## Measuring Forecast Accuracy in a Pharmacy

Read this article where forecasting approaches, along with a hybrid forecasting method are covered. What types of data can a company use in quantitative forecasts?

### Results and Discussion

#### Least Square Regression Model

Table 4. Actual and Forecasts using Least Squared Model

Month (x) Actual Sales (y) (million) XY X2 Forecast IEI IEI2 ǀEǀ/Y x100
1 25 25 1 32.92 7.92 62.73 31.68
2 29 58 4 32.42 3.42 11.70 11.79
3 28 84 9 31.92 3.92 15.37 14
4 35 140 16 31.42 3.58 12.82 10.23
5 33 165 25 30.92
2.18 4.75 6.61
6 32 192 36 30.42 1.58 2.50 4.94
7 36 252 49 29.92 6.08 36.97 16.89
8 41 328 64 29.42 11.58 134.10 28.24
9 45 405 81 28.92 16.08 258.57 35.73
10 20 200 100 28.42 18.42 339.30 92.1
11 23 253 121 27.92 4.92 24.21 21.39
12 15 180 144 27.42 12.42 154.25 82.8

78 362 2282 650

a= 33.42 b= -0.5

Therefore the regression line equation for forecast is F =

y = 33.42 + (-.5)X and (X=1=12) to generate the forecast for the 12 months.

The forecast accuracy performance measures are:

$\mathrm{MAD}=\Sigma / \mathrm{E} / / \mathrm{T}=92.1 / 12=7.675=7.68, \mathrm{MSE}=\Sigma / \mathrm{E} /{ }^{2} \mathrm{~T}=1057.27 / 12=88.11$

MAPE = (Absolute error / Actual Observed Value) × 1 00 = 356.4/12 = 29.7

Table 5. Summary of the results of the Forecast Accuracy Measures

Measure of Accuracy Moving Average Method Exponential Smoothing Method Least Cost Method