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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
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
7
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
9
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
11
Agenda
• 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
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 Pan
5
0
0 2 4 6 8 10Time (Second)
in
Water In Glass : CurrentWater in Pan : Current
1
0 40
WaterGlass2.mdl
14
Water InGlass
+
spigot flow rate
initial water in glass
desired water inglass
gapO
SB
Water in the Glass & Spigot Flow Rate
4 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
initial water in glass
desired water inglass
Water in the Glass & Spigot Flow Rate
4 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
• 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
17
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
18
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 draftschanging altitude due to
wind drafts
desired less actual
altitude adjustmenttime
changing altitude due tospeed increase
• Desired state – 40,000 ft• Current state – variable• Actions – variable vertical winds• Feedback
19
20
Proportional Autopilot for Holding Altitude During Vertical Wind Drafts
Altitude
desired altitude
changing altitude
wind draftschanging altitude due
to wind draftsWind Drafts and Altitude - No Control Loop
42,000 feet40 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 draftschanging altitude due
to wind drafts
desired less actual
altitudeadjustment time
changing altitude dueto speed increase
Wind Drafts and Altitude - With Control Loop
42,000 feet40 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
21
Planes
planepurchases
availablepassenger milesS
actual passengermiles
S
target increase inplanes
S
Burrs personalgrowth target
S
true servicecapacity
NewStaff
ExperiencedStaff
hiring induction departures
max hiringrate
proportionaccepted
S
S
interviewsSsize of hiring
teamS
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
OO
S
S
S
O
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 factor
S
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
22
Resource Performance
200 plane20 B passenger*mile/year
2 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
• 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
24
The following is from:
published in 1988
25
Elementary School
26
27
28
29
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/
30
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/
31
32
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
33
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
34
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.
35
The Rise & Fall of People Express1a
Background
de-regulation of US airline industry in early 1980s
charismatic founder Don Burr
passion for airlines and track record in the industry (credited with the turnaround of Texas Air)
Spectacular Success
from startup in 1981 to fifth largest US airline in 1986
revenues in excess of $ 1 billion and 5000 employees by 1986
deep 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 & Planes
6 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 team
interviews
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
Toward a Dynamic Hypothesis
Dominant Logic: PASSENGER GROWTHMarketing Policy: Word of Mouth
(See P-Ex Passengers.ITM1b)
Increase ofPotential
Passengers
Potential
Passengers
Pool 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
Toward a dynamic hypothesis:Summary of dominant feedback logic for tangible resources
Planes
dominant logic: Burr's vision of growth
Plane Purchases
R
Potentialpassengers
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
Toward a Dynamic Hypothesis
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
Toward a Dynamic Hypothesis
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
Toward a Dynamic Hypothesis
46
Planes
planepurchases
availablepassenger milesS
actual passengermiles
S
target increase inplanes
S
Burrs personalgrowth target
S
true servicecapacity
NewStaff
ExperiencedStaff
hiring induction departures
max hiringrate
proportionaccepted
S
S
interviewsSsize of hiring
teamS
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
OO
S
S
S
O
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 factor
S
S
Morecroft’s Dynamic Hypothesis based on his reading of the People Express Case – unfurled bit by bit on the following slides.
47
Planes
planepurchases
availablepassenger milesS
target increase inplanes
S
Burrs personalgrowth target
S
S
Fleet (planes) tangible resource management policy
48
Planes
planepurchases
availablepassenger milesS
actual passengermiles
S
target increase inplanes
S
Burrs personalgrowth target
S
S
potentialpassenger miles
PotentialPassengers increase of
potential passengers
S
relative fare
CompetitorFarechange in
competitor fare
time to changecosts
O
Peoples fare
OO
S
S
S
S
conversionratio
O
S
Potential Passenger tangible resource management policy.
49
Planes
planepurchases
availablepassenger milesS
actual passengermiles
S
target increase inplanes
S
Burrs personalgrowth target
S
S
potentialpassenger miles
PotentialPassengers increase of
potential passengers
S
relative fare
CompetitorFarechange in
competitor fare
time to changecosts
O
Peoples fare
OO
S
S
S
S
conversionratio
O
S
load factor
S
S
More policy for fleet management.
50
Planes
planepurchases
availablepassenger milesS
actual passengermiles
S
target increase inplanes
S
Burrs personalgrowth target
S
S
ServiceReputation
change in qualityof service
time to perceivequality
service qualityO
potentialpassenger miles
PotentialPassengersloss of potential
passengersincrease of
potential passengers
S
relative fare
churnS
CompetitorFarechange in
competitor fare
time to changecosts
O
Peoples fare
OO
S
S
S
O
S
S
conversionratio
O
S
load factor
S
S
Service reputation intangible resource management policy
51
Planes
planepurchases
availablepassenger milesS
actual passengermiles
S
target increase inplanes
S
Burrs personalgrowth target
S
true servicecapacity
S
MotivationS
growth rate
effectiveexperienced staff
S
ServiceReputation
change in qualityof service
time to perceivequality
service qualityOS
potentialpassenger miles
PotentialPassengersloss of potential
passengersincrease of
potential passengers
S
relative fare
churnS
CompetitorFarechange in
competitor fare
time to changecosts
O
Peoples fare
OO
S
S
S
O
S
S
conversionratio
O
S
Schange inmotivation
S
time to changemotivation
O
load factor
S
S
Staff motivation intangible resource management policy
52
Planes
planepurchases
availablepassenger milesS
actual passengermiles
S
target increase inplanes
S
Burrs personalgrowth target
S
true servicecapacity
S
MotivationS
growth rate
effectiveexperienced staff
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
OO
S
S
S
O
S
S
conversionratio
O
S
Schange inmotivation
S
time to changemotivation
O
load factor
S
S
Passenger effect on service quality, hence on service reputation and potential passenger loss rate.
