introduction to systems thinking and dynamic modeling (st&dm ): part i

1

Introduction to Systems Thinking and

Dynamic Modeling (ST&DM): Part I

For Tahoma School District on June 3, 2010

Tahoma contact: Dawn [email protected], 425-413-3424

Paul Newton (Boeing)[email protected], 206-544-7641Dr. Dexter Chapin (Seattle Academy of Arts and Sciences)[email protected], 206-323-6600Jim Ray (retired Boeing engineer)[email protected], 425-865-9319 (home)

June 3, 2010

mailto:[email protected]




2

Agenda: Intro to ST&DM Part I

• Broad application areas of systems thinking and dynamic modeling (ST&DM)

• Slinky• What is ST&DM?• Drug-related crime• Modeling example: filling a water glass• ST&DM at Boeing• First feedback loops

3

Broad Application Areas of ST&DM• To Technology Problems

– Control engineers do ST&DM all the time, although they might not call it that– Examples: autopilot, thermostat, paper machine, electric blanket, cruise control,

steam engine, electric motor, computer, etc.

• To Social Problems– Business dynamics– Family dynamics– Community dynamics– Insurgency dynamics– Ecological dynamics– Organizational dynamics– Urban dynamics– Etc…..

4

Hint: Structure and behavior

What is the systems lens?

Introduction from Meadows, D. H., & Wright, D. (2008). Thinking in systems: A primer. White River Junction, Vt: Chelsea Green Pub.

5

What is systems thinking?• A perspective and a set of conceptual tools

that enable us to understand the structure and behavior of dynamically complex problems

• A rigorous modeling method that enables us to build computer simulations of dynamically complex problems and use them to design more effective policies and organizations

[slightly modified from Sterman, John (2000) Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill]

What is system dynamics? Some quotes…System dynamics is the use of computer simulation for policy analysis in complex systems. Its big contribution is helping people to build progressively richer understandings of some dynamic problem, and anticipate weaknesses in policy initiatives that would develop over time. It gets a lot of its power from a 'feedback' perspective -- the realization that tough dynamic problems arise in situations with lots of pressures and perceptions that interact to form loops of circular causality, rather than simple one-way causal chains. Humans are really good at thinking up all that interconnected complexity and really weak at inferring its implications without the support of simulation models.

George RichardsonRockefeller College of Public Affairs and Policy, State University of New York at Albany

System dynamics deals with how things change through time, which includes most of what most people find important. It uses computer simulation to take the knowledge we already have about details in the world around us and to show why our social and physical systems behave the way they do. System dynamics demonstrates how most of our own decision-making policies are the cause of the problems that we usually blame on others, and how to identify policies we can follow to improve our situation. Jay Forrester

Sloan School of Management, Massachusetts Institute of Technology

The what, why and how of system dynamics:What: A rigorous way to help thinking, visualizing, sharing, and communication of the future evolution of complex organizations and

issues over time, Why: for the purpose of solving problems and creating more robust designs, which minimizes the likelihood of unpleasant surprises

and unintended consequences,How: by creating operational maps and simulation models which externalize mental models and capture the interrelationships of

physical and behavioral processes, organizational boundaries, policies, information feedback and time delays; and by using these architectures to test the holistic outcomes of alternative plans and ideas,

Within: a framework which respects and fosters the needs and values of awareness, openness, responsibility and equality of individuals and teams. Eric Wolstenholme

School of Management, University of Stirling, Scotland.

System dynamics is a framework for thinking about how the operating policies of a company and its customers, competitors, and suppliers interact to shape the company’s performance over time. System dynamics models are:1) Maps, diagrams, words, and friendly algebra to activate and capture team knowledge2) Frameworks to help organize, filter and structure the vast amount of knowledge that an experienced team shares, and3) Microworlds, microcosms of reality, learning environments that managers can use to test, challenge, and refine their own mental

models. John MorecroftLondon Business School, U.K.6

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The real system…

Edited extract

…vs. what we often see…

The trouble with feedback is that it is often invisible …

“System dynamics demonstrates how most of our own decision-making policies are the cause of the problems that we usually blame on others, and how to identify policies we can follow to improve our situation.”Jay ForresterSloan School of Management, MIT

Page 38 of Morecroft, John (2007) Strategic Modelling and Business Dynamics. Wiley

8

From Events to Dynamics and Feedback: Drug-related Crime

"Drugs are a big worry for me, not least because of the crimes that people commit to fund their dependency. We want the police to bust these rings and destroy the drugs. They say they're doing it and they keep showing us sacks of cocaine that they've seized, but the crime problem seems to be getting worse".

