Consider monthly demand for the abc corporation as shown in

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Reference no: EM13383130

Consider monthly demand for the ABC Corporation as shown in the table below. With these demand values, estimate a static (non adaptive) linear regression to identify static values of level, trend, and seasonality. To do this you will need to follow these steps we went through in class: de-seasonalize demand, calculate and run the linear regression for the de-seasonalized demand, calculate the seasonal factors, and estimate the forecast that incorporates these seasonal factors into the de-seasonalized regression.

Please present a table with your results below

Based on the level, trend, and seasonality values that you calculated and the changes that demand has experienced over time, what would be the simplest adaptive (dynamic) forecasting approach would you suggest ABC should follow to predict future demand as accurately as possible? Please answer this question after presenting your results' table below. Please justify this part of your answer conceptually. You do not need to perform any calculations.

Monthly Demand for ABC Corporation
*Sales*	*Year1*	*Year 2*	*Year 3*	*Year 4*	*Year 5*
January	2,000	3,000	2,000	5,000	5,000
February	3,000	4,000	5,000	4,000	2,000
March	3,000	3,000	5,000	4,000	3,000
April	3,000	5,000	3,000	2,000	2,000
May	4,000	5,000	4,000	5,000	7,000
June	6,000	8,000	6,000	7,000	6,000
July	7,000	3,000	7,000	10,000	8,000
August	6,000	8,000	10,000	14,000	10,000
September	10,000	12,000	15,000	16,000	20,000
October	12,000	12,000	15,000	16,000	20,000
November	14,000	16,000	18,000	20,000	22,000
December	8,000	10,000	8,000	12,000	8,000

Total	78,000	89,000	98,000	115,000	113,000

Reference no: EM13383130

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