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Scenario-based portfolio model for building robust and proactive strategies

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  • Vilkkumaa, Eeva
  • Liesiö, Juuso
  • Salo, Ahti
  • Ilmola-Sheppard, Leena

Abstract

In order to address major changes in the operational environment, companies can (i) define scenarios that characterize different alternatives for this environment, (ii) assign probabilities to these scenarios, (iii) evaluate the performance of strategic actions across the scenarios, and (iv) choose those actions that are expected to perform best. In this paper, we develop a portfolio model to support the selection of such strategic actions when the information about scenario probabilities is possibly incomplete and may depend on the selected actions. This model helps build a strategy that is robust in that it performs relatively well in view of all available probability information, and proactive in that it can help steer the future as reflected by the scenarios toward the desired direction. We also report a case study in which the model helped a group of Nordic, globally operating steel and engineering companies build a platform ecosystem strategy that accounts for uncertainties related to markets, politics, and technological development.

Suggested Citation

  • Vilkkumaa, Eeva & Liesiö, Juuso & Salo, Ahti & Ilmola-Sheppard, Leena, 2018. "Scenario-based portfolio model for building robust and proactive strategies," European Journal of Operational Research, Elsevier, vol. 266(1), pages 205-220.
    • Handle: RePEc:eee:ejores:v:266:y:2018:i:1:p:205-220
    DOI: 10.1016/j.ejor.2017.09.012
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    2. Ahti Salo, 2023. "On the boundaries of experimental research on scenario planning: A commentary on Derbyshire et al. (2022)," Futures & Foresight Science, John Wiley & Sons, vol. 5(2), June.
    3. Harju, Mikko & Liesiö, Juuso & Virtanen, Kai, 2019. "Spatial multi-attribute decision analysis: Axiomatic foundations and incomplete preference information," European Journal of Operational Research, Elsevier, vol. 275(1), pages 167-181.
    4. Liesiö, Juuso & Andelmin, Juho & Salo, Ahti, 2020. "Efficient allocation of resources to a portfolio of decision making units," European Journal of Operational Research, Elsevier, vol. 286(2), pages 619-636.
    5. Ahti Salo & Edoardo Tosoni & Juho Roponen & Derek W. Bunn, 2022. "Using cross‐impact analysis for probabilistic risk assessment," Futures & Foresight Science, John Wiley & Sons, vol. 4(2), June.
    6. Ian Durbach, 2019. "Scenario planning in the analytic hierarchy process," Futures & Foresight Science, John Wiley & Sons, vol. 1(2), June.
    7. Barbati, Maria & Corrente, Salvatore & Greco, Salvatore, 2020. "A general space-time model for combinatorial optimization problems (and not only)," Omega, Elsevier, vol. 96(C).
    8. Salo, Ahti & Andelmin, Juho & Oliveira, Fabricio, 2022. "Decision programming for mixed-integer multi-stage optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 299(2), pages 550-565.
    9. Seeve, Teemu & Vilkkumaa, Eeva, 2022. "Identifying and visualizing a diverse set of plausible scenarios for strategic planning," European Journal of Operational Research, Elsevier, vol. 298(2), pages 596-610.
    10. Liesiö, Juuso & Salo, Ahti & Keisler, Jeffrey M. & Morton, Alec, 2021. "Portfolio decision analysis: Recent developments and future prospects," European Journal of Operational Research, Elsevier, vol. 293(3), pages 811-825.
    11. Liesiö, Juuso & Xu, Peng & Kuosmanen, Timo, 2020. "Portfolio diversification based on stochastic dominance under incomplete probability information," European Journal of Operational Research, Elsevier, vol. 286(2), pages 755-768.
    12. Liesiö, Juuso & Kallio, Markku & Argyris, Nikolaos, 2023. "Incomplete risk-preference information in portfolio decision analysis," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1084-1098.

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