is driven by the complexity, i.e. number of variables involved, and the probability of successfully achieving the goals for the task or project
The probability of successfully predicting the outcome of a specific task or an entire project is driven by the complexity, i.e. number of variables involved, and the probability of successfully achieving the goals for the task or project
The probability of successfully predicting the outcome of a specific task or an entire project is driven by the complexity, i.e. number of variables involved, and the probability of successfully achieving the goals for the task or project
The probability of successfully predicting the outcome of a specific task or an entire project is driven by the complexity, i.e. number of variables involved, and the probability of successfully achieving the goals for the task or project
The probability of successfully predicting the outcome of a specific task or an entire project is driven by the complexity, i.e. number of variables involved, and the probability of successfully achieving the goals for the task or project
Ultimately resulting in the black hole of deadline-driven development that warps everything from code quality to customer experience as teams put deadlines above almost everything else
“When everything was GREEN it was secret, and people were managing the secret, now they are managing the reality.”
like any drug, the side effects often outweigh the benefits.
Shortcuts may speed initial value delivery but they often increase cost and time in the long run
Set based computer engineering
Set based computer engineering
Set based computer engineering
Unlike other applications, with business intelligence, you can’t simply scale by adding more servers, you need to build the right data architecture otherwise you’ll never meet the needs of the 1% responsible for 60% of your revenue.