System Dynamics: Systems Thinking and Modeling for a Complex World 1/13/2020 DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 1 SYSTEM DYNAMICS: SYSTEMS THINKING AND MODELING FOR A COMPLEX WORLD James Paine System Dynamics Group MIT Sloan School of Management IAP 2020 SESSION –JANUARY 13, 2020 01 Welcome! • Grab some food! • Introduction to the SD Group at MIT 02 Overview of Systems Thinking • What is ‘System Dynamics’? • What is ‘Systems Thinking’? • Tools of the trade and key concepts 03 Hands on! Fishbank Simulation • Teams of 4 (+/- 1) • One laptop per team needed 04 Debrief and wrapup • Fishbanks debrief • Tying it into Systems Thinking • Other SD resources at MIT Plan for Today 1
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System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 1
SYSTEM DYNAMICS:SYSTEMS THINKING AND MODELING FOR A COMPLEX WORLD
James Paine
System Dynamics Group
MIT Sloan School of Management
IAP 2020 SESSION – JANUARY 13, 2020
01 Welcome!
• Grab some food!
• Introduction to the SD Group at MIT
02 Overview of Systems Thinking
• What is ‘System Dynamics’?
• What is ‘Systems Thinking’?
• Tools of the trade and key concepts
03 Hands on! Fishbank Simulation
• Teams of 4 (+/- 1)
• One laptop per team needed
04 Debrief and wrapup
• Fishbanks debrief
• Tying it into Systems Thinking
• Other SD resources at MIT
Plan for Today
1
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 2
About Me
2
Background
• B.S. Chemical Engineering (UF)
• M.S. Mechanical Engineering (Ga Tech)
• MBA Operations Management and Marketing (WFU)
• Worked for ≈10 years in GE-Hitachi (nuclear engineering), Inmar (reverse logistics and continuous improvement), HanesBrands (product marketing)
James Paine
• MIT Sloan School of Management
• System Dynamics Group, emphasis on Behavioral Operations
Management
Research Interests
• Product development (and failure)
• Supply chain management and cost mitigation via behavioral modeling (BOM)
• Managerial decision making in non-optimal environments
“Everything I have ever done has converged to become system dynamics.”
-Jay W. Forrester
at the 1989 International meeting of the System Dynamics Society
MIT-originated field
Created by Dr. Jay Forrester in the mid-1950’s while at MIT
First formalized in 1958 with “Industrial Dynamics - A Major Breakthrough for Decision Makers"
Origins in control theory
Dr. Forrester had background in EE and pioneer in early digital computers. Inventor of Random Access Memory while working on MIT’s WHIRLWIND I general purpose digital computer
Came to understand that social systems are much harder to control than physical systems, and often source of difficulties faced in projects
First major application was stock-flow-feedback structure of GE appliance plant three-year employment cycle, refined ideas of System Dynamics
Broadened beyond corporate management throughout 60’s and 70’s, including resource management such as WORLD2 simulation for Club of Rome
Evolved beyond methodology to thinking framework with applications in numerous fields
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 16
Systems Thinking Tools: Stock and Flows
30
Hydraulic Metaphor
Greenhouse Gasses in the Atmosphere
Greenhouse Gas Emissions
Net Removal
Systems Thinking Tools: Stock and Flows
31
Stocks Flows
Balance Sheet
Wealth
CO2 in Atmosphere
Integrals
Water in a bathtub
Accounts Payable
Income and Expenditures
Cash Flow Statement
CO2 Emissions
Derivatives
Flows through faucet and drain
Vehicle Production
Product preorders
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 17
HANDS-ON
MANAGEMENT
FLIGHT SIMULATOR
James Paine
System Dynamics Group
MIT Sloan School of Management
Fishbanks
*Briefing and debriefing borrowed heavily from Dr. Hazhir Rahmandad and Dr. John Sterman
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 18
Fishbanks• Intro (almost over)
• Fishbanks!• Short break
• Results and Discussion
Winslow Homer, The Herring Net
Fishbanks game by originally developed by Prof. Dennis Meadows, 1986. Web version developed by Prof. John Sterman, MIT Sloan School of Management, with help from Prof. Andrew King, Tuck School of Business, Dennis Meadows, Keith Eubanks, and Forio.com, 2010. Translations available: Chinese, Spanish, Portuguese.
