Reference no: EM131389407

1. FOOD AND BEVERAGE SALES FOR THE VINTAGE RESTURANT ($1000s)

Month	First Year	Second Year	Third Year
January	242	263	282
February	235	238	255
March	232	247	265
April	178	193	205
May	184	193	210
June	140	149	160
July	145	157	166
August	152	161	174
September	110	122	126
October	130	130	148
November	152	167	173
December	206	230	235

FORECASTING FOOD AND BEVERAGE SALES

The Vintage Restaurant is on Captiva Island, a resort community near Fort Myers, Florida is owned and operated by Karen Payne. The restaurant just completed its third year of operation. During that time, Karen sought to establish a reputation for the restaurant as a high-quality dining establishment that specializes in fresh seafood. Through the efforts by Karen and her staff, her restaurant has become one of the best and fastest-growing restaurants on the island. To better plan for the future growth of the restaurant, Karen needs to develop a system that will enable her to forecast food and beverage sales by month for up to one year in advance.

The following data shows the value of food and beverage sales ($1000s) for the three years of operation.

Perform an analysis of the sales data for the Vintage Restaurant. Prepare a report for Karen that summarizes your findings, forecasts, and recommendations. Also include the following:

1. A time series plot. Comment on the underlying pattern in the time series

2. Using the dummy variable approach, forecast of sales for January through December of the fourth year

Assume that January sales for the fourth year turn out to be $295,000. What was your forecast error? If this error is a large, Karen may be puzzled about the difference between your forecast and the actual sales value. What can you do to resolve her uncertainty in the forecasting procedure?

2. TABLE 15.9 SALES FOR CARLSON DEPARTMENT STORES ($MILLIONS)

Month	Year 1	Year 2	Year 3	Year 4	Year 5
January		1.45	2.31	2.31	2.56
February		1.80	1.89	1.99	2.28
March		2.03	2.02	2.42	2.69
April		1.99	2.23	2.45	2.48
May		2.32	2.39	2.57	2.73
June		2.20	2.14	2.42	2.37
July		2.13	2.27	2.40	2.31
August		2.43	2.21	2.50	2.23
September	1.71	1.90	1.89	2.09
October	1.90	2.13	2.29	2.54
November	2.74	2.56	2.83	2.97
December	4.20	4.16	4.04	4.35

The Carlson Department Store suffered heavy damage when a hurricane struck on August 31. The store was closed for four months (Sept through Dec) and Carlson is now involved in a dispute with its insurance company about the amount of lost sales during the time the store was closed. Two key issues must be resolved:

1. The amount of sales Carlson would have made if the hurricane had not struck.

2. Whether Carlson is entitled to any compensation for excess sales due to increased business activity after the storm. More than $8 billion in federal disaster relief and insurance money came into the county, resulting in increased sales at department stores and numerous other businesses.

The table 15.19 gives Carlson sales data for the 48 months preceding the storm. The following table 15.20 reports total sales for the 48 months preceding the storm for all department stores in the county, as well as the total sales in the county for the four months the Carlson Department Store was closed. Carlson managers asked you to analyze this data and develop estimates of the lost sales at the Carlson Department Store for the months of September through December. They also asked you to determine whether a case can be made for excess storm-related sales during the same period. If such a case can be made, Carlson is entitled to compensation for excess sales it would have earned in addition to ordinary sales.

Prepare a report for the managers of the Carlson Department Store that summarizes your findings, forecasts, and recommendations. Also include the following:

1. An estimate of sales for Carlson Department Store had there been no hurricane.

2. An estimate of countrywide department store sales had there been no hurricane

3. An estimate of lost sales for Carlson Department Store for September through December.

In addition, use the countrywide actual departmental store sales for September through December and the estimate in part 2 to make a case for, or a against excess storm related sales.

Table 15.20 DEPARTMENT STORE SALES FOR THE COUNTY ($MILLIONS)

Month	Year 1	Year 2	Year 3	Year 4	Year 5
January		46.80	46.80	43.80	48.00
February		48.00	48.60	45.60	51.60
March		60.00	59.40	57.60	57.60
April		57.60	58.20	53.40	58.20
May		61.80	60.60	56.40	60.00
June		58.20	55.20	52.80	57.00
July		56.40	51.00	54.00	57.60
August		63.00	58.80	60.60	61.80
September	55.80	57.60	49.80	47.40	69.00
October	56.40	53.40	54.60	54.60	75.00
November	71.40	71.40	65.40	67.80	85.20
December	117.60	114.00	102.00	100.20	121.80