Skip to main content
SpringerLink
Log in

Scenario-Driven Planning with System Dynamics

  • Reference work entry
Complex Systems in Finance and Econometrics

  • 2935 Accesses

Article Outline

Glossary

Definition of the Subject

Introduction

Environmental Turbulence and Future Uncertainty

SdP with SD: The Modeling Process ≡ Strategic Situation Formulation

Case 1: Cyprus' Environment and Hotel Profitability

Case 2: A Japanese Chemicals Keiretsu (JCK)

Future Directions

Bibliography

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 599.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 549.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

Mental model:

how one perceives cause and effect relations in a system, along with its boundary, i. e., exogenous variables, and the time horizon needed to articulate, formulate or frame a decision situation; one's implicit causal map of a system, sometimes linked to the reference performance scenarios it might produce.

Product:

either a physical good or an intangible service a firm delivers to its clients or customers.

Real option:

right and obligation to make a business decision, typically a tangible investment. The option to invest, for example, in a firm's store expansion. In contrast to financial ‘call’ and ‘put’ options, a strategic real option is not tradable. Any time it invests, a firm might be at once acquiring the strategic real options of expanding, downsizing or abandoning projects in future. Examples include research and development (abbreviated R&D), merger and acquisition (abbreviated M&A), licensing abroad and media options.

Scenario:

a postulated sequence or development of events trough time; via Latin scena ‘scene’, from Greek \({\sigma\kappa\eta\nu\acute{\eta}}\), skēnē ‘tent, stage’. In contrast to a forecast of what will happen in the future, a scenario shows what might happen. The term scenario must not be used loosely to mean situation. Macro‐environmental as well as industry-, task- or transactional‐environmental scenarios are merely inputs to the strategic objectives and real options a firm must subsequently explore through strategic scenarios, computed or simulated with an explicit, formal system dynamics (abbreviated SD) model of its strategic situation. Computed strategic scenarios create the multiple perspectives that strategic thinkers need to defeat the tyranny of dogmatism that often assails firms, governments and other social entities or organizations.

Scenario‐driven planning (abbreviated SdP):

to attain high performance through strategic flexibility, firms use the SdP management technology to create foresight and to anticipate the future with strategic real options, in situations where the business environment accelerates frequently and is highly complex or interdependent, thereby causing uncertainty.

Situation:

the set of circumstances in which a firm finds itself; its (strategic) state of affairs.

Strategic management process (abbreviated SMP):

geared at detecting environmental threats and turning them into opportunities, it proceeds from a firm's mission, vision and environmental constraints to strategic goals and objectives to strategy design or formulation to strategy implementation or strategic action to evaluation and control to learning through feedback (background, Fig. 2).

SMP-1 environmental scanning:

monitors, evaluates and disseminates knowledge about a firm's internal and external environments to its people. The internal environment contains strengths and weaknesses within the firm; the external shows future opportunities and threats (abbreviated SWOT).

SMP-2 mission:

a firm's purpose, raison d'être or reason for being.

SMP-3 objectives:

performance (P) goals that SMP often quantifies for some P metrics.

SMP-4 policy:

decision‐making guidelines that link strategy design or formulation to action or implementation tactics.

SMP-5 strategy:

a comprehensive plan that shows how a firm might achieve its mission and objectives. The three strategy levels are: corporate, business and process or functional.

SMP-6 strategy design or formulation:

the interactive, as opposed to antagonistic, interplay of strategic content and process that creates flexible long-range plans to turn future environmental threats into opportunities; includes internal strengths and weaknesses as well as strategic mission and objectives, and policy guidelines.

SMP-7 strategic action or implementation:

the process by which strategies and policies are put into action through the development of programs, processes, budgets and procedures.

SMP-8 evaluation and control:

sub‐process that monitors activities and performance, comparing actual results with desired performance.

SMP-9 learning through feedback:

occurs as knowledge about each SMP element enables improving previous SMP elements (background, Fig. 2).

System:

an organized group of interrelated components, elements or parts working together for a purpose; parts might be either goal seeking or purposeful.

