The table below shows the sales data for the 48 months preceding the storm The following table 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 Management asks you to analyze this data and develop estimates of the lost sales at the Carlson Department Store for the months of September through December 2003 Management also wants 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 Table 1 Sales for Carlson Department Store, Sept 99 through Aug 03 Month 1999 2000 2001 2002 2003 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 Table 2 Department Store Sales for the County, Sept 99 through Dec 03 Month 1999 2000 2001 2002 2003 January 46 8 46 8 43 8 48 0 February 48 0 48 6 45 6 51 6 March 60 0 59 4 57 6 57 6 April 57 6 58 2 53 4 58 2 May 61 8 60 6 56 4 60 0 June 58 2 55 2 52 8 57 0 July 56 4 51 0 54 0 57 6 August 63 0 58 8 60 6 61 8 September 55 8 57 6 49 8 47 4 69 0 October 56 4 53 4 54 6 54 6 75 0 November 71 4 71 4 65 4 67 8 85 2 December 117 6 114 0 102 0 100 2 121 8 Managerial Report is due 5 April 2019 Prepare a report for the management of the Carlson department store that summarizes your findings, forecasts and recommendations Include the following An estimate of the sales had there been no hurricane Hint Remember to graph this time series data over the 48 month period to help you determine the type of approach to use to determine the forecast sales for the final 4 months of 2003 for Carlson department store Is there a trend in the data (growth or decline) Is there seasonality in the data (this is a department store Christmas time and beginning of school are normally big sales periods) Is there both trend and seasonality An estimate of the countywide department store sales had there been no hurricane Hint By comparing the forecast of county wide department store sales with actual sales, one can determine whether or not there are excess storm related sales By computing what is known as a lift factor the ratio of actual sales to forecast sales you have a measure of the magnitude of excess sales, if these do indeed exist Your final estimate of lost sales for the Carlson Department store for Sept Dec 2003

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Question: The table below shows the sales data for the 48 months preceding the storm. The following table reports total sales for the 48 months preceding

The table below shows the sales data for the 48 months preceding the storm. The following table 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. Management asks you to analyze this data and develop estimates of the lost sales at the Carlson Department Store for the months of September through December 2003. Management also wants 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.

Table 1 Sales for Carlson Department Store, Sept 99 through Aug 03

Month	1999	2000	2001	2002	2003
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

Table 2 Department Store Sales for the County, Sept 99 through Dec 03

Month	1999	2000	2001	2002	2003
January		46.8	46.8	43.8	48.0
February		48.0	48.6	45.6	51.6
March		60.0	59.4	57.6	57.6
April		57.6	58.2	53.4	58.2
May		61.8	60.6	56.4	60.0
June		58.2	55.2	52.8	57.0
July		56.4	51.0	54.0	57.6
August		63.0	58.8	60.6	61.8
September	55.8	57.6	49.8	47.4	69.0
October	56.4	53.4	54.6	54.6	75.0
November	71.4	71.4	65.4	67.8	85.2
December	117.6	114.0	102.0	100.2	121.8

Managerial Report is due 5 April 2019

Prepare a report for the management of the Carlson department store that summarizes your findings, forecasts and recommendations. Include the following:

An estimate of the sales had there been no hurricane.

Hint: Remember to graph this time series data over the 48-month period to help you determine the type of approach to use to determine the forecast sales for the final 4 months of 2003 for Carlson department store. Is there a trend in the data (growth or decline)? Is there seasonality in the data (this is a department store Christmas time and beginning of school are normally big sales periods)? Is there both trend and seasonality?

An estimate of the countywide department store sales had there been no hurricane.

Hint: By comparing the forecast of county-wide department store sales with actual sales, one can determine whether or not there are excess storm-related sales. By computing what is known as a "lift factor" the ratio of actual sales to forecast sales you have a measure of the magnitude of excess sales, if these do indeed exist

Your final estimate of lost sales for the Carlson Department store for Sept Dec 2003.

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