1. 2/4/2000Systems Presentation at Ole Miss1 Why systems thinking? b Because our logical deduction mechanisms are trained to induct linearly, not cyclically b We don’t see the feedback loops b Consequently, we don’t comprehend the opportunities for reinforcement or the consequences of limitations/constraints b Forrester: every decision, every action is embedded in an information feedback loop

2. 2/4/2000Systems Presentation at Ole Miss2 More motivation b We are immersed in and victims of structures that we have little awareness of b Causes and their effects are often spatially and temporally separated b Today’s problems are yesterday’s solutions b To make good decisions we need to understand dynamic complexity, not detail complexity

3. 2/4/2000Systems Presentation at Ole Miss3 Still more motivation b The integration that comes from the application of information technology is creating complexity at a frenetic pace b Out of the complexity comes the potential for chaos and catastrophe

4. Key Benefits of the ST b A deeper level of learning Far better than a mere verbal descriptionFar better than a mere verbal description b A clear structural representation of the problem or process b A way to extract the behavioral implications from the structure and data b A “hands on” tool on which to conduct WHAT IF

5. Senge’s Five Disciplines b Personal Mastery –because we need to be the very best we can be b Mental Models –because these are the basis of all decision-making b Shared Vision –because this galvanizes workers to pursue a common goal b Team Learning –because companies are organized into teams b Systems Thinking –because this is only tool for coping with complexity

6. 2/4/2000Systems Presentation at Ole Miss6 Reinforcement b What were those experiments with rats???

7. 2/4/2000 The Saga of Peoples Air b A totally different airline b Founded in 1980 to provide low-cost, high- quality airline service to travelers in the Eastern U.S. b Grew to nation’s 5th largest carrier b Brought in a host of innovative human resource policies b In 1986 lost $133M in first six months, and was taken over by Texas Air

8. 2/4/2000 What brought PEOPLES down?? b Many explanations b Some blame Burr’s “soft” people-oriented management policies b Some blamed the unions b 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”Load management could offer a limited number of low-cost seats while others were “full coach”

9. 2/4/2000 What variables to blame? b Fleet variables b Human resource variables b Competitive factors b Financial variables b Policy Levers

10. 2/4/2000 Fleet variables b Planes b Capacity of aircraft b Routes b Scheduled flights b Competitor routes b Service hours per plane per day b Fuel efficiency

11. 2/4/2000 Human resources b Service personnel b Aircraft personnel b Maintenance personnel b Hiring b Training b Turnover b Morale b Productivity b Experience b Team management b Job rotation b Stock ownership b Temporaries

12. 2/4/2000 Competitive Factors b Market size b Market segments b Reputation b Service quality b Competitor service quality b Fares “load Management” b Competitor fares

13. 2/4/2000 Financial variables b Revenues b Profit b Cost of plane operations b Cost of service operations b Cost of marketing b Wages b Stock price b Growth rate b Debt b Interest Rate

14. 2/4/2000 Policy Levers b Buying planes b Hiring people b Pricing b Marketing expenditures b Service scope

15. 2/4/2000 Enormous detail complexity b We could build a model that contained all of this detail b Or we could use the systems archetypes to disentangle this parable of complexity

16. 2/4/2000Systems Presentation at Ole Miss16 Systems Thinking basics b Peruse relevant literature b Talk to people knowledgeable about the problem b List relevant variables b Describe causal interactions between variables b Fully delineate the causal diagram b Draw behavior over time graphs

17. 2/4/2000Systems Presentation at Ole Miss17 Examples b Itch--scratch b population and growth rate of population b revenues, sales force size, sales b inventory, order rate, desired inventory,

18. 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?

