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Mirrors, networks, and boundaries

Mirrors, networks, and boundaries

This time ten years ago, a movement was starting to coalesce to better align developers and operators. Looking back in the rear view mirror, we can say pretty clearly that movement was on to something.

DevOps has transformed how organisations use technology and organise people to deliver value to their customers faster and more safely.

But the landscape is changing. New challenges are coming into view, and leaders need to start preparing themselves for what comes next. What’s got us here won’t get us there.

In this talk we’ll look at what organisational psychology, product design, and anthropology have to say about what skills we need when navigating uncertainty.

Lindsay Holmwood

March 27, 2019
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  1. Mirrors,
    networks, and
    boundaries
    what technical leaders need to know
    for the next 10 years of devops
    Lindsay Holmwood

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  2. Sensitive
    dependence on
    initial conditions

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  3. What were the
    initial conditions?

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  4. Post-GFC
    scarcity

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  5. Organisations were
    requiring increased
    operational tempo

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  6. Siloisation
    was becoming
    a less viable
    organisational
    strategy

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  7. Infrastructure was
    becoming
    commoditised &
    on-demand

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  8. Barrier of entry
    to dev tools
    had been lowered

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  9. The last
    10 years

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  10. Three lenses:
    Delivery
    Systems
    People

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  11. Operating
    models
    Delivery
    Before
    Waterfall

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  12. Operating
    models
    Delivery
    After
    Agile, Lean

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  13. Devops started as
    “agile systems
    administration”

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  14. Deploy
    frequency
    Delivery
    Before
    Weekly-to-monthly deploys

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  15. Deploy
    frequency
    Delivery
    After
    Multiple deploys a day

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  16. Continuous Delivery
    is the standard in
    web industry

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  17. Infrastructure Systems
    Before
    Blend of:
    ◦ bare metal + virtualised
    ◦ on-prem or “hosting”

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  18. Infrastructure Systems
    After
    IaaS, PaaS

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  19. Commodification
    of infrastructure

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  20. Infrastructure
    management
    Systems
    Before
    Scripting

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  21. Infrastructure
    management
    Systems
    After
    Powerful config management

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  22. Architecture Systems
    Before
    Monoliths

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  23. Architecture Systems
    After
    Microservices

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  24. Is this reality or
    aspirational?

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  25. Deployment
    unit
    Systems
    Before
    Virtual machines

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  26. Deployment
    unit
    Systems
    After
    Containers

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  27. Deployment
    unit
    Systems
    Future
    Functions?

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  28. How we
    respond to
    failure
    People
    Before
    Blame culture

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  29. How we
    respond to
    failure
    People
    After
    Just culture

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  30. Blameless
    post-mortems

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  31. Relationships to
    our co-workers
    People
    Before
    Silos

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  32. Relationships to
    our co-workers
    People
    After
    Empathy

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  33. Build DevOps
    culture through
    shared experiences

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  34. Devs on call
    +
    Ops shipping code

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  35. Organising around
    the deployment pipeline

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  36. What’s next?

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  37. “Prediction is very
    difficult, especially
    about the future.”

    – Niels Bohr

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  38. I’m not going to
    make predictions

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  39. Yes, but it’s not necessarily a bad thing.
    As long as the technology is an enabler of the
    underlying principles (communication,
    collaboration, a holistic view), the DevOps
    movement is still sound.

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  40. What are the
    conditions now?

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  41. The DevOps dream
    ain’t evenly distributed

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  42. …the overall industry
    is improving its
    software
    development and
    delivery practices

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  43. …low performers are
    struggling to keep
    up, widening the gap

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  44. Increasing,
    fragmented
    regulation

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  45. ◦ GDPR
    ◦ NDB + APP
    ◦ “the Netflix tax”

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  46. Good for society,
    a PITA for us

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  47. Frameworks for
    accountability

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  48. Custom ASICs
    are proliferating

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  49. Machine learning is
    becoming
    more accessible

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  50. Google
    Neural
    Machine
    Translation
    Source: NYT – The Great AI Awakening

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  51. Generative adversarial networks

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  52. Let’s talk about skills
    for managing
    uncertainty & ambiguity

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  53. Mental models for:
    ◦ Understanding culture
    ◦ Harnessing mirroring
    ◦ Mapping strategy
    ◦ Managing risk

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  54. Understanding
    culture

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  55. We don’t know shit
    about culture

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  56. Schein’s
    three levels
    of culture

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  57. Artifacts
    Values
    Assumptions

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  58. National ↩︎
    Organisational ↩︎
    Team ↩︎
    Occupational

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  59. physical
    manifestations
    of culture

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  60. documentation

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  61. most visible parts of
    an org’s culture

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  62. easiest part of a
    culture to adopt

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  63. conscious goals,
    strategies, and
    philosophies

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  64. rules that guide
    how we interact
    with people

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  65. rules that guide
    how we do
    our work

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  66. “we will dominate
    the market”

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  67. “management is
    available, and listen
    to our concerns”

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  68. “we value quality
    over delivery
    speed”

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  69. “nobody will be
    fired for making an
    honest mistake”

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  70. values:
    lived
    vs
    aspirational

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  71. Communication
    We have an obligation to communicate.

