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The Fresh Detergent Case

Enterprise Industries produces Fresh, a brand of liquid detergent. In order to more effectively manage its inventory, the company would like to better predict demand for Fresh. To develop a prediction model, the company has gathered data concerning demand for Fresh over the last 33 sales periods. Each sales period is defined as one month. The variables are as follows:

Period = Time period in month

Demand = Y = demand for a large size bottle of Fresh (in 100,000)

Price = the price of Fresh as offered by Ent. Industries

AIP = the Average Industry Price

ADV = Enterprise Industries Advertising Expenditure (in $100,000) to Promote Fresh in the sales period.

DIFF = AIP - Price = the "price difference" in the sales period

1.Download the data from Course Blackboard site into Excel spreadsheet.

2.Make time series scatter plots of all five variables (five graphs). Insert trend line, equation, and R-squared. Observe graphs and provide interpretation.

3.Construct scatter plots of Demand vs. DIFF and Demand vs. ADV, Demand vs. AIP, and Demand vs. Price. Insert fitted line, equation, and R-squared. Observe graphs and provide interpretation. Note that Demand is always on the Y axis.

4.Obtain the correlation matrix for all six variables and rank the variables that have strong correlation with Demand (must use absolute value.) Explain your findings in plain language.

5.Use 3-month and 6-month moving averages to predict the demand for October 2022. Find MAD for both forecasts and identify the preferred one based on each calculation. Is the moving average suitable method for forecasting for this data set? Explain your reasoning.

6.Use Exponential smoothing forecasts with alpha of 0.1, 0.2, ..., 0.9 to predict October 2022 demand. Identify the value of alpha that results in the lowest MAD.

7.Find the monthly seasonal indices for the demand values using Simple Average (SA) method. Find the de-seasonalized demand values by dividing monthly demand by respective seasonal indices.

8.Use regression to perform trend analysis on the de-seasonalized demand values. Is trend analysis suitable for this data? Find MAD and explain the Excel Regression output (trend equation, r, r-squared, goodness of model).

Period Price AIP ADV

Oct. 2022 $7.30 $7.65 $10.9

Nov. 2022 $7.45 $7.70 $11.5

Dec. 2022 $7.80 $7.95 $11.7

Excel Spreadsheet

Month/Yr.	PERIOD	PRICE	AIP	DIFF	ADV	DEMAND
Jan. 2020	1	6.1	5.8	-0.3	5.1	11.1
	2	5.75	6	0.25	6.75	13.3
	3	5.7	6.3	0.6	7.25	14.5
	4	5.7	5.7	0	7.3	14.1
	5	5.6	5.85	0.25	7.2	14
	6	5.6	5.8	0.2	6.5	13.5
	7	5.6	5.75	0.15	6.75	13.2
	8	6.3	5.85	-0.45	6.89	11.9
	9	6.4	5.65	-0.75	5.8	11.3
	10	6.2	6	-0.2	5.5	11.8
	11	5.9	6.1	0.2	6.5	11.8
	12	5.9	6	0.1	6.25	12.8
Jan. 2021	13	5.7	6.1	0.4	7	13.3
	14	5.75	6.2	0.45	6.9	14.3
	15	5.75	6.1	0.35	6.8	15.5
	16	5.8	6.1	0.3	6.8	15.4
	17	5.7	6.2	0.5	7.1	15.1
	18	5.8	6.3	0.5	7	14.8
	19	5.7	6.1	0.4	7.2	14.5
	20	5.8	5.75	-0.05	7.5	14
	21	5.8	5.75	-0.05	7.8	13.8
	22	5.75	5.65	-0.1	8.2	13.8
	23	5.7	5.9	0.2	8.3	14.3
	24	5.55	5.65	0.1	8.4	15.4
Jan. 2022	25	5.6	6.1	0.5	8.9	15.8
	26	5.65	6.25	0.6	9.1	16.5
	27	5.7	5.65	-0.05	9.3	17.2
	28	5.75	5.75	0	9.4	17.6
	29	5.8	5.85	0.05	9.3	17.3
	30	5.3	6.25	0.95	9.4	17.1
	31	5.4	6.3	0.9	9.5	16.8
	32	5.7	6.4	0.7	9.6	16
Sep. 2022	33	5.9	6.5	0.6	10	15.5

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