19. 2/4/2000Systems Presentation at Ole Miss19 Exponentially growing population model b 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. b The.04 births p er capita shall be referred to as a parameter called BIRTH RATE NORMAL

20. 2/4/2000 Experiments with growth models b Models with only one rate and one state b Average lifetime death rates b cohorts b Models in which the exiting rate is not a function of its adjacent state b Including effects from other variables ratios and table functionsratios and table functions

21. 2/4/2000 What do we have in terms of loops? b A growth loop certainly (reinforcing) The airline, unlike WonderTech was investing in its capital equipment infrastructureThe airline, unlike WonderTech was investing in its capital equipment infrastructure It was buying planes to accommodate the growthIt was buying planes to accommodate the growth b A balancing loop

22. 2/4/2000 What archetypes? b LIMITS TO GROWTH b SHIFTING THE BURDEN Erodiing goals (standards)Erodiing goals (standards) b The combination of these produces a third archetype The Growth and Underinvestment ArchetypeThe Growth and Underinvestment Archetype This was first seen in the WonderTech ScenarioThis was first seen in the WonderTech Scenario

23. 2/4/2000 The Simplified Structure--p. 133

24. 2/4/2000 The Simulation Structure-- Reinforcing Loop

25. 2/4/2000 The Simulation

26. 2/4/2000Systems Presentation at Ole Miss26 From Causal Diagram to Schematic (Stock & Flow) Diagram b Some simple causal models b Some associated schematic models b Some rules

27. 2/4/2000Systems Presentation at Ole Miss27 Can you construct the schematic model for this Causal model?

28. 2/4/2000Systems Presentation at Ole Miss28 We know what that is

29. 2/4/2000Systems Presentation at Ole Miss29 How about this one?

30. 2/4/2000Systems Presentation at Ole Miss30 We know what it is

31. 2/4/2000Systems Presentation at Ole Miss31 Some rules b There are two types of causal links in causal models InformationInformation FlowFlow b Information proceeds from stocks and parameters toward rates where it is used to control flows b Flow edges proceed from rates to states (stocks) in the causal diagram always

32. 2/4/2000Systems Presentation at Ole Miss32 Loops b In any loop involving a pair of quantities/edges, b one quantity must be a rate b the other a state or stock, b one edge must be a flow edge b the other an information edge

33. 2/4/2000Systems Presentation at Ole Miss33 CONSISTENCY b All of the edges directed toward a quantity are of the same type b All of the edges directed away from a quantity are of the same type

34. 2/4/2000Systems Presentation at Ole Miss34 Rates and their edges

35. 2/4/2000Systems Presentation at Ole Miss35 Parameters and their edges

36. 2/4/2000Systems Presentation at Ole Miss36 Stocks and their edges

37. 2/4/2000Systems Presentation at Ole Miss37 Auxiliaries and their edges

38. 2/4/2000Systems Presentation at Ole Miss38 Outputs and their edges

39. 2/4/2000Systems Presentation at Ole Miss39 STEP 1: Identify parameters b Parameters have no edges directed toward them

40. 2/4/2000Systems Presentation at Ole Miss40 STEP 2: Identify the edges directed from parameters b These are information edges always

41. 2/4/2000Systems Presentation at Ole Miss41 STEP 3: By consistency identify as many other edge types as you can

42. 2/4/2000Systems Presentation at Ole Miss42 STEP 4: Look for loops involving a pair of quantities only b Use the rules identified above

43. System Dynamics Software b STELLA and I think High Performance Systems, Inc.High Performance Systems, Inc. best fit for K-12 educationbest fit for K-12 education b Vensim Ventana systems, Inc.Ventana systems, Inc. Free from downloading off their web site: www.vensim.comFree from downloading off their web site: www.vensim.com Robust--including parametric data fitting and optimizationRobust--including parametric data fitting and optimization best fit for higher educationbest fit for higher education b Powersim What Arthur Andersen is usingWhat Arthur Andersen is using

44. What is system dynamics b A way to characterize systems as stocks and flows between stocks b Stocks are variables that accumulate the affects of other variables b Rates are variables the control the flows of material into andout of stocks b Auxiliaries are variables the modify information as it is passed from stocks to rates

45. A DEMO

46. 2/4/2000 Nature’s Templates: the Archetypes b Structures of which we are unaware hold us prisoner –The swimmer scenario b Certain patterns of structure occur again and again: called ARCHETYPES

47. 2/4/2000 We are creating a “language” b reinforcing feedback and balancing feedback are like the nouns and verbs b systems archetypes are the basic sentences b Behavior patterns appear again in all disciplines--biology, psychology, family therapy, economics, political science, ecology and management b Can result in the unification of knowledge across all fields