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 19
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 20
Three oceans, Seven teams each
Teams of three to five (aim for 4)
A1
A2
A3 A4
A5
A6
A7
I1
I2I3
I4I5
I6I7
P1P2
P3
P4
P5P6
P7
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 21
Your GoalMaximize your team’s Net Worth at the end of the game.
Net Worth =
Bank Balance+
Value of Fleet
The winner is the team with the highest Net Worth at game end
$
Profit
Profit = Income - Expenses
Fish Sales
Ship Trade Sells
Interest Earning
Harbor Operation
Costs
Ship Purchases
New Ship Orders
Interest Charges
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 22
Income
Catch x Price ($20 per fish)Fish Sales
Ship Sales
Interest Earnings
2%/year if Minimum Bank Balance is greater than zero
Price set by auction
Expenses
Harbor: $ 50/year per shipCoastal Fishery: $150/year per shipDeep Sea Fishery: $250/year per ship
Harbor Operation
Costs
ConstructionNew Ships: $300 each. Charged at end of current year. Delivered the following year
Ship Purchases
Buy a ship at auction. Cost: your winning bid per ship * number bought
Interest Charges
5%/yr if Minimum Bank Balance is less than zero.
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 23
Sequence of Debits and Credits
Ban
k B
alan
ceStart year with bank balance that accumulated through all past years
If you buy ships at auction or from other teams, the cost is subtracted
START AUCTION
You are then charged for the operating costs of your fleet
Your fish catch is calculated and sales are credited as income
DECISION COSTS AND INCOME CALCULATED
The minimum balance is calculated and your account adjusted up or down based on the interest charged or earned
Finally, your account is charged for any new ships you ordered at the beginning of the year
Fishing Fleet
• Initial Fleet =3 Ships/team
• Fleet Growth- Purchase from other teams via auctions
- Order new ships
• Fleet Reduction- Sales to other teams via auctions
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 24
Ordering New Ships
Each year you may order the construction of new ships.
The maximum order is half of your current fleet (initial fleet + auction purchases).
If total fleet is an odd number, your maximum order is rounded up to the next whole number.
Catch
Catch influenced by:Number of Ships,Ship Effectiveness,
Weather
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 25
Recent History of the Fisheries
Ship Effectiveness
25
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 26
• Three oceans: Atlantic, Pacific, Indian
• 7 teams in each ocean, 3-5 people per team
• The oceans are separate
• Fish do not move between oceans
• Ships do not move between oceans
• Conditions identical except for your decisions
FishBanks
Let’s go fishing…
Winslow Homer, Fishing Boats, Key West (1903)
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 27
Login
• 1 Laptop per team (put all others away please)
• Go to: http://bit.ly/fishbanks
•STOP – wait for instructions
Alt link: http://forio.com/simulate/mit/fishbanks/simulation/login.html
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 42
1. Renewable resources can be used no faster than they regenerate.
2. Pollution and wastes can be emitted no faster than natural systems can absorb them, recycle them, or render them harmless.
3. Nonrenewable resources can be used no faster than renewable substitutes can be introduced.
Source: Herman Daly (e.g., H. Daly (1990) Ecological Economics 2, 1).
