Quantitative Analysis for Management, 13/e

5.3 Measures of Forecast Accuracy

We discuss several different forecasting models in this chapter. To see how well one model works or to compare that model with other models, the forecast values are compared with the actual or observed values. The forecast error (or deviation) is defined as follows:

$$\text{Forecast} \text{error}=\text{Actual} \text{value}-\text{Forecast} \text{value}$$

One measure of accuracy is the mean absolute deviation (MAD). This is computed by taking the sum of the absolute values of the individual forecast errors and dividing by the number of errors (n):

$$\text{MAD}\text{=}\frac{\sum \left|\text{Forecast}\text{error}\right|}{n}$$ (5-1)

To illustrate how to compute the measures of accuracy, the naïve model will be used to forecast one period into the future. The naïve model does not attempt to address any of the ...