System dynamics (abbreviated SD):

a lucid modeling method born from the need to manage business performance through time. Thanks to Forrester [23], who discovered that all change propagates itself through stock and flow sequences, and user‐friendly SD software (iThink \({^{\text{\fontfamily{cmr}\fontsize{2}{2}\selectfont\textregistered}}}\), Vensim \({^{\text{\fontfamily{cmr}\fontsize{2}{2}\selectfont\textregistered}}}\), etc.), SD models let managers see exactly how and why, like other biological and social organizations, business firms perform the way they do. Unlike other social sciences, SD shows exactly how feedback loops, i. e., circular cause and effect chains, each containing at least one time lag or delay, interact within a system to determine its performance through time.

Variable or metric:

something that changes either though time or among different entities at the same time. An internal change lever is a decision or policy variable that a strategy‐design modeling, or client, team controls. An external change trigger is an environmental or policy variable that a strategy‐design modeling team does not control. Both trigger and lever variables can initiate change and be either endogenous or exogenous to a model of a system.

Bibliography

Primary Literature

  1. Acar W (1983) Toward a theory of problem formulation and the planning of change: Causal mapping and dialectical debate in situation formulation. UMI, Ann Arbor

    Google Scholar 

  2. Ackoff RL (1981) Creating the corporate future. Wiley, New York

    Google Scholar 

  3. Ackoff RL, Emery FE (1972) On purposeful systems. Aldine‐Atherton, Chicago

    Google Scholar 

  4. Amara R, Lipinski AJ (1983) Business planning for an uncertain future: Scenarios and strategies. Pergamon, New York

    Google Scholar 

  5. Anderson TJ (2000) Real options analysis in strategic decision making: An applied approach in a dual options framework. J Appl Manag Stud 9(2):235–255

    Google Scholar 

  6. Ansoff HI (1985) Conceptual underpinnings of systematic strategic management. Eur J Oper Res 19(1):2–19

    Article  Google Scholar 

  7. Ansoff HI, McDonnell E (1990) Implanting strategic management, 2nd edn. Prentice‐Hall, New York

    Google Scholar 

  8. Brauers J, Weber M (1988) A new method of scenario analysis for strategic planning. J Forecast 7(1):31–47

    Article  Google Scholar 

  9. Brenkert AL (1998) Carbon dioxide emission estimates from fossil‐fuel burning, hydraulic cement production, and gas flaring for 1995 on a one degree grid cell basis. Oak Ridge National Laboratory, Carbon Dioxide Information Analysis Center, Oak Ridge, TN (Database: NDP-058A 2-1998)

    Google Scholar 

  10. Christensen CM (1997) The innovator's dilemma: When new technologies cause great firms to fail. Harvard Business School Press, Cambridge

    Google Scholar 

  11. CYSTAT (2000) Cyprus key figures: Tourism. The Statistical Service of Cyprus (CYSTAT), Nicosia

    Google Scholar 

  12. Daft RL, Weick KE (1984) Toward a model of organizations as interpretation systems. Acad Manag Rev 9:284–295

    Article  Google Scholar 

  13. de Geus AP (1992) Modelling to predict or to learn? Eur J Oper Res 59(1):1–5

    Article  Google Scholar 

  14. Dewey J (1938) Logic: The theory of inquiry. Holt, Rinehart and Winston, New York

    Google Scholar 

  15. Donaldson L (1992) The Weick stuff: Managing beyond games. Organ Sci 3(4):461–466

    Article  Google Scholar 

  16. Drucker J, Higgins M (2001) Hotel rage: Losing it in the lobby. Wall Street J (Fri 16 Feb):W1–W7

    Google Scholar 

  17. Duncan RB (1972) Characteristics of organizational environments and perceived environmental uncertainty. Adm Sci Q 17:313–327

    Article  Google Scholar 

  18. Eberlein RL (2002) Vensim\({^{\text{\fontfamily{cmr}\fontsize{2}{2}\selectfont\textregistered}}}\) PLE Software, V 5.2a. Ventana Systems Inc, Harvard

    Google Scholar 

  19. Eden C (1994) Cognitive mapping and problem structuring for system dynamics model building. Syst Dyn Rev 10(3):257–276