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  72. Respect
    We treat others as we would like to be
    treated.

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  73. Integrity
    We work with customers and prospects
    openly, honestly, and sincerely.

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  74. Excellence
    We are satisfied with nothing less than
    the very best in everything we do.

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  75. Ethical
    We conduct business affairs in
    accordance with all applicable laws
    and in a moral and honest manner.

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  76. Work as imagined
    vs
    Work as done

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  77. Be clear about what
    values are what

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  78. beliefs, perceptions,
    thoughts, feelings

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  79. exist at an
    unconscious level

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  80. hard to discern

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  81. “anyone can take
    on leadership
    responsibility”

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  82. “bad outcomes come
    from bad people”

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  83. “it’s OK to withhold
    information”

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  84. “individual
    performance is
    valued over team
    performance”

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  85. “we can trust that team”

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  86. Artifacts
    Values
    Assumptions

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  87. Our systems are
    artifacts

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  88. Our processes are
    artifacts

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  89. Artifacts
    Values
    Assumptions

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  90. Tools are a
    snapshot of our
    org’s culture

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  91. Tools are a
    snapshot of our
    org’s values and
    assumptions

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  92. Artifacts influence
    behaviour

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  93. Encode the org
    behaviour you want
    to see into your
    artifacts

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  94. Change your org’s
    values by changing
    your artifacts

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  95. Artifact:
    All changes go through
    a CD pipeline.

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  96. Value:
    We create fast feedback
    loops to learn from
    changes in production.

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  97. Artifact:
    Developers and
    managers do on-call

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  98. Value:
    Performance,
    availability and
    sustainability are
    everyone’s
    responsibility

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  99. Artifact:
    Our ceremonies
    include and engage
    non-technical disciplines

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  100. Value:
    Nobody has all the
    answers. We succeed by
    working together.

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  101. But the tools are only a 

    means to an end

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  102. The goal is
    transforming our
    ways of working

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  103. Harnessing
    mirroring

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  104. "Organizations which design
    systems are constrained to
    produce designs which are
    copies of the communication
    structures of these
    organizations."
    – Melvin Conway

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  105. “In a complex system, the technical
    architecture and the division of labor
    will “mirror” one another in the sense
    that the network structure of one will
    correspond to the structure of the other.”

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  106. Two separate
    research traditions
    studying mirroring

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  107. 1. Computer science
    Conway’s law

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  108. 2. Management
    Org + product design &
    orgs + products as
    complex systems

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  109. What is mirroring?

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  110. Two networks

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  111. Organisational

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  112. Organisational Technical
    Mirroring

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  113. We do this to
    solve problems

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  114. We do this to
    take people to where
    the problems are

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  115. Who owns
    this system?
    ? ?
    ?

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  116. We do this because
    it’s economical

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  117. Organization design:
    an information
    processing view
    Galbraith, 1974

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  118. As uncertainty increases,
    the amount of
    information that must be
    processed by decision
    makers increases

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  119. The org can respond by
    reducing the need to
    process information

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  120. The org can respond by
    increasing the capacity to
    process information

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  121. The org can respond by
    Increase the capacity to
    process information
    devops

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  122. Creation of lateral relations:
    Direct contact
    Liaison roles
    Task forces
    Teams
    Integrating roles
    Managerial linking roles
    Matrix organisation

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  123. Creation of lateral relations:
    Matrix organisation
    Teams

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  124. Creation of lateral relations:
    Matrix organisation
    Teams
    Dev Ops Design
    Frontend Backend App eng Infra UX/UI Research

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  125. Dev Ops Design
    Frontend Backend App eng Infra UX/UI Research
    Why do we stop at
    dev and ops?

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  126. Dev Ops Design
    Frontend Backend App eng Infra UX/UI Research
    We can also include:
    support
    marketing
    design
    analytics
    legal
    finance

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  127. Dev Ops Design
    Frontend Backend App eng Infra UX/UI Research
    What happens
    if we don’t?

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  128. Architectural Innovation: The
    Reconfiguration of Existing
    Product Technologies and the
    Failure of Established Firms
    Henderson & Clark, 1990

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  129. 3 year study
    of semiconductor
    photolithographic
    alignment equipment
    industry

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  130. field based study,
    high rate-of-change industry

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  131. 4 waves of innovation
    between 1962-1986

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  132. 4 waves of innovation
    new leader after each:
    Kulicke ↩︎
    Kasper ↩︎
    Perkin-Elmer ↩︎
    GCA ↩︎
    Nikon

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  133. 4 waves of innovation
    each incumbent
    could not course correct

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  134. 4 waves of innovation
    each incumbent
    invested heavily
    in new technology

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  135. 4 waves of innovation
    each incumbent
    structured organisation
    and communication
    based on product
    architecture

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  136. 4 waves of innovation
    What about this
    makes sense?

