The Nine Roses Restaurant, in New Orleans, is owned and operated by Lana and Jeffrey Lee. The restaurant just completed its third year of operations. Since opening Nine Roses, the Lees have sought to establish a reputation for the restaurant as a high-quality dining establishment that specializes in fresh seafood. Through the efforts of Lana and Jeffrey as well as their staff, Nine Roses has become one of the best and fastest growing restaurants in New Orleans. To better plan for future growth of the restaurant, Lana and Jeffrey needs to develop a system that will enable them to forecast food and beverage sales by month for up to one year in advance. The file “Nine Roses” shows the value of food and beverage sales ($1000s) for the first three years of operation.   A time series plot. Comment on the underlying pattern in the time series. An analysis of the seasonality of the data. Indicate the seasonal indices for each month, and comment on the high and low seasonal sales months. Do the seasonal indices make intuitive sense? Discuss. Using the decomposition approach, calculate the seasonally-adjusted sales forecasts 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 large, Lana and Jeffrey may be puzzled about the difference between your forecast and the actual sales value. What can you do to resolve their uncertainty in the forecasting procedure?   First Year Month Sales   Second Year Month Sales   Third Year Month Sales   January 242     January 263     January 282   February 235     February 238     February 255   March 232     March 247     March 265   April 178     April 193     April 205   May 184     May 193     May 210   June 140     June 149     June 160   July 145     July 157     July 166   August 152     August 161     August 174   September 110     September 122     September 126   October 130     October 130     October 148   November 152     November 167     November 173   December 206     December 230     December 235

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The Nine Roses Restaurant, in New Orleans, is owned and operated by Lana and Jeffrey Lee. The restaurant just completed its third year of operations. Since opening Nine Roses, the Lees have sought to establish a reputation for the restaurant as a high-quality dining establishment that specializes in fresh seafood. Through the efforts of Lana and Jeffrey as well as their staff, Nine Roses has become one of the best and fastest growing restaurants in New Orleans.

To better plan for future growth of the restaurant, Lana and Jeffrey needs to develop a system that will enable them to forecast food and beverage sales by month for up to one year in advance. The file “Nine Roses” shows the value of food and beverage sales ($1000s) for the first three years of operation.

 

  1. A time series plot. Comment on the underlying pattern in the time series.
  2. An analysis of the seasonality of the data. Indicate the seasonal indices for each month, and comment on the high and low seasonal sales months. Do the seasonal indices make intuitive sense? Discuss.
  3. Using the decomposition approach, calculate the seasonally-adjusted sales forecasts for January through December of the fourth year.
  4. Assume that January sales for the fourth year turn out to be $295,000. What was your forecast error? If this error is large, Lana and Jeffrey may be puzzled about the difference between your forecast and the actual sales value. What can you do to resolve their uncertainty in the forecasting procedure?

 

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