    Article  Google Scholar 

  20. Eden C (2004) Analyzing cognitive maps to help structure issues or problems. Eur J Oper Res 159:673–686

    Article  Google Scholar 

  21. Eilon S (1984) The Art of Reckoning: Analysis of performance criteria. Academic Press, London

    Google Scholar 

  22. Emery FE, Trist EL (1965) The causal texture of organizational environments. Hum Relat 18:21–32

    Article  Google Scholar 

  23. Forrester JW (1958) Industrial dynamics: A major breakthrough for decision makers. Harvard Bus Rev 36(4):37–66

    Google Scholar 

  24. Forrester JW (1961) Industrial dynamics. MIT Press, Cambridge

    Google Scholar 

  25. Forrester JW (1987) Lessons from system dynamics modeling. Syst Dyn Rev 3(2):136–149

    Article  Google Scholar 

  26. Forrester JW (1992) Policies, decisions and information sources for modeling. Eur J Oper Res 59(1):42–63

    Article  Google Scholar 

  27. Georgantzas NC (1995) Strategy design tradeoffs‐free. Hum Syst Manag 14(2):149–161

    Google Scholar 

  28. Georgantzas NC (2001) Simulation modeling. In: Warner M (ed) International encyclopedia of business and management, 2nd edn. Thomson Learning, London, pp 5861–5872

    Google Scholar 

  29. Georgantzas NC (2001) Virtual enterprise networks: The fifth element of corporate governance. Hum Syst Manag 20(3):171–188, with a 2003 reprint ICFAI J Corp Gov 2(4):67–91

    Google Scholar 

  30. Georgantzas NC (2003) Tourism dynamics: Cyprus' hotel value chain and profitability. Syst Dyn Rev 19(3):175–212

    Article  Google Scholar 

  31. Georgantzas NC (2007) Digest\({^{\text{\fontfamily{cmr}\fontsize{2}{2}\selectfont\textregistered}}}\) wisdom: Collaborate for win-win human systems. In: Shi Y et al (eds) Advances in multiple criteria decision making and human systems management. IOS Press, Amsterdam, pp 341–371

    Google Scholar 

  32. Georgantzas NC, Acar W (1995) Scenario‐driven planning: Learning to manage strategic uncertainty. Greenwood‐Quorum, Westport

    Google Scholar 

  33. Georgantzas NC, Katsamakas E (2007) Disruptive innovation strategy effects on hard-disk maker population: A system dynamics study. Inf Resour Manag J 20(2):90–107

    Google Scholar 

  34. Georgantzas NC, Sasai K, Schrömbgens P, Richtenburg K et al (2002) A chemical firm's penetration strategy, balance and profitability. In: Proc of the 20th international system dynamics society conference, 28 Jul–1 Aug, Villa Igiea, Palermo, Italy

    Google Scholar 

  35. Gharajedaghi J (1999) Systems thinking: Managing chaos and complexity – A platform for designing business architecture. Butterworth‐Heinemann, Boston

    Google Scholar 

  36. Godet M (1987) Scenarios and strategic management: Prospective et planification stratégique. Butterworths, London

    Google Scholar 

  37. Godet M, Roubelat F (1996) Creating the future: The use and misuse of scenarios. Long Range Plan 29(2):164–171

    Article  Google Scholar 

  38. Hax AC, Majluf NS (1996) The strategy concept and process: A pragmatic approach, 2nd edn. Prentice Hall, Upper Saddle River

    Google Scholar 

  39. Helmer O (1983) Looking forward. Sage, Beverly Hills

    Google Scholar 

  40. Hodgin RF (2001) Clear Lake Area Industry and Projections 2001. Center for Economic Development and Research, University of Houston‐Clear Lake, Houston

    Google Scholar 

  41. Huss WR, Honton EJ (1987) Scenario planning: What style should you use? Long Range Plan 20(4):21–29

    Article  Google Scholar 

  42. Istvan RL (1992) A new productivity paradigm for competitive advantage. Strateg Manag J 13(7):525–537

    Article  Google Scholar 

  43. Jarillo JC (1988) On strategic networks. Strateg Manag J 9(1):31–41

    Article  Google Scholar 

  44. Jarillo JC, Martínez JI (1990) Different roles for subsidiaries: The case of multinational corporations in Spain. Manag J 11(7):501–512