[Morecroft (2007) p 46]

Typical description of the problemby the victims of drug-related crime

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Dynamics of Drug-Related Crime

Time in Years

Drug-RelatedCrime

Unintended

puzzlingdivergence

reported

tolerable

[Morecroft (2007) p 47]

What feedbackstructure couldexplain thispuzzling divergence?

10

CLD for Drug-Related Crime

drug-related crime

call for policeaction

drug seizures

supply

pricedemand

+

+

-

-

+

+ Crime Spiral

[Morecroft (2007) p 47-48]

Among the variables below, construct a CLD that could create this puzzling divergence.

Event-oriented thinking.

“What feedback structure could explain this puzzling divergence? Reported crime is growing and we know that growth arises from reinforcing feedback. The persistence of unwanted growth in crime suggests a feedback loop that weaves its way around society, and by doing so it goes unnoticed.”

Why does price not influence demand as it does in most markets?

Stakeholders represented?- Community- Police- Drug users- Drug dealers

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Agenda



Combined Qualitative & Quantitative Thinking Example:

Filling a water glass(Go to Vensim)

12

Drug Related Crime: qualitative, yet mathematical, thinking.

WaterGlass1.mdl

13

Water InGlass

spigot flow rate

initial water in glass

overflow rate

height of glass

Water in Pan

initial water in pan

Water in the Glass and Pan5

00 2 4 6 8 10

Time (Second)

in

Water In Glass : CurrentWater in Pan : Current

1

0 4 0

WaterGlass2.mdl

14

Water InGlass

+

spigot flow rate


desired water inglass

gapO

SB

Water in the Glass & Spigot Flow Rate4 in2 in/Second

3 in1.5 in/Second

2 in1 in/Second

1 in0.5 in/Second

0 in0 in/Second

0 1 2 3 4 5 6 7 8Time (Second)

Water In Glass : Current inspigot flow rate : Current in/Second

0

3.5

WaterGlass3.mdl

15

Water InGlass

+

spigot flow rate


desired water inglass

Water in the Glass & Spigot Flow Rate4 in2 in/Second

3 in1.5 in/Second

2 in1 in/Second

1 in0.5 in/Second

0 in0 in/Second

0 1 2 3 4 5 6 7 8Time (Second)

Water In Glass : Current inspigot flow rate : Current in/Second

gapO

initial spigot flowrate

Beffect of gap on

flow rate

0

3.5

1

16

Agenda



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ST&DM in Boeing: Where is it done?

• The modeling and simulation group Paul Newton (one of the two presenters of this slide show) belongs to…– …is part of Boeing Research & Technology, Boeing’s R&D organization– …is like an internal consulting firm: fee for service to BCA & BDS– …does other kinds of modeling and simulation as well– …contains four people doing ST&DM, with several others learning, and

is hiring (we have growing demand)– …has 1 PhD, 2 Master’s, 1 Bachelor’s– …engages summer interns, from HS seniors, to PhD students.

• Elsewhere in Boeing– Boeing Test & Evaluation: systems thinking to improve organizational

change and performance dynamics– Scattered interest elsewhere, e.g. BCA, Information Technology

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ST&DM in Boeing: Dynamic Business Problems

• Boeing examples:– Learning curve dynamics– Aerospace industry dynamics– Future workforce dynamics (STEM)– New business strategy dynamics

• Boeing customer examples:– Boeing Commercial Airplanes (BCA) customers example: business

strategy dynamics, like People Express shown below– Boeing Defense Systems (BDS) customers example: better

understanding insurgency & irregular warfare dynamics• Show two examples:

– Autopilot (airplane design – technical systems)– People Express Vensim model (business design – social systems)

Proportional “Altitude Hold” Autopilot

Altitude

desired altitude

changing altitude

wind drafts changing altitude due towind drafts

desired less actual

altitude adjustmenttime

changing altitude due tospeed increase

• Desired state – 40,000 ft• Current state – variable• Actions – variable vertical winds• Feedback

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20

Proportional Autopilot for Holding Altitude During Vertical Wind Drafts

Altitude

desired altitude

changing altitude

wind drafts changing altitude dueto wind drafts

Wind Drafts and Altitude - No Control Loop42,000 feet

40 miles/hour

37,000 feet0 miles/hour

32,000 feet-40 miles/hour

0 2 4 6 8 10 12 14 16 18 20Time (Minute)

desired altitude : NoControlLoop feetAltitude : NoControlLoop feetwind drafts : NoControlLoop miles/hour

No Control Loop

Altitude

desired altitude

changing altitude

wind drafts changing altitude dueto wind drafts

desired less actual

altitudeadjustment time

changing altitude dueto speed increase

Wind Drafts and Altitude - With Control Loop42,000 feet

40 miles/hour

37,000 feet0 miles/hour

32,000 feet-40 miles/hour

0 2 4 6 8 10 12 14 16 18 20Time (Minute)

desired altitude : NoControlLoop feetAltitude : NoControlLoop feetwind drafts : NoControlLoop miles/hour

