Graphorisms applied v0.03

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A graphic language for articulating the state and boundaries of complex systems at a high level. The goal is high level abstraction so that false reductionist data or approximation isn't allowed. High …

A graphic language for articulating the state and boundaries of complex systems at a high level. The goal is high level abstraction so that false reductionist data or approximation isn't allowed. High Level Metaphor is used to convey meaning which can then be expanded on.

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  • let me know if you would like access to the original graphorism files for download etc.
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  • this is probably horrible as a stand alone presentation, but explains complex processes using a high level of graphic abstraction method.

    It is used to get people seeing systems, state and risk from a shared perspective. A lot of systems thinking going on here.

    feel free to expand on it and adapt it for your domain of expertise. It is CC rights of attribution.
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  • 1.
  • 2. systemsthinking& Graphorismsfor capital allocation Nick Gogerty
    Seekfeedback of prototype project
    Describe complex problems & environments as systems
    Graphorisms = graphic models & metaphors
    Allocate capital to stable, long lived, higher margin competitive systems
  • 3. systems thinking:framing problems
    System involving flows or repeat process
    change and dynamics of change
  • 4. process
    Cycles or repeats
    growth clockwise
    shrinkage counter clockwise
    Abstract with open boundary
    Operates in an environment
    Interacts at boundaries
    Purposely shown as abstract
    Stasis is death
    Has limits (input, flow or output)
  • 5. narrative systems thinking
    Talking, showing and walking through some problems
    Talk through the paths
    normal accidents: hidden system paths
  • 6. shared perspective & people’s goals
    Growth/decline (increasing or decreasing an externality of the system)
    Stability (maintaining the status quo / usually focuses of risk management prevention of instability)
    Termination of the current system (wholesale change)
  • 7. critical instability & system capacity
    risk tight coupling
    grains of sand/avalanche model (log normal events) from linear input
    straw on the camels back not important
    Tension & Capacity
  • 8. butterfly wing flaps aren’t important: system tension (sensitivity) is
    Causal loops attenuate (over link focus is useless) and counterproductive “reductionist folly”
    Tension among components and process is important ”specificevents are irrelevant"
    Understand homeostasis boundaries of stability / failure shift
  • 9. Risk types
    Concentration (low diversity, low redundancy)
    Tight coupling /Too efficient optimized
    Over capacity / tension
    Failure by design: System over optimize = normal accident
    Model truth: All components fail. All systems end.
  • 10. Graphorism
  • 11. System questions make a graphorism
    required elements: relationship, state and boundary
    What are the actors/resources and context?
    What is the system, process, output or input to be explained?
    What are the boundaries and capacities of the system (links, resources)?
    What is the state or dynamic to be shown?
    Identify tensions (safety stability v. efficiency)
  • 12. Graphorisms: goals and uses of
    Graphic metaphor + aphorism
    not complete state diagram
    language for (Subject, object verb and state) representations
    designed for cocktail napkins
    graphical abstractions for how system growth, change and end
    fuzzy flow chart or operations diagram easy to learn / share
  • 13. Graphorismrules
    Not literal representation: real outputs are sloppy and lumpy not smooth
    Purposely abstract away details of system ”reduce false complexity completeness”
    Presented as open for debate
    Graphorism requires context
    Layer specific "not wholistic”
    Multiple graphorisms used for components, relationships and conditional states
  • 14. elements
    Process (growing, shrinking, dead, failing)
    Resource competition "crowding/capacity"
    Sub system components (linked/related)
    Scale variant (limited presentation) = more is different (network of networks)
    Process environment "stable, failing to collapse, growing, tightly coupled, loosely coupled"
    Boundary (input, output, capacity for flow)
    Fuzzy noise, error bounds / futility of detailed measurement
  • 15. actors
    Subject /nouns (process/person/entity)
    Lifecycle limit
    Resources (money, energy, carbon, air, time)
    boundary / barrier or threshold
    links / chains (often sub processes themselves)