    Google Scholar 

  45. Kahn H, Wiener AJ (1967) The next thirty‐three years: A framework for speculation. Daedalus 96(3):705–732

    Google Scholar 

  46. Lissack MR, Roos J (1999) The next common sense: The e‑manager's guide to mastering complexity. Nicholas Brealey Publishing, London

    Google Scholar 

  47. Mason RO, Mitroff II (1981) Challenging strategic planning assumptions. Wiley, New York

    Google Scholar 

  48. Miller D, Friesen PH (1983) Strategy making and environment: The third link. Strateg Manag J 4:221–235

    Article  Google Scholar 

  49. Millet SM, Randles F (1986) Scenarios for strategic business planning: A case history for aerospace and defence companies. Interfaces. 16(6):64–72

    Article  Google Scholar 

  50. Mojtahedzadeh MT, Andersen D, Richardson GP (2004) Using Digest\({^{\text{\fontfamily{cmr}\fontsize{2}{2}\selectfont\textregistered}}}\) to implement the pathway participation method for detecting influential system structure. Syst Dyn Rev 20(1):1–20

    Article  Google Scholar 

  51. Moore GA (1991) Crossing the chasm. Harper‐Collins, New York

    Google Scholar 

  52. Morecroft JDW (1985) Rationality in the analysis of behavioral simulation models. Manag Sci 31:900–916

    Article  Google Scholar 

  53. Morecroft JDW (1988) System dynamics and microworlds for policymakers. Eur J Oper Res 35:310–320

    Article  Google Scholar 

  54. Nakicenovic N, Davidson O, Davis G et al (2000) Summary for policymakers–Emissions scenarios: A special report of working group III of the intergovernmental panel on climate change (IPCC). World Meteorological Organization (WMO) and United Nations Environment Programme (UNEP), New York

    Google Scholar 

  55. Nicolis JS (1986) Dynamics of hierarchical systems: An evolutionary approach. Springer, Berlin

    Google Scholar 

  56. Oliva R (2004) Model structure analysis through graph theory: Partition heuristics and feedback structure decomposition. Syst Dyn Rev 20(4):313–336

    Article  Google Scholar 

  57. Oliva R, Mojtahedzadeh MT (2004) Keep it simple: A dominance assessment of short feedback loops. In: Proc of the 22nd international system dynamics society conference, 25–29 July 2004, Keble College, Oxford University, Oxford UK

    Google Scholar 

  58. Ozbekhan H (1977) The future of Paris: A systems study in strategic urban planning. Philos Trans Royal Soc London. 387:523–544

    Google Scholar 

  59. Pascale RT (1984) Perspectives on strategy: The real story behind Honda's success. California Manag Rev 26(Spring):47–72

    Google Scholar 

  60. Pine BJ-I, Victor B, Boynton AC (1993) Making mass customization work. Harvard Bus Rev 71(5):108–115

    Google Scholar 

  61. Porter ME (1985) Competitive advantage: Creating and sustaining superior performance. Free Press, New York

    Google Scholar 

  62. Porter ME (1991) Towards a dynamic theory of strategy. Strateg Manag J 12(Winter Special Issue):95–117

    Article  Google Scholar 

  63. Randers J (1980) Guidelines for model conceptualization. In: Randers J (ed) Elements of the system dynamics method. MIT Press, Cambridge, pp 117–139

    Google Scholar 

  64. Raynor ME (2007) The strategy paradox: Why committing to success leads to failure [And What to Do About It]. Currency‐Doubleday, New York

    Google Scholar 

  65. Repenning NP (2003) Selling system dynamics to (other) social scientists. Syst Dyn Rev 19(4):303–327

    Article  Google Scholar 

  66. Richardson GP (1991) Feedback thought in social science and systems theory. University of Pennsylvania Press, Philadelphia

    Google Scholar 

  67. Richmond B et al (2006) iThink\({^{\text{\fontfamily{cmr}\fontsize{2}{2}\selectfont\textregistered}}}\) Software V 9.0.2. iSee Systems™, Lebanon

