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Why systems thinking?. Because our logical deduction mechanisms are trained to induct linearly, not cyclically We don’t see the feedback loops Consequently, we don’t comprehend the opportunities for reinforcement or the consequences of limitations/constraints

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why systems thinking
Why systems thinking?
  • Because our logical deduction mechanisms are trained to induct linearly, not cyclically
  • We don’t see the feedback loops
  • Consequently, we don’t comprehend the opportunities for reinforcement or the consequences of limitations/constraints
  • Forrester: every decision, every action is embedded in an information feedback loop

Systems Presentation at Ole Miss

more motivation
More motivation
  • We are immersed in and victims of structures that we have little awareness of
  • Causes and their effects are often spatially and temporally separated
  • Today’s problems are yesterday’s solutions
  • To make good decisions we need to understand dynamic complexity, not detail complexity

Systems Presentation at Ole Miss

still more motivation
Still more motivation
  • The integration that comes from the application of information technology is creating complexity at a frenetic pace
  • Out of the complexity comes the potential for chaos and catastrophe

Systems Presentation at Ole Miss

key benefits of the st
Key Benefits of the ST
  • A deeper level of learning
    • Far better than a mere verbal description
  • A clear structural representation of the problem or process
  • A way to extract the behavioral implications from the structure and data
  • A “hands on” tool on which to conduct WHAT IF
senge s five disciplines
Senge’s Five Disciplines
  • Personal Mastery
      • because we need to be the very best we can be
  • Mental Models
      • because these are the basis of all decision-making
  • Shared Vision
      • because this galvanizes workers to pursue a common goal
  • Team Learning
      • because companies are organized into teams
  • Systems Thinking
      • because this is only tool for coping with complexity
reinforcement
Reinforcement
  • What were those experiments with rats???

Systems Presentation at Ole Miss

the saga of peoples air
The Saga of Peoples Air
  • A totally different airline
  • Founded in 1980 to provide low-cost, high-quality airline service to travelers in the Eastern U.S.
  • Grew to nation’s 5th largest carrier
  • Brought in a host of innovative human resource policies
  • In 1986 lost $133M in first six months, and was taken over by Texas Air
what brought peoples down
What brought PEOPLES down??
  • Many explanations
  • Some blame Burr’s “soft” people-oriented management policies
  • Some blamed the unions
  • Others blamed the use of Americans’ Sabre Reservation system
    • Load management could offer a limited number of low-cost seats while others were “full coach”
what variables to blame
What variables to blame?
  • Fleet variables
  • Human resource variables
  • Competitive factors
  • Financial variables
  • Policy Levers
fleet variables
Fleet variables
  • Planes
  • Capacity of aircraft
  • Routes
  • Scheduled flights
  • Competitor routes
  • Service hours per plane per day
  • Fuel efficiency
human resources
Service personnel

Aircraft personnel

Maintenance personnel

Hiring

Training

Turnover

Morale

Productivity

Experience

Team management

Job rotation

Stock ownership

Temporaries

Human resources
competitive factors
Competitive Factors
  • Market size
  • Market segments
  • Reputation
  • Service quality
  • Competitor service quality
  • Fares “load Management”
  • Competitor fares
financial variables
Revenues

Profit

Cost of plane operations

Cost of service operations

Cost of marketing

Wages

Stock price

Growth rate

Debt

Interest Rate

Financial variables
policy levers
Policy Levers
  • Buying planes
  • Hiring people
  • Pricing
  • Marketing expenditures
  • Service scope
enormous detail complexity
Enormous detail complexity
  • We could build a model that contained all of this detail
  • Or we could use the systems archetypes to disentangle this parable of complexity
systems thinking basics
Systems Thinking basics
  • Peruse relevant literature
  • Talk to people knowledgeable about the problem
  • List relevant variables
  • Describe causal interactions between variables
  • Fully delineate the causal diagram
  • Draw behavior over time graphs

