Scenario Planning vs Traditional Forecasting
Scenario Planning vs Traditional Forecasting
One of the most iconic methods of organizational planning
is scenario planning. In scenario
planning, organizations make flexible strategic plans based on different
scenarios, which are predicted as possible and considered based on the advantages,
disadvantages, and implications of each scenario. Scenario planning helps to
simplify a tremendous amount of data into a limited number of possibilities (Schoemaker,
1995). In traditional forecasting, however, the future outcome is predicted
based on historical data and trends. It utilizes statistical analysis,
historical patterns, and other quantitative methods to predict future events.
Typically, in scenario planning, an organization identifies
critical uncertainties, such as technology, economy, and social, that could
impact the organization’s strategic plans. Scenarios are created to reflect
different combinations of the major uncertainties, which adequately and coherently
describe possible future outcomes. The implications of each scenario are
analyzed, and robust and flexible strategies are developed to adapt to them
(Schoemaker, 1995).
In the traditional forecasting method of prediction, there
is a heavy dependence on the analysis of historical data such as sales figures
and market demands. This analysis is often through quantitative methods relying
on mathematical and statistical tools to project and make predictions about
relationships found between variables. Traditional forecasting is commonly used
in various fields, including finance, supply chain management, inventory
planning, and economics. Organizations use the predictions offered by
traditional forecasting to make educated decisions about production, inventory
levels, pricing, and market strategies.
Scenario Planning helps organizations take a
holistic look into various factors that can impact an organization’s future,
prepare for numerous possibilities, and build resilience by preparing for
multiple future possibilities, making them more adaptable to change. This
encourages creative and futuristic thinking, which fosters innovations and
alerts organizations to potential risks by analyzing trends. However, scenario
planning is resource-intensive, which serves as a blocker for smaller
companies. It is affected by the bias and subjectivity of expert opinions and
may overemphasize unlikely scenarios.
Traditional forecasting is data-driven and relies on
historical data, providing a basis for making data-driven decisions. This makes
its prediction accurate in the short term when historical patterns are stable
and reliable. It often offers efficient and more cost-effective short-term
predictions based on readily available data. The flaws of this method include
the rapidly changing environments, which may throw off the assumption that the
future will most likely resemble the past. Also, because it relies heavily on
quantitative methods of analysis, it neglects qualitative approaches such as
expert opinions.
In contrasting both scenario planning and traditional
forecasting, it is often the case to look at the approach, the focus, and
perspectives.
Approach
Scenario planning explores a range of possibilities and
focuses on understanding the implications of each scenario, but traditional
forecasting relies on historical data and the ability to establish
relationships between variables using statistical methods to make predictions
about future outcomes.
Focus
Scenario planning often incorporates qualitative data and
expert opinions, not just historical quantitative data. Traditional forecasting
is primarily quantitative, focusing on numerical data and mathematical models
and neglecting other methods of data collection
Perspective
In Scenario planning, scenarios can extend into the
long-term future, considering the impact of trends and uncertainties over a
more extended period, while traditional forecasting typically provides accurate
results for the short term but becomes less reliable for longer time horizons.
References
Chermack, T. J., & Lynham, S. A. (2002). Definitions and Outcome
Variables of Scenario Planning. Human Resource Development Review, 1(3),
366–383. https://doi.org/10.1177/1534484302013006.
GLOBIS Insights. (2023, July 28). Scenario planning: Thinking differently
about future innovation [Video]. YouTube. https://youtu.be/y-CccEPJJ7k
Kolog, E. A., Owusu, A., Devine, S.N., & Entee, E. (2020). Handbook of Research on Managing Information Systems in
Developing Economies https://www.igi-global.com/dictionary/data-avalanche/86041 DOI: 10.4018/978-1-7998-2610-1.ch002
Schoemaker, P. (1995). Scenario Planning: A Tool for Strategic Thinking. Sloan Management
Review, 36, 25-40.
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