    Google Scholar 

  68. Schön D (1983) Organizational learning. In: Morgan G (ed) Beyond method. Sage, London

    Google Scholar 

  69. Schrage M (1991) Spreadsheets: Bulking up on data. San Francisco Examiner

    Google Scholar 

  70. Schwenk CR (1984) Cognitive simplification processes in strategic decision making. Strateg Manag J 5(2):111–128

    Article  Google Scholar 

  71. Senge PM, Sterman JD (1992) Systems thinking and organizational learning: Acting locally and thinking globally in the organization of the future. Eur J Oper Res 59(1):137–150

    Article  Google Scholar 

  72. Simon HA (1979) Rational decision making in business organizations. Am Econ Rev 69(4):497–509

    Google Scholar 

  73. Singer AE (1992) Strategy as rationality. Hum Syst Manag 11(1):7–21

    Google Scholar 

  74. Singer AE (1994) Strategy as moral philosophy. Strateg Manag J 15:191–213

    Article  Google Scholar 

  75. Sterman JD (2000) Business dynamics: Systems thinking and modeling for a complex world. Irwin McGraw‐Hill, Boston

    Google Scholar 

  76. Sterman JD, Wittenberg J (1999) Path dependence, competition and succession in the dynamics of scientific revolution. Organ Sci 10(3, Special issue: Application of complexity theory to organization science, May–Jun):322–341

    Article  Google Scholar 

  77. Turner F (1997) Foreword: Chaos and social science. In: Eve RA, Horsfall S, Lee ME (eds) Chaos, complexity and sociology. Sage, Thousand Oaks, pp xi–xxvii

    Google Scholar 

  78. Wack P (1985) Scenarios: Uncharted waters ahead. Harvard Bus Rev 63(5):73–89

    Google Scholar 

  79. Wack P (1985) Scenarios: Shooting the rapids. Harvard Bus Rev 63(6):139–150

    Google Scholar 

  80. Zeleny M (1988) Parallelism, integration, autocoordination and ambiguity in human support systems. In: Gupta MM, Yamakawa T (eds) Fuzzy logic in knowledge‐based systems, decision and control. Elsevier Science, North Holland, pp 107–122

    Google Scholar 

  81. Zeleny M (2005) Human systems management: Integrating knowledge, management and systems. World Scientific, Hackensack

    Book  Google Scholar 

  82. Zentner RD (1987) Scenarios and the chemical industry. Chem Marketing Manag (Spring):21–25

    Google Scholar 

Books and Reviews

  1. Bazerman MH, Watkins MD (2004) Predictable surprises: The disasters you should have seen coming and how to prevent them. Harvard Business School Press, Boston

    Google Scholar 

  2. Bower G, Morrow D (1990) Mental models in narrative comprehension. Science 247(4938):44–48

    Article  Google Scholar 

  3. Mittelstaedt RE (2005) Will your next mistake be fatal? Avoiding the chain of mistakes that can destroy your organization. Wharton School Publishing, Upper Saddle River

    Google Scholar 

  4. Morecroft JDW (2007) Strategic modeling and business dynamics: A feedback systems approach. Wiley, West Sussex

    Google Scholar 

  5. Schnaars SP (1989) Megamistakes: Forecasting and the myth of rapid technological change. The Free Press, New York

    Google Scholar 

  6. Schwartz P (1991) The art of the long view. Doubleday‐Currency, New York

    Google Scholar 

  7. Tuchman B (1985) The March of folly: From troy to vietnam. Ballantine Books, New York

    Google Scholar 

  8. Vennix JAM (1996) Group model building: Facilitating team learning using system dynamics. Wiley, Chichester

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Fordham University Business Schools, New York, USA

    Nicholas C. Georgantzas

Authors
  1. Nicholas C. Georgantzas
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. RAMTECH LIMITED, 122 Escalle Lane, Larkspur, CA, 94939, USA

    Robert A. Meyers Ph. D. (Editor-in-Chief) (Editor-in-Chief)

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag

About this entry

Cite this entry

Georgantzas, N.C. (2009). Scenario-Driven Planning with System Dynamics. In: Meyers, R. (eds) Complex Systems in Finance and Econometrics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7701-4_37

Download citation

  • DOI: https://doi.org/10.1007/978-1-4419-7701-4_37

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-7700-7

  • Online ISBN: 978-1-4419-7701-4

  • eBook Packages: Business and Economics

Publish with us

Policies and ethics

Search

Navigation