48. 2/4/2000 Recurring behavior patterns b Do we know how to recognize them? b Do we know how to describe them? b Do we know how to prescribe cures for them? b The ARCHETYPES describe these recurring behavior patterns

49. 2/4/2000 The ARCHETYPES b provide leverage points, intervention junctures at which substantial change can be brought about b put the systems perspective into practice b About a dozen systems ARCHETYPES have been identified b All ARCHETYPES are made up of the systems building blocks: reinforcing processes, balancing processes, delays

50. 2/4/2000 Before attacking the ARCHETYPES we need to understand simple structures b the reinforcing feedback loop b the balancing feedback loop b THE DEMO b Pages 520-525 in Austin/Burns--your handout

51. 2/4/2000 ARCHETYPE 1: LIMITS TO GROWTH b 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.

52. 2/4/2000 Management Principle relative to ARCHETYPE 1 b Don’t push growth or success; remove the factors limiting growth

53. 2/4/2000 ARCHETYPE 1: LIMITS TO GROWTH b Useful in all situations where growth bumps up against limits b Firms grow for a while, then plateau b Individuals get better for a while, then their personal growth slows. b Falling in love is kind of like this –The love begins to plateau as the couple get to know each other better

54. 2/4/2000 Structure

55. Understanding the Structure b High-tech orgs grow rapidly because of ability to introduce new products b This growth plateaus as lead times become too long

56. 2/4/2000 How to achieve Leverage b Most managers react to the slowing growth by puching harder on the reinforcing loop b Unfortunately, the more vigorously you push the familiar levels, the more strongly the balancing proces resists, and the more futile your efforts become. b Instead, concentrate on the balancing loop--changing the limiting factor –This is akin to Goldratt’s Theory of Constraints-- remove the bottleneck, the impediment

57. 2/4/2000 Applications to Quality Circles and JIT b Quality circles work best when there is even-handed emphasis on both balancing and reinforcing loops b JIT has had to focus on recalcitrant suppliers b THERE WILL ALWAYS BE MORE LIMITING PROCESSES –When once source of limitatiin is removed, another will surface b Growth eventually WILL STOP

58. 2/4/2000 Create your own LIMITS TO GROWTH story b Identify a limits to growth pattern in your own experience b Diagram it What is growingWhat is growing What might be limitationsWhat might be limitations Example--the COBA and University capital campaignsExample--the COBA and University capital campaigns NOW, LOOK FOR LEVERAGENOW, LOOK FOR LEVERAGE

59. 2/4/2000 Test your LIMITS TO GROWTH model b Talk to others about your perception b Test your ideas about leverage in small real-life experiments b Run and re-run the simulation model b Approach possible resistance and seek WIN-WIN strategies with them

60. 2/4/2000 ARCHETYPE 2: shifting the burden b 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.

61. 2/4/2000 The Stereotype Structure Symptiom-Correcting Process Problem-Correcting Process Addictioin Loop

62. 2/4/2000 Special Case: Eroding Goals b Full employment meant 4% unemployment in the 60%, but 6 to 7% unemployment in the early 1980’s b 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 b “If all else fails, lower your goals..”

63. 2/4/2000 EXAMPLE

64. Another Example Costs of Higher Ed not funded by State Raise tuition, add course fees, etc. Lower enrollments Perceived cost to the student

65. 2/4/2000 Still Another Example Symptom-correcting process Problem-correcting Process Addiction Loop

66. 2/4/2000 “Shifting the Burden” is an insidious problem b Is has a subtle reinforcing cycle b This increases dependence on the symptomatic solution b But eventually, the system loses the ability to apply the fundamental solution b The system collapses

67. 2/4/2000 Senge Says b Today’s problems are yesterday’s solutions b We tend to look for solutions where they are easiest to find

68. 2/4/2000 HOW TO ACHIEVE LEVERAGE b Must strengthen the fundamental response Requires a long-term orientation and a shared visionRequires a long-term orientation and a shared vision b Must weaken the symptomatic response Requires a willingness to tell the truth about these “solutions”Requires a willingness to tell the truth about these “solutions”

