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You are the supply chain manager for an electronics-manufacturing company. In this assignment, you will use the following data to obtain forecasts for your company through various forecasting techniques.
Quarter
Forecast
Actual Demand
Error
4Q 2008
200
220
1Q 2009
220
215
2Q 2009
215
210
3Q 2009
210
220
4Q 2009
220
225
1Q 2010
225
240
2Q 2010
240
255
3Q 2010
260
4Q 2010
270
1Q 2011
Do not use Microsoft Excel utilities for this assignment.
Using the three quarters moving average, find out the forecasts for 3Q 2010, 4Q 2010, and 1Q 2011.
Compute the forecasts for 3Q 2010, 4Q 2010, and 1Q 2011 using exponential smoothing with a smoothing factor of 0.6.
Compute the forecasts for all quarters of 2010 using the three quarter weighted moving average, with the most recent data weighted at 0.5, the second-most recent data weighted at 0.35, and the third-most recent data weighted at 0.15.
Using the data provided in the above table, explain what forecasting techniques are being used for 2008 and the first two quarters of 2009.
Computed the forecasting error using the exponential smoothing technique.
Computed the forecasting error using the weighted moving average method.
On the basis of your calculations, explain which technique provides the most accurate forecast for your company. Explain your answer with critical reasoning.
Quarter
Forecast
Actual Demand
Error
4Q 2008
200
220
1Q 2009
220
215
2Q 2009
215
210
3Q 2009
210
220
4Q 2009
220
225
1Q 2010
225
240
2Q 2010
240
255
3Q 2010
260
4Q 2010
270
1Q 2011
Explanation / Answer
For three Quarters moving average, we takae average of previous three Quarters to arrive at the new forecasted nos for the new Quarter
Based on this for 3Q 2010, the moving average is (240+225+220)/3 = 228
Similarly caclulated for other Quarters
THe Error is calculated as difference between Demand and Forecast
and Mean forecast error MAF, as mean of all errors and Mean Aboslute Deviation, MAD as average deviation of absolute values of All errors
Moving Average Technique
Explonential Smoothing
In this technique we use both Demand value and forecasted value of previous month to come with the new months forecasted nos
New Forecast value is = smoothing factor * Demand of previous month + (1-Smoothing factor)* forecast of previous month
With Smoothing facotr given = 0.6
The calculated forecast nos are
Similarly for weighted average , higher weighatage to most recent forecast volumes and lesser weights to older values
Have used three techinques to forecast
Forecasting error using exponential smoothing =
MAF = 9 and MAD = 11
similarly weighted moving average method = MAF =13 and MAD =16
On the basis of Calcilations Exponetial smoothing method has most accurate foreacst model since it has the least MAF and MAD. THis is because it incorporates the actual demand in its model. and its also forecasts the newer values based on the most recent forecast nos, i.e the older the time series values, the less important they become for the calculation of the forecast.The present forecast error is taken into account in subsequent forecasts.
Quarter Forecast Actual Demand Error Absoulte Error 4Q 2008 200 220 20 20 1Q 2009 220 215 -5 5 2Q 2009 215 210 -5 5 3Q 2009 210 220 10 10 4Q 2009 220 225 5 5 1Q 2010 225 240 15 15 2Q 2010 240 255 15 15 3Q 2010 228 260 32 32 4Q 2010 231 270 39 39 1Q 2011 233 MAF MAD 14 16Explonential Smoothing
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