Forecasts are defined as “educated assumptions about future trends and events,” which are affected by technology, cultural changes, new products, competition, government laws and politics, and economic conditions, among others (David & David, 2017). Forecasting techniques are essential in almost all decision-making and while there have been many developed over the years, the selection of a method depends on the context of the forecast, the relevance and availability of historical data, the degree of accuracy, the time period, the cost and benefit, and the time available for making the analysis.
In general, there are three basic types: qualitative techniques, time series analysis and projection, and causal models.
My strategic plan proposes a market expansion for my current organization. Because it’s new, I believe the best model for me to use is a qualitative model, such as market research and historical analogy. Currently, one of our acquisitions does have this service line that we are not tapping into, so there is some historical data that I can use as a basis for my historical analogy piece. There is very little competition in this market within our geographical reach but there are other organizations that offer this service of which I will include in my market research.
David, F. R. & David, F. R. (2017). Strategic Management: A Competitive Advantage Approach, Concepts and Cases, 16th edition. Prentice Hall.
John C. ChambersSatinder K. MullickDonald D. Smith. (2014, August 01). How to Choose the Right Forecasting Technique. Retrieved from https://hbr.org/1971/07/how-to-choose-the-right-forecasting-technique
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