53
Planes
planepurchases
availablepassenger milesS
actual passengermiles
S
target increase inplanes
S
Burrs personalgrowth target
S
true servicecapacity
NewStaff
ExperiencedStaff
hiring induction departures
max hiringrate
proportionaccepted
S
S
interviewsSsize of hiring
teamS
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
OO
S
S
S
O
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 factor
S
S
Staff resource tangible resource management policy
54
Planes
planepurchases
availablepassenger milesS
actual passengermiles
S
target increase inplanes
S
Burrs personalgrowth target
S
true servicecapacity
NewStaff
ExperiencedStaff
hiring induction departures
max hiringrate
proportionaccepted
S
S
interviewsSsize of hiring
teamS
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
OO
S
S
S
O
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 factor
S
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
actual passengermiles
S
load factor
SO
growth reductionfrom load
Otarget increase inplanes O
SBurrs personalgrowth target
true servicecapacity
New StaffExperienced
Staffhiring induction departures
total staff
S
S
O
max hiring rateproportionaccepted
interviewssize of hiring team
interview ratepriority to hiring
maximum staff perplane
limit on staff
S
turnover
S
S
time to gainexperience
O
S
Motivation
change ofmotivation
S
growth rate
indicatedmotivation
S
S
O
time to changemotivation
normalproductivity
effectiveexperienced staff
Shidden coaching
coaching load
S
S
O
O
S
S
OS
ServiceReputation
change in quality ofservice
time to perceivequality
service quality
O
O
S
potentialpassenger miles
flights per year
miles per flight
maximum marketsize multipleroute share limitaverage carriers
per route
maximumpassenger miles
route saturation
O
S
PotentialPassengers
loss of potentialpassengers
increase of potentialpassengers
effect of routesaturation
S
O
S
relative fare
churnS
CompetitorFare
change incompetitor fare
time to changecosts
O
date Peoples fare
O
OS
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
relative productivity ofnew to experienced staff
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
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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
60
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?”
63
64
- 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
Planes
planepurchases
availablepassenger milesS
actual passengermiles
S
target increase inplanes
S
Burrs personalgrowth target
S
true servicecapacity
NewStaff
ExperiencedStaff
hiring induction departures
max hiringrate
proportionaccepted
S
S
interviewsSsize of hiring
teamS
interview rate
Spriority to
hiring
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 quality
OOS
potentialpassenger miles
PotentialPassengersloss of potential
passengersincrease of
potential passengers
S
relative fare
churnS
CompetitorFarechange in
competitor fare
time to changecosts
O
Peoples fare
OO
S
S
S
O
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 factor
S
S
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People Express References
1) 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.
66
Stuff We Didn’t Get To(but could on another day, if you want to)
• People Express Airlines Example
• Paper Folding Exercise & Modeling
• Fishing in Bonavista, Newfoundland game
• Standing & holding hands in a circle loops exercise
• High School economics simulation
• Systems Thinking Skills
67
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
68
Stuff We Didn’t Get To(but could on another day, if you want to)
• People Express Airlines Example
• Paper Folding Exercise & Modeling
• Fishing in Bonavista, Newfoundland game
• Standing & holding hands in a circle loops exercise
• High School economics simulation
• Systems Thinking Skills
69
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 dramatic
ally declin
es!
5 ships per year g
o out of b
usiness
But it is
too la
te – we’re
finished!
Fishing is good!
Stuff We Didn’t Get To(but could on another day, if you want to)
• People Express Airlines Example
• Paper Folding Exercise & Modeling
• Fishing in Bonavista, Newfoundland game
• Standing & holding hands in a circle loops exercise
• High School economics simulation
• Systems Thinking Skills
70
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
http://www.amazon.com/Systems-Thinking-Playbook-Exercises-Capabilities/dp/1603582584/ref=sr_1_1?ie=UTF8&s=books&qid=1267883826&sr=1-1
Stuff We Didn’t Get To(but could on another day, if you want to)
• People Express Airlines Example
• Paper Folding Exercise & Modeling
• Fishing in Bonavista, Newfoundland game
• Standing & holding hands in a circle loops exercise
• High School economics simulation
• Systems Thinking Skills
72
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
73
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 salesfractional 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)
75
marginal propensityto consume
Inventory
desired inventory
ExpectedSales change in
expected salesfractional adjustment
desired inventorycoverage
autonomous spending
national production national sales
inventory correction
fractional correction
incomeinduced spending
Which representation would be more meaningful to most people?
76
Inventory, Production and Sales
250 $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
marginal propensityto consume
Inventory
desired inventory
ExpectedSales change in
expected salesfractional adjustment
desired inventorycoverage
autonomous spending
national production national sales
inventory correction
fractional correction
incomeinduced spending
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?
77
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
78
Stuff We Didn’t Get To(but could on another day, if you want to)
• People Express Airlines Example
• Paper Folding Exercise & Modeling
• Fishing in Bonavista, Newfoundland game
• Standing & holding hands in a circle loops exercise
• High School economics simulation
• Systems Thinking Skills
79
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
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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