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  137. Henderson & Clark’s
    framework for defining innovation
    Based on Schumpeter, 1942

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  138. Strongly mirrored
    Broken mirror

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  139. Henderson & Clark’s
    framework for defining innovation
    Based on Schumpeter, 1942
    Mirror
    Don’t

    mirror

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  140. Mapping strategy

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  141. Strategy is not just
    having a plan –

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  142. – it’s understanding
    how you react in a
    complex environment

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  143. Your criteria for
    making decisions
    when you
    face uncertainty

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  144. “Everyone has a plan
    until they get punched
    in the mouth”
    – Mike Tyson

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  145. Why do we map?

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  146. Build collective
    context

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  147. Inform strategic
    technology decisions

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  148. Understand and
    visualise tradeoffs

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  149. – Sidney Dekker
    “multiple overlapping and partially
    contradictory descriptions of the same act
    are always possible, and even necessary, to
    approximate the complexity of reality”

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  150. Navigate complexity
    Discover ambiguities
    Discover uncertainties

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  151. Don’t replace
    architecture diagrams

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  152. Arch diagrams + maps:
    complimentary tools

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  153. What is a
    Wardley map?

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  154. It’s a tool that clarifies:
    * Relationships
    * Position in value chain
    * Evolution/maturity

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  155. It’s a tool that clarifies:
    * Hot spots
    * Where new initiatives fit

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  156. Evolution/maturity
    Visibility to customers

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  157. Start with user needs

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  158. Then add
    most visible systems

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  159. Solid lines represent
    dependencies

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  160. Add dependent systems

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  161. Direction of travel

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  162. Visualise
    opportunities

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  163. Keep in mind:
    * Subjective
    * Visibility informs priority
    * Maturity informs investment
    * Don’t replace arch diagrams
    * Maps change over time

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  164. As the complexity of
    a system increases,
    the accuracy of any
    single agent's own
    model of that system
    decreases rapidly.
    Woods' Theorem

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  165. medium.com/wardleymaps

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  166. learn.hiredthought.com/p/wardley-mapping

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  167. • What are complex
    system
    • Simple, rugged, and
    dancing landscapes
    • The interesting in-
    between
    • Explore/exploit

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  168. stella.report

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  169. Managing risk

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  170. Likelihood
    % chance the thing
    will happen in the
    next 12 months

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  171. Impact
    $ cost of impact
    expressed as range*
    *90% confidence interval

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  172. Use maps to
    understand your
    risk landscape

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  173. 1. Understand
    aggregate risk
    position

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  174. 2. Compare to
    appetite

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  175. 2. Compare to
    appetite
    Probability of exceeding loss
    0%
    25%
    50%
    75%
    100%
    Loss exceeded
    10 100 1,000 10,000 100,000 1,000,000 10,000,000 100,000,000
    Current Appetite Residual

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  176. Probability of exceeding loss
    0%
    25%
    50%
    75%
    100%
    Loss exceeded
    10 100 1,000 10,000 100,000 1,000,000 10,000,000 100,000,000
    Current Appetite Residual

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  177. 3. Invest in:
    ◦ Reducing uncertainty
    ◦ Mitigation

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  178. The biggest risk?

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  179. We only look for
    answers in our field

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  180. Our niche becomes
    obsolete

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  181. We used to laugh at
    the box huggers

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  182. But building your own
    PaaS in AWS?

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  183. The 2019 version of
    being a box hugger

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  184. COTS PaaS meets
    user needs of
    95% of teams

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  185. Your niche is
    going to disappear.

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  186. – Edward Deming
    "It is not necessary to
    change. Survival is not
    mandatory."

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  187. Move up the stack

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  188. Understand the
    business model

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  189. Learn skills to
    navigate
    uncertainty &
    ambiguity

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  190. Kill your heroes

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  191. Thank you!
    ❤ the talk? Let @auxesis know.

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  192. Learn more:
    ◦ Algorithmic Impact Assessment report 2018
    ◦ Stella Report
    ◦ Wardley Mapping for busy people
    ◦ Wardley Maps book
    ◦ The Great Courses: Understanding complexity

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  193. Learn more:
    ◦ How to measure anything
    ◦ How to measure anything in cybersecurity
    ◦ Organisational culture and leadership
    (Schein)

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  194. Learn more:
    ◦ Organization design: an information
    processing view (Galbraith, 1974)
    ◦ Architectural Innovation: The
    Reconfiguration of Existing Product
    Technologies and the Failure of Established
    Firms (Henderson and Clarke, 1990)

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