IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v25y2009i4p813-825.html
   My bibliography  Save this article

Decision making and planning under low levels of predictability: Enhancing the scenario method

Author

Listed:
  • Wright, George
  • Goodwin, Paul

Abstract

In this paper we review and analyse scenario planning as an aid to anticipation of the future under conditions of low predictability. We examine how successful the method is in mitigating issues to do with inappropriate framing, cognitive and motivational bias, and inappropriate attributions of causality. Although we demonstrate that the scenario method contains weaknesses, we identify a potential for improvement. Four general principles that should help to enhance the role of scenario planning when predictability is low are discussed: (i) challenging mental frames, (ii) understanding human motivations, (iii) augmenting scenario planning through adopting the approach of crisis management, and (iv) assessing the flexibility, diversity, and insurability of strategic options in a structured option-against-scenario evaluation.

Suggested Citation

  • Wright, George & Goodwin, Paul, 2009. "Decision making and planning under low levels of predictability: Enhancing the scenario method," International Journal of Forecasting, Elsevier, vol. 25(4), pages 813-825, October.
    • Handle: RePEc:eee:intfor:v:25:y:2009:i:4:p:813-825
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169-2070(09)00091-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Green, Kesten C., 2002. "Forecasting decisions in conflict situations: a comparison of game theory, role-playing, and unaided judgement," International Journal of Forecasting, Elsevier, vol. 18(3), pages 321-344.
    2. Wright, George, 2002. "Game theory, game theorists, university students, role-playing and forecasting ability," International Journal of Forecasting, Elsevier, vol. 18(3), pages 383-387.
    3. Fildes, Robert & Goodwin, Paul & Lawrence, Michael & Nikolopoulos, Konstantinos, 2009. "Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning," International Journal of Forecasting, Elsevier, vol. 25(1), pages 3-23.
    4. Paul Goodwin & George Wright, 2001. "Enhancing Strategy Evaluation in Scenario Planning: a Role for Decision Analysis," Journal of Management Studies, Wiley Blackwell, vol. 38(1), pages 1-16, January.
    5. Wright, George & Cairns, George & Goodwin, Paul, 2009. "Teaching scenario planning: Lessons from practice in academe and business," European Journal of Operational Research, Elsevier, vol. 194(1), pages 323-335, April.
    6. Joseph F. Porac & Howard Thomas & Charles Baden‐Fuller, 1989. "Competitive Groups As Cognitive Communities: The Case Of Scottish Knitwear Manufacturers," Journal of Management Studies, Wiley Blackwell, vol. 26(4), pages 397-416, July.
    7. Orrell, David & McSharry, Patrick, 2009. "System economics: Overcoming the pitfalls of forecasting models via a multidisciplinary approach," International Journal of Forecasting, Elsevier, vol. 25(4), pages 734-743, October.
    8. Robert Fildes & Paul Goodwin, 2007. "Good and Bad Judgment in Forecasting: Lessons from Four Companies," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 5-10, Fall.
    9. George Burt & George Wright & Ron Bradfield & George Cairns & Kees van der Heijden, 2006. "The Role of Scenario Planning in Exploring the Environment in View of the Limitations of PEST and Its Derivatives," International Studies of Management & Organization, Taylor & Francis Journals, vol. 36(3), pages 50-76, January.
    10. John M Bryson, 2004. "What to do when Stakeholders matter," Public Management Review, Taylor & Francis Journals, vol. 6(1), pages 21-53, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Derbyshire, James & Wright, George, 2017. "Augmenting the intuitive logics scenario planning method for a more comprehensive analysis of causation," International Journal of Forecasting, Elsevier, vol. 33(1), pages 254-266.
    2. Litsiou, Konstantia & Polychronakis, Yiannis & Karami, Azhdar & Nikolopoulos, Konstantinos, 2022. "Relative performance of judgmental methods for forecasting the success of megaprojects," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1185-1196.
    3. Leitner, Johannes & Leopold-Wildburger, Ulrike, 2011. "Experiments on forecasting behavior with several sources of information - A review of the literature," European Journal of Operational Research, Elsevier, vol. 213(3), pages 459-469, September.
    4. Kunc, Martin & O'Brien, Frances A., 2017. "Exploring the development of a methodology for scenario use: Combining scenario and resource mapping approaches," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 150-159.
    5. Fildes, Robert & Goodwin, Paul, 2021. "Stability in the inefficient use of forecasting systems: A case study in a supply chain company," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1031-1046.
    6. Franses, Philip Hans & Legerstee, Rianne, 2013. "Do statistical forecasting models for SKU-level data benefit from including past expert knowledge?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 80-87.
    7. Legerstee, R. & Franses, Ph.H.B.F. & Paap, R., 2011. "Do experts incorporate statistical model forecasts and should they?," Econometric Institute Research Papers EI2011-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Sroginis, Anna & Fildes, Robert & Kourentzes, Nikolaos, 2023. "Use of contextual and model-based information in adjusting promotional forecasts," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1177-1191.
    9. Rianne Legerstee & Philip Hans Franses, 2014. "Do Experts’ SKU Forecasts Improve after Feedback?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 69-79, January.
    10. Förster, Bernadette & von der Gracht, Heiko, 2014. "Assessing Delphi panel composition for strategic foresight — A comparison of panels based on company-internal and external participants," Technological Forecasting and Social Change, Elsevier, vol. 84(C), pages 215-229.
    11. Goodwin, Paul, 2002. "Forecasting games: can game theory win?," International Journal of Forecasting, Elsevier, vol. 18(3), pages 369-374.
    12. Franses, Philip Hans & Kranendonk, Henk C. & Lanser, Debby, 2011. "One model and various experts: Evaluating Dutch macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 482-495.
    13. Wright, George & Rowe, Gene, 2011. "Group-based judgmental forecasting: An integration of extant knowledge and the development of priorities for a new research agenda," International Journal of Forecasting, Elsevier, vol. 27(1), pages 1-13, January.
    14. Green, Kesten C., 2002. "Embroiled in a conflict: who do you call?," International Journal of Forecasting, Elsevier, vol. 18(3), pages 389-395.
    15. Reimers, Stian & Harvey, Nigel, 2024. "Bars, lines and points: The effect of graph format on judgmental forecasting," International Journal of Forecasting, Elsevier, vol. 40(1), pages 44-61.
    16. repec:eee:intfor:v:27:y:2011:i:1:p:1-13 is not listed on IDEAS
    17. Önkal, Dilek & Zeynep Sayım, K. & Lawrence, Michael, 2012. "Wisdom of group forecasts: Does role-playing play a role?," Omega, Elsevier, vol. 40(6), pages 693-702.
    18. Kabak, Özgür & Ülengin, Füsun & Önsel Ekici, Şule, 2018. "Connecting logistics performance to export: A scenario-based approach," Research in Transportation Economics, Elsevier, vol. 70(C), pages 69-82.
    19. Spithourakis, Georgios P. & Petropoulos, Fotios & Nikolopoulos, Konstantinos & Assimakopoulos, Vassilios, 2015. "Amplifying the learning effects via a Forecasting and Foresight Support System," International Journal of Forecasting, Elsevier, vol. 31(1), pages 20-32.
    20. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.
    21. Wright, George & Cairns, George & Goodwin, Paul, 2009. "Teaching scenario planning: Lessons from practice in academe and business," European Journal of Operational Research, Elsevier, vol. 194(1), pages 323-335, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:intfor:v:25:y:2009:i:4:p:813-825. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.