Control Loop40000

1

With Control Loop

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Planesplane

purchases

availablepassenger milesS

actual passengermiles

S

target increase inplanes

S

Burrs personalgrowth target

S

true servicecapacity

NewStaff

ExperiencedStaffhiring induction departures

max hiringrate

proportionaccepted

S

S

interviewsS size of hiringteam

S

interview rateS

priority tohiring

S

turnover

S

S

time to gainexperience

OS

MotivationS

growth rate

normalproductivity

effectiveexperienced staff

hiddencoaching

S

S

S

ServiceReputation

change in qualityof service

time to perceivequality

service qualityOOS

potentialpassenger miles

PotentialPassengersloss of potential

passengersincrease of

potential passengers

S

relative fare

churnS

CompetitorFarechange in

competitor fare

time to changecosts O

Peoples fare

OOS

S

SO

S

S

conversionratio

O

S

relative productivity ofnew to experienced staff

S

O S

S

S

O

Schange inmotivation

S

time to changemotivation

O

load factorS

S

Morecroft’s Dynamic Hypothesis for People Express Airlines

“People Express’ resource accumulation processes…include a tangible resource system

that contains three reinforcing feedback loops, each a compelling engine of growth in its own right...These three growth

engines…drive the kind of spectacular growth actually achieved by People Express….But, the three engines of tangible resource growth are not well coordinated because the underlying policies governing resource accumulation are so different. As fleet expansion and passenger growth begin to outstrip staff expansion, problems become evident in the intangibles of perceived service level, customer satisfaction, and employee motivation. No management action is taken to fix these problems, however, because: (1) the unmanaged intangible resources initially provide relatively

weak signals to the rest of the organization of latent growth stresses; and (2) the powerful logics underlying the policies governing tangible resource accumulation are insensitive to such weak signals. This seeming lack of alignment of resource accumulation policies, leading to a virtual paralysis in the face of growing problems, and, eventually as impending doom, is symptomatic of a loss of management coordination under conditions of dynamic complexity.”3,pages35&36

People Express Airlines Performance

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Resource Performance200 plane

20 B passenger*mile/year2 fraction4 dmnl

100 plane10 B passenger*mile/year

1 fraction2 dmnl

0 plane0 passenger*mile/year0 fraction0 dmnl

1980 1981 1982 1983 1984 1985 1986 1987 1988Time (year)

Planes : Current planeactual passenger miles : Current passenger*mile/yeartrue service capacity : Current passenger*mile/yearService Reputation : Current fractionMotivation : Current dmnl

time to changecosts

Burrs personalgrowth target coaching loadpriority to hiring time to gain

experience

40.7 0.30.2

2

23

Agenda



24

The following is from:

published in 1988

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Elementary School

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Intermediate Grades

The Middle (Junior High) School Years.

The High School Years.

Software• Vensim PLE (free for educational use – to run models

Paul showed, & to create & save your own models)– Download Vensim PLE (Personal Learning Edition) from

http://vensim.com/freedownload.html– When installing,

• uncheck the default checkbox that reads "Install Vensim PLE for evaluation purposes. Use limited to 60 days"

• check the checkbox for "Install Vensim PLE for academic, public research or personal use. Commercial, proprietary, classified or operational use not allowed.”

• Stella Trial Version (trial version is save-disabled, but will run models Dexter showed)– Download trial from http://www.iseesystems.com/

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http://vensim.com/freedownload.html

http://www.iseesystems.com/

Learning More: ST&DM in K12 Education

• Websites focused on ST&DM in K12 education:– http://clexchange.org/

• Read this paper: http://sysdyn.clexchange.org/sdep/papers/D-4434-3.pdf • Conference in June 2010, and not again until summer 2012:

http://clexchange.org/conference/cle_2010conference_registrationinfo.html• Jay Forrester: founder of the field:

http://sysdyn.clexchange.org/people/jay-forrester.html – http://www.watersfoundation.org/

• Among many other things, an online course for teachers• Books:

– Introduction to Systems Thinking with Stella, by Barry Richmond. http://www.iseesystems.com/store/college_university/books.aspx

– Thinking in Systems – A Primer (2008), by Donella Meadows. – Strategic Modelling and Business Dynamics: A Feedback Systems Approach (2007), by

John Morecroft– Modeling the Environment , 2nd edition (2010), by Andrew Ford– Many more books listed at:

