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Use of scenario planning as a theory‐driven evaluation tool

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  • James Derbyshire

Abstract

Theory‐driven evaluation (TDE) is an approach for prescribing an evaluation’s purposes, users and uses, general activities, strategies, and methods in the form of a “program theory.” While widely used, the literature highlights a number of common deficiencies in TDEs, among which is the tendency for underdeveloped program theories because of a lack of specificity on the theory‐creation process, and because the emergent nature of change renders it difficult to identify relevant theory a priori, leading to uncertainty. Theoretical underdevelopment may reduce the effectiveness of change initiatives and make their evaluation problematic due to a lack of clarity regarding what the program was originally expected to achieve, and how. This paper addresses this issue by showing that scenario planning can assist TDE by (a) making explicit initial causal logic and theory; (b) facilitating useful debate and discussion among multiple stakeholders; and (c) facilitating consideration of how contingent and complex causation may lead to unexpected outcomes, allowing for consideration of adaptations that may be needed as a program unfolds. This paper shows that scenario planning is highly congruent with a complex‐realist understanding of evaluation that emphasizes causal indeterminism. In sum, we show how scenario planning can be used as a TDE tool.

Suggested Citation

  • James Derbyshire, 2019. "Use of scenario planning as a theory‐driven evaluation tool," Futures & Foresight Science, John Wiley & Sons, vol. 1(1), March.
  • Handle: RePEc:wly:fufsci:v:1:y:2019:i:1:n:e1
    DOI: 10.1002/ffo2.1
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    1. Kupers, Roland & Wilkinson, Angela, 2014. "The Essence of Scenarios," University of Chicago Press Economics Books, University of Chicago Press, number 9789089645944.
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    4. 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.
    5. Wilkinson, Angela & Kupers, Roland & Mangalagiu, Diana, 2013. "How plausibility-based scenario practices are grappling with complexity to appreciate and address 21st century challenges," Technological Forecasting and Social Change, Elsevier, vol. 80(4), pages 699-710.
    6. 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.
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