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Transcript of Slide 1 The future of systems modelling and the approaching "tipping point" for the whole field 7th...
Slide 1
The future of systems modelling and the approaching "tipping point" for the whole field
7th Annual Gathering of the UK Chapter of the System Dynamics Society Harrogate, 9th & 10th February 2006
Justin Lyon, Simudyne and Dr. Dante Suarez, Simudyne and Trinity University
Slide 2
GE
BT
SAP
Microsoft
QinetiQ
Hawkeye
HVR
VBM
PSAS
PSUK
GSD
FJ
RS
CE
ERA
GB
DEL
FW
FRS
AXI
SSSK
Simulation Science
ORS
Strategy and Marketing
DH
SYM
GS
DTDM
DM
EW
SDG
McKinsey & Co.
S8
LW
FS
AL
Processes
SIE
SDS
SOCK
LVT
LBS
MIT
GRV
MM
D&B
RFG
MG
MASG
DK
OD
DS
MM
SFI
I8
OP
IS
Ernst & Young
PA
Who are we?
Slide 3
Simulation Science Market Reaches $20 Billion by 2010
15% growth projected by top industry analysts
Tipping point for Simulation Science occurs 2006 – 2007
Market Size
$-
$2,000,000,000.00
$4,000,000,000.00
$6,000,000,000.00
$8,000,000,000.00
$10,000,000,000.00
$12,000,000,000.00
$14,000,000,000.00
$16,000,000,000.00
$18,000,000,000.00
$20,000,000,000.00
2006 2007 2008 2009 2010
Software
Services
Slide 4
1998 - 2005
Simulation Science – Fifty Years in the Making and Growing Fast
1950 - 1998
SD
ABM
DES
Convergence‘Tipping
Point’
ABM
DES
2006• Simulation Science ‘Tips’• Explosive Growth• Hybrid Modeling• Paradigm Shift• Billions €, £, $
2006• Simulation Science ‘Tips’• Explosive Growth• Hybrid Modeling• Paradigm Shift• Billions €, £, $
SD
Slide 5
Market Trends Drive Adoption of Simulation Science by Global 1000
Simulation diffuses from natural sciences into social sciences
Less tolerance from Wall Street and the City for mistakes
Data-driven decision making with measurable ROI
Technology innovations
No strategy, only strategic execution
Press – Fortune, Forbes, Marketing, Strategy + Business
Slide 6
Barriers to the Adoption of Simulation Science by Global 1000
Economics and the myth of rational humans
Conflicting jargon of simulation experts is confusing
Scientific ego and the arrogance of simulation experts
Ignorance is bliss
Making something easy unnecessarily hard
Slide 7
Linear and Nonlinear Science areComplementary and Used Together
Most social science is based on linear models.
Linearity is based on independence of agents.
Under an assumption of linearity:The whole equals the sum of its parts.
Linearity works well with some systems
Nonlinear models quickly become intractable without computers.
Simulation Science: Enrico Fermi and the computer experiment.
Slide 8
Nonlinear Science = Simulation Science
Nonlinear Science: Zoology is the science that mostly studies non-elephant species.
Agents are interrelated.
Solutions to the system are complex:
the algorithm is the shortest solution.
Emergence:
The whole does not equal the sum of its parts.
The whole can be greater (or lesser) than the sum of its parts.
Slide 9
Simulation Science is a Great Tool for Harnessing Complexity to Achieve Results
Simulation Science is the study of how elaborate patterns and behaviors over time can: Emerge from very simple rules (policies, algorithms).Emerge from very simple structures (architectures).
Dynamics stem from the interactions of the agents over time, not necessarily the agents themselves.The neurons in the brain.The anthill as the organism.The humans in the corporation.
System Dynamics and Agent Based Modelling are great tools for harnessing complexity to achieve desired outcomes when managing and manipulating complex adaptive systems
Slide 10
How can we improve our marketing to ‘tip’ the ideas of Simulation Science?
Simulation Science is facing a sales and marketing challenge
It goes to the very heart of what many people hold dear
It challenges individuals most cherished beliefs
It makes it really hard to sell
Slide 11
Economics and its Realm of Action is Based on a Simplistic (and Outdated) View of Reality
The Utility function represents the individual, and it is set to reflect her preferences.
A paradigm based on the individual: an exogenous entity.
Key assumptions: markets exist for all possible goods, markets are perfectly competitive, and transaction costs are negligible.
Pareto Optimality: The optimum you get to where there is no way of making anyone happier without hurting someone else.
Economics is in dire need of a fundamental overhaul to bring it into alignment with 21st Century real world science!
