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Consultant Essay

2454 words - 10 pages

Forecasting Methods Assignment
University of Phoenix
MGT 554: Operations Management 
Steven Williams
August 28, 2006

Forecasting can be defined as Estimating or predicting future events or conditions. Forecasts may be long-term or short-term. The techniques used may be quantitative (often making sue of computers) or qualitative. Quantitative forecasting models may be classified into (a) causal models in which independent variables are used to forecast dependent variables, and (b) time series models, which produce forecasts by extrapolating the historical values of the variables of interest by, e.g., moving averages.
Seasonal Model
Seasonality is a ...view middle of the document...

A seasonal index of 1.25 indicates that the expected value for that month is 25% greater than 1/12 of the overall average. A seasonal index of 80 indicates that the expected value for that month is 20% less than 1/12 of the overall average (Hossein, 1994-2006).
Deseasonalizing Process
Deseasonalizing the data, also called Seasonal Adjustment is the process of removing recurrent and periodic variations over a short time frame, e.g., weeks, quarters, months. Therefore, seasonal variations are regularly repeating movements in series values that can be tied to recurring events. The Deseasonalized data is obtained by simply dividing each time series observation by the corresponding seasonal index (Hossein, 1994-2006).
Almost all time series published by the US government are already deseasonalized using the seasonal index to unmasking the underlying trends in the data, which could have been caused by the seasonality factor (Hossein, 1994-2006).
Incorporating seasonality in a forecast is useful when the time series has both trend and seasonal components. The final step in the forecast is to use the seasonal index to adjust the trend projection. One simple way to forecast using a seasonal adjustment is to use a seasonal factor in combination with an appropriate underlying trend of total value of cycles (Hossein, 1994-2006).
Technological Forecasting Model
Technological forecasting is a subset of futures research. Futures research is an umbrella term which encompasses "any activity that improves understanding about the future consequences of present developments and choices" (Amara and Salanik, 1972, p. 415). In defining forecasting, the authors offer the following progression. Forecasting is:
1. A statement about the future,
2. A probabilistic statement about the future:
3. A probabilistic, reasonably definite statement about the future:
4. A probabilistic, reasonably definite statement about the future, based upon an evaluation of alternative possibilities. (Amara and Salanik, 1972, p. 415)
Technological forecasting includes "all efforts to project technological capabilities and to predict the invention and spread of technological innovations" (Ascher, 1979, p. 165). Martino (1983) states that a technological forecast includes four elements: the time of the forecast or the future date when the forecast is to be realized, the technology being forecast, the characteristics of the technology or the functional capabilities of the technology, and a statement about probability (Donnelly, n.d.).
Forecasting a technology is a difficult task and includes "the uncertainty and unreliability of data, the complexity of 'real world' feedback interactions, the temptation of wishful or emotional thinking, the fatal attraction of ideology, [and] the dangers of forcing soft and somewhat pliable 'facts' into a preconceived pattern" (Ayers, 1969, p. 18).
These methods also rely...

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