HeathCo is a manufacturing company that produces a line of skiwear that is sold under various brand
Question:
HeathCo is a manufacturing company that produces a line of skiwear that is sold under various brand names. The Product Manager of HeathCo has contracted with you to develop a model to forecast company sales. You will be supplied with quarterly sales data from 2007 through 2016. They want a model that will allow them to forecast sales one year (four quarters) out. You will use the HeathCo Sales Data worksheet in the HeathCo_Sales.xlsx workbook for this case study. In this case study, you will run a time-series decomposition model and compare the results to the best fitting model from the previous case study(s).
- Time-series Decomposition Model
- Use the data from the years 2007 to 2015 to create a time-series decomposition model using ForecastX. Reserve 2016 data as a holdout to evaluate the accuracy of your models.
- On the Data Capture tab, make sure the Data to be Forecast only includes data through 2015 (Row 37) and set the Forecast Periods to 4.
- On the Forecast Method tab, set the Forecast Technique to Decompostion. Make sure the Type is set to Multiplicative and the Forecast Method for Decomposed data is set to Simple Exponential Smoothing.
- On the Statistics tab, check the MAPE option on the tab and the Root Mean Sq Error on the Accuracy tab of the More Statistics pop-up option.
- On the Reports tab, uncheck the Standard option, check the Audit option, and check the Fitted Values Table option.
- Press Finish and View Output. Save your results. Copy the results worksheet to a workbook with the data file.
- Based on a review of the model fit graph in ForecastX, do the model results show a similar trend to the trend of data series? Explain your answer. Write your answer in the box below.
- Based on a review of the model fit graph in ForecastX, do the model results show a similar seasonal pattern to the seasonal pattern of data series? Explain your answer. Write your answer in the box below.
- Write a brief description of the model fit using the ForecastX MAPE and RMSE output. Include the values of the MAPE and RMSE measures in your description. Write your answer in the box below.
- Calculate the MAPE and RMSE model accuracy using the four quarters of holdout data and the forecasts for the same four quarters in the ForecastX output. Label your results in an Excel workbook using the prompt number.
- Write a brief description of the model accuracy. Include the values of the MAPE and RMSE measures in your description. Write your answer in the box below.
- In a separate Word document, write a concise summary report in APA format for the general manager. Your report should include an introduction, methodology, results, conclusions/recommendations, and references. The introduction must include a brief literature review (see template for instructions and details). The recommendation to the general manager should include whether the time-series decomposition model is likely to be more useful for making predictions for his intended business purpose than the best previous model.
Period | Sales |
Mar-07 | 72962 |
Jun-07 | 81921 |
Sep-07 | 97729 |
Dec-07 | 142161 |
Mar-08 | 145592 |
Jun-08 | 117129 |
Sep-08 | 114159 |
Dec-08 | 151402 |
Mar-09 | 153907 |
Jun-09 | 100144 |
Sep-09 | 123242 |
Dec-09 | 128497 |
Mar-10 | 176076 |
Jun-10 | 180440 |
Sep-10 | 162665 |
Dec-10 | 220818 |
Mar-11 | 202415 |
Jun-11 | 211780 |
Sep-11 | 163710 |
Dec-11 | 200135 |
Mar-12 | 174200 |
Jun-12 | 182556 |
Sep-12 | 198990 |
Dec-12 | 243700 |
Mar-13 | 253142 |
Jun-13 | 218755 |
Sep-13 | 225422 |
Dec-13 | 253653 |
Mar-14 | 257156 |
Jun-14 | 202568 |
Sep-14 | 224482 |
Dec-14 | 229879 |
Mar-15 | 289321 |
Jun-15 | 266095 |
Sep-15 | 262938 |
Dec-15 | 322052 |
Mar-16 | 313769 |
Jun-16 | 315011 |
Sep-16 | 264939 |
Dec-16 | 301479 |
Business Forecasting with Forecast X
ISBN: 978-0073373645
6th edition
Authors: Holton wilson, barry keating, john solutions inc