Predicting lost revenue case study composition

Carlson Mall suffered heavy damage from a storm on August 31. As a result the store was closed to get four several weeks, September through December. Carlson is in dispute with its insurance provider regarding the misplaced sales intended for the length of time your local store was closed.

Section II: Problem Identification

Two problems to address will be the amount of sales Carlson department store could have made if there had been no typhoon and if they may be entitled to any compensation pertaining to excess revenue due to elevated business activity after the tornado.

One even more important factor is the fact eight billion dollars dollars in federal devastation relief and insurance funds came in for the county which often increased sales at department stores and numerous other businesses in the place.

Section III: Approach:

The process to be used is forecasting with seasonality in order to obtain approximate product sales data to get the months that Carlson was sealed.

Section 4: Options

Following reviewing several methods of predicting and their measures of forecasting accuracy the linear forecasting method is proved to be the most effective considering that the mean square problem, and the mean absolute error and the imply absolute percentage error are extremely close to absolutely no.

*See attached Excel spreadsheet for additional clarification/breakdown of forecasting strategies. However , although the linear pattern line can be handy it can also demonstrate to be inappropriate for people who do buiness retail product sales. Real developments change their slope and intercept over time and hardly ever tend to follow a fixed right line. Consequently , linear regression with seasonality will be used to ascertain lost sales.

In the past five years Carlson’s overall month to month average pertaining to sales was 2 . 43375. The regular monthly averages pertaining to the weeks under consideration happen to be as follows; September: 1 . 8975 October: 2 . 215 November: 2 . 775 and 12 ,: 4. 1875. Approximately thirty nine percent of Carlson’s sales happen within the Sept through January months. The seasonal index as present in physique 6. several further breaks this down. While critiquing Carlsondepartment store’s forecasted sales for Sept through Dec and taking into account that the time period is during the holiday season; it really is apparent that sales commonly increase during this time period in relation to seasonality.

Section Sixth is v: Conclusions/Recommendations

Determine 6. 6th displays the forecast of lost sales for Carlson had presently there been zero hurricane. This table shows that Carlson is allowed to 12. 43 million in lost product sales for the four weeks that it was sealed. The surrounding department stores showed a frequent increase in product sales during the four listed a few months (September through December) since shown in figure six. 9. The amount of sales had been well previously mentioned what was commonly forecasted (On average the surrounding department stores performed 18. 67 million previously mentioned forecast). How much sales during this period frame elevated by 27. 03 percent. Based from this data, Carlson should be provided extra compensation for the increase of sales they would have came across from devastation relief cash and insurance money. Carlson would have received an approximate enhance of 3. 36 million in sales, for that reason making the overall compensation due to Carlson from their insurance provider 15. 788 million to get lost revenue.

Section MIRE: Other Factors

Some other factors that may need further account are shifting holidays, or perhaps the effect of holiday seasons on the foretelling of method. Several holidays may have changing dates which will impact several month in a manner that depends upon the date.

Section VII: Methods

References

Anderson, D. R., Sweeny, D., Williams, T., Cann, J., Cochran, J., Fry, M., & Ohlmann, M. (2013). Quantitative Methods For Business. Mason, ALSO: South-Western Cengage Learning.

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