• http://clexchange.org/lom/cle_books.htm• http://pegasuscom.com/

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http://clexchange.org/

http://sysdyn.clexchange.org/sdep/papers/D-4434-3.pdf

http://clexchange.org/conference/cle_2010conference_registrationinfo.html

http://sysdyn.clexchange.org/people/jay-forrester.html

http://www.watersfoundation.org/

http://www.iseesystems.com/store/college_university/books.aspx

http://clexchange.org/lom/cle_books.htm

http://pegasuscom.com/

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Stuff We Didn’t Get To(but maybe we’ll cover these another day…)

• People Express Airlines Example detail

• Paper Folding Exercise & Modeling

• Fishing in Bonavista, Newfoundland game

• Standing & holding hands in a circle loops exercise

• High School economics simulation

• Systems Thinking Skills

Modeling in HS Science

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Examples shown by Dr. Dexter ChapinScience teacher at Seattle Academy of Arts and Sciences

and

Author of the book, “Master Teachers: Making a Difference on the Edge of Chaos”http://www.amazon.com/Master-Teachers-Making-Difference-Chaos/dp/1578868637/ref=reader_auth_dp

Intern story – Dexter’s student Sarah

http://www.amazon.com/Master-Teachers-Making-Difference-Chaos/dp/1578868637/ref=reader_auth_dp

http://www.amazon.com/Master-Teachers-Making-Difference-Chaos/dp/1578868637/ref=reader_auth_dp

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History of People Express Videos

http://blog.flightwisdom.com/2009/07/31/history-people-express/

In the presentation, we will only view one or two of the videos here.The others are well worth watching to get the whole story.

http://blog.flightwisdom.com/2009/07/31/history-people-express/

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The Rise & Fall of People Express1a

Backgroundde-regulation of US airline industry in early 1980scharismatic founder Don Burrpassion for airlines and track record in the industry (credited with the

turnaround of Texas Air)

Spectacular Successfrom startup in 1981 to fifth largest US airline in 1986revenues in excess of $ 1 billion and 5000 employees by 1986deep discount prices and innovative people management policies

Even More Spectacular Failure“burned-out and bought out corporate carcass in only six months”2

36

People Express Problem Behavior1b

Passengers & Planes6 M pssngrs200 plane

3 M pssngrs100 plane

0 pssngrs0 plane

1980 1981 1982 1983 1984 1985 1986 1987 1988Time (year)

passengers : Current pssngrsPlanes : Current plane

What caused the success?

What caused the failure?

John Morecroft, of London Business School, analyses the causes using:1) Resource Based View (RBV)2) The notion of “dominant

logic”3) System dynamics (or more

commonly – systems thinking)

37

Toward a dynamic hypothesis:Tangible and Intangible Resources3,p34

• Tangible– Planes– Staff – Passengers

• Intangible– Service Reputation– Staff Morale

Note high degree of aggregation of resources!

Planes, staff and passengers could be greatly disaggregated, but , for Morecroft, such disaggregation is not necessary to explain the rise and fall of People Express.

The rise and fall depends on “dynamic” complexity” rather than “detail complexity.”

Dynamic complexity is present in business or social systems whenever cause and effect are subtle or where the effects over time of interventions are not obvious. For example, when an action has dramatically different effects in the short run and the long run, or when the local consequences of an action differ from consequences elsewhere in the system, then there is dynamic complexity.4

Burr'sPersonal

Growth Target

vision

Target Increase in Planes

Dominant Logic: FLEET EXPANSION(See P-Ex Planes.ITM1b)

Planes

PlanePurchases

Pool of Readily Available Used Planes, so no need to represent‘Planes in Construction‘. Planes have long lifetime, so no need to model outflow.

Note: Some “role” selects information to use for the “plane purchases” policy! (conceptual linkage to VNA?)

38

Toward a Dynamic Hypothesis

Dominant Logic: STAFF EXPANSION Recruitment Policy

(See P-Ex Staff.ITM1b)

size of thehiring teaminterviews

rigour of screening

New Staff

Hiring Induction

ExperiencedStaff labour market

Departures

labour market

servicecapacitystaff

productivity

Note: Some “role” selects information to use for the “hiring” policy! (conceptual linkage to VNA?)

39


Dominant Logic: PASSENGER GROWTHMarketing Policy: Word of Mouth

(See P-Ex Passengers.ITM1b)

Increase ofPotential

Passengers

Potential

PassengersPool of fliers in region served by People Express.Size depends on scope of service and convenience(routes and schedule)

Fliers with a favourable impression of People Express

Fliers hearing favourable comments about People Express

marketingspend

relative farelow, low price

conversion ratio

servicereputation

Loss ofPotential

Passengers

churn

Pool of fliers in region served by People Express

Fliers losing interest in People Express

Note: Some “role” selects information to use for the “increase of potential passengers” policy! (conceptual linkage to VNA?)