Slide 12
Individual vs. Group Selection is the Root of the Anger and Fear of Simulation Science
History matters and individuals are not independent
The ‘Reductionism Nightmare’
Genes (Agents) do not make sense by themselves.Your children need a decent ‘pool of genes’ for them to preserve the
species.
Individuals (Agents) cannot survive by themselves.
Optimal species’ scales of environment exploitation.Many small and malleable individuals in species vs. large organized
wholes.
Slide 13
The Basics of the Proposed Model Combines Agent Based Modelling with System Dynamics
Endogenous utility functions.Endogenous utility functions.
The agent is not clearly defined. The agent is not clearly defined. It possesses coordinated subcomponents.It possesses coordinated subcomponents.It is fuzzy.It is fuzzy.
Slide 14
What do we mean by Fuzzy Agents?
Hispanics in USA
Latina Americans share culture among themselves
NAFTA Joins Canada, USA and Mexico
The USA and Europe share historic alliance, but may struggle for world leadership
The European Union creates a more cohesive agglomerate
Slide 15
Resulting behavior over timeResulting behavior over timeAimsAims
Resulting Resulting forceforce
Intertemporal Intertemporal aimsaims
t1 t4t2 t5t3
A. The static decomposition of desireA. The static decomposition of desire B. The intertemporal decomposition of utilityB. The intertemporal decomposition of utility
Patterns of Behavior are the Results of Accumulation and Depletion over Time
Slide 16
Agents Accumulate into a ‘Level’: Bounded Agents Accumulate into a ‘Level’: Bounded and Binding. It is a ‘Stock’. A ‘Bathtub’. and Binding. It is a ‘Stock’. A ‘Bathtub’.
There are people in our System Dynamics simulations!!
Slide 17
Answering “Whose Utility Am I Maximizing” Requires Moving Beyond the Individual
I maximize the utility of the one I am today.I maximize the utility of the one I am today.
I maximize the utility of all my “I’s”.I maximize the utility of all my “I’s”.
I maximize the utility of my family, of my group, of my country, I maximize the utility of my family, of my group, of my country, of my species.of my species.
The lines of who are my own, who is not, and who are my The lines of who are my own, who is not, and who are my enemies are not drawn, but are in constant change.enemies are not drawn, but are in constant change.
We must recognize the self interest of groups.We must recognize the self interest of groups.
Relative objects and subjects.Relative objects and subjects.
Slide 18
Back in to Utility
Individuals are only one of the many levels where utility Individuals are only one of the many levels where utility maximization is happening.maximization is happening.
In lower levels, individuals are a composition of inter-temporal utility In lower levels, individuals are a composition of inter-temporal utility maximizations.maximizations.
To form higher levels, sets of individuals may decide to join and To form higher levels, sets of individuals may decide to join and form groups that maximize their joint utility.form groups that maximize their joint utility.
These sets of individuals, or of other subsets, have the incentive to These sets of individuals, or of other subsets, have the incentive to become cohesive and coordinated.become cohesive and coordinated.
Slide 19
UUss
Realm of Action for the ‘Utility of Self’ function
Our utility functions are constrained by the ‘levels’ to which we belong.
Slide 20
Upper levels’ Upper levels’ realms of actionrealms of action
Individual’s Individual’s UtilityUtility
CollectiveCollective ForceForce
BehaviorBehavior
UUss
CountryFamily
Self
Instinct
UUff
UUii
UUcc
By Only Focusing on the Us People Ignorant of Simulation Science are Driving Us to Extinction
Slide 21
The World is Divided into Nested Levels of Agents
The agent in a social system simulation:The agent in a social system simulation:Represents strategic or non-strategic decision making;Represents strategic or non-strategic decision making;Is constrained by the upper level to which it belongs.Is constrained by the upper level to which it belongs.Created by the evolution of adaptability and responsiveness; Created by the evolution of adaptability and responsiveness; Confines the subcomponents that belong to it.Confines the subcomponents that belong to it.
The upper levels may be created by a conscious decision The upper levels may be created by a conscious decision OROR by a blind, by a blind, algorithmic evolutionary force.algorithmic evolutionary force.
Upper levels can represent coordination, identification with others, institutions, Upper levels can represent coordination, identification with others, institutions, implicit laws, religion, a credit bureau.implicit laws, religion, a credit bureau.
The lower levels seemingly disappear as the subcomponents become more The lower levels seemingly disappear as the subcomponents become more coordinated.coordinated.
Slide 22
Determinants of Behavior are Key Questions for the Future of Simulation Science
How can we simulate “fuzzy” agents?How can we simulate “fuzzy” agents?
