Scenario Planning

 

 

 

Out of several foresight methods, scenario-type planning is used the most – primarily because the method is future-focused, which paves way for the systematic utilization of knowledge from numerous experts in a particular field, and also aid in exploring the incorporated impact of a variety of doubts (Van der Heijden, et al., 2002). Due to the opportunity scenario-type planning provides by being able to envisage reasonable future states, strategies can be developed to avoid potential threats, to take advantage of chances, and to reduce risk as well (Remirez, & Selin, 2014). According to Varum and Melo (2010), bracing an organization for a variety of plausible futures is what scenario planning is about, not predicting the future. On the other hand, standard forecasting attempts to predict the future by relying on present and past data – this however breeds uncertainty because it does not entail the impact of novel scenarios in the future (Bradfield, et al., 2005). Nonetheless, standard forecasting tries to produce the right prediction most of the time.

A good example is the financial crises that took place in 2008 which was fomented by financial institutions. However, according to the Dahlem Report, academic economists failed to spot the crises beforehand due to their over-reliance on forecasting via mathematical models that indecorously assume economies and markets are integrally secure, and also ignores vivid influences like social factors, etc. (Colander, et al., 2009). These mathematical models usually fail to forecast sudden and important alterations in market conditions because the new events are not modeled in their test statistics. This is one of the reasons why scenario-type planning is considered to be more strategic and superior to quantitative forecasting models – it provides a greater level of preparedness and flexibility. Furthermore, scenario-type planning includes analyzing the relationship between forces like economical, technical, and social trends in order to elucidate the current state, in addition to stipulating awareness about the future (Sohrabi, 2018). The process is illustrated below.

  

 

In technology strategy development, scenario-type planning is often utilized (Tran, & Daim, 2008). This provides a variety of blueprints for me to use for future innovation efforts – like the impact emotion AI will have in the healthcare industry, specifically with mental health issues. 

 

 

 

 

 

 

 

References

Bradfield, R., Wright, G., Burt, G., Cairns, G., & Van Der Heijden, K. (2005). The origins and evolution of scenario techniques in long range business planning. Futures, 37(8), 795-812.

Colander, D., Föllmer, H., Haas, A., Goldberg, M. D., Juselius, K., Kirman, A., ... & Sloth, B. (2009). The financial crisis and the systemic failure of academic economics. Univ. of Copenhagen Dept. of Economics Discussion Paper, (09-03).

Ramírez, R., & Selin, C. (2014). Plausibility and probability in scenario planning. Foresight.

Sohrabi, S. (2018, July 27). Scenario Planning with AI for Risk Management - IBM Research. Retrieved August 23, 2020, from https://www.ibm.com/blogs/research/2018/07/ai-scenario-planning/

Tran, T. A., & Daim, T. (2008). A taxonomic review of methods and tools applied in technology assessment. Technological Forecasting and Social Change, 75(9), 1396-1405.

Van der Heijden, K., Bradfield, R., Burt, G., Cairns, G., & Wright, G. (2002). The sixth sense: Accelerating organizational learning with scenarios. John Wiley & Sons.

Varum, C. A., & Melo, C. (2010). Directions in scenario planning literature–A review of the past decades. Futures, 42(4), 355-369.