The Vintage Restaurant, on Captiva Island near Fort Myers, Florida, is owned and

Question

The Vintage Restaurant, on Captiva Island near Fort Myers, Florida, is owned and operatedby 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 establish-ment that specializes in fresh seafood. Through the efforts of Karen and her staff, herrestaurant has become one of the best and fastest-growing restaurants on the island.To better plan for future growth of the restaurant, Karen needs to develop a system thatwill enable her to forecast food and beverage sales by month for up to one year in advance.Table 15.18 shows the value of food and beverage sales ($1000s) for the ?rst three years of operation. Managerial Report Perform an analysis of the sales data for the Vintage Restaurant. Prepare a report for Karenthat summarizes your ?ndings, forecasts, and recommendations. Include the following:

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

.2.Using the dummy variable approach, forecast sales for January through Decemberof the fourth year.Assume that January sales for the fourth year turn out to be $295,000. What was yourforecast error? If this error is large, Karen may be puzzled about the difference betweenyour forecast and the actual sales value. What can you do to resolve her uncertainty in theforecasting procedure?

Assume that January sales for the fourth year turn out to be $295,000. What was yourforecast error? If this error is large, Karen may be puzzled about the difference betweenyour forecast and the actual sales value. What can you do to resolve her uncertainty in theforecasting procedure? Copyright | CENGAGE Learning | An Introduction to Management Science | Edition 13 | cong131290@gmail.com | Printed from www.chegg.com

Explanation / Answer

First Second Growth % in 2nd year Third Growth % in 3rd year 3rd Year Forecast JANUARY 242 263 8.68% 282 7.22% 310 FEBRUARY 235 238 1.28% 255 7.14% 261 MARCH 232 247 6.47% 265 7.29% 285 APRIL 178 193 8.43% 205 6.22% 225 MAY 184 193 4.89% 210 8.81% 223 JUNE 140 149 6.43% 160 7.38% 173 JULY 145 157 8.28% 166 5.73% 183 AUGUST 152 161 5.92% 174 8.07% 187 SEPTEMBER 110 122 10.91% 126 3.28% 143 OCTOBER 130 130 0.00% 148 13.85% 151 NOVEMBER 152 167 9.87% 173 3.59% 193 DECEMBER 206 230 11.65% 235 2.17% 265 Average Sales/ month 176 188 200 217 % Increase in Forecast 6.84% 6.62% 8.41% As shown in the table the calculation is as below Growth % in 2nd Year = % increaase in forecast in 2nd year as compared to 1st year. Same way Growth % in 3rd Year = % increase in forecast in 3rd year as compated to 2nd year. Now, to calculate the forecast in the 4th year, as per the time series method, We have to give weithge to past data, and FORECAST for the next period Let us give 25% weitage each to 2nd and 3rd year on year growth % and 25 % to respective months The Forecast for the 4th year will be as plotted in the last column' Then Forecast for the 4th year January is 310,000. Actual is 290, the error is of 20,000 $

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