Here's where I'm having a problem. I'm ok with the Store. It's the projected loss. What I perceive would be: to take the County store's 2017 through 2020 sales for September through December and get their average. Then compare September through December 2021 for the percentage difference. Then apply that to the store. In comparing it to the store, I'm unsure, of two questions. First, do I take the percentage difference from the County in 2021 and apply that to my average for September through December of the store to get adjusted gross sales loss, or to apply a percentage to what a party calculated as lost sales in the first spreadsheet to my already estimated loss in the spreadsheet of the Store?.

The Kingsley Department Store suffered heavy damage when a hurricane struck on August 31, 2020. The store was closed for four months (SeptDec 2020) and Kingsley is now involved in a dispute with its insurance company concerning the number of lost sales during the time the store was closed. Two key issues must be resolved: 1. The amount of sales Kingsley would have made if the hurricane had not struck; and 2. Whether Kingsley is entitled to any compensation for excess sales from 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 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 Kingsley Department Store was closed. Management asks you to analyze this data and develop estimates of the lost sales at the Kingsley Department Store for the months of September through December 2020. 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, Kingsley is entitled to compensation for excess sales it would have earned in addition to ordinary sales. 4Table 1 - Sales for Kingsley Department Store, Sept 16 through Aug 21Table 2 - Department Store Sales for the County, Sept 17 through Dec 21Prepare a report for the management of the Kingsley department store that summarizes your findings, forecasts and recommendations. Include the following: 1. 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 2021 for Kingsley 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? 2. 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 3. Your final estimate of lost sales for the Kingsley Department store for Sept Dec 2021.

Table 1 Sales for Kingsley Department Store, Sept 16 through Aug 21
4 Month Estimate 2021 Sept. - Dec.
Month	2017	2018	2019	2020	2021
January		2.45	3.31	3.31	3.56
February		2.8	2.89	2.99	3.28
March		3.03	3.02	3.42	3.69
April		2.99	3.23	3.45	3.48
May		3.32	3.39	3.57	3.73
June		3.2	3.14	3.42	3.37
July		3.13	3.27	3.4	3.31
August		3.43	3.21	3.5	3.23
September	2.71	2.9	2.89	3.09	2.90
October	2.9	3.13	3.29	3.54	3.22
November	3.74	3.56	3.83	3.97	3.78
December	5.2	5.16	5.04	5.35	5.19
Table 2 Department Store Sales for the County, Sept 17 through Dec 21
Month	2017	2018	2019	2020	2021
January		47.3	47.3	44.3	48.5
February		48.5	49.1	46.1	52.1
March		60.5	59.9	58.1	58.1
April		58.1	58.7	53.9	58.7
May		62.3	61.1	56.9	60.5
June		58.7	55.7	53.3	57.5
July		56.9	51.5	54.5	58.1
August		63.5	59.3	61.1	62.3
September	56.3	58.1	50.3	47.9	69.5		56.42	19.472
October	56.9	53.9	55.1	55.1	75.5		59.3	18.445
November	71.9	71.9	65.9	68.3	85.7		72.74	19.269
December	118.1	114.5	102.5	100.7	122.3		111.62	21.517