40


Toward a dynamic hypothesis:Summary of dominant feedback logic for tangible resources

Planes

dominant logic: Burr's vision of growth

Plane Purchases R

Potential

passengers

dominant logic: word-of-mouth

Increase ofPotentialpassengers

R

Experienced StaffNew Staff

dominant logic: selectivity and staff involvement

Hiring Induction

R

41

PEOPLE EXPRESS - THE SUCCESS STORYSimulations of P-Ex Full Model.ITM

42

ANALYSIS OF INTANGIBLE RESOURCES

service reputation

motivation

43


SERVICE REPUTATION An Invisible Intangible Resource – see P-Ex Full Model.ITM

Change ofService Reputation

Service Reputation

service quality as perceived by the flying public - based on accumulated experience and hearsay

service quality as experiencedon day of flying

currentservice quality

gap

passengermiles service

capacity

PotentialPassengers

dynamic complexitymasks link betweenservice quality and potential passengers

44


MOTIVATION AND PRODUCTIVITYMore Dynamic Complexity – see P-Ex Full Model.ITM

Change ofMotivation

StaffMotivation staff

productivity

growth

profitsharing

stockoptions

profits fleet size

performancerelated factors

work teams &minimal hierarchy

hard work culture

job rotation &simple work practices

participation &responsibility

quality of CSMs & selective recruiting

structural andcultural factorsBurr's 'people' precepts

indicated motivation

gap

45


46

Planesplane

purchases



S


S


S


NewStaff


max hiringrate

proportionaccepted

S

S


S

interview rateS

priority tohiring

S

turnover

S

S


OS

MotivationS

growth rate

normalproductivity


hiddencoaching

S

S

S

ServiceReputation



service qualityOOS





S

relative fare

churnS


competitor fare


Peoples fare

OOS

S

SO

S

S

conversionratio

O

S


S

O S

S

S

O


S


O

load factorS

S

Morecroft’s Dynamic Hypothesis based on his reading of the People Express Case – unfurled bit by bit on the following slides.

47

Planesplane

purchases



S


S

S

Fleet (planes) tangible resource management policy

48

Planesplane

purchases



S


S


S

S


PotentialPassengers increase of


S

relative fare


competitor fare


Peoples fare

OOS

S

S

S

conversionratio

O

S

Potential Passenger tangible resource management policy.

49

Planesplane

purchases



S


S


S

S


PotentialPassengers increase of


S

relative fare


competitor fare


Peoples fare

OOS

S

S

S

conversionratio

O

S

load factorS

S

More policy for fleet management.

50

Planesplane

purchases



S


S


S

S

ServiceReputation



service qualityO





S

relative fare

churnS


competitor fare


Peoples fare

OOS

S

SO

S

S

conversionratio

O

S

load factorS

S

Service reputation intangible resource management policy

51

Planesplane

purchases



S


S


S


S

MotivationS

growth rate


S

ServiceReputation



service qualityOS





S

relative fare

churnS


competitor fare


Peoples fare

OOS

S

SO

S

S

conversionratio

O

S


S


O

load factorS

S

Staff motivation intangible resource management policy

52

Planesplane

purchases



S


S


S


S

MotivationS

growth rate


S

ServiceReputation



service qualityOOS





S

relative fare

churnS


competitor fare


Peoples fare

OOS

S

SO

S

S

conversionratio

O

S


S


O

load factorS

S

Passenger effect on service quality, hence on service reputation and potential passenger loss rate.

53

Planesplane

purchases



S


S


S


NewStaff


max hiringrate

proportionaccepted

S

S


S

interview rateS

priority tohiring

S

turnover

S

S


OS

MotivationS

growth rate

normalproductivity


hiddencoaching

S

S

S

ServiceReputation



service qualityOOS





S

relative fare

churnS


competitor fare


Peoples fare

OOS

S

SO

S

S

conversionratio

O

S


S

O S

S

S

O


S


O

load factorS

S

Staff resource tangible resource management policy

54

Planesplane

purchases



S


S


S


NewStaff


max hiringrate

proportionaccepted

S

S


S

interview rateS

priority tohiring

S

turnover

S

S


OS

MotivationS

growth rate

normalproductivity


hiddencoaching

S

S

S

ServiceReputation



service qualityOOS





S

relative fare

churnS


competitor fare


Peoples fare

OOS

S

SO

S

S

conversionratio

O

S


S

O S

S

S

O


S


O

load factorS

S

Morecroft’s Dynamic Hypothesis“People Express’ resource accumulation processes…include a tangible resource system

that contains three reinforcing feedback loops, each a compelling engine of growth in its own right...These three growth