Systems Presentation at Ole Miss

examples
Examples
  • Itch--scratch
  • population and growth rate of population
  • revenues, sales force size, sales
  • inventory, order rate, desired inventory,

Systems Presentation at Ole Miss

a single sector exponential growth model

A single-sector Exponential growth Model

Consider a simple population with infinite resources--food, water, air, etc. Given, mortality information in terms of birth and death rates, what is this population likely to grow to by a certain time?

exponentially growing population model
Exponentially growing population model
  • In 1900 there were just 1.65 billion people on the planet. Today, there are more than 6 billion people on the planet. Every year there are .04 births per capita and .028 deaths per capita.
  • The .04 births p er capita shall be referred to as a parameter called BIRTH RATE NORMAL

Systems Presentation at Ole Miss

experiments with growth models
Experiments with growth models
  • Models with only one rate and one state
  • Average lifetime death rates
  • cohorts
  • Models in which the exiting rate is not a function of its adjacent state
  • Including effects from other variables
    • ratios and table functions
what do we have in terms of loops
What do we have in terms of loops?
  • A growth loop certainly (reinforcing)
    • The airline, unlike WonderTech was investing in its capital equipment infrastructure
    • It was buying planes to accommodate the growth
  • A balancing loop
what archetypes
What archetypes?
  • LIMITS TO GROWTH
  • SHIFTING THE BURDEN
    • Erodiing goals (standards)
  • The combination of these produces a third archetype
    • The Growth and Underinvestment Archetype
    • This was first seen in the WonderTech Scenario
from causal diagram to schematic stock flow diagram
From Causal Diagram to Schematic (Stock & Flow) Diagram
  • Some simple causal models
  • Some associated schematic models
  • Some rules

Systems Presentation at Ole Miss

we know what that is
We know what that is

Systems Presentation at Ole Miss

how about this one
How about this one?

Systems Presentation at Ole Miss

we know what it is
We know what it is

Systems Presentation at Ole Miss

some rules
Some rules
  • There are two types of causal links in causal models
    • Information
    • Flow
  • Information proceeds from stocks and parameters toward rates where it is used to control flows
  • Flow edges proceed from rates to states (stocks) in the causal diagram always

Systems Presentation at Ole Miss

loops
Loops
  • In any loop involving a pair of quantities/edges,
  • one quantity must be a rate
  • the other a state or stock,
  • one edge must be a flow edge
  • the other an information edge

Systems Presentation at Ole Miss

consistency
CONSISTENCY
  • All of the edges directed toward a quantity are of the same type
  • All of the edges directed away from a quantity are of the same type

Systems Presentation at Ole Miss

rates and their edges
Rates and their edges

Systems Presentation at Ole Miss

parameters and their edges
Parameters and their edges

Systems Presentation at Ole Miss

stocks and their edges
Stocks and their edges

Systems Presentation at Ole Miss

auxiliaries and their edges
Auxiliaries and their edges

Systems Presentation at Ole Miss

outputs and their edges
Outputs and their edges

Systems Presentation at Ole Miss

step 1 identify parameters
STEP 1: Identify parameters
  • Parameters have no edges directed toward them

Systems Presentation at Ole Miss

step 2 identify the edges directed from parameters
STEP 2: Identify the edges directed from parameters
  • These are information edges always

Systems Presentation at Ole Miss

step 3 by consistency identify as many other edge types as you can
STEP 3: By consistency identify as many other edge types as you can

Systems Presentation at Ole Miss

step 4 look for loops involving a pair of quantities only
STEP 4: Look for loops involving a pair of quantities only
  • Use the rules identified above

