FORECASTING METHODS USED BY MANAGERS
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FORECASTING METHODS
Forecasting is a deliberate action to determine a possible future scenario as Graf, (2002) states. The business world has become a competitive pool and so each competitor always seeks an edge over the other. Forecasting helps managers to make the right decisions that would be beneficial to the business in the future.
Shah, (2009) illustrates two main types of forecasting methods; Qualitative and quantitative methods. The method picked depends on the following factors; level of detail, units of analysis, time horizon required, cost, ease of use and accuracy required. The qualitative approach is more of an opinion oriented hence it is, usually, subjective in most cases.
The quantitative method relies more on mathematical data and can be proved scientifically.
According to Graf (2002), ‘‘qualitative method is divided into; Executive opinion, market research and Delphi Method``. In the executive opinion, a group of managers come together and discusses among themselves the possible future scenarios and from these discussions they come up with forecasts. In the market research process, interviews are conducted to get consumer opinions on specific products and surveys are also used to determine trends. In the Delphi approach, a group of experts in that particular field comes together and using their knowledge and experience, generate future possible scenarios.
The quantitative method is composed of two major models; Time series model and casual model. The time series model uses past patterns to predict future events. Patterns within a specified period are analyzed and then the assumption is made that in the future similar patterns will occur with a few variations. The time series model contains elements such as naive, simple mean, moving average, weighted moving average and exponential smoothing. The casual model employs the concepts of action and reaction; it took that if a particular occurrence leads to a particular situation then in the future when such an incident occurs then the same situation is expected. The casual model, also known as associative model, also uses the concept of indicators to predict future scenarios. It uses the concepts of linear regression and multiple regressions, which is by large, an extension of linear regression.