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Case Study 2:
The Carlson Department Store suffered heavy damage when a hurricane struck on August 31, 2013. The store was closed for four months (Sept – Dec 2013) and Carlson is now involved in a dispute with its insurance company concerning the amount of lost sales during the time the store was closed. Two key issues must be resolved:
- The amount of sales Carlson would have made if the hurricane had not struck; and
- Whether Carlson 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 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 2013. 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 ’09 through Aug ‘13
Month |
2009 |
2010 |
2011 |
2012 |
2013 |
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 ’09 through Dec ‘13
Month |
2009 |
2010 |
2011 |
2012 |
2013 |
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 3 November 2021
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 2013 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 2013.
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