Forecasting

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Forecasting is the process of estimation in unknown situations. Prediction is a similar, but more general term, and usually refers to estimation of time series, cross-sectional or longitudinal data. In more recent years, Forecasting has evolved into the practice of Demand Planning in every day business forecasting for manufacturing companies. The discipline of demand planning, also sometimes referred to as supply chain forecasting, embraces both statistical forecasting and consensus process.

Forecasting is commonly used in discussion of time-series data.

Contents

[edit] Categories of forecasting methods

[edit] Time series methods

Time series methods use historical data as the basis for estimating future outcomes.

[edit] Causal / econometric methods

Some forecasting methods use the assumption that it is possible to identify the underlying factors that might influence the variable that is being forecasted. For example, sales of umbrellas might be associated with weather conditions. If the causes are understood, projections of the influencing variables can be made and used in the forecast.

e.g. Box-Jenkins

[edit] Judgemental methods

Judgemental forecasting methods incorporate intuitive judgements, opinions and probability estimates.

[edit] Other methods

[edit] Forecasting accuracy

The forecast error is the difference between the forecast value and the actual value for the corresponding period.

\ E_t = Y_t - F_t

where E is the forecast error at period t, Y is the actual value at period t, and F is the forecast for period t.

Measures of aggregate error:

Mean Absolute Error (MAE) \ MAE = \frac{\sum_{t=1}^{N} |E_t|}{N}
Mean Absolute Percentage Error (MAPE) \ MAPE = \frac{\sum_{t=1}^N |\frac{E_t}{Y_t}|}{N}
Percent Mean Absolute Deviation (PMAD) \ PMAD = \frac{\sum_{t=1}^{N} |E_t|}{\sum_{t=1}^{N} |Y_t|}
Mean squared error (MSE) \ MSE = \frac{\sum_{t=1}^N {E_t^2}}{N}
Root Mean squared error (RMSE) \ RMSE = \sqrt{\frac{\sum_{t=1}^N {E_t^2}}{N}}

Please note that the business forecasters and demand planners in the industry refer to the PMAD as the MAPE, although they compute this volume weighted MAPE. Difference between MAPE and WMAPE is explained in Calculating Demand Forecast Accuracy

See also

[edit] Application of forecasting

Forecasting has application in many situations:

[edit] References

    • Armstrong, J. Scott (ed.) (2001). Principles of forecasting: a handbook for researchers and practitioners (in English). Norwell, Massachusetts: Kluwer Academic Publishers. ISBN 0-7923-7930-6. 
    • Kress, George J.; Snyder, John (30 May 1994). Forecasting and market analysis techniques: a practical approach (in English). Westport, Connecticut, London: Quorum Books. ISBN 0-89930-835-X. 

    [edit] See also


    [edit] External links

    [1] The main source of information about forecasting on the internet is the Forecasting Principles site, forecastingprinciples.com. Forecasting Principles summarizes all useful knowledge about forecasting for researchers, practitioners, and educators. It is provided as a public service by the International Institute of Forecasters. The Institute publishes the journals International Journal of Forecasting and Foresight, and organizes International Symposia on Forecasting and forecasting workshops.

    The Institute of Business forecasting is the organization that provides seminars and conferences in demand planning and supply chain forecasting. Articles from practitioners are published by the Journal of Business Forecasting.

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