engines…drive the kind of spectacular growth actually achieved by People Express….But, the three engines of tangible resource growth are not well coordinated because the underlying policies governing resource accumulation are so different. As fleet expansion and passenger growth begin to outstrip staff expansion, problems become evident in the intangibles of perceived service level, customer satisfaction, and employee motivation. No management action is taken to fix these problems, however, because: (1) the unmanaged intangible resources initially provide relatively

weak signals to the rest of the organization of latent growth stresses; and (2) the powerful logics underlying the policies governing tangible resource accumulation are insensitive to such weak signals. This seeming lack of alignment of resource accumulation policies, leading to a virtual paralysis in the face of growing problems, and, eventually as impending doom, is symptomatic of a loss of management coordination under conditions of dynamic complexity.”3,pages35&36

55

Planes

plane purchases

service days peryear

passenger miles perplane day

availablepassenger miles

S


S

load factorSO

growth reductionfrom load

Otarget increase inplanes O

S Burrs personalgrowth target


New Staff ExperiencedStaff

hiring induction departures

total staff

SS

O

max hiring rateproportionaccepted

interviewssize of hiring team

interview ratepriority to hiring

maximum staff perplane

limit on staff

S

turnover

S

S


O

S

Motivation

change ofmotivation

S

growth rate

indicatedmotivation

S

S

O


normalproductivity


Shidden coaching

coaching load

S

S

O

O

S

S

OS

ServiceReputation

change in quality ofservice


service quality

O

O

S


flights per year

miles per flight

maximum marketsize multipleroute share limitaverage carriers

per route

maximumpassenger miles

route saturation

O

S


passengersincrease of potential

passengers

effect of routesaturation

S

O

S

relative fare

churnS

CompetitorFare

change incompetitor fare

time to changecosts

O

date Peoples fare

OO

S

S

SSO

S

S

gross profitrevenue

<Peoples fare>

<actual passengermiles>

operating cost ofplanes cost of service

unit operating cost <Planes>

staff per plane

<total staff> cost of staff

fraction servicecost

rookie fraction

<ExperiencedStaff>

<New Staff>

potential servicecapacity

<Motivation> <normalproductivity>

passengers<flights per year>

<miles per flight>

initial planes

load factorinfluence time

initial potentialpassengers

initial competitorfare

<Time>

conversion ratio

O

S

initial experiencedstaff

initial new staff

S


S

initial motivation

initial servvicereputation

cost multiple

<actual passengermiles>

vision of servicetime to perceive

service reputation

initial growth rate

time to perceivegrowth

<ServiceReputation>

Sketch of Morecroft’s Full Simulation Model

56

Resource Performance

1980 1981 1982 1983 1984 1985 1986 1987 1988Time (year)

Planes : BaseSim planepassenger*mile/yearactual passenger miles : BaseSim

true service capacity : BaseSim passenger*mile/yearService Reputation : BaseSim fraction

200 plane

100 plane

0 plane

20 B passenger*mile/year

10 B passenger*mile/year

0 passenger*mile/year

2 fraction

1 fraction

0 fraction

4 dmnl

2 dmnl

0 dmnl

Motivation : BaseSim dmnl

Simulation of Morecroft’s Dynamic Hypothesis…

Does that Morecroft’s hypothesis CAN create the behavior-over-time of interest mean that his hypothesis is correct?

…shows that his hypothesis CAN create the behavior-over-time of interest!

Peter Senge’s Dynamic Hypothesis for the rise and fall of People’s Express2(Fig1)

57

Which dynamic hypothesis, Senge’s or Morecroft’s, is correct?

How do we answer this question?

How does this systems stuff help us then, if it can’t definitively answer this question?

Having seen this case study, how do you think we use ST&DM at Boeing?

58

We model interesting behaviors (problems?), not whole systems

We don’t model the whole system.

Instead we use the systems lens to model interesting (often problematic) behaviors-over-time.

The system we model contains only those elements of the whole system that are deemed necessary to give rise to the behaviors-over-time of interest.

The systems lens is not about answers, but about LEARNING to ask better questions.

System dynamics’ iterative modeling process

1. Problem Articulation(Boundary Selection)

3. Formulation4. Testing

5. PolicyFormulation& Evaluation

2. DynamicHypothesis

Figure 3-1 Results of any step can yield insights that lead to revisions in any earlier step (indicated by the links in the center of the diagram).

From Chapter 3, pages 83 – 105 in Sterman, John (2000) Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill

Monitoring and Evaluation

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Events

Behavior Patterns,Change over time

Systemic Structure

IncreasingLeverage

The Iceberg

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A leverage point – where small action yields large results

“Maybe we should write that spot down.” 61

Events

Behavior Patterns,Change over time

Systemic Structure

IncreasingLeverage

The Iceberg

Mental Models 62

Sometimes we get stuck in our mental models following rules that don't really exist

“Hey! They’re lighting their arrows!...Can they do that?”

