Question

A manager of a store that sells and installs spas wants to prepare a forecast for January, February, and March of next year. Her forecasts are a combination of trend and seasonality. She uses the following equation to estimate the trend component of monthly demand: Ft = 60 + 4t, where t = 0 in June of last year. Seasonal relatives are .89 for January, .95 for February, and 1.11 for March. What demands should she predict? (Round your answers to 2 decimal places.)

Answer 1

		last year	jan
			feb
			mar
			apr
			may
		last year	jun	0
			jul	1
			aug	2
			sep	3
			oct	4
			nov	5
			dec	6
		this year	jan	7
			feb	8
			mar	9
			apr	10
			may	11
			jun	12
			jul	13
			aug	14
			sep	15
			oct	16
			nov	17
			dec	18
We need this month jan		next year	jan	19
We need this feb		next year	feb	20
We need this month of march		next year	mar	21

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This is best done in 2 stages:

Stage 1:

Compute the Trend = Yt

We need to find Y Jan Next Year, Y Feb Next Year, and Y March Next year which is just 19,20, and 21 ( see the excel table – it is just a simple sequential counting of months from June last year at 0 to Jan next year = one and a half years, hence 19 months.)

Formula for trend is already given as 60 + 4t

The value of t for the 3 months is found by simply adding as follows:

Ft = 60 + 4 * t

Ft for Jan = Y Jan Next Year = 60 + 4 * 19 = 136

Ft for Feb = Y Feb Next Year = 60 + 4 * 20 = 140

Ft for Mar = Y Mar Next Year = 60 + 4 * 21 = 144

Stage 2:

Compute the forecast = trend * seasonal relative

The seasonal relative for each month is already given in the question as 0.89, 0.95, and 1.11 for the 3 months respectively.

We found the 3 trends above as 136, 140, and 144 for the 3 months respectively.

Hence January fore cast = 0.89 * 136 = 121.04

February fore cast = 0.95 * 140 = 133

March fore cast = 1.11 * 144 = 159.79994

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