69. 2/4/2000 Create your own “Shifting the Burden” Story b Is there a problem that is getting gradually worse over the long term? b Is the overall health of the system gradually worsening? b Is there a growing feeling of helplessness? b 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

70. 2/4/2000 To structure your problem b Identify the problem b Next, identify a fundamental solution b Then, identify one or several symptomatic solutions b Finally, identify the possible negative “side effects” of the symptomatic solution

71. 2/4/2000 Review b We have now seen two of the basic systems archetypes. The Limits to Growth ArchetypeThe Limits to Growth Archetype The Shifting the Burden ArchetypeThe Shifting the Burden Archetype b As the archetypes are mastered, they become combined into more elaborate systemic descriptions. b The basic “sentences” become parts of paragraphs b The simple stories become integrated into more involved stories

72. 2/4/2000 Seeing Structures, not just Trees b Helps us focus on what is important and what is not b Helps us determine what variables to focus on and which to play less attention to

73. 2/4/2000 WonderTech: The Chapter 7 Scenario b A lesson in Growth and Underinvestment b 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 ArchetypeA combination of variants of the Limits to Growth Archetype and the Shifting the Burden Archetype

74. 2/4/2000 The WonderTech Scenario b 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.

75. The Reinforcing Loop

76. The Balancing Loop: Following the LTG Archetype

77. The Growth Curve: Page 117

78. What’s happened? b 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.

79. The WonderTech Scenario b 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. b 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.

80. The Shifting the Burden Component

81. Put the whole thing together

82. Comments on The Senge Methodology b Sees problems as conforming to a finite number of “archetypes” b Formulates models based on combinations of the archetypes b Addresses problem-driven situations What about situations and systems that are technology-driven, dynamics-driven, exogenously-driven, anything but problem- drivenWhat about situations and systems that are technology-driven, dynamics-driven, exogenously-driven, anything but problem- driven

83. More Comments on the Senge Methodology b But does this become sufficiently general to accommodate all dynamical “scenarios and situations”? b 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 connectionsA lot of variables (RATE VARIABLES, specifically) get left out in terms of connections

84. More Comments on the Senge Methodology b The focus is on characterizing the dynamics, not on how to capture that in terms of stocks, flows and information paths b He doesn’t label his edges with “+” or “-” signs

85. Another methodology: The Sector Approach to SD model formulation b Begin by identifying the sectors A “sector” is all the structure associated with a single flowA “sector” is all the structure associated with a single flow There could be several states in a single sectorThere could be several states in a single sector b Determine the within-sector structure Reuse existing “molecules” where possibleReuse existing “molecules” where possible b Determine the between-sector information infrastructure There are no flows and therefore no stocks or rates hereThere are no flows and therefore no stocks or rates here

86. 2/4/2000 A Single-sector Exponential goal-seeking Model b 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.

87. 2/4/2000 A Two-sector Housing/population Model b 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.

88. 2/4/2000 Two-sector Population/housing Model, Continued b 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.

89. 2/4/2000 What are the main sectors and how do these interact? b Population b Housing

90. 2/4/2000 What is the structure within each sector? b Determine state/rate interactions first b Determine necessary supportng infrastructure PARAMETERSPARAMETERS AUXILIARIESAUXILIARIES

91. 2/4/2000 What does the structure within the population sector look like? b RATES: in-migration, out-migration, net death rate b STATES: population b PARAMETERS: in-migration normal, out- migration normal, net death-rate normal

92. 2/4/2000 What does the structure within the housing sector look like? b RATES: construction rate, demolition rate b STATES: housing b AUXILIARIES: Land availability multiplier, land fraction occupied b PARAMETERS: normal housing construction, average lifetime of housing b PARAMETERS: land occupied by each unit, total residential land

93. 2/4/2000 What is the structure between sectors? b There are only AUXILIARIES, PARAMETERS, INPUTS and OUTPUTS

94. 2/4/2000 What are the between-sector auxiliaries? b Housing desired b Housing ratio b Housing construction multiplier b Attractiveness for in-migration multiplier b PARAMETER: Housing units required per person

95. 2/4/2000Systems Presentation at Ole Miss95