Hu
man
Activity
Eco
syst
em S
ervi
ces
The “Daly Rules”
Feedback structure Governing Renewable Resources
Fish Stock
Net Recruitment Catch
+
Fish Density
Maximum FishStock
+
-
Fractional NetRecruitment
+
+
Catch per Ship
Fleet Size
+
+
+R1
Population
Growth
B1
Limits to
Growth
B2
Fishing
Effectiveness
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 43
Fractional Net Recruitment vs. Fish Density
0
0 1 Fish Density, S/Smax (Dimensionless)
Fra
cti
on
al N
et
Rec
ruit
men
t (1/year)
Impact of Technology on Ship Effectiveness
0
0 1Fish Density, S/Smax
(Dimensionless)
Catc
h p
er
Sh
ip
(Fis
h/S
hip
/ye
ar)
Low Technology
High Technology
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 44
0
0 1 Fish Density, S/Smax (Dimensionless)
Ne
t R
ecru
itm
en
t (fish/year)
Net Recruitment vs. Fish Density
Net Recruitment vs. Fish Density
0
0 1 Fish Density, S/Smax (Dimensionless)
Ne
t R
ecru
itm
en
t (fish/year)
Reinforcing Feedback Dominant (R1)
Balancing Feedback Dominant (B1)
Unstable Equilibrium
Stable Equilibrium
MSY
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 45
Overshoot and Collapse
Simulation:
Fleet (potential
catch) grows
2%/year
Overshoot and Collapse: Examples
• Carrying capacity of the Earth:- climate change, - ozone layer, - ground water, - agricultural soils, - forests, - etc.
• Borrowing to maintain lifestyle
• Speculative bubbles
(housing, tech stocks, art, etc.)
• Abusing trust and good will - Misleading accounting - Telephone Marketing- False online reviews
• Drinking
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 46
“The Tragedy of The Commons”Garrett Hardin. Science 1968; 162:1243-8.
G. Hardin,
1915-2003
Photo: 1986
The Tragedy of the Commons
“No technical solution can rescue us.…”
“Each man is locked into a system that compels him to
increase his herd without limit—in a world that is limited.
Ruin is the destination toward which all men rush, each pursuing his own best interest…”
“We may well call it ‘the tragedy of the commons,’ using
the word ‘tragedy’ as the philosopher Whitehead used it:
‘The essence of dramatic tragedy is not unhappiness. It
resides in the solemnity of the remorseless working of things.’
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 47
“Common Pool Resources”
• Limited Stock and Rate of Renewal• Easily Appropriable (Low barriers to access)• Rival (What you use, I can’t use)
• EXAMPLES:
• Pastures
• Fish
• Forests
• Irrigation
• Clean Air & Water
• Climate
• Roads and Highways
• Parking Spaces
• Views
• Server Resources
• Trust among
consumers
Causes of Collapse (1)
Collapse of the carrying capacity can occur when underlying resources are
Nonrenewable or
Renewable but Consumable or Degradable
Collapse is worse with
• Common pool resources (Tragedy of the Commons)
• Slow or limited regeneration potential
• Tipping points created by positive feedbacks
• Irreversibilities due to e.g.
➢ Trophic cascade
➢ Evolutionary impacts
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 48
Causes of Overshoot (2)
• Long Delays in
Changes in Resource level (Physical/Biological delay)
Measuring resource level (Perception delay)
Understanding causes (Research delay)
Recommending action (Political/social delay)
Implementing policies (Political/social delay)
Policy impact (Physical/Biological delay)
Note: Delays are partly physical and partly political and social. Those with vested interests in the status quo often misrepresent the situation to delay action (e.g. tobacco, lead in gasoline, toxics in food, climate change).
Privatization can help, but has Limits• Enforcement
• Requires effective rule of law to enforce property rights.
• Conflict around equity, fairness.
• High discount rate• Owners may find it in their interest to harvest unsustainably
• Irreducible externalities• You can pen up your sheep, but your fish? Air? Water? Climate?
• Dynamic complexity• Difficulty of measuring resource stocks, consumption, regeneration
• Long delays in detecting and responding to overexploited resource
• Long recovery delays
• Nonlinearities, thresholds, ‘side effects’
System Dynamics: Systems Thinking and Modeling for a Complex World
1/13/2020
DO NOT DISTRIBUTE: Intended for registrants of the MIT System Dynamics Group IAP 2020 Session only 49
Limits to Privatization• Moxnes (1998): Experiment similar to Fishbanks
but with perfect private property rights: no Tragedy of Commons
• 74% of subjects overbuilt fleets; average fleet 60% above optimal