Scenario Planning VS Traditional Forecasting

 

    To gain some form of competitive advantage, companies from all industries need to accurately forecast demand. Without proper planning on what needs to be done for growth, the probability to lose clients or that competitive advantage is higher (Qi & Sadowski, 2001). Based on the complexity or uncertainty of the problem, it is not an easy task to achieve. Planning should be made based on the expected outcomes, considering the uncertainty of the future. Scenario planning and Traditional forecasting are two methods that can help to understand these expectations. In this piece of work, we are going to talk about these two methods.

Figure 1: scenaniro planning

            

    Before we start diving into the differences between scenario planning and traditional forecasting, we should first give a brief description of each of these methods. Scenario planning is a practice through which a group of experts plans for an uncertain future by exploring multiple possibilities of what might happen. This method is usually implemented by decision-makers and planners within an organization (Wade, 2012).  They need to identify all the external factors, early indicators, and potential outcomes before proceedings (fig. 1). On the other hand, traditional forecasting methods are the usage of historical data to make an optimal decision that maximizes some businesses metrics such as asset performance or revenue. The method can be both quantitative and qualitative to identify all independent variables and reduce the margin of errors. Some of these forecasting techniques include, but are not limited to, Delphi and regression analysis (Martin & Gerdsri, 2006).

Figure 2: traditional forecasting

 
    Considering each method and their prediction approach, we can draw the line on their differences. For instance, Scenario planning relies on few sets of scenarios while traditional forecasting methods use historical data to make similar predictions. As stated by Cumming and Carpenter (2003), relying on historical data to forecast business outcomes comes with a large margin of errors if you don’t take into consideration trends or novel events. Similarly, relying on a limited set of scenarios or biased scenarios can undermine the group's capacity to analyze uncertainty surrounding a decision. Also, there are potential conflicts that can emerge when a group of experts is underrepresented.

    Independently of the methods implemented to investigate multiple plausible futures, it is critical to understand the limitations and benefits of scenario planning and traditional forecasting before their adoption. Some decision-makers or planners have been able to combine the two methods to reduce the margin of errors and improve their performances.

References

1. Wade, W. (2012). Scenario planning: A field guide to the future. John Wiley & Sons.

1. Peterson, G. D., Cumming, G. S., & Carpenter, S. R. (2003). Scenario planning: a tool for conservation in an uncertain world. Conservation biology, 17(2), 358-366.

1. Daim, T. U., Rueda, G., Martin, H., & Gerdsri, P. (2006). Forecasting emerging technologies: Use of bibliometrics and patent analysis. Technological Forecasting and Social Change, 73(8), 981-1012.

1. Alon, I., Qi, M., & Sadowski, R. J. (2001). Forecasting aggregate retail sales:: a comparison of artificial neural networks and traditional methods. Journal of Retailing and Consumer Services, 8(3), 147-156.