XI - Forecasting Dumot Plus PDF

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exercise for midterm...

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Demand Forecasting Question midterm exam – Dumot Plus Vinet is the Operations Manager of a small business. One of his responsibilities is to forecast the demand for various products manufactured by the company Dumot Plus. To begin with, he separated the items with an independent demand from the items with a dependent demand. 1

Clearly explain why items with an independent demand require forecasts while items with a dependent demand do not. (3 points)

The table and graph below represent sales of product X.

© Logistics and Operations Management Department, HEC Montréal, 2010

2

In order to choose the forecasting method to use for product X, Mr. Vinet analyzes the information he has collected. What are the important characteristics of the demand pattern for product X?

For another product, Mr. Vinet analyzes the total monthly sales. He questions the results obtained last year by using the exponential smoothing method. The following table presents the forecast, actual demand, the individual error and the squared error.

© Logistics and Operations Management Department, HEC Montréal, 2010

January February March April May June July August September October November December

Forecast 218.70 215.37 210.54 223.55 203.26 212.03 216.50 218.75 209.08 219.81 205.58 208.66

Demand 215 210 225 201

Individual error -3.70 -5.37 14.46 -22.55

Squared error 13.69 28.84 209.18 508.67

217 219 208 221 204 209

4.97 2.50 -10.75 11.92 -15.81 3.42

24.75 6.24 115.57 142.21 249.88 11.69

Average

-0.32

121.63

Note: The values for December were voluntarily taken out. You do not need to calculate them. 3.

What is the smoothing factor (alpha) used by Mr. Vinet? Show your calculation.

4.

Fill in the boxes left blank in the table above.

5.

In your opinion, is the current method biased or not? Justify your answer with relevant calculations.

Demand Forecasting © Logistics and Operations Management Department, HEC Montréal, 2010

Solution midterm exam – Dumot Plus 1.

Demand for independent demand products comes from the market, the customers. It must be forecasted. From this forecast, we will calculate requirements for products with a dependent demand. For these items, we must plan instead of forecast.

2.

Seasonality over a 3-month period and random variations.

3.

α = 0.9 We can use the formula in either of its forms with any data in the table to get the same result.

4.

Demand for May: 212.03 = 0.9D + (0.1 x 203.26) where D = 213 Individual error: 213 – 203.26 = 9.74 Squared error: (9.74)2 = 94.87

5

Average cumulative error: -0.32 The model does not seem biased since the average cumulative error is close to 0 (slight negative bias).

© Logistics and Operations Management Department, HEC Montréal, 2010...