Traditional Forecasting vs. Scenario Planning

 Decision-makers often experience failure in their approach to making decisions based on a predisposition to rationality, focus on only external variables, conflicts in information and knowledge, and mental models built on biased premise or policy (Chermack, 2004).   While traditional forecasting methods leverage many of the pitfalls identified by Chermack (2004), the scenario planning methodology provides a more versatile approach in the decision-making process. 

Traditional Forecasting vs. Scenario Planning

Organizations leveraging traditional forecasting models in their decision-making process 

rely heavily on historical data (Stoll Quevedo, 2020). By applying data mining techniques, forecasting models have a specific dependency on data structure and the data processing applied to the data.  Statistical analysis and visualization models use exact computations and calculations to determine the results' dependencies based on identified inputs and hypothesized relationships between the data (Stoll Quevedo, 2020).  Typically, mean calculations and subsequent analysis of the data to the mean value serve as a standard method for influencing decisions based on a given situation or hypothesis's statistical likelihood.

While the statistical probability and strength depicted in numbers may serve as a traditional means for predicting future results, scenario planning has emerged as an alternate, innovative method for influencing decision making (Frum, 2013).   Scenario planning incorporates a more strategic approach to the decision-making process without being tied to a statistically driven, most likely scenario (Wade, 2012).  While traditional forecasting methods build upon single-threaded dependencies engrained in historical data, scenario planning looks at alternate strategies beyond the statistically probable into more potential futures (Wade, 2012).  Scenario planning also considers additional factors, both internal and external, in deriving multiple possible outcomes for consideration in the decision-making process.  As experienced in the migration of news delivery from traditional print media to online methods, social and technological changes significantly impact the decision-making process, which has shown to be challenging to derive by statistical calculations.  Frum (2013) argued that scenario planning goals seek to uncover options to manage the unknown nature of the future while managing emerging risk facing organizations. 

Benefits and Use of Traditional Forecasting and Scenario Planning

Traditional forecasting tends to serve a more reliable decision-making process in highly statistically dependent situations where predictive behaviors are known, and the number of influencing factors is relatively small.  Scenario planning serves as a more suitable approach when numerous factors emerge, the data is difficult to quantify, or when a strong statistical outcome cannot be derived.  

The benefits of the scenario planning approach over the traditional forecasting methodology include a wider aperture of the organizational landscape by taking into account the identification of multiple scenarios that could result from the data as well as the variety of factors that could impact the future beyond a prospective statistical probability (Frum, 2013).  

References

Chermack, T. J. (2004). Improving decision-making with scenario planning. Futures, 36(3), 295-309.

Frum, D. (2013, August 6). World Association of Newspapers Scenario Planning. Retrieved December 18, 2020, from http://personalexpertsystem.blogspot.com/2013/08/world-association-of-newspapers.html

Stoll Quevedo, F. C. (2020). A comparison of machine learning and traditional demand forecasting methods (Order No. 27833151). Available from ProQuest One Academic. (2447270249). Retrieved from https://proxy.cecybrary.com/login?url=https://www-proquest-com.proxy.cecybrary.com/dissertations-theses/comparison-machine-learning-traditional-demand/docview/2447270249/se-2?accountid=144789

Wade, W. (2012). Scenario Planning [Colorado Technical University (CTU)].  Retrieved from https://coloradotech.vitalsource.com/#/books/9781118237410/


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