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- Stock and flow diagrams (SFDs), or simply flow diagrams- Causal loop diagrams (CLDs)- Hybrid diagrams (add boxes to the stocks in a CLD)

Neither representation is better than the other.One’s choice depends on the nature of the problem, and one’s objective for producing the diagram (beyond the scope of today’s talk).

Three types of diagrams that

systems thinkers draw

Planesplane

purchases



S


S


S


NewStaff


max hiringrate

proportionaccepted

S

S


S

interview rateS

priority tohiring

S

turnover

S

S


OS

MotivationS

growth rate

normalproductivity


hiddencoaching

S

S

S

ServiceReputation



service qualityOOS





S

relative fare

churnS


competitor fare


Peoples fare

OOS

S

SO

S

S

conversionratio

O

S


S

O S

S

S

O


S


O

load factorS

S

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People Express References1) Morecroft, John (2007) Strategic Modelling and Business Dynamics, Wiley, including

book CD contents for Chapter 6, especiallya) Notes for using P-Ex model components.pdfb) People Express simulation models

2) Morecroft, John (2009) System Dynamics, RBV, and Behavioural Theories of Firm Performance: Lessons from People Express. Proceedings of the System Dynamics Society Conference, Albuquerque, NM 2009. http://www.systemdynamics.org

3) Morecroft, John, Ron Sanchez, Aime Heene (2002) Resource Management Under Dynamic Complexity, Chapter 2 in Systems Perspectives on Resources, Capabilities, and Management Processes.

4) Senge, Peter (1990 & 2006) The Fifth Discipline: The Art and Science of the Learning Organization. Doubleday

5) Morecroft, John, Ron Sanchez, Aime Heene (2002) Integrating Systems Thinking and Competence Concepts in a New View of Resources, Capabilities, and Management Processes; Chapter 1 in Systems Perspectives on Resources, Capabilities, and Management Processes.

http://www.systemdynamics.org/

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Stuff We Didn’t Get To(but could on another day, if you want to)

• People Express Airlines Example






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Paper Folding Exercise

From

The Systems Thinking Playbook: Exercises to Stretch and Build Learning and Systems Thinking Capabilities

By Linda Booth Sweeney and Dennis Meadows

http://www.amazon.com/Systems-Thinking-Playbook-Exercises-Capabilities/dp/1603582584/ref=sr_1_1?ie=UTF8&s=books&qid=1267883826&sr=1-1





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Harvested Fishery Behavior Over Time4,000 fish1,000 fish/year

80 ship

2,000 fish500 fish/year

40 ship

0 fish0 fish/year0 ship 0 5 10 15 20 25 30 35 40

Time (year)

Natural Fishery Behavior Over Time4,000 fish

2,000 fish

0 fish0 5 10 15 20 25 30 35 40

Time (year)Fish in the Sea : harvested fishery fishcatch rate : harvested fishery fish/yearShips at Sea : harvested fishery shipFish in the Sea : natural fishery fish

Bonavista, Newfoundland Fishing Simulation Game

Adapted from Morecroft, John (2007) Strategic Modelling and Business Dynamics. Wiley

Fish in theSeanet fish increase

rate

S

sea carryingcapacity

Crowding Loop

Net Growth Loop

density

O

S

catch rate

Fishing Loop

Ships inHarbor

purchase of newships this year

ships moved toharbor this year

initial fish stock

OS

Ships at Sea

So Bonavista adds 2 ships per year

Fish catch rate dramatically declines!

5 ships per year go out of business

But it is too late – we’re fin

ished!

Fishing is good!








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71

Standing and Holding Hands in a Circle Feedback Loops Exercise

From

The Systems Thinking Playbook: Exercises to Stretch and Build Learning and Systems Thinking Capabilities

By Linda Booth Sweeney and Dennis Meadows













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Figure 6-2 Four equivalent representations of stock and flow structure.