Systems Presentation at Ole Miss

system dynamics software
System Dynamics Software
  • STELLA and I think
    • High Performance Systems, Inc.
    • best fit for K-12 education
  • Vensim
    • Ventana systems, Inc.
    • Free from downloading off their web site: www.vensim.com
    • Robust--including parametric data fitting and optimization
    • best fit for higher education
  • Powersim
    • What Arthur Andersen is using
what is system dynamics
What is system dynamics
  • A way to characterize systems as stocks and flows between stocks
  • Stocks are variables that accumulate the affects of other variables
  • Rates are variables the control the flows of material into andout of stocks
  • Auxiliaries are variables the modify information as it is passed from stocks to rates
nature s templates the archetypes
Nature’s Templates: the Archetypes
  • Structures of which we are unaware hold us prisoner
      • The swimmer scenario
  • Certain patterns of structure occur again and again: called ARCHETYPES
we are creating a language
We are creating a “language”
  • reinforcing feedback and balancing feedback are like the nouns and verbs
  • systems archetypes are the basic sentences
  • Behavior patterns appear again in all disciplines--biology, psychology, family therapy, economics, political science, ecology and management
  • Can result in the unification of knowledge across all fields
recurring behavior patterns
Recurring behavior patterns
  • Do we know how to recognize them?
  • Do we know how to describe them?
  • Do we know how to prescribe cures for them?
  • The ARCHETYPES describe these recurring behavior patterns
the archetypes
The ARCHETYPES
  • provide leverage points, intervention junctures at which substantial change can be brought about
  • put the systems perspective into practice
  • About a dozen systems ARCHETYPES have been identified
  • All ARCHETYPES are made up of the systems building blocks: reinforcing processes, balancing processes, delays
before attacking the archetypes we need to understand simple structures
Before attacking the ARCHETYPES we need to understand simple structures
  • the reinforcing feedback loop
  • the balancing feedback loop
  • THE DEMO
  • Pages 520-525 in Austin/Burns--your handout
archetype 1 limits to growth
ARCHETYPE 1: LIMITS TO GROWTH
  • A reinforcing process is set in motion to produce a desired result. It creates a spiral of success but also creates inadvertent secondary effects (manifested in a alancing process) that eventually slow down the success.
management principle relative to archetype 1
Management Principle relative to ARCHETYPE 1
  • Don’t push growth or success; remove the factors limiting growth
archetype 1 limits to growth1
ARCHETYPE 1: LIMITS TO GROWTH
  • Useful in all situations where growth bumps up against limits
  • Firms grow for a while, then plateau
  • Individuals get better for a while, then their personal growth slows.
  • Falling in love is kind of like this
      • The love begins to plateau as the couple get to know each other better
understanding the structure
Understanding the Structure
  • High-tech orgs grow rapidly because of ability to introduce new products
  • This growth plateaus as lead times become too long
how to achieve leverage
How to achieve Leverage
  • Most managers react to the slowing growth by puching harder on the reinforcing loop
  • Unfortunately, the more vigorously you push the familiar levels, the more strongly the balancing proces resists, and the more futile your efforts become.
  • Instead, concentrate on the balancing loop--changing the limiting factor
      • This is akin to Goldratt’s Theory of Constraints--remove the bottleneck, the impediment
applications to quality circles and jit
Applications to Quality Circles and JIT
  • Quality circles work best when there is even-handed emphasis on both balancing and reinforcing loops
  • JIT has had to focus on recalcitrant suppliers
  • THERE WILL ALWAYS BE MORE LIMITING PROCESSES
      • When once source of limitatiin is removed, another will surface
  • Growth eventually WILL STOP
create your own limits to growth story
Create your own LIMITS TO GROWTH story
  • Identify a limits to growth pattern in your own experience
  • Diagram it
    • What is growing
    • What might be limitations
    • Example--the COBA and University capital campaigns
    • NOW, LOOK FOR LEVERAGE
test your limits to growth model
Test your LIMITS TO GROWTH model
  • Talk to others about your perception
  • Test your ideas about leverage in small real-life experiments
  • Run and re-run the simulation model
  • Approach possible resistance and seek WIN-WIN strategies with them
archetype 2 shifting the burden
ARCHETYPE 2: shifting the burden
  • An underlying problem generates symptoms that demand attention. But the underlying problem is difficult for people to address, either because it is obscure or costly to confront. So people “shift the burden” of their problem to other solutions--well-intentioned, easy fixes that seem extremely efficient. Unfortunately the easier solutions only ameliorate the symptoms; they leave the underlying problem unaltered. The underlying problem grows worse and the system loses whatever abilities it had to solve the underlying problem.
the stereotype structure
The Stereotype Structure