  • 16. relationships of components (verbs)
    Throughput change
    Component and system tension ratio with an instability threshold
    Capacity risk
  • 17. states: system dynamics (adjectives/modifiers)
    Linked / dependent / clustered
    Symbiotic (stable) v. Parasitic (detrimental)
    Activity level: (static = dead),Homestatic (stable / governed / robust)
    Failure/d (at component/system level)
    Point failure ≠ system failure
    Growing/shrinking (increasing decreasing
    Tension/capacity/limit (used/available)
    Coupled component dependency (tight/loose)
  • 18. rules & universal system ?’s
    All systems end. When?
    All components fail. What happens?
    All systems linked? What links count?
    All things change. What next adjacency?
    Everything is finite? What are capacities tensions?
  • 19. Sources of risk system failure
    Capacity / tension/ brittleness
    Supply / externality
    Hidden path (normal accident)
    Age / component failure
  • 20. tragedy of the commons
  • 21. Gresham’s law (cluster evolutionrisk) in banking, insurance & CDS
  • 22. Gresham’s process
    Designed / behavorial to failure / instability
    Needs regulation of control
    Tragedy of commons due to feedback delay
  • 23. Wicked problems
  • 24. Graphorisms may help communication of "wicked problems"
    No unique "correct view of the problem”
    Many possible intervention points
    Often a-logical, illogical or multi-valued
    Different views of problem and solutions are contradictory
    Problem solver out of contact with problems and solutions
    Considerable uncertainty / ambiguous
    Problems are interconnected to other problems
    Data are often uncertain or missing
  • 25. Capital Allocation
  • 26. systems thinking applied to capital allocation to make money
    Can you identify competitive cluster & lifecycle stability?
    What is source of value / pricing power?
    What are relative growth factors?
    How are hidden paths minimized?
  • 27. not value or growth investing
    Systems thinking investing “thoughtful capital allocation”
    Process driving margin & capital returns
    Process driving sustainability
    Capacity constraints & tension
  • 28. first rule don't lose capital / value = first rule survive!
    always trade safety for efficiency or speed
    Goal compounding growth (system time)
    risk =loss of value creation systemin portfolio (not volatility)
    Lumpy (true natural) not false smooth
  • 29. price asabstraction / opinion
    Price is 2 opposing views about value expressed at a point in time
    99% can’t beat buy and hold (don’t understand value creation process)
    99% of price generation is useless information about the value creating system
  • 30. 1. thinkin competitive clusters
    Customer choice set
    Seek stable low innovation = niche survival
    Inverse Gresham's law (process good crowding)
    Winner take most
    Capacity boundaries?
    Niche capacity relative to what ?
  • 31. Unit of moat =innovationarchetypes (10 Doblin)
    Business Model innovation: 
    Networking innovation: 
    Enabling Process:
    Core Process:
    Product Performance: 
    Product System: 
    Customer Experience:
  • 32. innovation as evolution
  • 33. 3 blind men view the elephant moat
    Customers know what they like may not be able to articulate rational
    Competitors know what they can’t do
    Neither may the know the how, what or why of the moat
  • 34. Moat types& metrics (depth /duration)
    Belief-Brand (Coke, Wrigley, P&G)
    Learned behavior / (msoffice, Geico) switching cost
    Geography (Wal-mart, BNSF) displacement cost
    Social signalling (Rolex) belief barrier
    Network and scale effects (BNSF, i-tunes) switch cost
  • 35. sloppy process of system life
    details are less important than states
    “moat” margin homeostasis
    Understand tension among componentsis risk
    Carryingcapacity everything is a niche
  • 36. risk
    inflection points tight coupling "tension"
    Events are less important (system time counts)
    Capacity demand?
    Source of moat /cluster shape
  • 37. Key questions ???
    All things end. When?
    What is the relative value creating process for survival?
    How stable is the shape of the cluster and evolution in the niche?
    What are the boundaries and carrying capacities?
  • 38. Buffett example:Lubrizol $9b
    Complex entity (system of system moats) portfolio of clusters
    multiple dominant clusters moat shows up in ROC long term position (critical pieces of bigger systems) low price sensitivity
    Stable 40% dominance in some markets
    Distribution, technical, brand and price leadership moats
    Visible in high historical ROEs stable cluster (out of commodity box)
    Management knows how to allocate to earn cluster returns