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BUS300 Operations Management
Task :
Human Resources Inc. (HR Inc.) is a small company that conducts seminars on productivity issues for corporate executives. HR Inc. focuses on improving the quality of work and the attitude of workers in service organizations. The company tries to provide seminar participants with the tools essential for dealing with hard-to-measure issues.
Originally, its seminars were geared toward hospital administration —specifically, topics included how to motivate nursing staffs and how to provide quality care for patients. Over the years, the demand for seminars has grown, as has the company’s client base. Clients now include insurance executives who want to improve the quality and productivity of their claim recorders, travel agency directors who want to improve the service of their agencies, and managers of secretarial pools who wish to improve the attitudes in their offices.
HR Inc. has offered one seminar each season since 1990. Each seminar lasts for one week and is typically held at a resort or spa. The location has varied over the years, but the winter seminars have tended to be in Florida, the spring seminars in Chicago, the summer seminars in the Carolinas, and the fall seminars in the northeast corridor (between Washington and Boston).
The table shows the number of persons attending seminars since Hr Inc. began.
Table. The number of Participants
|
Participants |
||||||||||
|
Year |
2000 |
2001 |
2002 |
2003 |
2004 |
2005 |
2006 |
2007 |
2008 |
|
|
Quarter |
Winter |
624 |
588 |
608 |
607 |
690 |
832 |
703 |
776 |
950 |
|
Spring |
30 |
205 |
218 |
305 |
214 |
263 |
423 |
450 |
339 |
|
|
Summer |
323 |
191 |
249 |
431 |
405 |
389 |
509 |
540 |
660 |
|
|
Fall |
420 |
477 |
470 |
447 |
452 |
479 |
575 |
603 |
619 |
|
Assignments: use Ms. Excel Spreadsheet to do the following.
You may copy and paste the data to your Excel Spreadsheet. I would also suggestion that you re-arrange data into a 2-dimension table (Quarters, # of Participants). To do so will make your job easier.
A spreadsheet template has be posted in the same Canvas folder you may use to help you complete the project in a structure and organized way.
Forecast
Use a 4-Quarter Moving AverageMethod to forecast the # of the participants from Winter 2001 to Winter 2009.
Use a Linear Projection Forecast Methodto forecast the # of the emergency visit from Winter 2000 to Winter 2009.
Use an Exponential Smoothing Forecast Method,with a = 0.4, to forecast the # of the emergency visit from Winter 2001 to Winter 2009. Assume that initial forecast for Fall 2000 is 450.
Discussion
Plot One(nice) Chart the following 4 Data Series over time (Winter 2001 to Fall 2008):
the historical data series,
the data series of forecasts obtained in 1a), 1b) and 1c).
What data pattern you may conclude from the chart of historical data series
Intuitively, which of the three forecasts you made in question 1 seems the best.
Use one of forecast Error Measurements, either MAD,or MSE, or MAPE (you choose) to determine which of the forecasts from 1a), 1b) or 1c) provides the best (smallest) forecasting error summary from the given historical data set. Is your conclusion same as the one you reached in 2)-b)-ii)?
Remark. It is important to point out that error comparison of different forecast methods should be done on a Consistent Base. That is, the forecast error comparison for different forecast methods is meaningful only when we compare errors from the Same Range of forecasts.
Use the same Forecast Error Measurementyou used in question 3), find the best smoothing parameter a (i.e. the a that leads to the smallest forecast error) of Exponential Smoothing Forecast Method.
For the Exponential Smoothing forecastobtained in 1c), use Tracking Signal to monitor the forecast results and draw a conclusion on whether or not the forecasts are Biased, assume C = 3, and -C = -3 to be the control limits of the tracking signal method.
For the given historical data set,
Based on the data patternof the three-year data set, one can argue that the forecast methods used in 1a)-c), or, in general, we may conclude that Moving average, Linear Trend Project, and Exponential Smoothing Method should not be good Forecasting methods for the given data set since the seasonal data pattern exists. Can you elaborate?
Propose Your Own Forecast Method(Other than the Moving Average, Linear Trend Project, and Exponential Smoothing Method we did in question 1)) that might be better than the forecast methods 1a) – 1c). Use the Forecast Method proposed to do forecasts from Winter 2000 to Winter 2009.
Use the SameForecast Error Measurement as you used in part 3) to calculate forecasting error for your method, and then check to see if your method is better.?
BUS300 Operations Management
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