Symptiom-Correcting

Process

Addictioin Loop

Problem-Correcting

Process

special case eroding goals
Special Case: Eroding Goals
  • Full employment meant 4% unemployment in the 60%, but 6 to 7% unemployment in the early 1980’s
  • Gramm-Rudman bill called for reaching a balanced budget by 1991, but this was shifted to 1993 and from 1993 to 1996 and from 1996 to 1998
  • “If all else fails, lower your goals..”
another example
Another Example

Raise tuition, add course fees, etc.

Costs of Higher Ed not funded by State

Perceived cost to the student

Lower enrollments

still another example
Still Another Example

Symptom-correcting

process

Addiction Loop

Problem-correcting

Process

shifting the burden is an insidious problem
“Shifting the Burden” is an insidious problem
  • Is has a subtle reinforcing cycle
  • This increases dependence on the symptomatic solution
  • But eventually, the system loses the ability to apply the fundamental solution
  • The system collapses
senge says
Senge Says
  • Today’s problems are yesterday’s solutions
  • We tend to look for solutions where they are easiest to find
how to achieve leverage1
HOW TO ACHIEVE LEVERAGE
  • Must strengthen the fundamental response
    • Requires a long-term orientation and a shared vision
  • Must weaken the symptomatic response
    • Requires a willingness to tell the truth about these “solutions”
create your own shifting the burden story
Create your own “Shifting the Burden” Story
  • Is there a problem that is getting gradually worse over the long term?
  • Is the overall health of the system gradually worsening?
  • Is there a growing feeling of helplessness?
  • Have short-term fixes been applied?
      • The Casa Olay problem of using cupouns to generate business and then can’t get away from using the coupons because their customer base is hucked on coupons
to structure your problem
To structure your problem
  • Identify the problem
  • Next, identify a fundamental solution
  • Then, identify one or several symptomatic solutions
  • Finally, identify the possible negative “side effects” of the symptomatic solution
review
Review
  • We have now seen two of the basic systems archetypes.
    • The Limits to Growth Archetype
    • The Shifting the Burden Archetype
  • As the archetypes are mastered, they become combined into more elaborate systemic descriptions.
  • The basic “sentences” become parts of paragraphs
  • The simple stories become integrated into more involved stories
seeing structures not just trees
Seeing Structures, not just Trees
  • Helps us focus on what is important and what is not
  • Helps us determine what variables to focus on and which to play less attention to
wondertech the chapter 7 scenario
WonderTech: The Chapter 7 Scenario
  • A lesson in Growth and Underinvestment
  • What Senge gets out of this is the Growth and Underinvestment Archetype
    • A combination of variants of the Limits to Growth Archetype and the Shifting the Burden Archetype
the wondertech scenario
The WonderTech Scenario
  • WonderTech continues to invest in the growth side of the process. Sales grow but then plateau. Management puts more sales people into the field. Offers more incentives to sales force. But because of long lead times, customers wane. “Yes you have a great product, but you can’t deliver on your lead time promise of eight weeks. We know; we’ve heard from your other customers.” In fact, the company relaxed its lead-time standard out to twelve to sixteen weeks because of insufficient capacity.
what s happened
What’s happened?
  • WT’s management did not pay much attention to their delivery service. They mainly tracked sales, profits, market share and return on investment. WT’s managers waited until demand fell off before getting concerned about delivery times. But this is too late. The slow delivery time has already begun to correct itself. The management was not very concerned about the relaxed delivery time standard of eight weeks.
the wondertech scenario1
The WonderTech Scenario
  • The firm decides to build a new manufacturing facility. But the facility comes on line at a time when sales are declining and lead times are coming back to the eight-week standard.
  • Of every 10 startup companies, 5 will disappear with five years, only 4 survive into their tenth year and only 3 into their fifteenth year.