How can we reproduce the appearance of agency in a simulation?How can we reproduce the appearance of agency in a simulation?
Why & how does evolution grant agency?Why & how does evolution grant agency?
How do we define agency? How do we define agency?
How do we define consciousness? How do we define consciousness?
Selfishness vs. Altruism.Selfishness vs. Altruism.
Slide 23
Optimality in a Hierarchically Decomposed World
To describe reality . . . To describe reality . . . Create a benchmark position where all behavior is optimal, so Create a benchmark position where all behavior is optimal, so
long as we identify the true active agent.long as we identify the true active agent.
Suboptimal behavior is thus a product of too much:Suboptimal behavior is thus a product of too much:‘‘zoom in’ or zoom in’ or ‘‘zoom out’. zoom out’.
Can we find an upper level in which the subparts are better off Can we find an upper level in which the subparts are better off without destroying the upper level?without destroying the upper level?
Institutions represent a better exploitation of the environment.Institutions represent a better exploitation of the environment.
Markets to exchange behavior. Markets to exchange behavior.
Slide 24
By Changing the Structure of a Business We Can Initiate a ‘Positive’ Phase Transition.
Cellular Automata Classes:Cellular Automata Classes:I I II II “IV” “IV” III III
Dynamical Systems:Dynamical Systems:Order Order “Complexity” “Complexity” Chaos Chaos
Matter:Matter:Fluid Fluid “Phase Transition” “Phase Transition” Gas Gas
Life: Life: Too Static Too Static “Life” “Life” Too Noisy Too Noisy
Businesses and Societies:Businesses and Societies:Too Rigid Too Rigid “Optimal” “Optimal” AnarchyAnarchy
Slide 25
Simulation Science Growth - One Year
Ignite Scenario
£0.00
£5,000,000.00
£10,000,000.00
£15,000,000.00
£20,000,000.00
£25,000,000.00
2005 2006
Failure
Pessimistic
Likely
Optimistic
Slide 26
System Dynamics Growth: Two Years
Three Year Scenarios
£0
£25,000,000
£50,000,000
£75,000,000
£100,000,000
2005 2006 2007
Failure without H
Pessimistic without H
Pessimistic with H
Likely with H
Optimistic with H
Slide 27
System Dynamics Growth - Five Years
Five Year Scenarios
£0.00
£100,000,000.00
£200,000,000.00
£300,000,000.00
£400,000,000.00
£500,000,000.00
£600,000,000.00
£700,000,000.00
£800,000,000.00
£900,000,000.00
£1,000,000,000.00
2005 2006 2007 2008 2009 2010
Failure
Pessimistic
Likely
Optimistic
Slide 28
System Dynamics Collapse - Five Years
Failure Scenario
£0
£1,000,000
£2,000,000
£3,000,000
£4,000,000
£5,000,000
£6,000,000
£7,000,000
£8,000,000
2005 2006 2007 2008 2009 2010
Failure
Slide 29
Process for Educating the Global 1000 about System Dynamics and Simulation
Adaptation of Dr. Kim Warren and Lars Finskud’s work on the Customer Conviction Chain.
An approach lauded as “one of the top 10 marketing theories” in Marketing magazine in October 2005
“Inspiration for the next Coca-Cola or Unilever marketing campaign might come from a computer game that looks an awful lot like The Sims.” in Forbes, November 2005
Slide 30
Declare
1Contact Brand Directors at XXXX.
SIMUDYNE conducts research on the use of simulation for FMCG!
Next ObjectiveGet meeting with appropriate top executives – CFO, CTO, CIO, CEO
Meetings with Brand, Consumer Marketing and Finance
Convert
4
Develop proposal& close deal
£500,000
Meet face to face with XXXX and
convince them on System Dynamics
Convince
3
Confidentiality agreement signed
S + P + I
Educate XXXX for 15 minutes and secure next meeting
Educate
2
Telephone meeting with XXXX at XXXXX
As Always – The Community Must Focus on the Flows that Drive Accumulation of Apostles
Connect
Deliver great work
5
Slide 31
SIMUDYNE’S Vision
To be the largest and most well-known simulation service provider in the world. Our intent is to be as pervasive as Visa is in the financial services industry. We are the key partner and system provider that every corporation and government has in its arsenal to make decisions and optimize success.
We do this by providing consultative services in creating simulations hosted in an encrypted internet-based environment that permeates all levels of an organization to virtually and collaboratively assess strategy, process and resource decisions.
We will radically change, improve and simplify the way in which strategy, process and resource decisions are made. Our clients literally see the future before it happens.
Slide 32
Thank You!