Kit KwanMGMT 3620Assignment 25/5/2008

DistCo Warehouse Forecasting

1. Select the best forecasting model and justify why it is better than other model.

Today, most company use forecasting model because it allows more accurate

seasonal forecasting than other models. There are a lot of forecasting techniques and

the models are going to use, here we use the Multiplicative Decomposition (Seasonal)

method and basic for smoothing the average of all data, and Exponential Smoothing.

How do we determine which model is the best for forecasting? The more accurate the

mode it is, the better for forecasting. Generally, the overall accuracy of any

forecasting model can be determined by comparing the forecasted values with the

actual or observed values. From the data we compute, then compare the data and pick

the best from 1996 to 2000 tends to decrease from quarter 1-2, quarter 2-3 tends to

increase, and quarter 3-4 tends to increase as well. Also, when we compute the

forecast error of MAD and MSE, we can see the lower the error the smaller MAD and

MSE, the most accurate forecast. Therefore, the Multiplicative decomposition method

is the better choice of forecasting model.

Forecasting Data (2001) (thousand of cases):

Quarters Unadjusted Forecast Seasonal Factor Adjusted Forecast1 258.8439 0.9883 255.80742 263.6052 0.8427 222.14283 268.3665 1.0515 282.18004 273.1279 1.1175 305.2336

2. What quarterly inventory is to be expected in each quarter of 2001?

We are comparing the 4 forecasting methods data above. We can see that the

Multiplicative Decomposition (Seasonal) has the smallest Mean Absolute Deviation

and also R (Correlation Coefficients), 0.9775, is close to 1. Therefore, this method is

more accurate than other method.

Forecasting Model MAD MSE R (Correlation Coefficient)Moving Average 20.7813 502.2891Exponential Smoothing 24.0913 698.0305Exponential Smoothing with trend 24.4737 771.7382Multiplicative Decomposition (Seasonal) 7.0555 66.7882 0.9755

3. Should DistCo acquire more warehouse capacity in 2001?

DistCo business in 2001 inventory forecasting data will growth up to 305.2336

thousand cases of product at the end of 4th quarter. This exceeds 25.2336 thousand

cases from its current maximum of 280 thousand cases. Therefore, I think we need to

have more space to build this business because the company’s management should

acquire other warehouse in 2001 and for the expansion in the future.

4. What are the potential factors that may affect the forecast accuracy of the model

you have selected?

Seasonal is the gradual upward or downward movement in time series that related

to weather ore holidays season. For example, the weather fluctuations that are

representative of the season are one factor affecting the seasonality. People are easier

to catch a cold in winter rather than in summer, because of the cold weather. Besides,

uncharacteristic weather patterns such as snow in summer would be considered

irregular influences. Seasonality is data pattern that repeats itself after a period of day,

weeks, moths or quarter. Therefore, we need to understand what season means to

make our business increasing or decreasing. Then we can have a plan to take care of

it. The following table provide seasonal based on the quarter from 1996 to 2000.

From this table, we can see the 4th quarter seems to have higher cases of product on

average than other quarter.

Table for the seasonal based on the quarter from 1996 to 2000:

Quarter Inventory DemandAverage Demand

(1996-2000)

Overall Average Demand

Seasonal Index

1996 1997 1998 1999 20001 176 189 205 223 239 206.4 208.85 0.98832 134 157 180 192 217 176.0 208.85 0.84273 186 195 212 234 271 219.6 208.85 1.05154 195 211 229 248 284 233.4 208.85 1.1175

Total 835.4 208.85

Finally, inflation can affect the demand and supply in the market. In the shortage,

price will increase which will cause the demand decrease. Therefore, the forecast may

not fit to the data we expect.