comments on the senge methodology
Comments on The Senge Methodology
  • Sees problems as conforming to a finite number of “archetypes”
  • Formulates models based on combinations of the archetypes
  • Addresses problem-driven situations
    • What about situations and systems that are technology-driven, dynamics-driven, exogenously-driven, anything but problem-driven
more comments on the senge methodology
More Comments on the Senge Methodology
  • But does this become sufficiently general to accommodate all dynamical “scenarios and situations”?
  • It is difficult to translate his archetypes and causal models into running system dynamics simulations
    • A lot of variables (RATE VARIABLES, specifically) get left out in terms of connections
more comments on the senge methodology1
More Comments on the Senge Methodology
  • The focus is on characterizing the dynamics, not on how to capture that in terms of stocks, flows and information paths
  • He doesn’t label his edges with “+” or “-” signs
another methodology the sector approach to sd model formulation
Another methodology: The Sector Approach to SD model formulation
  • Begin by identifying the sectors
    • A “sector” is all the structure associated with a single flow
    • There could be several states in a single sector
  • Determine the within-sector structure
    • Reuse existing “molecules” where possible
  • Determine the between-sector information infrastructure
    • There are no flows and therefore no stocks or rates here
a single sector exponential goal seeking model
A Single-sector Exponential goal-seeking Model
  • Sonya Magnova is a television retailer who wishes to maintain a desired inventory of DI television sets so that she doesn’t have to sell her demonstrator and show models. Sonya’s ordering policy is quite simple--adjust actual inventory I toward desired inventory DI so as to force these to conform as closely as possible. The initial inventory is Io. The time required for ordered inventory to be received is AT.
a two sector housing population model
A Two-sector Housing/population Model
  • A resort community in Colorado has determined that population growth in the area depends on the availability of hoousing as well as the persistent natural attractiveness of the area. Abundant housing attracts people at a greater rate than under normal conditions. The opposite is true when housing is tight. Area Residents also leave the community at a certain rate due primarily to the availability of housing.
two sector population housing model continued
Two-sector Population/housing Model, Continued
  • The housing construction iindustry, on the other hand, fluctuates depending on the land availability and housing desires. Abundant housing cuts back the construction of houses while the opposite is true when the housing situation is tight. Also, as land for residential development fills up (in this mountain valley), the construction rate decreases to the level of the demolition rate of houses.
what is the structure within each sector
What is the structure within each sector?
  • Determine state/rate interactions first
  • Determine necessary supportng infrastructure
    • PARAMETERS
    • AUXILIARIES
what does the structure within the population sector look like
What does the structure within the population sector look like?
  • RATES: in-migration, out-migration, net death rate
  • STATES: population
  • PARAMETERS: in-migration normal, out-migration normal, net death-rate normal
what does the structure within the housing sector look like
What does the structure within the housing sector look like?
  • RATES: construction rate, demolition rate
  • STATES: housing
  • AUXILIARIES: Land availability multiplier, land fraction occupied
  • PARAMETERS: normal housing construction, average lifetime of housing
  • PARAMETERS: land occupied by each unit, total residential land
what is the structure between sectors
What is the structure between sectors?
  • There are only AUXILIARIES, PARAMETERS, INPUTS and OUTPUTS
what are the between sector auxiliaries
What are the between-sector auxiliaries?
  • Housing desired
  • Housing ratio
  • Housing construction multiplier
  • Attractiveness for in-migration multiplier
  • PARAMETER: Housing units required per person
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