Hydraulic Metaphor:

Stock and Flow Diagram:

Integral Equation:

Differential Equation:

Stock (t) = Stock (to) + [ Inflow(s) – Outflow(s) ] dt òt0

t

Stockinflow outflow

d(Stock)/dt (t) = Net change in stock = Inflow (t) – Outflow (t)

[Sterman (2000), Chapter 6]

FourEquivalentRepresentations

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An Intimidating (to most people) Mathematical Model of the Structural Causes of Business Cycles

1) E = A + cY

2) dS/dt = Y - E

3) S* = hE*

4) Y = E* + μ(S* - S)

5) dE/dt = λ(E – E*)

E is national expenditure ($/time)A is autonomous expenditure ($/time)c is the marginal propensity to consume, 0 < c < 1Y is national output ($/time)

dS/dt is the net change in the level of inventories per unit time ($/time)S is the level of inventories ($)

S* is the desired level of inventories ($)h is a constant (h > 0), called the desired inventory-sales ratio (time)E* is expected (or planned) sales ($/time)

μ is a constant (μ > 0) of proportionality (1/time)

dE/dt is the change in expected sales per unit time ($/time/time)λ is a constant (λ > 0) of proportionality (1/time)

Richmond, Barry (1997) Sophisticated Dynamics Without Complex Mathematics, Stella Applications Guide, pp. 49-67 andScarfe, Brian L. (1977) Cycles, Growth Inflation: A Survey of Contemporary Macrodynamics.

74

marginal propensityto consume

desired inventory

ExpectedSales change in

expected sales fractional adjustment

desired inventorycoverage

autonomous spendingInventory

national production national sales

inventory correctionfractional correction

incomeinduced spending

An identical sketch illustrating the same model for the structural causes of business cycles

(= the aggregate expenditure that occurs within a macroeconomy, independent of the income of consumers within the economy)

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Inventory

desired inventory




autonomous spending


inventory correction

fractional correction


Which representation would be more meaningful to most people?

76

Inventory, Production and Sales250 $

1,000 $/Month

150 $800 $/Month

50 $600 $/Month

0 6 12 18 24 30 36 42 48 54 60Time (Month)

Inventory : Current $national production : Current $/Monthnational sales : Current $/Month


Inventory

desired inventory




autonomous spending


inventory correction

fractional correction


Sophisticated DynamicsWithout Complex Mathematics! (Really?)

Structure

produces

BehaviorIn response to autonomous spending increase of 25% at the fourth month.

Do you see anything “wrong” with this model?

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Figure 6-2 Four equivalent representations of stock and flow structure.

Hydraulic Metaphor:

Stock and Flow Diagram:

Integral Equation:

Differential Equation:

Stock (t) = Stock (to) + [ Inflow (s) – Outflow (s) ] ds òt0

t

Stockinflow outflow

d(Stock)/dt (t) = Net change in stock = Inflow (t) – Outflow (t)

[Sterman (2000), Chapter 6]

FourEquivalentRepresentations

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Systems Thinking Skills• 10,000 meter thinking1

• System as cause thinking1

• Dynamic thinking1,2

• Operational thinking1,2

• Closed-loop thinking1,2

• Non-linear thinking1

• Scientific thinking1,2

• Empathic thinking1

• Continuum thinking2

• Generic thinking2

• Structural thinking2

• Quantitative Thinking3

1) Richmond, Barry (2001) Systems Thinking and the Stella Software: Thinking, Communicating, Learning, and Acting More Effectively in the New Millenium, Chapter 1 in Richmond, Barry (2001) An Introduction to Systems Thinking. Available in print from High Performance Systems, Inc. Hanover, NH. www.iseesystems.com

2) Richmond, Barry (1993) Systems thinking: critical thinking skills for the 1990s and beyond. System Dynamics Review Vol. 9 No 2. (Summer 1993) 113-133. Downloadable from www.clexchange.org.

3) Richmond, Barry (2002) In Search of a Clear Picture for Unifying our Community of Practice. Creative Learning Exchange’s 2002 Systems Thinking and Dynamic Modeling Conference in Durham, NH. Downloadable from http://www.clexchange.org/conference/cle_2002conference.htm 80

http://www.hps-inc.com/

http://www.clexchange.org/

http://www.clexchange.org/conference/cle_2002conference.htm

What distinguishes/defines Systems Thinking isa unique collection of thinking skills1

10,000 Meters ThinkingSystem as Cause ThinkingDynamic Thinking

Filtering Skills(what to include, what to omit;

and at what level of aggregation?)

Operational ThinkingClosed-loop ThinkingContinuum ThinkingNonlinear Thinking

Representing Skills(stocks, flows, converters,

feedback loops)

Quantitative ThinkingScientific Thinking

Simulating Skills(internally-consistent numbers;

controlled experiments)

1) This slide copied from Richmond, Barry (2002) In Search of a Clear Picture for Unifying our Community of Practice. Creative Learning Exchange’s 2002 Systems Thinking and Dynamic Modeling Conference in Durham, NH. Downloadable from http://www.clexchange.org/conference/cle_2002conference.htm

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http://www.clexchange.org/conference/cle_2002conference.htm

Thank you!

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Paul [email protected]


introduction to systems thinking and dynamic modeling (st&dm ): part i

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