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Demand Forecasting and Forecasting Error

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I need some help with Forecasting/Demand Planning. Can you assist me with the following attached information on an excel spreadsheet.

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Forecasting/Demand Planning

CASE: A chain of grocery stores had the following weekly demand cases for a particular brand of laundry soap:

WEEK 1 2 3 4 5 6 7 8 9 10

Demand 31 22 33 26 21 29 25 22 20 26

1. Develop three- and four-period moving average forecasts, and compute MSE for each.
Which provides the better forecasts? What would be your forecast for week 11?

2. Develop an exponential smoothing forecast with smoothing constants of x = 0.1 and
0.3. What would be your forecast for week 11?

3. Compute the tracking signal for each of your forecasts in parts 1 & 2. Is there any
evidence of bias?

4. Might a different model provide better results?

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Solution Summary

The solution provides a brief explanation of each of the forecasting methods (Moving Average, and Exponential Smoothing) as well as measures (Running Sum of Forecast Errors, Tracking Signal, Mean Squared Error, Mean Absolute Percentage Error, Mean Absolute Deviation) of forecast error. The attached Excel spreadsheet shows the formulas and the graphs to calculate these measures.

Solution Preview

Notice: for each question you have to create two charts and two sets of solutions. I am just providing you with the first set of solution and charts.

1. n-Month Moving Average: The average of the n most recent months.

2. Exponential Smoothing: The idea is similar to weighted moving average, but instead of choosing different weights for different periods, we only choose one parameter known as alpha. For detail description do a Google search and you will find lot of ...

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