Futuring and Innovation: Planning and Forecasting I

CS875-2202C-01

Raphael Brown

Colorado Technical University

Instructor: Dr. Cynthia Calongne

Date: 03/31/22 

Scenario Planning Versus Traditional Planning

In their decision-making approach, decision-makers frequently encounter failure because they have a predisposition to rationality; however, they focus on only external variables, conflicts in information and knowledge, mental models built on biased premise or policy, and mental models built on biased premise or policy (Chermack, 2004). In contrast to standard forecasting methodologies, the scenario planning technique avoids many of the difficulties outlined by Chermack (2004) and allows for a more flexible approach to the decision-making process.

Scenario planning vs. traditional forecasting: Which is better?

Historical data is primarily relied upon by organizations that use standard forecasting models in their decision-making process (Stoll Quevedo, 2020). When data mining methods are used, forecasting models have a particular dependence on the data structure and the data processing techniques used on the data. To establish the findings' dependencies based on specified inputs and predicted links between the data, statistical analysis and visualization models use accurate computation and calculating methods that are precise (Stoll Quevedo, 2020). Typically, mean calculations and subsequent examination of the data to arrive at the mean value serve as a typical way for influencing judgments based on the statistical probability of a particular scenario or hypothesis in a given situation or hypothesis. As an alternative to the conventional way of forecasting future outcomes using statistical probability and strength, scenario planning has developed a new and unique method of influencing decision-making processes (Frum, 2013). It combines a more strategic approach to the decision-making process, rather than being connected to a statistically driven, most probable scenario, as is the case with traditional planning (Wade, 2012). While standard forecasting techniques are based on single-threaded dependencies ingrained in historical data, scenario planning considers other tactics that go beyond the statistically likely and into more possible futures instead of traditional forecasting approaches (Wade, 2012). Scenario planning considers a variety of extra aspects, both internal and external, to generate a large number of alternative outcomes that may be considered throughout the decision-making process. As seen by the movement of news transmission from conventional print media to online techniques, social and technical developments substantially influence the decision-making process, which has proven to be difficult to predict using statistical calculations in the past. Frum (2013) noted that scenario planning aims to reveal choices for managing the uncertain nature of the future while also controlling the increasing risks that businesses are confronting.

Scenario planning and traditional forecasting have several advantages and are both used.

Traditional forecasting tends to function as a more trustworthy decision-making process in highly statistically dependent circumstances where predictive behaviors are known. The number of influencing elements is relatively modest, unlike more recent forecasting methods. The use of scenario planning is more appropriate when a large number of components arise, the data is difficult to quantify, or when a firm statistical conclusion cannot be drawn from the available data. When compared to traditional forecasting methodologies, scenario planning offers several advantages, including a greater aperture of the organizational landscape because it takes 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/